GEOmedia 3 2020

Rivista bimestrale - anno XXIV - Numero 3/2020 - Sped. in abb. postale 70% - Filiale di Roma

LAND CARTOGRAPHY

GIS

CADASTRE

GEOGRAPHIC INFORMATION

PHOTOGRAMMETRY

3D

SURVEY TOPOGRAPHY

CAD

BIM

EARTH OBSERVATION SPACE

WEBGIS

UAV

URBAN PLANNING

CONSTRUCTION

LBS

SMART CITY

GNSS

ENVIRONMENT

NETWORKS

LiDAR

CULTURAL HERITAGE

Mag/Giu 2020 anno XXIV N°3

Terra Seismic

earthquake prediction

EO, VGI AND AI FOR

LAND MANAGEMENT

DISASTER RISK REDUCTION

WITH EARTH OBSERVATION

MONITORING ZNOSKO

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The “everything digital” geospatial environment

This issue, mainly edited in English for the annual fair of INTERGEO, is facing, for the first

time, the international Geo-IT community in a digital meeting!

INTERGEO organizers says that exhibitors will meet international trade fair visitors, speakers

will meet their audience, and everything will be as usual. But we all know that things will not

be as usual and we hope that in the very next future the industrial economy of the Geospatial

community will run again, but surely in a different way.

In this “everything digital” environment, GEOmedia decided not to change producing a print

publication. Why? Because our readers still want it. Especially in this period were the pleasure

of getting away from the screens and continue enjoy geospatial information on a print paper

is really a great opportunity. But how are going other similar publications in the world? Many

decided to stop printing, mainly because of paper press process cost, but many other not. One for

all is an example for all of us, and we want to share with you the answer of Neil Sandlers to the

why xyHT is still a print magazine: “Yes, we are, and for some very good reasons. You, our readers,

still demand print. Our numbers show that 19,870 of you are holding a print version of this issue in

your hands, and 10,912 of you are looking at a digital edition on your phones or computers”.

Our numbers are not the same, we are in Italy not in USA, and our magazine is mainly in Italian

language, but the ratio looks the same.

Our first focus this issue is on Earthquake prediction with the article by Oleg Elshin of Terra

Seismic, an international team of scientists with over 30 years of experience in developing

effective technologies & methods in seismic forecasting. Oleg explain us that Terra Seismic can

predict most major earthquakes (M6.2 or greater) at least 2 - 5 months before they will strike,

based on determinations of the stressed areas that will start to behave abnormally before major

earthquakes.

The second focus approach the fusion of Earth Observation, Volunteered Geographic

Information and Artificial Intelligence for improved Land Management in an article by Vyron

Antoniou and Flavio Lupia.

Despite the coronavirus pandemic, the worldwide economic crisis and the general slow-down

of space activities, the temperature is high about the NASA Artemis program, meant to land in

2024 again on the Moon. The report of Marco Lisi “Positioning, Navigation and Timing for

Planetary Exploration and Colonization: to the Moon and Beyond” heralds the presence of a lot

of geomatics in next years.

Vincenzo Massimi on the article “Disaster risk reduction and reconstruction in Indonesia with

Earth Observation” report how Indra and Planetek Italia contributed with a batch of EO-based

services, for terrain deformation mapping before and after the 7.5 magnitude earthquake of

September 28, 2018 in the island of Sulawesi, Indonesia.

Gabriele Garnero, in the report “Control and monitoring of the Znosko Glacier in Antarctica”

with Fabian Brondi Rueda, Giovanni Righetti and Stefano Serafini will focus on the generation

of correct digital elevation models (DEM) for the monitoring of the glacier observed since the

1990s by Peru’s IGN (Instituto Geográfico Nacional), demonstrating that a correct geodesic setting

allows to obtain high resolution geospatial products.

Enjoy your reading.

Buona lettura,

Renzo Carlucci

In this

issue...

FOCUS

REPORT

COLUMNS

With Terra Seismic

earthquake

prediction, we can be

better

prepared for

earthquakes in Italy

by Oleg Elshin

6

22 SPACE AND EARTH

24 ESA Image

30 AUGMENTED REALITY

40 NEWS

42 AEROFOTOTECA

46 AGENDA

10

Fusing Earth

Observation,

Volunteered

Geographic Information

and Artificial

Intelligence for improved

Land Management

By Vyron Antoniou, Flavio Lupia

In cover image - stressed

areas and anomalies map in

Italy on 01.10.2008, six

months before 2009

L’Aquila earthquake

geomediaonline.it

GEOmedia, published bi-monthly, is the Italian magazine for

geomatics. Since more than 20 years publishing to open a

worldwide window to the Italian market and vice versa.

Themes are on latest news, developments and applications in

the complex field of earth surface sciences.

GEOmedia faces with all activities relating to the acquisition,

processing, querying, analysis, presentation, dissemination,

management and use of geo-data and geo-information. The

magazine covers subjects such as surveying, environment,

mapping, GNSS systems, GIS, Earth Observation, Geospatial

Data, BIM, UAV and 3D technologies.

ADV

Positioning, Navigation

and Timing

for Planetary

Exploration and

Colonization: to the

Moon and Beyond

by Marco Lisi

16

3DTARGET 21

ARCHIMETER 9

AUTODESK 29

EPSILON 14

ESRI ITALIA 39

CODEVINTEC 45

GEOBUSINESS 15

GEC SOFTWARE 2

GEOMAX 33

GIS3W 20

GTER 41

Disaster risk

reduction and

reconstruction in

Indonesia with Earth

Observation

by Vincenzo Massimi

26

PLANETEK 48

STONEX 47

TEOREMA 46

TOPCON 40

In the background image,

many multicolored curves

and handles of the Flinders

Mountains - the largest

mountain system of southern

Australia - appear in this

image in false-color captured

by the Copernicus Sentinel

mission-2.

34

Control and

monitoring of the

Znosko Glacier in

Antarctica

by Fabian Brondi Rueda,

Gabriele Garnero,

Giovanni Righetti,

Stefano Serafini

This image was captured on

December 31 2019 from the

two-satellite Sentinel-2, whose

goal is to ensure coverage

and the distribution of data

required by the program European

Copernicus. The data

were tried through the selection

of spectral bands useful

to classify the geological features.

This image also does

part of the video program

Earth from Space.

una pubblicazione

Chief Editor

RENZO CARLUCCI, direttore@rivistageomedia.it

Editorial Board

Vyron Antoniou, Fabrizio Bernardini, Mario Caporale,

Luigi Colombo, Mattia Crespi, Luigi Di Prinzio,

Michele Dussi, Michele Fasolo, Marco Lisi, Flavio Lupia,

Beniamino Murgante, Aldo Riggio, Mauro Salvemini,

Domenico Santarsiero, Attilio Selvini, Donato Tufillaro

Managing Director

FULVIO BERNARDINI, fbernardini@rivistageomedia.it

Editorial Staff

VALERIO CARLUCCI, GIANLUCA PITITTO,

redazione@rivistageomedia.it

Marketing Assistant

TATIANA IASILLO, diffusione@rivistageomedia.it

Design

DANIELE CARLUCCI, dcarlucci@rivistageomedia.it

MediaGEO soc. coop.

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Issue closed on: 28/08/2020.

Science & Technology Communication

FOCUS

With Terra Seismic earthquake

prediction, we can be better

prepared for earthquakes in Italy

by Oleg Elshin

Fig 1 - Stressed area in Italy on 01.10.2008, six months before 2009 L’Aquila earthquake."

Earthquakes have represented a permanent threat to Italy throughout the

country’s entire history: seismic events have been well known since Roman

times. The country also suffered major events in the 20th century. The most

tragic was the 1908 M7.1 Messina earthquake and subsequent tsunami that

almost completely destroyed the cities of Messina and Reggio Calabria,

leaving more than 80,000 victims in its wake. This threat still hangs over the

Italian people. Just within the last decade, the 2009 L’Aquila quake, the 2012

Emilia Romagna quakes and the 2016 Central Italy quakes reminded us that

we live in a dangerous and seismically active period for Italy.

The traditional response

to earthquake-related

danger is based on

long-term preparation in areas

where major earthquakes were

historically recorded. These

preparations usually include

establishing more resilient

building standards for new

buildings and reinforcing old

heritage. Italy is home to a

plethora of invaluable historic

buildings that are very vulnerable

to earthquakes. According

to some estimates, only about

25% of Italian buildings are

built in accordance with seismic

standards and only about

40% of current Italian infrastructure

is earthquake proof.

Akin to many other seismic

regions around the world,

insurance is not usually used

as a tool to obtain earthquake

damage relief in Italy. It’s estimated

that only about one per

cent of Italian buildings are insured

against earthquakes (2).

Recent events have again clearly

demonstrated that the

traditional approach provides

a little help in preventing

human loss, saving historic

buildings and mitigating the

economic damage produced by

earthquakes. For instance, the

Italian Civil Protection Agency

estimated the economic losses

from the 2016 October

earthquakes at €16.5 billion.

The insured loss was just €208

million, which indicates that

only 1.3% of the overall economic

loss was insured (3). Thus,

Italy remains very vulnerable to

6 GEOmedia n°3-2020

FOCUS

major earthquakes. With this

in mind, we need to find new

and better solutions to address

the danger posed by earthquakes

in Italy.

Fortunately, science and

technology progresses, and

global earthquake prediction,

a radically novel technology,

has created new and very promising

prospects for mitigating

earthquake danger in Italy and

globally. Terra Seismic, the

world’s first company of its

kind, has successfully developed

satellite Big Data technology

that can predict most

major earthquakes (M6.2+ or

greater) at least 2-5 months

before they will occur. The

technology has been in practical

use since 2013.

Terra Seismic’s unparalleled

technology

has been successfully

tested against historical

data for global

and Italian quakes

that have occurred

in the last 50 years.

Backward testing

shows that the

technology would

have successfully detected

all major M6+

Italian earthquakes

since 1980.

Global earthquake

prediction is based

on simple and universally

understandable

assumptions.

While earthquakes

occur suddenly for

humans, these perils

are not sudden for

nature. Nature needs

time to accumulate

a huge amount of

stress before producing

a major

earthquake. The area

where the future

earthquake will hit

will be stressed and

behave differently from other

areas in the vicinity. These areas

of abnormal behavior can be

detected well in advance and

this gives humans a warning

period to prepare effectively for

forthcoming major earthquakes.

Italians know that earthquakes

are a real and permanent danger,

but every new event still

catches Italy underprepared.

With radically new technology

and a much better understanding

of earthquake build-up

processes, what can we do differently

now?

Firstly, we now know that seismic

danger is distributed unevenly

across time and different

Italian regions. A specific pe-

culiarity of Italy is that periods

of high seismic activity may

be interspersed with relatively

quiet and prolonged risk-free

periods. Italy could establish

a special earthquake preparedness

and recovery fund,

which would accumulate funds

during quiet seismic periods

and spend money effectively

just before major earthquakes.

Secondly, the scarce resources

available for preparedness

could be more efficiently allocated

across Italian regions.

While almost all Italian regions

are exposed to earthquake risks,

funds could be invested mainly

in the region that will be affected

by a forthcoming major

earthquake.

Fig. 2 – Real predictions, stressed areas

and anomalies map: some latest case

analysed.

GEOmedia n°3-2020 7

FOCUS

Thirdly, we need to carefully

reanalyze and draw lessons

from past Italian events to

predict the potential secondary

consequences associated with

earthquakes. For example, the

2016 Amatrice quake shows

that destroyed and damaged

roads and bridges may hinder

the prompt arrival of rescue

teams and heavy rescue machinery

in the damaged area, and

so on.

Terra Seismic can predict most

major earthquakes (M6.2 or greater)

at least 2 - 5 months before

they will strike. Global earthquake

prediction is based on determinations

of the stressed areas that will

start to behave abnormally before

major earthquakes. The size of the

observed stressed areas roughly

corresponds to estimates calculated

from Dobrovolsky’s formula.

To identify abnormalities and

make predictions, Terra Seismic

applies various methodologies,

including satellite remote sensing

methods and data from groundbased

instruments. We currently

process terabytes of information

daily, and use more than 80 different

multiparameter prediction

systems. Alerts are issued if the

abnormalities are confirmed by

at least five different systems. We

observed that geophysical patterns

of earthquake development and

stress accumulation are generally

the same for all key seismic regions.

Thus, the same earthquake

prediction methodologies and

systems can be applied successfully

worldwide. Our technology has

been used to retrospectively test

data gathered since 1970 and it

successfully detected about 90 percent

of all significant quakes over

the last 50 years.

www.terraseismic.org

Fourthly, detailed action plans

could be developed before

major events to address a region’s

specific characteristics.

According to these plans, the

government would need to

examine and reinforce the critical

and important infrastructure

in the area of a forthcoming

quake – hospitals, schools,

cultural heritage buildings, etc.

The rational use of millions of

euros on effective loss prevention

measures before earthquakes

hit is estimated to save

billions that are usually spent

on recovery after earthquakes.

Thus, thanks to this approach,

billions of euros’ worth of economic

damage could be prevented

in Italian earthquakes

and these huge savings allocated

to other purposes.

Fifthly, besides government

funding, private money and,

specifically, insurance companies

could play a greater role in

preparedness and earthquake

risk mitigation. Earthquake insurance

penetration is currently

very low in Italy. One of the

main reasons for this situation

is that quake insurance is very

expensive due to incorrect quake

risk assessment. Earthquake

prediction will assess quake

risk much more accurately,

thus allowing insurers to offer

much lower premiums

for many Italian regions and

make insurance coverage more

attractive. Innovation will create

conditions for affordable

earthquake insurance to penetrate

into the Italian market.

Finally, in Italy, building collapses

are responsible for most

deaths during earthquakes.

The death toll would be significantly

lower if people were

outside and distanced from old

buildings when the quake strikes.

As such, a timely warning

for people to simply sleep and

spend more time outside buildings

before major earthquakes

represents a very cheap and

effective solution. Training

drills and early warning alarms

will be effective at preventing

significant human loss due to

earthquakes. Based on Terra

Seismic’s global technology,

we can dramatically reduce the

human loss arising from these

awful perils and better protect

Italy. Terra Seismic calls for

cooperation with the Italian

Central and Regional governments

in order to improve

preparedness for forthcoming

events.

REFERENCES AND

FURTHER READINGS

1.Elshin, O. and Tronin, A.A.

(2020) Global Earthquake Prediction

Systems. Open Journal of

Earthquake Research, 9, 170-180.

https://arxiv.org/abs/2003.07593

2.Earthquake-resistant buildings: the

vulnerability of Italy’s infrastructure

https://www.webuildvalue.com/en/

infrastructure-news/earth-quakeresistant-buildings.html

3.2016 Central Italy earthquakes

cost an estimated 208 million euros:

PERILS

https://www.canadianunderwriter.

ca/claims/2016-central-italy-

earthquakes-cost-estimated-

208-million-euros-perils-

1004122686/#:~:text=The%20

Italian%20Civil%20Protection%20

Agency,insured%20loss%20of%20

the%20Aug.

KEYWORDS

Global earthquake prediction;

Big Data and novel technologies;

Earthquakes; Remote sensing;

Terra Seismic

ABSTRACT

Terra Seismic can predict most

major earthquakes (M6.2 or greater)

at least 2 - 5 months before

they will strike.

AUTHOR

Oleg Elshin

oleg.elshin@terraseismic.com

President at Terra Seismic

Alicante, Spain /

Baar, Switzerland


Via Balilla 192

Canosa di Puglia (BT)

76012

FOCUS

tel. 0883 887466

mob. +39 347 4810454

info@archimeter.it

AMBIENTE

ARCHEOLOGIA

ARCHITETTURA

INFRASTRUTTURE

REALTA’ VIRTUALE


FOCUS

Fusing Earth Observation, Volunteered

Geographic Information and Artificial

Intelligence for improved Land Management

by Vyron Antoniou, Flavio Lupia

Earth Observation data deluge is

calling for Artificial Intelligence

methods to support geomatics in

producing valuable information

for land management.

Open-source data, software

and services and volunteered

geographic information will be

relevant contributors.

Existing and future developments

in Earth Observation

The last few years we have witnessed

a proliferation of Earth

Observation (EO) systems with

improved sensing capabilities

and shorter revisiting periods.

Perhaps one of the most successful

paradigms of freely available

EO data is those provided

by the European Commission

(EC) Copernicus program

through the Sentinel constellation.

However, broad EO data

availability was unknown until

recently. At the beginning,

high resolution imagery was a

sole privilege of governments

or robust private companies,

while later, broadly available

imagery was of medium resolution

and long revisiting

times (e.g. through the Landsat

program). Today though, initiatives

like Sentinel provide

free imagery of up to 10m

resolution and of 5-day revisiting

period. Taking advantage

of these developments, many

stakeholders turn to the pu-


FOCUS

mes, in or outside Data Cubes,

still remains a challenge. To

this end, an interesting development

comes from advances

in Artificial Intelligence

(AI), Machine Learning (ML)

and Deep Learning (DL).

Important breakthroughs that

took place during the last

few years have contributed to

their proliferation. First, it is

the improvements of the AI/

ML/DL field itself. New algorithms,

improved models and

better processes allow AI/ML/

DL to excel in long standing

problems and challenges compared

to existing solutions and

show the potential of the field

in the future. A second factor is

the open approach that many

stakeholders hold towards AI

issues. Partially from concerns

that have to do with the power

and the control that AI models

can have over important decisions

and partially inspired

by the principles set by opensource

software and wiki-based

projects, AI models, training

datasets and other helpful material

are freely accessible onliblicly

available data to cover

their needs as high quality

and timely imagery is easily

accessible from individuals

and researchers up to start-up

companies. As a consequence,

the private sector today needs

to offer imagery well below the

thresholds set by freely available

data pushing the spacebased

EO in a virtuous cycle.

A similar positive momentum

exists for the global co-ordination

of EO sensors. Examples

can be found in initiatives such

as the GEO (Group on Earth

Observations), an international

organization consisting of

more than 200 governments

and organizations. Its mission

is to implement GEOSS

(Global Earth Observation

System of Systems) which

is a set of interacting earth

observation, information and

processing systems aiming to

provide access to information

to a broad range of users and

purposes. GEOSS links these

systems, facilitates the sharing

of environmental data and information,

ensures that these

data are accessible and assures

their quality, provenance and

interoperability. More than

150 data providers contribute

to GEOSS and in total, there

are around 200 million datasets

available. A direct result of these

developments is the creation

of huge volumes of data, on

top of the already produced

ones. It is expected that more

than 8500 smallsats (i.e., less

than 500 Kg) will be launched

in the next decade alone, at an

average of more than 800 satellites

per year, and the constellations

will account for 83%

of the satellites to be launched

by 2028 (Euroconsult, 2019),

many of which will be for EO

purposes.

New Challenges – New

Solutions

All these create new challenges

when it comes to efficiently

storing, managing, processing

and analysing EO imagery.

Moreover, there is increased

need for automation and

end-to-end methodologies for

image analysis in order to take

advantage of the wealth of data

generated. An interesting way

forward is paved by the progress

in satellite imagery Data

Cubes. Data Cubes are novel

approaches for storing, organizing,

viewing and analyzing

large volumes of imagery and

thus, enable more efficient

management and analysis

methods. They allow a homogenized

way of storing timerepeating

imagery for a defined

area. This creates a virtual cube

of data over a specific area

where the z-axis corresponds to

time. Data Cubes ensure high

quality and consistency of the

stored data while they provide

the necessary infrastructure,

tools and services. However,

processing of large data volu-

Fig. 1 - An example of artificial neural network with a hidden layer (Source: https://commons.wikimedia.org/wiki/File:Artificial_neural_network.svg)


FOCUS

ne which lower the entry bar

of an individual to this field.

Moreover, big companies offer

for free the necessary computational

power so that anyone

can experiment and progress

into the AI domain (see for

example Google’s Colab -

https://colab.research.google.

com/).

Machine Learning in

Geomatics

In general, ML/DL is revolutionizing

how massive data

volumes are analysed. In the

Geomatics domain, ML/DL

allows the development of

geospatial applications that,

a few years ago, were beyond

reach in terms of efficiency and

processing capacity. Examples

can be found in satellite image

artefact reduction (Wegner et

al., 2018); image denoising

(Huang et al., 2019); pansharpening

(Yang et al., 2017)

or super resolution (Huang et

al., 2015) to name a few. Of

course, the ML/DL field is not

without challenges. One of

the most puzzling ones is the

stability of the results. Gilmer

et al. (2018) illuminates the

problem and explains how easy

it is for deep neural networks

(DNN), which are highly accurate

on benchmark datasets,

to be confused and perform

poorly when they have to work

with real-life adversarial cases.

For example, Hendrycks et al.

(2019) show that with a set

of adversarial images a DNN

achieved an accuracy of approximately

2%, which was a

drop of approximately 90%

compared to its accuracy with

the benchmark IMAGENET

dataset. However, ML/DL is

constantly gaining momentum

and the user and developer

pool is getting bigger and more

active in all domains, including

Geomatics. This trend is also

seconded by multiple virtual

places where engineers meet

and compete to produce novel

or more efficient AI models.

For example, the Kaggle platform

(https://www.kaggle.

com/) hosts open competitions

Fig. 2 - A filter in the first layer of a convolutional artificial neural network interpreting an image

(Source: https://commons.wikimedia.org/wiki/File:Convolutional_Neural_Network_Neural-

NetworkFilter.gif).

that challenge researchers and

developers to present models

that are capable of accurately

evaluating benchmark datasets.

Similar is the concept behind

the DigitalGlobe challenge

(https://spacenetchallenge.

github.io/) which focus

exclusively in remote sensing

application, the Crowd AI

mapping challenge (https://

www.crowdai.org/challenges/

mapping-challenge) which

focuses on building detection

for humanitarian response in

areas with poor mapping coverage,

and the Defense Science

and Technology Laboratory

(Dstl) challenge, which focus

on natural or manmade features,

such as waterways and

buildings from multispectral

satellite imagery.

Volunteered Geographic

Information in the service of

Machine Learning

One important factor that

affects the progress of ML/

DL is the availability of training

datasets. In Geomatics,

the solution can be found in

the growth of Volunteered

Geographic Information

(VGI). For more than a decade

now, VGI is spearheading

the creation of freely available

data. OSM, the flagship of

VGI, provides global coverage

with free data where someone

can find vectors that outline

natural and man-made features

including land use and land

cover data. The geometry of

the features, along with their

imagery counterpart, can form

rich sources of training datasets

that can be used to train ML/

DL models in order to perform

complex processes such as automatic

road network extraction,

object detection or land

classification (Antoniou and

Potsiou 2020).


FOCUS

Agriculture and Earth

Observation

It is widely recognized that EO

and geospatial data of high quality,

frequency and with wider

accessibility can enable and fully

support global, regional and

country initiatives and regulations.

New data-driven approaches

and Big Data Analytics

provide unique opportunities

to track and monitor human

actions toward sustainability as

required by Agenda 2030 in a

really consistent and comparable

manner.

At EU level, environmental and

agricultural sector will benefit

for the deluge of data from EO

(e.g. Copernicus Programme)

and other sources (in-situ/proximal/ground

sensors) helping

to support the European Green

Deal - the roadmap for addressing

climate change issues making

the EU economy

sustainable and the new

Common Agricultural Policy

(CAP).

CAP is already exploiting

Copernicus satellite data to

generate several products: land

use/land cover and crop type

maps, land take, crop conditions,

soil moisture, high nature

value farmland, and landscape

fragmentation. In addition,

CAP subsidies to farmers will

take advantage of the EO data

to perform the full monitor of

the farmers compliance and to

dramatically reduce the sample

field checks.

In this arena, managing petabytes

of data from EO and other

sources data to be synergistically

integrated will be the challenge

and new tools, such as AI, will

be pivotal in extracting actionable

geospatial information. To

this end, EU is moving toward

the development of cutting-edge,

ethical and secure AI trough

a coordinated effort and cooperation

among Member States,

as stated by the Coordinated

Plan on Artificial Intelligence

(European Commission, 2018).

Agriculture and Machine

Learning

The growing use of ICT in agriculture

and precision farming

have opened up the Digital

Agriculture era where a large

amount of data coming from

a variety of sensors will enable

data-driven precise farming strategies.

The final goal is always

to handle a complex system of

systems, where several components

(soil, weather, crops and

farm management) interact at

different spatial and temporal

scales, in search of sustainability

of farm inputs and growth of

product quality and economic

performances.

ML/DL techniques have already

been proven as a powerful

tool to unravel the complexities

of the agricultural ecosystem.

Liakos et al. (2018), in their review

found the following as the

most promising applications:

crop management (yield estimates,

diseases and weeds detection,

crop quality and identification),

livestock management

(animal welfare and production),

water and soil management.

ML/DL models dominate

in the field of crop management

where there is a consolidated

use of imagery that can be used

directly, often without the need

of data fusion from different

sources. ML applications are less

common when data recorded

from different sensors need to

be integrated into big datasets

thus, requiring a lot of effort

to be managed (e.g. livestock

management). Literature reports

Artificial Neural Networks

(ANNs) and Support Vector

Machines (SVMs) as the most

widespread models used in agriculture.

Despite the difficulties to

compare the experimental

conditions of the literature,

Kamilaris & Prenafeta-Boldú

(2018) in their review found

that DL-based technics (mainly

Convolutional Neural Networks

- CNNs) have always better performances

when compared with

classical state-of-the-art approaches

using EO and Unmanned

Aerial Vehicle data in various

agricultural areas (leaf classification,

leaf and plant disease

detection, plant recognition and

fruit counting). Moreover, several

papers reported advantages

of DL in terms of reduced effort

in feature engineering where

manual identification of specific

components is always challenging

and time consuming.

Other advantages are the good

performance in generalization

and the robustness in difficult

conditions (such as illumination,

complex background,

different resolution, size and

orientation of the images).

What lies ahead

In general, ML/DL approaches

seem very promising for addressing

the complexity of the agricultural

domain by providing

the ingredients to move towards

a knowledge-based agriculture.

In Geomatics, the need for large

annotation datasets, as training

inputs, can be supported by

VGI which offer large volumes

of free data. However, at the

same time, several weaknesses

need to be addressed such as the

limitation to generalize beyond

the boundaries of benchmark

datasets, time-consuming preprocessing

and safeguarding the

consistency of the results in order

to further accelerate the use

of AI/ML/DL. Finally, we stress

the need to orchestrate these

promising solutions dealing

with specific aspects of agriculture

within a wider decisionmaking

environment.


FOCUS

REFERENCES

Antoniou, V., & Potsiou, C. (2020). A Deep Learning

Method to Accelerate the Disaster Response Process.

Remote Sensing, 12(3), 544.

Euroconsult, 2019. Smallsat Market to Nearly Quadruple

over Next Decade. Available at http://www.

euroconsult-ec.com/5_August_2019

European Commission, 2018. Coordinated Plan on Artificial

Intelligence. Available at https://eur-lex.europa.

eu/legal-content/EN/TXT/?uri=COM:2018:795:FIN

Gilmer, J.; Adams, R.P.; Goodfellow, I.; Andersen,

D.; Dahl, G.E. Motivating the Rules of the Game

for Adversarial Example Research. arXiv 2018, ar-

Xiv:1807.06732.

Hendrycks, D., Zhao, K., Basart, S., Steinhardt, J., &

Song, D. 2019. Natural adversarial examples. arXiv

preprint arXiv:1907.07174.

Huang, W., Xiao, L., Wei, Z., Liu, H., & Tang, S.,

2015. A new pan-sharpening method with deep neural

networks. IEEE Geoscience and Remote Sensing Letters,

12(5), 1037-1041.

Huang, Z., Zhang, Y., Li, Q., Li, Z., Zhang, T., Sang,

N., & Xiong, S., 2019. Unidirectional variation

and deep CNN denoiser priors for simultaneously

destriping and denoising optical remote sensing images.

International Journal of Remote Sensing, 40(15),

5737-5748.

Kamilaris, A., & Prenafeta-Boldú, F. X. (2018). Deep

learning in agriculture: A survey. Computers and electronics

in agriculture, 147, 70-90.

Liakos, K. G., Busato, P., Moshou, D., Pearson, S., &

Bochtis, D. (2018). Machine learning in agriculture: A

review. Sensors, 18(8), 2674.

Wegner, J.D., Roscher, R., Volpi, M. and Veronesi,

F., 2018. Foreword to the Special Issue on Machine

Learning for Geospatial Data Analysis.

Yang, J., Fu, X., Hu, Y., Huang, Y., Ding, X., & Paisley,

J., 2017. PanNet: A deep network architecture for pansharpening.

In Proceedings of the IEEE International

Conference on Computer Vision (pp. 5449-5457).

KEYWORDS

Earth observation; VGI; machine learning;

deep learning; digital agriculture, land management

ABSTRACT

The ever-growing availability of Earth Observation (EO)

data is demonstrating a wide range of potential applications

in the realm of land management. On the other hand, large

volumes of data need to be handled and analysed to extract

meaningful information and Geomatics coupled with new

approaches such as Artificial Intelligence (AI) and Machine

Learning (AI) will play a pivotal role in the years to come.

Training datasets need to be developed to use these new

models and Volunteered Geographic Information can be

one of the promising sources for EO processing. Among

the various applications, agriculture may benefit from the

large dataset availability and AI processing. However, several

issues remain unsolved and further steps should be taken in

the near future by researchers and policy makers.

AUTHOR

Vyron Antoniou

Multi-National Geospatial Support Group

Frauenberger Str. 250, 53879, Euskirchen,

Germany

v.antoniou@ucl.ac.uk

Flavio Lupia

flavio.lupia@crea.gov.it

CREA Council for Agricultural

Research and Economics

Via Po, 14 00198, Rome, Italy


FOCUS

in collaborazione con

Il Servizio Pubblico della distribuzione

in relazione ai cambiamenti

Modelli di prevenzione Piani d’azione Sviluppo sostenibile

28 e 29 OTTOBRE

Presso Piave Servizi - Codognè (TV)

USO VERTICALE

Per programma & iscrizioni

Non è una fiera e neppure un convegno, ma una nuova formula di incontro e comunicazione che, pur tenendo

conto delle dinamiche tradizionali, non manca di rispondere a quelle che sono le legittime esigenze

delle aziende: far conoscere i propri prodotti e tecnologie suscitando interesse; e quelle dei gestori: essere

aggiornati su tutte le novità e tecnologie innovative di un mercato in continuo fermento.

In questo modo chi deve vendere, e chi deve acquistare, si troveranno faccia a faccia in un reciproco scambio

di opinioni, informazioni, esigenze.

Attraverso la formula dello speech, si potrà assistere ai vari interventi di presentazione anche in maniera discontinua,

senza l’obbligo di rimanere incollati alla sedia trascurando le indispensabili pubbliche relazioni

che sono il vero focus di ogni incontro.

CON IL PATROCINIO DI

ASSOCIAZIONE REGIONALE CONSORZI GESTIONE

E TUTELA DEL TERRITORIO E ACQUE IRRIGUE

CONSIGLIO DI BACINO

L.R. del Veneto n. 17 del 27 april

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REPORT

Positioning, Navigation and Timing

for Planetary Exploration and

Colonization: to the Moon and Beyond

by Marco Lisi

Despite the coronavirus pandemic,

the worldwide economic crisis and

the general slow-down of space

activities, the temperature is high

about the NASA Artemis program,

meant to land in 2024, 52 years after

the last Apollo mission and 20 years

of confinement in low Earth orbit,

human beings on the Moon.

To justify this maintained

focus, during a recent

press conference, NASA

Administrator Jim Bridenstine

said bold aspirations are needed

now more than ever, given the

coronavirus pandemic: “We

need to give people hope, we

need to give them something

that they can look up to, dream

about, something that will inspire

not just the nation but the

entire world”.

With the Artemis program,

NASA plan to collaborate with

commercial and international

partners to establish a permanent

“base camp” and a sustainable

exploration of the Moon

by the end of the decade. The

ultimate goal is to use what will

be learned on and around the

Moon to take the next giant

leap: sending astronauts to

Mars.

Challenges ahead are numerous:

as a matter of example, studies

performed at ESA and NASA

determined that local materials

and 3D printing technologies

would be the best for constructing

buildings and other structures,

which means no need for

transporting resources from the

Earth at an astronomical cost.

But the problems to be solved

for the realization of a stable

manned infrastructure on the

Moon (a true follow-on of the

International Space Station) involve

much more than just building

technologies. The Moon

“base camp” will have to meet

very stringent requirements in

terms of operations, logistics,

and safety of life. From an

architectural viewpoint, the

“Moon base” will have to be

expandable and “open” to the

integration with other systems,

hence integrability and expandability

will be key issues. But

first and above all, a permanent

base on the Moon will have to

be affordable and sustainable,

i.e., its cost will need to be assessed

over its life-cycle, under a

long term technical, economic,

and political perspective.

The exploration of the Moon

with human and robotic missions

and its colonization,

through the establishment of

a permanent base, will require

many vital supporting infrastructures,

such as communication

networks and positioning,

navigation, and timing (PNT)

systems.

All architectural approaches

considered so far by NASA and

ESA to develop communications

and PNT infrastructures

on the Moon can be divided

into two main categories:

• Comprehensive, well-structured

and forward-looking (but

costly) architectures, based on

constellations of orbiters and

relay satellites;


REPORT

• “ad hoc”, flexible, expandable

architectures, based on a fusion

of all available resources

and commercial technologies.

The second approach looks like

a more promising, affordable,

and sustainable solution.

A Lunar Communication

Network

The Moon communication

infrastructure shall be able to

provide several capabilities, that

can be summarized in two main

categories: users/applications

that need low data rate and

very reliable links, and those

that require high data rate links.

The first category includes

monitoring and control of the

base camp systems/payloads

and essential audio, video, and

file transfer among users. Links

for these applications shall have

high service availability (for

instance 99.99%) also in case

of emergencies and (lunar) disasters,

regardless of Moon phases,

Earth position, terrestrial

weather conditions, etc. The

second category instead includes

HTTP surfing, high quality,

Audio/Video communications,

video streaming, HD television,

file sharing, cloud computing,

etc. These applications will be

provided with a service availability

lower than the first category

(for instance 98%).

A pragmatic answer to these

requirements might consist in a

scalable network that relies on

terrestrial, wireless technologies,

such as 4G and 5G, intending

to limit the effort of designing

and developing dedicated

technologies for the Moon

“base camp” (fig. 1).

Consequently, the design of the

lunar communication network

will be mainly devoted to the

definition of its cell distribution

on the lunar surface. The

cell distribution will strongly

depend on the network (performance,

functional, and operational)

requirements, the lunar

site location, and the selected

air interface.

Starting from these inputs, a

possible strategy for defining

the cell distribution is summarized

in Fig.2 and described as

follows. The “Moon Base” requirements

and the, e.g., 5G air

interface definition are inputs

for the definition of the link

budgets, in particular for the

transmitting and the receiving

chains, to derive the maximum

attainable path loss. At the same

time, the base camp location

physical and environmental

properties are a starting point

for the definition of a path

loss model, that can be derived

through analysis based on the

already available information

and, in the future, from testing

in specific environmental conditions.

Once that path loss

model and link budgets are

completed and consolidated,

the coverage distribution of a

single cell can be determined.

The coverage will depend on

its location (latitude, longitude,

height from the surface), the

adopted antennas, and the surrounding

infrastructure: notice

that all these parameters can

be elaborated from software

Fig. 2 - Logical steps for the design of the lunar cellular network

Fig. 1 - Modular, Expandable Moon Navigation & Communications

Infrastructure

tools and the coverage pattern

computed for several positions.

This allows deriving a first iteration

of the cell distribution,

and thus of the lunar cellular

network, by dovetailing several

cells on the selected site and

verifying that the total coverage

meets the initial requirements.

An important component in

the Moon Base communication

network is the backhauling link

with Earth, which allows 5G

communication terminals to access

all services in the terrestrial

network (e.g. a Skype© call

from a Lunar operator inside

the habitat with its family on

Earth).

The backhauling link will be

designed to provide an ultrahigh

data rate and high-availa-


REPORT

Positioning, Navigation and

Timing on the Moon

Fig. 3 - Example of possible 5G communication network with backhauling to Earth realized using Moon

orbiter satellites

bility link. Candidate technologies

for backhauling are both

microwave and optical communications,

each of them with

advantages and disadvantages

in terms of data rates, weather

sensitivity, and pointing accuracy

An example of backhauling

configuration is the one shown

in fig. 3 where orbiters are in

stable orbits around the Moon

and relay all the traffic from the

Earth directly to Moon ground

stations.

Alternatively, the backhauling

could be realized through a

direct link Moon-Earth. A possible

configuration is depicted

in Fig.4, where 5G stations are

wired to optical backhauling

stations that communicate directly

with Earth.

Fig. 4 - Example of possible 5G communication network with backhauling to Earth realized through

direct-to-Earth optical link.

Lunar positioning

Since 2001, the Aurora space

exploration program has led

the European activities towards

the potential deployment of

human bases on Mars and the

Moon. Within this framework,

two feasibility studies of a reduced

planetary navigation and

communications system were

performed. Both studies concluded

that COTS equipment,

based on IEEE 802.16 WiMAX

standard, could be used to fulfill

the mission requirements for

short-range activities (i.e., link

distance below 8 km), but longrange

activities were not foreseen

to be covered only with an

infrastructure on the planetary

surface. Future 5G technology

is expected to overcome these

challenges and to provide the

necessary coverage, flexibility,

and performance required by a

permanent base.

The 5G standard looks like a

promising standard to support

communication and positioning

capabilities for a wide range

of applications, such as massive

Internet of Things (IoT),

mission-critical control, and

enhanced mobile broadband.

For this purpose, advanced

wireless technologies, such as

massive MIMO antennas and

wideband millimeter-wave links

are foreseen. Similarly to the

4G LTE standard, 5G multicarrier

waveforms will allow the

flexible allocation of data, as

well as dedicated pilot signals

for positioning purposes. These

pilot signals can be used to perform

ranging measurements for

time-of-arrival (ToA) location

methods, and multi-antenna

techniques can enable angle-ofarrival

(AoA) localization.

The 5G networks for the Moon

Base mission are designed ac-


REPORT

cording to the requirements for

potential manned and robotic

activities. The main design

parameters are the cell site location,

cell coverage, and signal

bandwidth. These parameters

define the achievable communication

and positioning capabilities.

The configuration of

multiple cell sites over a certain

area, i.e., the geometry of cell

sites with respect to the receiver,

determines the dilution of

precision (DOP) of ToA and

AoA methods. The cell coverage

mainly depends on the height

of the cell mast, transmit power,

antenna pattern, and propagation

conditions. For instance,

on the Moon, a cell tower of 10

meters above the surface is required

to achieve a line-of-sight

(LoS) distance to the horizon of

almost 6 km, but this distance

may be limited by the irregular

topography of the surface. Last,

the spectrum allocation of the

positioning resources (i.e., pilot

signals) determines the ranging

accuracy, as well as the data

rate. Design procedures developed

for 5G terrestrial networks

could be adapted to the conditions

on the Moon. In some

situations, the ToA estimates

will need to be combined with

data from inertial measurement

units. Furthermore, in mesh or

ad hoc networks, such as device-to-device

(D2D) communications,

cooperative positioning

between wireless sensors or sites

may provide additional location

solutions.

Precise synchronization of lunar

stations

5G systems on Earth rely on

GNSS signals for precise synchronization.

GNSS receivers

are used to provide precise

timing in different parts of

the 4G LTE ground network,

which requires within 3 to

10 microseconds accuracy,

Fig. 5 - GNSS space antenna developed for GEO orbit.

depending on the application

and the standard adopted. On

Earth, such accuracies are easily

achievable by a professional

GNSS timing receiver, which

has an accuracy in the order of

tens of nanoseconds. This same

approach could be adopted for

Moon-based 5G gateway stations.

Clearly, on the Moon, the

conditions are significantly

different with respect to the

Earth surface. The use of GNSS

(such as GPS or Galileo) signals

in the Moon environment has

been studied in past ESA contracts.

The major challenges to

be considered are:

• Signal power: in addition

to the higher free-space loss,

the majority of the received

signals come from the GNSS

transmitter antennas’ sidelobes

(with considerably lower

gains). Additionally, stronger

signals may interfere with the

correct acquisition and tracking

of weaker signals (nearfar

effect), with a consequent

impact on receiver sensitivity

and robustness;

• Dynamics: high ranges for

Doppler and Doppler rates

hinder acquisition and impose

additional stress on the

tracking loops, also making it

more difficult to process weak

signals;

• Geometry: the geometry of

the usable satellites is considerably

worse than for terrestrial

applications. Additionally,

occultation by the Earth and

Moon and receiver sensitivity

(minimum C/N0 required

to acquire and track GNSS

signals) may also have an impact

on the dilution of precision

(DOP).

The studies however showed

that GNSS could be used for

MTO (Moon transfer orbit),

LLO (Lunar Low Orbit), D&L

(Lunar Descent and Landing)

and, with strong limitations, for

Lunar Surface real-time positioning.

The accurate synchronization

of the 5G base stations on the

Moon surface can be achieved

using a professional high sensitivity

timing GNSS receiver

equipped with a directional

high gain antenna (fig. 5), kept

pointing to the Earth.

The receiver will be configured

in timing mode, i.e., it will


REPORT

compute only a precise time

solution, by assuming a precise

knowledge of the antenna

location (better, of its phasecenter),

assessed at least once

through non-GNSS methods.

Such information can be kept

in the receiver, which will then

only work as a timing receiver.

The need for long coherent

integration and the high dynamics,

as well as the need for a

reliable back-up, will suggest

the use of miniaturized atomic

clocks to avoid degradation of

the performances during the

integration (COTS miniaturized

atomic clocks are already

available in the market and

currently used in professional

ground equipment).

Conclusion

The exploration of the Moon

with human and robotic missions

and its colonization,

through the establishment of

permanent bases, will require

planetary communications

and navigation infrastructures.

An affordable, no-nonsense

approach might rely on the

use of COTS components,

presently deployed on Earth

in LTE and 5G networks, for

communication and navigation

on the Moon surface.

This approach largely satisfies

the requirements of performance,

reliability, affordability,

and sustainability, as based on

commercial technology and

being incrementally expandable

over time.

ABSTRACT

With the Artemis program, NASA plans to

collaborate with commercial and international

partners to land in 2024 human beings

on the Moon and then to establish a

permanent “base camp” by the end of the

decade.

Challenges ahead are numerous: the Moon

“base camp” will have to meet very stringent

requirements in terms of operations,

logistics, and safety of life; moreover, a permanent

base on the Moon will have to be

affordable and sustainable, i.e., its cost will

need to be assessed over its life-cycle, under a

long term technical, economic, and political

perspective.

The exploration of the Moon with human

and robotic missions and its colonization,

through the establishment of a permanent

base, will require many vital supporting

infrastructures, such as communication

networks and positioning, navigation, and

timing (PNT) systems.

KEY WORDS

Positioning; navigation; timing; GNSS;

Moon; infrastructure; network; communication;

IoT; 5G

AUTHOR

Dr. Ing. Marco Lisi

ingmarcolisi@gmail.com

Independent Consultant

Aerospace & Defence


REPORT


SPACE AND EARTH

May 30, 2020: US astronauts reach

space with a national, commercial

space vehicle

by Marco Lisi

Fig. 1 - SpaceX Crew Dragon capsule, ready for launch

In the middle of the worldwide

Coronavirus pandemic,

after nine years from the Space

Shuttle Atlantis's final flight on

July 2021, US astronauts reach

space with a national, commercial

space vehicle.

May 30, 2020, a historic day

for the US and Space exploration

at large: a SpaceX Falcon

9 rocket carrying the company's

Crew Dragon spacecraft

is launched from NASA’s

Kennedy Space Center in

Florida, with NASA astronauts

Robert Behnken and Douglas

Hurley onboard (fig. 1).

For the first time in history

and after nine years from the

Space Shuttle Atlantis's final

flight on July 2021 (thirteen

years from the Columbia’s

tragedy in 2003), NASA astronauts

have launched from

American soil in a commercially

built and operated American

crew spacecraft on its way to

the International Space Station.

The day after, May 31, the

Crew Dragon capsule, named

Endeavour, successfully docked

with the International Space

Station, bringing the company’s

first crew to the only

mankind’s orbiting outpost

(fig. 2).

The Crew Dragon’s docking

validated one of the most innovative

features of SpaceX’s

vehicle: its automated docking

system. The capsule is designed

to autonomously approach the

ISS and latch on to a docking

port, based on a standardized

interface, needing no intervention

from its human passengers.

The Crew Dragon mission

success is at the same time a

reason for hope in the future

of Space exploration, in particular,

the planned mission

to the Moon, and, which is

even more important, a confirmation

of the effectiveness

of the NewSpace paradigm. As

pointed out by the Washington

Post web site (June 22, 2020):

“the contract that resulted in

the Dragon crewed spacecraft

was issued by NASA in 2014.

Six years and $3 billion later, it

has flown astronauts into orbit.

What SpaceX did was show

that a well-led entrepreneurial

team can achieve results that

were previously thought to

require the efforts of superpowers,

and in a small fraction of

the time and cost, and even —

as demonstrated by its reusable

Falcon launch vehicles — do

things deemed impossible altogether.

This is a revolution.”.

Crew Dragon belongs to the

Dragon 2 class of reusable


SPACE AND EARTH

spacecraft developed and

manufactured by American

aerospace manufacturer

SpaceX. Dragon 2 includes

two versions: Crew Dragon

(fig. 3), a capsule qualified

for manned missions, capable

of carrying up to seven

to 7 passengers to and

from Low Earth Orbit, and

Cargo Dragon, a robotic

vehicle that can bring more

than 3,000 kilograms to

the ISS.

The per-seat cost that

NASA will pay for

SpaceX's Crew Dragon

capsule is around $55

million, to be compared

with the about $86 million

currently paid for each

seat aboard Russia's threeperson

Soyuz spacecraft,

which has been astronauts'

only ride to and from the

ISS since NASA's space

shuttle fleet was grounded

in July 2011. With the

first commercial orbital

flight with crew on board,

and if the per-seat price is

further reduced, another

dream of NewSpace might

realize: that of commercial

space tourism. As a matter

of fact, SpaceX and Space

Adventures have already signed

a deal to launch up to

four passengers into Earth

orbit on a Crew Dragon

spacecraft by 2021.

Fig. 2 - SpaceX Crew Dragon automated docking with the ISS.

Author

Dr. Ing. Marco Lisi

ingmarcolisi@gmail.com

Independent Consultant

Aerospace & Defence

Fig. 3 - Crew Dragon physical dimensions


MERCATO

24 GEOmedia n°1/2-2020

NEWS

ESA - Gulf of Kutch, India

September 06 2020

The Copernicus Sentinel-2 mission takes us over the Gulf

of Kutch – also known as the Gulf of Kachchh – an inlet of the

Arabian Sea, along the west coast of India. The Gulf of Kutch divides the

Kutch and the Kathiawar peninsula regions in the state of Gujarat. Reaching

eastward for around 150 km, the gulf varies in width from approximately 15 to 65

km. The area is renowned for extreme daily tides which often cover the lower lying areas

– comprising networks of creeks, wetlands and alluvial tidal flats in the interior region.

Gujarat is the largest salt producing state in India. Some of the white rectangles dotted around

the image are salt evaporation ponds which are often found in major salt-producing areas.

The arid climate in the region favours the evaporation of water from the salt ponds. Just north

of the area pictured here, lies the Great Rann of Kutch, a seasonal salt marsh located in the Thar

desert. The Rann is considered the largest salt desert in the world. The Gulf of Kutch has several

ports including Okha (at the entrance of the gulf), Mandvi, Bedi, and Kandla. Kandla, visible on

the northern peninsula in the left of the image, is one of the largest ports in India by volume of cargo

handled. The gulf is rich in marine biodiversity. Part of the southern coast of the Gulf of Kutch was

declared Marine Sanctuary and Marine National Park in 1980 and 1982 respectively – the first

marine conservatory established in India. The park covers an area of around 270 sq km, from Okha

in the south (not visible) to Jodiya. There are hundreds of species of coral in the park, as well as

algae, sponges and mangroves.

Copernicus Sentinel-2 is a two-satellite mission. Each satellite carries a high-resolution camera

that images Earth’s surface in 13 spectral bands. The mission’s frequent revisits over

the same area and high spatial resolution allow changes in water bodies to be closely

monitored.

This image was acquired on 4 April 2020.

Credits: European Space Agency

GEOmedia n°1/2-2020 25

REPORT

Disaster risk reduction and

reconstruction in Indonesia

with Earth Observation

by Vincenzo Massimi

Fig. 1 – Sulawesi Earthquake (Credits EU Civil Protection)

On September 28, 2018, a 7.5 magnitude earthquake struck the

island of Sulawesi, Indonesia. The epicentre was the provincial

capital of Palu, located on a bay on the island’s northwest

coast. The quake triggered a tsunami that swept 10-meter tall

waves of seawater and swamped the city. The combination

of the earthquake, tsunami, soil liquefaction and landslides

claimed well over 2000 lives, destroyed homes, buildings,

infrastructures and farmland in several districts.

Recognizing the need to relocate settlements from the

liquefaction-prone areas, the Indonesian government

developed the Master Plan for Recovery and Reconstruction for

Central Sulawesi through the EARR and SWIP projects.

Indra and Planetek Italia

contributed to the implementation

of this plan with a

batch of EO-based services. The

main information provided was

related to terrain deformation

mapping (before the earthquake)

followed by the update of

terrain information mapping

(in the months immediately

after the earthquake) and reconstruction

monitoring with Very

High Resolution images. The

collaboration went on with a

capacity-building workshop and

a knowledge transfer activity held

in Jakarta in June 2019 regarding

the technical aspects of the delivered

products and training sessions

for local users to teach them to

use the Geohazards Exploitation

Platform (GEP) of ESA.

The main purpose of the delivery

of the information products was

to help the local authorities better

understand the hazards associated

with seismic activity, flooding and

landslides, so they can make more

informed decisions in elaborating

a redevelopment master plan.

As noted during the workshop,

the terrain deformation maps

are helping the authorities in the

evaluation of the effects caused

by the disaster on the land surface

stability.

These activities were carried

out in the context of the

European Space Agency funded

project EO4SD DRR (EO for

Sustainable Development –

Disaster Risk Reduction). The

project was led by Indra, with


REPORT

Planetek Italia, ZAMG, BRGM,

Gisat, Argans and Nazka as subcontractors.

All activites were carried out

in cooperation with the Asian

Development Bank and the

Indonesian National Institute of

Aeronautics and Space and involved

representatives from numerous

Indonesian institutions.

Supporting the disaster risk management

over the area affected

by the 2018 Sulawesi earthquake

with PS InSAR analysis

Planetek Italia provided the millimetric

measurements derived

from Synthetic Aperture Radar

(SAR) through the Persistent

Scatterers Interferometry (PSI)

technique. The PSI technique

exploits the SAR satellite images

to generate as output the ground

motion maps related to the periods

before and after the event of

2018.

Two different pre and post

event maps have been delivered

through the extremely intuitive

Business Intelligence visualization

tools of the Rheticus®

platform, to support the decision

makers that are involved in the

reconstruction activities in Palu.

Rheticus® is a geospatial platform

for massive Earth observation

data processing owned and operated

by Planetek Italia.

The two delivered maps are the

“ground motion” map and the

“buildings motion” map, and are

described in the following.

1) The pre- and post-earthquake

ground motion maps have

been delivered over wide spatial

areas covering the liquefaction

and landslides areas. The map

provides the movements – even

as small as few millimeters – of

each measured point (Persistent

Scatterers / Distributed

Scatterers) located on buildings

and infrastructure elements in the

urban and peri-urban zones as

shown in figure 3:

For each measured point (PS/

Fig. 2 - Palu, Indonesia. Map of the ground motion during the six months following the event.

DS), the web interface provides

a pop-up window (figure 4) that

shows the displacement detailed

information.

2) The “building motion” map

provides the level of concern on

each monitored element such as

buildings, roads and other infrastructures

on a monthly basis,

based on the ground motion map

(see figure 5). The map integrates

the ground/building motion

measurements described above

with the VHR images to monitor

the reconstruction stages. Doing

so, the Rheticus® platform delivered

regular monitoring of the

reconstruction status based on

the Very-High Resolution optical

satellite images and the classes of

motion of each single monitored

element (e.g. buildings) based on

the measurements of displacement

of the monitored elements

itself and their nearby areas. The

integrated information has been

delivered over the Palu area allowing

the characterization of the

movements of the wide areas and

of each single building based on

the PSI ground motion map and

to retrieve the reconstruction and

rehabilitation statistics based on

the interpretation of the VHR

satellite images.

In addition to these information

products, the project also

included a week-long course in

Jakarta organised by the Asian

Development Bank and the

Fig. 3 - Ground motion maps in Palu (pre vs post-earthquake 28/09/2018).


REPORT

Fig. 4 - Example of one PS displacement (mm) over time computed through the PSI over Palu

area after the earthquake. In this figure it is possible to see all the geo-analytics and filtering

tools for the exploitation of the ground motion map.

Indonesian National Institute of

Aeronautics and Space. Attended

by more than 60 representatives

from numerous Indonesian institutions,

experts from Indra,

Planetek and BRGM explained

technical details, methodologies

and usage of these satellite data

products.

Representatives from the Asian

Development Bank noted: “Users

explained that they are particularly

interested in the ground deformation

maps – they offer great insight

into how the land surface has changed

and are essential for Indonesia

to redevelop effectively.”

The ground motion analysis

was performed through the

Rheticus® cloud platform, which

implements the SPINUA Multi-


Fig. 5 - Palu® reconstruction monitoring service user interface with the integrated reconstruction

status and displacement information.

Temporal Interferometry algorithm

for SAR data processing.

The SPINUA processing chain

is developed by GAP srl, a spinoff

company of Politecnico di

Bari, Italy, in order to generate

ground motion maps. SPINUA

algorithm has been extensively

tested and validated in the past

20 years with long stacks of SAR

data (acquired in L, C and X

bands) with particular attention

to research activities aimed at

improving the state of the art of

SAR techniques. These activities

are carried out in collaboration

with academic and research

institutions. As documented in

the scientific literature, SPINUA

represents one of the first and

effective solutions for multitemporal

SAR interferometry.

SPINUA is based on Persistent

Scatterers and Distributed

Scatterers Interferometry relying

on the identification and monitoring

of single objects (PS) or areas

(DS) that remain highly coherent

through time.

The Rheticus platform is a multitenant

high level performing

cloud-computing platform for

the automatic massive processing

of long-time series satellite

data, retrieved directly thanks

to the API connection to the

satellite providers (e.g. ESA API

Hub Access). The high level of

automation along with a dedicated

detailed logging and alert

system allows an easy monitoring

of the processing chain status.

Rheticus output is also available

in Machine to Machine mode

(M2M) via standard exchange

protocols (e.g. WMS), making

the platform an information hub

that delivers content to other

online systems. Export capabilities

of data and information are

also available, allowing users to

download products in standard

formats, and facilitating their

exploitation in other external application

environments.

KEYWORDS

earthquake; risk; EO based services; monitoring; rheticus;

cloud-computing; automatic processing; data satellite

ABSTRACT

On September 28,2018, a 7.5 magnitude earthquakestruckthe

island of Sulawesi, Indonesia. The epicentre was the provincial

capital of Palu, located on a bay on the island’s northwest coast. The

quake triggered a tsunami that swept 10-meter tallwavesof seawater

and swamped the city. The combination of the earthquake,

tsunami, soil liquefaction and landslides claimed well over 2000

lives, destroyed homes, buildings, infrastructuresand farmland

in several districts.Recognizing the need to relocate settlements

from the liquefaction-prone areas, the Indonesiangovernment

developed the Master Plan for Recovery and Reconstruction for

Central Sulawesi through the EARR and SWIP projects.

Indra and Planetek Italia contributed to the implementation of

this plan with a batch of EO-based services. The main information

provided was related toterrain deformation mapping (before

the earthquake)followed by the update of terrain information

mapping (in the months immediately after the earthquake)and

reconstruction monitoring with Very High Resolution images.

The collaboration went onwith a capacity-building workshop

and aknowledge transfer activity held in Jakarta in June 2019

regarding the technical aspects of the delivered products andtraining

sessionsfor local users to teach them to use the Geohazards

Exploitation Platform (GEP) of ESA.

AUTHOR

Vincenzo Massimi

RheticusTechnicalSpecialist

vincenzo.massimi@planetekitalia.it

Planetek Italia

Angelo Amodio (Planetek Italia) Angel Utanda,

Alberto Alonso (Indra Sistemas), Philippe Bally (ESA),

Paolo Manunta (ESA/ADB),

Davide Nitti, Raffaele Nutricato (GAP)

REPORT

BIM PER LE INFRASTRUTTURE

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Inizia il tuo viaggio BIM:

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Autodesk, the Autodesk logo, AutoCAD, Civil 3D, InfraWorks, and Revit are registered trademarks or trademarks of Autodesk, Inc., and/or its subsidiaries

and/or affiliates in the USA and/or other countries. All other brand names, product names, or trademarks belong to their respective holders. Autodesk

reserves the right to alter product and services offerings, and specifications and pricing at any time without notice, and is notresponsible GEOmedia for n°3-2020 typographical 29

or graphical errors that may appear in this document. ©2020 Autodesk, Inc. All rights reserved.

AUGMENTED REALITY

GARTNER CONFIRMS THE AUGMENTED REALITY

IN THE TOP TEN OF THE MAIN TECHNOLOGICAL

TRENDS, WHILE THE INTERACTIVE HOLOGRAPHIC

VISUALIZATION TECHNIQUE BEGINS TO

EXPERIMENT WITH INNOVATIVE AND INTERESTING

IMPLEMENTATION PROCEDURES.

XR 2020:

News & Events

by Tiziana Primavera

Innovative Tech

Evangelist - AR/VR

senior expert

To date, the market for interactive

visual technologies

is certainly rapidly growing, a

decade has passed since the first

curves of Hype (The Hype Cycle

model is a methodology developed

by Gartner, an information

technology consultancy, research

and analysis firm, to graphically

represent the maturity, adoption

and application of specific

technologies.), which described

the likely trend of the technologies,

at the pioneering and progressive

times (Fig. 1).

Undoubtedly confirming what

he had described, currently in

his Top Ten, concerning upcoming

trends in the technology

sector, Gartner outlines an evolutionary

overview of possible

scenarios and includes an interesting

development that specifically

characterizes augmented

reality.

In fact, this technology, today

definitely matured from the

point of view of hardware and

software, is used in many sectors,

to induce a sensory overcoming

- from this specific point of view,

it is possible to make a classification

of contemporary technologies

covering the following

categories:sensory (hearing,

vision, perception); (exoskeletons,

prostheses); (implants for

the treatment of seizures); gene

therapy and cell therapy - expanding,

improving experiences of

a human or physical cognitive

nature.

Its recent and possible integration

with artificial intelligence,

also makes it ready for a considerable

overcoming of the current

limits currently experienced, to

project itself towards new interesting

and sophisticated application

frontiers (Fig. 2).

The possible impacts in the

production sectors and social

life, the possible behavioral repercussions

in daily life or in the

business sectors make augmented

reality as one of the top 10

technological trends identified

by therefore mentioned consultancy/analysis

for the next 5-10

years.

Today, major international players

are aiming for a progressive

and growing democratization of

AR (AR stands for “augmented

reality) technology, simplifying

and not only significantly improving

development and implementation

procedures and tools

for developers or end users.

In fact, we are witnessing the

recent phenomenon of the integration

of AR systems, also of

the "easy to use" type, all within

socially well-known applications,

(e.g. Instagram, Snapchat) or

Fig. 1 – A) Schematization of the Hype Cycle, which characterizes the main stages of evolution of each technology. B) Interesting to observe that in 2009 augmented

reality began its rise progressively, and was classified as one of those technologies destined to become mainstream over a period of about 5-10 years.


AUGMENTED REALITY

basic applications dedicated to

productivity, such as Teamviewer

pilot, which, relying on its own

relevant global market of about 2

billion installations, has therefore

distorted the concept of remote

assistance, ensuring a highly progressive

image in line with new

functional needs.

Using SLAM, Simultaneous

Localization and Mapping

technology, the application allows

spatial reconstruction of

the surrounding environment

to allow you to locate the objects

placed in it.

This allows operators no longer

only mirroring video streams,

but also the ability to highlight

objects and/or supersede indicative

arrows, to facilitate the

understanding of the maintenance

procedure for those who are

carrying out the assistance work.

All this is easy without having

special programming skills or relevant

to the sector (Figg. 3-4).

But if you turn your attention

to the most complex functional

scenarios, you can in a custom

taylor perspective, witness

countless more articulate and

complex augmented reality applications,

designed to increase

safety or productivity in different

industries, to improve the ability

to make decisions in a reduced

time with the help of information

related to the context of use.

In fact, there are many AR/VR

systems developed internationally

in professional fields in the

health sectors - with diagnostic

imaging it is possible to reconstruct

the physiological anatomy

of sick organs of a single patient

e.g. eyeball / brain / spine etc..),

and thanks to the over-imposition

of such three-dimensional

data in Mixed Reality during the

intervention, with an accurate

real-virtual collimation, it is

possible to proceed with surgeries

with special awareness and

operational precision. In some

Fig. 2 - Real-time detection, vision systems able to "detect" thefruits and understand the degree of maturity in order

to be collected, even in environmental contexts in rather complex and artificial environments.

areas, the surgery is even assigned

to robotic-guided femtosecond

lasers, able to recognize

the characteristics and be able to

proceed to the custom surgery.

(surgical optics) - AEC, Cultural

Heritage, marketing/ADV or

training contexts, just to name a

few or to improve learning and

considerably improve cognitive

processes in the areas of training

and/or training on the job.

One aspect that concerns this

progressive and utilitarian mainstream

adoption is that it inevitably

has several implications of a

not only cultural but also ethical

nature.

On the other hand, it is clear

that research, innovation has

Figg. 3-4 Land images show the ability to communicate interactively with maintenance staff by marking points of

interest or inserting explanatory arrows remotely (Teamviewer pilot).


AUGMENTED REALITY

considerably faster times than

governments in legislating in

this regard, and international

alignment is desirable in order

to balance development opportunities

and side risks inherently

associated with the social introduction

of each new technology.

Sensitive issues recently discussed

by the CEO of Google in

Brussels.

Next-generation interactive

holograms open new paths to

visual research

Alongside an advanced stage

inherent in the Mixed Reality

sector, it is interesting at the

same time to observe the first

steps of extremely innovative

research, aimed at pursuing

the perceptual increase of reality,

thanks to the creation of

three-dimensional interactive

holograms generated with an

innovative calculation procedure,

extremely faster and manageable

with not particularly powerful

hardware.

The new algorithms make it possible

to significantly reduce the

processing of three-dimensional

data, paving the way for nextgeneration

augmented reality

devices.

The academic research team

(Takashi Nishitsuji, Tomoyoshi

Shimobaba, Takashi Kakue e

Tomoyoshi Itoha) found that

a complete rendering of 3D

polygons for all applications was

unnecessary, and focused exclusively

on the three-dimensional

representation of the edges, it

was able to significantly reduce

the computational load of hologram

calculations (Holography is

an optical technology of storing

visual information in the form

of a very fine interweaving of

interference fringes with the use

of coherent, properly projected

laser light; the image created by

the interference fringes is characterized

by an illusion of threedimensionality).

The method is extremely fast,

56 times faster than conventional

algorithms, but above all it

significantly lowers the computational

load and does not require

a responsible graphics processing

unit (GPU).

Essentially, faster calculations on

simpler cores translate into the

possibility of using lighter, more

compact and, above all, energyefficient

devices, which for these

specificities can be used in a wider

range of applications.

It is therefore hypothesized versatile

heads-up display (HUD)

on the windshields of cars/aircraft/ships

in support of their

driving or new near-eye devices

(NED)capable of transmitting

instructions on technical procedures.

This is a first step in the frontier

of traditional holographic

research to support AR, reminiscent

of the first wireframe

export trials of digital artifacts

in AR more than a decade ago,

but certainly these new technologies

of classical holography

will also evolve and contribute

to characterize new perceptual

modes of the space around us,

which will be permeated by new

interpretative semantics or new

features, certainly different and

broader in its experiential meanings

from how we have perceived

it to date.


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REPORT

Control and monitoring of the

Znosko Glacier in Antarctica

by Fabian Brondi Rueda, Gabriele Garnero, Giovanni Righetti, Stefano Serafini

Fig. 1 - Location of the area (j=62° 06’ S, l= 58° 28’ W)

Since the 1990s, Peru’s IGN (Instituto Geográfico Nacional)

has carried out intensive documentation and monitoring

activities in the Antarctic territories. During the last few years,

these activities have focused on the Znosko glacier.

The importance of this project is based on the generation of

correct digital elevation models (DEM).

In fact, a correct geodesic setting allows to obtain high

resolution geospatial products. These inputs represent the

fundamental support for the study of the glacial mass balance

by institutions such as ANA (Autoridad Nacional del Agua) and

INAIGEN (Instituto Nacional de Investigación en Glaciares y

Ecosistemas de Montaña).

This paper clarifies survey activities carried out so far, analysis

and results achieved, and perspectives for next missions.

Monitoring activities were carried out in an international

cooperation context, involving the Instituto Geográfico

Nacional (PE) and MEDS AMSTERDAM BV Society (NE) under

the scientific supervision of Politecnico di Torino (ITA).

The Instituto Geográfico

Nacional activity in Antarctica

The Instituto Geografico Nacional,

as head of geospatial information

in Peru, collaborated

with the other participating institutions,

providing them technical-cartographic

support during

the development of research

projects. During this collaboration,

topographic maps were

generated in the areas adjacent

to the Machu Picchu Science

Station.

The missions covered various

scientific aspects, such as:

4environmental factors regulating

the distribution of bentonite

organisms;

4sampling of ice coring for the

measurement of environmental

isotopes;

4study of the potential of Antarctic

lichens as indicators of

climate change;

4geomorphology and glacial

assessment of Punta Crepín;

4macro-algae acquisition and

their dehydration.


REPORT

Fig. 2 - The environment

of Znosko Glacier.

Fig. 3 - Passive geodesic network of the IGN in Antarctica.

Area

Sup. ha

Znosko 900

Langer 400

Wiracocha 1000

Monte Flora 200

Petrel gigante 135

Tab. 1 – Survey areas and extensions

The ongoing climate changes

have pushed research groups,

such as ANA and the Servicio

Nacional de Meteorología and

Hidrología del Perú; to generate

geospatial information on the

Znosko glacier.

Znosko Glacier

Znosko glacier is located in the

southern Shetland Islands, in

territories claimed by Argentina,

Chile and UK.

Located at an average altitude

of 22 m above sea level, the terrain

around the glacier is hilly:

highest nearby point is Admiral

Peak, 305 meters above sea level,

located 1.3 kilometers south the

glacier.

This territory is not anthropized,

in fact the nearest inhabited locality

is the Brazilian station

Commandante Ferraz, about

5 kilometers east of the glacier,

and the Peruvian station Machu

Picchu.

Gen-19 Feb-20 Difference Displacement

ELEV.

ELEV.

ELEV.

NAME East North

GEOID East North

GEOID East North

GEOID DIST. DIREC.

ANTAR XXVI 1 423421.479 3116628.701 4.098 423421.485 3116628.684 4.092 -0.006 0.017 0.006 0.018 SE

ANTAR XXVI 2 425890.704 3117550.113 10.061 425890.700 3117550.118 10.102 0.004 -0.005 -0.041 0.006 NW

ANTAR XXVI 3 425656.967 3115914.359 40.038 425656.967 3115914.351 40.032 0.000 0.008 0.006 0.008 S

ANTAR XXVI 4 430017.689 3116142.604 17.882 430017.693 3116142.609 17.898 -0.004 -0.005 -0.016 0.006 NE

ANTAR XXVI 5 431716.898 3116130.278 2.504 431716.882 3116130.282 2.503 0.016 -0.004 0.001 0.016 NE

ANTAR XXVI 6 430628.472 3113947.196 11.212 430628.470 3113947.203 11.213 0.002 -0.007 -0.001 0.007 NW

ANTAR XXVI 7 427494.726 3110835.728 37.729 427494.739 3110835.725 37.734 -0.013 0.003 -0.005 0.013 SE

ANTAR XXVI 8 422688.250 3110417.789 9.988 422688.264 3110417.784 9.981 -0.014 0.005 0.007 0.018 SE

TUM01 423494.774 3113442.19 41.393 423494.698 3113442.2 41.47 0.076 -0.007 -0.077 0.076 NW

Tab. 2 – The IGN passive network


REPORT

the order of 2.5-3 hours each,

useful for evaluating the overall

stability of the area and the tectonic

movements of these plates.

Interpretation of data in this

table, currently drafted in UTM

SIRGAS-ROU98 zone 21E coordinates,

reveals a significant

movement of all points; among

these, the TUM01 summit in

particular has a translation of

over 7 cm in one year only.

For example, Italy has a global

movement of the order of 3 cm/

year in the direction N-NE,

which decreases to 2-3 mm/year

if assessed with European references,

with different orientations

depending on the tectonic

micro-plates.

The interest so far aroused by the

evidence of these movements

suggests rescheduling the execution

of the measures for the next

five years, in order to evaluate

with increased accuracy detected

data. Eventually new coordinates

will be included into the

global reference system IGS14.

Fig. 4 – RTK Survey Antar XXVII - Training set (green dots, 70%) and Test set (red triangles, 30%).

Monitoring of the Znosko glacier:

Missions XXVI and XXVII

Missions XXVI and XXVII were

carried out respectively in January

2019 and February 2020.

They involved, in addition to

the Znosko glacier, also other areas

subject to photogrammetric

survey to create a digital model

and orthoimages (Table 1).

Overall stability check

In the last 2 years, a passive

monitoring network has been

set up covering 9 points, among

which were measured with static

geodetic measurements some

baselines with observations of

Glaciers geometries evaluation

To evaluate the geometry of the

glacier and therefore estimate the

involved volumes, it was considered

appropriate to use only the

basic data obtained from GNSS

measurements in RTK mode.

In fact, there are reliability problems,

in using autocorrelation of

images mostly occupied by ice,

and therefore devoid of recognizable

textures and elements.

Altitude profiles with an average

wheelbase of around seventy

meters were used, these were

obtained in the 2019 (Antar

XXVI) and 2020 (Antar XXVII)

campaigns.

Differential corrections were

performed, using a pair of

points near the detection area,

resting on the ASTA reference

vertex positioned near the flagpole

of the Machu Picchu base.

Fig. 5 - Digital model and altimetric contour lines variations between the XXVI and XXVII campaigns.


REPORT

Fig. 6 - Comparisons between the situations 2019 (A) and 2020 (B).

Interpolator model estimating

In order to identify the optimal

interpolator model based on distribution

of points and conformation

of soil, it was decided to

proceed with an estimate of the

residues derived from the application

of different interpolating

models, based on previous research

experiences.

A subset of data training (70%

of the total) -only for the dataset

constituted by RTK points,

obtained in February 2020 for

a total of 1406- was selected,

while the remaining part was

considered as a test.

The models used were the following:

4IDW with exponent 2;

4Kriging with spherical semivariogram;

4Spline with smoothing of

both the surface and the first

derivative, all with a minimum

number of 12 points.

Synthetic results are reported

in Table 3.

Fig. 7 - Comparisons between the situations 2019 (A) and 2020 (B) for the NE zone of Figure 6.


REPORT

IDW Kriging Spline

Media -0.291 -0.135 0.048

Varianza 2.530 0.459 0.632

Max_Ass 3.032 1.065 5.464

Tab. 3 – Residuals on the different interpolator models.

Based on the evaluated residues,

it was preferred to operate

using the Kriging algorithm

on all available datasets.

Ablation analysis

(2020 vs 2019)

The altimetric differences estimation,

highlights a discrete

variability of the snow surface.

This variable becomes

important if assessed in relation

to the short period of time

elapsed between the two findings

(13 months). The ablation

is significant on the whole area

subject to RTK investigations,

with average values in the order

of 4-5 meters.

Significant area variations were

also found.

Fig. 6 shows the variation between

the ortho-image of the

2019 and 2020 campaigns:

In this, the digitization performed

on the basis of the orthophoto

of the year 2020 (B),

is compared with the orthophoto

of the year 2019 (A).

This simple analysis highlights

the retreat of the ice (the mixed

land-ice areas are highlighted

with a dotted background).

The difference mentioned

above, in linear terms, in various

cases reaches hundreds of

meters.

When considering the uncovered

terrain, less significant

differences are observed, especially

when compared with

the phenomenon previously

described.

An interesting detail is easily

appreciated in the North-West

area (Fig. 7), in this, the limits

of the frozen area, (highlighted

by the arrow), show an advance

of the surface towards

the sea, a sign of an evident

spillage phenomenon.

This collapse affects a large

area with an advancement of

the front of about 70 m.

Future projections

This surfaces study, highlights

a huge decrease in the ice mass

during the year 2020 compared

to the year 2019, and in

the same period a significant

process of the transfer into the

sea, probable consequence of a

glacial collapse.

As mentioned above, given

the obvious limitations of the

DEM models derived from

photogrammetry, only the

RTK survey was used for model

generation.

While representing a robust

methodology, going through

glaciers by foot with geodesic

tools has at least three critical

issues:

4not adequate for the analysis

of large extensions;

4difficult to repeat due to the

hostility of the surrounding

environment;

4high risk for the safety of the

personnel involved in the execution

of the survey.

The hope is to overcome the

limitations and problems mentioned

above in the coming

campaigns, through the integration

of LiDAR systems to

be used in the analysis of larger

surfaces.

Acknowledgments

The authors thank General de

Brigada Fernando PORTILLO

ROMERO, Jefe of the Instituto

Geográfico Nacional of Peru.

REFERENCES

GARNERO, G.; GODONE, D.

(2013) Comparisons between different

interpolation techniques, The International

Archives of the Photogrammetry,

Remote Sensing and Spatial Information

Sciences, Volume XL-5/W3 (ISSN: 2194-

9034), Pagg. 139-144 [DOI: 10.5194/

isprsarchives-XL-5-W3-139-2013,

WOS:000358309600021, SCOPUS:

2-s2.0-84924290459].

MOTTA, M.; DIOLAIUTI, G.; VAS-

SENA, G.; SMIRAGLIA, C. (2003) Mass

balance and Energy balance at Strandline

Glacier (Terra Nova Bay, Antarctica):

Methods and preliminary results, Proceedings

of the 4th Meeting on Italian Antarctic

Glaciology, Terra Antarctica reports n.8,

Editors: Massimo Frezzotti & Valter Maggi,

pp. 21-28, Siena.

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antartide.pdf

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comercio-antartida-retroceso-glaciarznosko-noticia-611907-noticia/

https://www.cnbc.com/2020/04/30/

climate-change-antarctica-greenland-ice-

melt-raised-sea-levels-by-half-inch-in-last-

16-years.html

https://www.theguardian.com/environment/2020/mar/11/polar-ice-caps-meltingsix-times-faster-than-in-1990s

https://www.scientificamerican.com/article/

heres-how-much-ice-antarctica-is-losingmdash-its-a-lot1/

https://climate.nasa.gov/vital-signs/icesheets/

KEYWORDS

Antarctica; survey; geodesic network;

geospatial; DEM; glacial mass balance

ABSTRACT

The study and analysis of climate change

is a global challenge against which environmental,

but also economic and social

changes, will be measured.

This memorandum illustrates the recent

activities carried out by the IGN Peru in

collaboration with European institutions.

AUTHOR

Fabian Brondi Rueda

fabianbrondi@hotmail.com

IGN - Instituto Geográfico Nacional,

Lima (PE)

Gabriele Garnero

gabriele.garnero@unito.it

DIST – Politecnico e Università degli

Studi di Torino (ITA)

Giovanni Righetti

g.righetti@medsamsterdam.eu

Stefano Serafini

s.serafini@medsamsterdam.eu

MEDS BV – Hengelo (NL)


REPORT

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40 GEOmedia n°1/2-2020

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FORMAZIONE

GEOmedia n°1/2-2020 41

RICERCA E INNOVAZIONE

AEROFOTOTECA

L’AEROFOTOTECA

NAZIONALE

RACCONTA....

The Role of the Air

Photographic Archive at the

ICCD in Interpreting the

Archaeology of the Tiber Delta

and the Isola Sacra

by Kristian Strutt

Between 1998 and 2012, the

Portus Project investigated the

archaeology of Rome’s Imperial

port and its surrounding

area through archaeological

fieldwork. The project, directed

by Prof. Simon Keay at the

Department of Archaeology,

University of Southampton,

was a collaborative effort involving

the Universities of

Southampton and Cambridge,

the British School at Rome and

the Parco Archeologico di Ostia

Antica together with other organisations.

A significant portion

of the project work in the field

consisted of non-intrusive archaeological

survey, comprising

geophysical survey (Fig. 1),

fieldwalking and topographic

survey (Fig.2). The first years

of the project (1998-2004)

consisted of geophysical survey

and fieldwalking around Portus

and the environs of the Imperial

port (the results of which are

published in Keay et al. 2005).

Subsequent survey (2008-2012)

was also conducted in the area

between Portus and Ostia

Antica, the Isola Sacra, to investigate

the nature and extent of

the archaeological remains linking

Portus to the city of Ostia

(results of the Isola Sacra survey

are due for publication this

summer in Keay et al. forthcoming).

The project covered

much of the overall landscape

with geophysical survey (Fig.

3), and the work provided an

opportunity for utilising an integrated

approach to landscape

Fig. 1 - Fluxgate gradiometer magnetometry being carried out on the Isola Sacra (photo:

K. Strutt).

archaeology, drawing not only

on the main field methods used

in the profession, but using

other datasets available from archive

sources, including satellite

imagery, LiDAR and archaeological

database entries, work

which also formed the basis of

the author’s doctoral research

(Strutt 2019). Use of archive

data also provided the opportunity

to access and analyse the air

photographs held by the ICCD,

providing the most useful dataset

for the archive-based analytical

work, and results crucial to

the full interpretation of the

archaeology between Portus and

Ostia.

Previous Use of Air Photos in

the Tiber Delta

The use of air photographic

images for archaeology is not

Fig. 2 - Topographic survey being conducted using a GPS with base station and rover (photo:

K. Strutt).


AEROFOTOTECA

new, with pioneering work

being conducted in the first

years of the 20 th century in

particular (Crawford 1928;

Crawford and Keiller 1928;

Guaitoli 2003), and a balloon

flight forming the basis of

early aerial photographs of the

ancient city of Ostia in 1911

(Shepherd 2006). The nature

of the development of aerial

photography, and in particular

the advent of the technique for

military use, meant significant

developments in the technology.

The intense action in the

Mediterranean during World

War II also meant that a large

number of photographs were taken

by different air forces, principally

the Luftwaffe, the Royal

Air Force and US Airforce

(Shepherd 2013; 2013a).

The location of the Tiber delta

and Portus means that the area

formed the focus of intensive

reconnaissance photography

during WWII, much of which

has been deposited at the

ICCD. The photographs were

taken from different altitudes,

under different lighting conditions,

and at different times of

the year, allowing the researcher

to analyse material under varying

ground conditions, where

sub-surface archaeology may

show up only in certain seasons

or under particular crops.

These air photographs in the

area of the Tiber delta formed

the focus in some of Bradford’s

(1957) work, demonstrating the

form of the Trajanic Harbour

at Portus and the associated

Claudian Canal. The approach

devised by the Portus Project in

reassessing this landscape also

provided an opportunity to

integrate the air photographic

records held at the ICCD.

The Portus Project and the

Survey of the Isola Sacra

The primary use of the air photographs

from the Aerofototeca

at the ICCD was to secure

high and low altitude photographs

for the area surrounding

Portus. Different swathes of

photography, digitised in the

archive, were geo-referenced

using ArcGIS software, to form

a background of air photos for

the project (Fig. 4). Many of

the archaeological features in

the vicinity of Portus showed

in these images, in which the

RAF photos were used. Features

showing in the photographs

were digitised, allowing the

overlay of these features with

our geophysical survey interpretations.

These, together

with the interpretations of

satellite imagery, overlaid with

data from the archaeological

gazetteer, formed the basis of

the analysis and interpretation

of the landscape (Keay et al.

2005; Keay et al. 2014; 2014a;

Keay et al. forthcoming; Strutt

2019).

While this methodology provided

contextual information on

a number of sites and features

in this landscape, many showed

both in the results of the geophysical

survey and in the air

photographs. One particular

Fig. 3 - Coverage of geophysics for the area of Portus and the

Isola Sacra, showing the magnetometry and the large-scale

landscape approach taken by the research.

example illustrates the absolute

necessity of integrating the historic

air photographs with the

project survey data. Our survey

of the Isola Sacra had provided

Fig. 4 - A composite of RAF air photographs from the Aerofototeca of the ICCD.


AEROFOTOTECA

evidence of a possible ancient

canal crossing the area between

Portus and Ostia (Keay et al.

2011). As the survey progressed

it was not always possible to

gain access to survey particular

areas of the landscape. Analysis

of modern satellite imagery

proved that much of the survey

area had been built on in the

latter part of the 20th century.

It was to the historic air photographs

that the project team

turned in an effort to glean as

much evidence of the archaeology

as possible. The RAF

photographs showed very little

on the Isola Sacra, in direct

contrast to the area around

Portus. However, investigation

of the photographs taken by

Fig. 5 - Photograph taken by the Aeronautica Militare (AM_1957_149_1_23_62640_0 a) showing

Portus, Ostia and the Isola Sacra. It is these photos that show, faintly, the line of the Roman canal

across the Isola Sacra.

Fig. 6 - Composite image with the results of the magnetometry overlaid on the

Aeronautica Militare air photo, showing the coverage of the geophysics, and how

the tracing of the east side of the canal would not have been possible without integrating

methods.

the Aeronautica Militare in

1957 revealed photographs that

indicated a faint linear feature

across the study area (Fig. 5).

As the survey progressed on the

ground, the results of the magnetometry

were integrated in

our GIS with the images taken

by the Aeronautica Militare,

showing that the feature marked

the eastern side of an ancient

Roman canal, traversing the

Isola Sacra from Portus to the

bank of the Tiber opposite

Ostia. Varying access to land

meant that much of this area

could not be surveyed, and thus

the air photographs formed

a critical component of the

analysis and interpretation for

the archaeology of the area (Fig.

6).

The archives of the Aerofototeca

at the ICCD proved crucial to

the full analysis of this important

archaeological landscape,

and the combination of different

techniques provided a

strong methodological approach

to the study of the area.


AEROFOTOTECA

REFERENCES

Bradford, J.S.P. (1957), Ancient Landscapes: Studies in Field Archaeology. London; G. Bell and Sons.

Crawford, O. G. S. (1928) Air Survey and Archaeology. Norwich: Ordnance Survey.

Crawford, O. G. S. and Keiller, A. (1928) Wessex from the Air. Oxford: Clarendon Press.

Guaitoli, M. (2003) Lo sguardo di Icaro. Le collezioni dell’Aerofototeca Nazionale per la conoscenza del territorio. Roma: Campisano.

Keay, S., Millett, M., Paroli, L. and Strutt, K. (2005) Portus. London: The British School at Rome and Soprintendenza Archeologica di Ostia.

Keay, S., Millett, M. and Strutt, K. (2014) ‘The canal system and Tiber delta at Portus.

Assessing the nature of man-made waterways and their relationship with the natural environment’, Water History, 6(1), 11–30.

Keay, S., Parcak, S. and Strutt, K. (2014a) ‘High resolution space and ground-based remote sensing and implications for landscape archaeology: the case from

Portus, Italy’, Journal of Archaeological Science, 52, 277–292.

Shepherd, E. J. (2006) ‘Il “Rilievo Topofotografico di Ostia dal Pallone” (1911)’, Archeologia Aerea 2,15–38.

Shepherd, E. J., Leone, G., Negri, A. and Palazzi, D. (2013) La collezione aerofotografica British School at Rome (BSR) conservata in ICCD-Aerofototeca

Nazionale (AFN). Report 2013 sullo stato di avanzamento delle attività. Rome.Ministero dei Beni e delle Attività Culturali e del Turismo.

Shepherd, E. J., Palazzi, D. S., Leone, G. and Mavica, M. M. M. (2013a) ‘La collezione c . d . USAAF dell’ Aerofototeca Nazionale. Lavori in corso’, Archeologia

Aerea, 6,13–32.

Strutt, Kristian, David (2019) Settlement and land use in the Tiber Delta and its environs 3000 BC – AD 300. University of Southampton, Doctoral Thesis.

https://eprints.soton.ac.uk/433953/

ABSTRACT

The air photographic archive of the ICCD provides an essential resource for archaeological research in Italy and the Mediterranean.

This paper reviews the use of archive material for the Portus Project, and its role in interpreting the ancient landscape of Portus

and Ostia at the mouth of the river Tiber, where analysis of air photos was integrated with geophysical survey and archaeological

fieldwork.

KEYWORDS

Archaeology; Geophysics; Portus; Maritime Archaeology; Roman; Landscapes; Magnetometry; Air Photographs; ICCD

AUTHOR

Kristian Strutt

kds@soton.ac.uk

Department of Archaeology, University of Southampton

Highfield, Southampton, SO17 1BF

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