EuroSDR Projects - Host Ireland

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Detection of buildings was not a big problem in SAR and the optical imagery, due to the large size of industrial buildings. Regarding the classification of parking areas, one can say that the big ones were detected and classified in optical and even in SAR images. The smaller ones lead to more problems in SAR imagery. The same is essentially true for bridges and land use boundaries. Table 8 shows an overview of qualitative comparison. Main Road Roads Alleys Built-Up Areas Parking Runway Railway 208 SAR image detected predominantly detected few to none well detected but no distinction of industrial or urban areas, separate big houses were detected well big parking areas could be detected detected partially detected 5.3.3 Summary – Oberpfaffenhofen land use boundary, bridges Optical image detected detected predominantly detected well detected but no distinction of industrial or urban areas, separate houses were detected well, even small ones mostly all parking areas were detected detected all interpreters detected the railways well Table 8: Qualitative Comparison of Oberpfaffenhofen Although the resolution of sensor data is a bit higher compared to the test sites of Copenhagen and Fjärdhundra (3 m instead of 4 m), there are no significant discrepancies between interpretations of these test sites. Accuracy and quality of interpreting forest, agricultural and built-up areas as well as linear objects show results similar to those in Copenhagen and Fjärdhundra. Regarding the special areas of this test site, it was surprising that nearly all participants detected and classified the excavation area correctly. More problems occurred in the interpretation of the airport area. Special regions on this site could be detected, but were not classified well. These problems, however, were equal in SAR and optical imagery. Thus, it appears that industrial areas with very special land uses and objects are almost impossible to interpret correctly. 5.4 Test Site Trudering 5.4.1 Areal and Linear Objects The data set of the Trudering test site mainly contains rural and industrial areas and has a resolution of 1.5 m per pixel, which is the highest resolution among the test imagery. The images have a size of 2813 x 2289 pixels. The evaluation of the optical image was carried out by four participants and the evaluation of the SAR image by seven participants. This test site predominantly consists of agricultural and built-up areas. The forest areas are small parts with few trees and only cover one percent of the image area. A small lake is located in the north west of the images, which appears different in SAR and optical images due to the exposure date of the images. Therefore, two different reference maps were created for this small area. Two other small parts of the images have different content so they were covered with a small mask to avoid discrepan-
cies in analysis. The following figures (Figure 29 - Figure 34) show the results of analyses for areal and linear objects. 120,00 100,00 80,00 60,00 40,00 20,00 0,00 Agriculture - sar Interpret 1 Interpret 3 Interpret 5 Interpret 7 Interpret 9 falsch positiv 1,18 2,12 1,12 1,42 0,44 falsch negativ 9,47 5,32 6,85 7,93 9,33 richtig 90,53 94,68 93,15 92,07 90,67 120,00 100,00 80,00 60,00 40,00 20,00 0,00 Built-Up - sar falsch positiv 5,13 11,05 10,39 12,82 19,44 falsch negativ 11,97 3,45 3,46 5,11 5,46 richtig 88,03 96,55 96,54 94,89 94,54 160,00 140,00 120,00 100,00 80,00 60,00 40,00 20,00 0,00 120,00 100,00 80,00 60,00 40,00 20,00 Figure 29: Trudering Result, Agricultural Area Interpret 1 Interpret 3 Interpret 5 Interpret 7 Interpret 9 Forest - sar falsch positiv 14,37 1,24 4,57 45,10 48,04 falsch negativ 55,05 39,95 33,52 41,84 49,88 richtig 44,95 60,05 66,48 58,16 50,12 0,00 Agriculture - optic Interpret 2 Interpret 4 Interpret 8 Interpret 10 falsch positiv 1,92 0,47 3,76 0,00 falsch negativ 5,40 9,19 2,67 0,00 richtig 94,60 90,81 97,33 0,00 120,00 100,00 80,00 60,00 40,00 20,00 0,00 Figure 30: Trudering Result, Built-Up Area Interpret 1 Interpret 3 Interpret 5 Interpret 7 Interpret 9 Built-Up - optic Interpret 2 Interpret 4 Interpret 8 Interpret 10 falsch positiv 13,51 12,00 8,58 0,00 falsch negativ 1,81 1,55 4,04 0,00 richtig 98,19 98,45 95,96 0,00 160,00 140,00 120,00 100,00 80,00 60,00 40,00 20,00 0,00 Figure 31: Trudering Result, Forested Area Forest - optic Interpret 2 Interpret 4 Interpret 8 Interpret 10 falsch positiv 0,36 3,50 19,03 33,67 falsch negativ 21,58 24,39 54,91 24,72 richtig 78,42 75,61 45,09 75,28 209
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European Spatial Data Research Nove
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PRESIDENT 2006 - 2008: Stig Jönsso
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H. Kaartinen and J. Hyyppä: EVALUA
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4.3.1 Data and study area..........
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2 QUESTIONNAIRES...................
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Abstract The objective of the EuroS
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The analysis of the structural qual
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Figure 2-3: Hermanni test site. Fig
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Espoonlahti Hermanni Senaatti Photo
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2.2 Reference Data 2.2.1 Field Meas
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Used data Time use Laser Aerial Gro
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Step 3: Import to CCModeler Figure
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Figure 3-4: Sequence of manual phot
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Figure 3-8: Workflow of laser scann
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Figure 3-11: Parametric building mo
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Each group of connected pixels clas
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Figure 3-18: Topological points and
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Detailed Description (Letters refer
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assumption is made: the two longest
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Figure 3-25: A 3D building model wi
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ICC used the same methods as Nebel
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where p75th is the value at the 75
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CyberCity Stuttgart Hamburg IGN ICC
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CyberCity Hamburg Stuttgart IGN ICC
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Height Cyber- City Hamburg Stuttgar
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Height Cyber- City Stuttgart IGN IC
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Height Cyber- City Stuttgart IGN IC
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Height Cyber- City HamburgStuttgart
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Height Cyber- City HamburgStuttgart
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All targets Eaves Ridges Height IGN
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CyberCity achieved a good quality i
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Point density, shadowing of trees a
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Height accuracy IQR [m] 1.6 1.4 1.2
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All Cyber- Ham- ICC laser+ Nebel+ I
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All Cyber- HamStutt- ICC laser+ Neb
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In building length determination (F
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degrees, std 6.3 degrees). In Senaa
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5 Discussion and Conclusions It can
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References Alharthy A. and Bethe, J
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Fraser, C.S., Baltsavias, E. and Gr
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Khoshelham K., 2004. Building Extra
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Sequeira, V., Ng, K., Wolfart, E.,
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Index of Figures Figure 2-1: Senaat
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Index of Tables Table 2-1: Aerial i
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90 Senaatti by Delft. Wireframe mod
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92 Espoonlahti by IGN, with and wit
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94 Senaatti by IGN, with and withou
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96 Hermanni by Aalborg.
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98 CyberCity ICC laser+aerial ICC l
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100 IGN FOI outlines Nebel+Partner
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Difference Images, Whole Test Site,
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Difference Images, Whole Test Site,
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Difference Images, Modelled Buildin
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Difference Images, Modelled Buildin
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EuroSDR-Project Commission 2 “Ima
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2 Project highlights The project Ch
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116 Feature Characteristics Object
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New are those combinations that ind
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120 Figure 4-1: Orthophotomosaic fr
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4.1.2 Segmentation The first step o
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124 Class Features Vegetation Ratio
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4.1.4 Change map As the results of
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Two types of changes were assigned
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130 Figure 4-11: Evaluation of chan
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132 Figure 4-13: Orthophotos of stu
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different villages were identified
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136 Figure 4-16: Change maps of Swi
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spectral reflectance. Shadows (blac
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140 Figure 4-19: Change map of Germ
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Figure 4-21: Diagnostics as given b
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144 Automatic Accepted Rejected Hum
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4.4.2 Segmentation, classification
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differentiated very well. The chang
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150 Figure 4-31: Ultracam real-colo
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152 Figure 4-35: Classification of
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154 Figure 4-38: Subset of change m
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5 Conclusions and Outlook In this p
Page 161: Annex 1 EuroSDR Change Detection Wo
Page 164 and 165: What is the impact of changing spat
Page 167: Annex 2 Paper presented at IGARSS05
Page 170 and 171: covering 2 x 2 km with reference da
Page 172 and 173: 170 Red roof Bright object 0 20 40
Page 175: Annex 3 EuroSDR CD Workshop Nicosia
Page 178 and 179: 176 method 1 indicates land cover c
Page 181: Annex 4 Comments on change map by B
Page 184 and 185: enzen mehr zu erwarten. Doch laut
Page 187 and 188: Abstract The EuroSDR “Sensor and
Page 189 and 190: 2 Test Sites and Test Data The test
Page 191 and 192: Figure 3: Data set Fjärdhundra, ag
Page 193 and 194: The map of Sweden is only available
Page 195 and 196: 3.2 Accounting for Different Acquis
Page 197 and 198: 4 Analysis 4.1 Basic Information In
Page 199 and 200: 4.2.2 Linear Objects Since it is no
Page 201 and 202: 5 Results of Phase I 5.1 Test Site
Page 203 and 204: 5.1.2 Qualitative Comparison In add
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Page 207 and 208: 5.3 Test Site Oberpfaffenhofen 5.3.
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Page 213 and 214: 5.4.2 Qualitative Comparison The ra
Page 215 and 216: Acknowledgments We thank all partic
Page 217: Index of Tables Table 1: Contest Ph
Page 221 and 222: Abstract Roads are important object
Page 223 and 224: overview over the whole area. We ra
Page 225 and 226: m and above no longer plays an impo
Page 227 and 228: 3 Test Data and Evaluation Criteria
Page 229 and 230: and straight enough. • Markus Ger
Page 231 and 232: Name (best) Test area Completeness
Page 233 and 234: • ADS40_1 and 2: Results for both
Page 235 and 236: • Ikonos1_Sub1: This image shows
Page 237 and 238: Figure 7: Ikonos3_Sub1 - Bacher; co
Page 239 and 240: Finally, we want to note some impor
Page 241 and 242: load nor response time for anybody
Page 243: Zhang, C., 2004. Towards an Operati
Page 246 and 247: objects, and their cooperation with
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Page 254 and 255: 7. What is the average time differe
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If others please specify: 2. What d
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Complex crossings (more than 4 road
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Combination of a) or b) with c) [0]
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If yes, using: DTM and / or [2] D
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Appendix 4: General Characteristics
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Most important features for practic
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IKONOS The images come from the SI
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Appendix 6: Documentation by Beumie
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Appendix 8: Documentation by Zhang
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LIST OF OEEPE/EuroSDR OFFICIAL PUBL
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25 Ducher, G.: Test on Orthophoto a
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EuroSDR Projects - Host Ireland

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