Workshop Proceedings - Inter Islamic Network on Space Sciences ...

Theme 1: Country Reports
Application of Remote Sensing for Agricultural Statistics: The Tunisian
Experience
Talhaoui Wafa, Haffani Myriam, Sghaier Nabil, Bacha Sinan, Sayah Najeh,
Othmani Sofiane and Bouzguenda Neila
Abstract
Monitoring, estimating and forecasting of agricultural
production are very important for managing the regional
and local food security. Thus, it is necessary to have a
powerful strategy for making agricultural statistics by the
use of efficient tools. In this paper; we present the Tunisian
experience in the use of remote sensing technologies for
the estimation of cereal areas, yield and production.
and variability from the point of view of climate and cereal
crop behavior as well as production.
This paper shall present the methodology adopted and
the results obtained in the estimation of cereal areas,
using three different approaches: The first approach
adopts the Classification methods using SPOT images, the
second approachs uses statistical methods by means of
vegetation index extracted from Spot Vegetation data and
the third one uses a statistical model.
Introduction
In Tunisia, cereal is one of seven strategic agricultural
products. Hence, it is an imperative need for policy makers
to forecast early productions to engage the necessary
provisions on cereal importation, crop management,
storage, processing, etc.. Thus, it is necessary to have a
powerful strategy for making agricultural statistics by the
use of efficient tools to enhance and improve the present
statistical methods in the ministry of agriculture.
Methodology
Fig. The Study area
Objectives and Framework
The project is titled “Cereal Monitoring and Forecasting
of Wheat and Barley Production by Remote Sensing. The
ultimate objective of the project is to develop an
operational system for monitoring and forecasting of
cereal crops.
The project was implemented over a period of three years,
which consists of three phases: The first phase was
allocated to the data collection and preparation. The
second phase consisted of the development of
methodology and model parameters, while in the final
phase the work shall be completed by developing an
operational forecasting system.
Study Area
The study area is constituted by ten provinces of Tunisia
(Fig. 1); These provinces are dominated by cereal crop.
Seven of them are located in the North and three in the
Center of Tunisia. The study area presents an heterogeneity
Remotely sensed data have been widely used in the field
of agriculture mainly for cereal area estimation, cereal
crop monitoring and cereal yields estimation. To achieve
our objectives, we adopted a methodology based on the
analysis of remotely sensed data extracted from a low
resolution satellite image “Spot Vegetation”. Also, we
used also high resolution satellites images of Spot 5.
Spectral response characteristics of healthy vegetation
can easily be characterized in different parts of the
electromagnetic spectrum. To further enhance the
discrimination between different spectral vegetation
classes, computation of different vegetation indices using
infrared and red band data in the electromagnetic
spectrum, for describing the crop growth conditions, are
commonly used.
The commonly used vegetation index is the Normalized
Difference Vegetation Index (NDVI) defined as:
NDVI = IR–R / IR+R
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