- Page 1 and 2:
European Spatial Data Research Nove
- Page 3 and 4:
PRESIDENT 2006 - 2008: Stig Jönsso
- Page 5 and 6:
H. Kaartinen and J. Hyyppä: EVALUA
- Page 7 and 8:
4.3.1 Data and study area..........
- Page 9:
2 QUESTIONNAIRES...................
- Page 13 and 14:
Abstract The objective of the EuroS
- Page 15 and 16:
The analysis of the structural qual
- Page 17 and 18:
Figure 2-3: Hermanni test site. Fig
- Page 19 and 20:
Espoonlahti Hermanni Senaatti Photo
- Page 21 and 22:
2.2 Reference Data 2.2.1 Field Meas
- Page 23 and 24:
Used data Time use Laser Aerial Gro
- Page 25 and 26:
Step 3: Import to CCModeler Figure
- Page 27 and 28:
Figure 3-4: Sequence of manual phot
- Page 29 and 30:
Figure 3-8: Workflow of laser scann
- Page 31 and 32:
Figure 3-11: Parametric building mo
- Page 33 and 34:
Each group of connected pixels clas
- Page 35 and 36:
Figure 3-18: Topological points and
- Page 37 and 38:
Detailed Description (Letters refer
- Page 39 and 40: assumption is made: the two longest
- Page 41 and 42: Figure 3-25: A 3D building model wi
- Page 43 and 44: ICC used the same methods as Nebel
- Page 45 and 46: where p75th is the value at the 75
- Page 47 and 48: CyberCity Stuttgart Hamburg IGN ICC
- Page 49 and 50: CyberCity Hamburg Stuttgart IGN ICC
- Page 51 and 52: Height Cyber- City Hamburg Stuttgar
- Page 53 and 54: Height Cyber- City Stuttgart IGN IC
- Page 55 and 56: Height Cyber- City Stuttgart IGN IC
- Page 57 and 58: Height Cyber- City HamburgStuttgart
- Page 59 and 60: Height Cyber- City HamburgStuttgart
- Page 61 and 62: All targets Eaves Ridges Height IGN
- Page 63 and 64: CyberCity achieved a good quality i
- Page 65 and 66: Point density, shadowing of trees a
- Page 67 and 68: Height accuracy IQR [m] 1.6 1.4 1.2
- Page 69 and 70: All Cyber- Ham- ICC laser+ Nebel+ I
- Page 71 and 72: All Cyber- HamStutt- ICC laser+ Neb
- Page 73 and 74: In building length determination (F
- Page 75 and 76: degrees, std 6.3 degrees). In Senaa
- Page 77 and 78: 5 Discussion and Conclusions It can
- Page 79 and 80: References Alharthy A. and Bethe, J
- Page 81 and 82: Fraser, C.S., Baltsavias, E. and Gr
- Page 83 and 84: Khoshelham K., 2004. Building Extra
- Page 85 and 86: Sequeira, V., Ng, K., Wolfart, E.,
- Page 87 and 88: Index of Figures Figure 2-1: Senaat
- Page 89: Index of Tables Table 2-1: Aerial i
- Page 93 and 94: Wireframe models of Espoonlahti, Se
- Page 95 and 96: Hermanni by IGN, with and without t
- Page 97 and 98: Amiens by IGN, with and without tex
- Page 99 and 100: CyberCity Hamburg ICC laser+aerial
- Page 101 and 102: CyberCity Hamburg ICC laser+aerial
- Page 103: Espoonlahti Senaatti Amiens Hermann
- Page 106 and 107: 104 Laser data only: ICC laser, FOI
- Page 108 and 109: 106 Laser data only: ICC laser, Aal
- Page 110 and 111: 108 Laser data only: ICC laser, FOI
- Page 112 and 113: 110 Laser data only: ICC laser, Aal
- Page 115 and 116: Abstract This report describes a me
- Page 117 and 118: Object based classifiers, such as e
- Page 119 and 120: Even though a rule based system is
- Page 121 and 122: Country Number of classes Single bu
- Page 123 and 124: Figure 4-3: Digital cadastral map o
- Page 125 and 126: 4.1.3 Classification Figure 4-6: Se
- Page 127 and 128: Figure 4-7: Classification of 1994
- Page 129 and 130: Figure 4-9: Result of evaluation of
- Page 131 and 132: DCM 2004 DCM 1994 Agriculture Build
- Page 133 and 134: 4.2 Switzerland 4.2.1 Data and Stud
- Page 135 and 136: 4.2.2 Segmentation, classification
- Page 137 and 138: Figure 4-15: Classification of Swis
- Page 139 and 140: 4.3 Germany 4.3.1 Data and study ar
- Page 141 and 142:
Land use Classification Forest Mead
- Page 143 and 144:
the archive have been selected for
- Page 145 and 146:
Figure 4-23: ATKIS data: green = gr
- Page 147 and 148:
German method. Since eCognition is
- Page 149 and 150:
Land use Classification Forest Mead
- Page 151 and 152:
Figure 4-29: Ultracam false-colour
- Page 153 and 154:
Figure 4-33: Classification of real
- Page 155 and 156:
The classification results were com
- Page 157 and 158:
Figure 4-40: Subset of change map f
- Page 159:
References BAATZ, M., SCHÄPE A., 2
- Page 163 and 164:
Change Detection Workshop 16.-17.6.
- Page 165:
Feedback will be given at next work
- Page 169 and 170:
Object-Oriented Classification of O
- Page 171 and 172:
Table 3 gives an overview over the
- Page 173:
data were selected as they contain
- Page 177 and 178:
Change Detection Workshop 26.10.200
- Page 179:
additional tests and/or adjustment
- Page 183 and 184:
Projekt „Change Detection“ z.H.
- Page 185:
EuroSDR-Project Commission 2 “Ima
- Page 188 and 189:
1.2 Contest Phases In phase 1 test
- Page 190 and 191:
188 Figure 1: Data set Copenhagen,
- Page 192 and 193:
The pictures show the same display
- Page 194 and 195:
3 Reference Data In order to have a
- Page 196 and 197:
a) c) 194 Copenhagen Fjärdhundra T
- Page 198 and 199:
Figure 9 shows one example of image
- Page 200 and 201:
To obtain standardised values for t
- Page 202 and 203:
200 160,0 140,0 120,0 100,0 80,0 60
- Page 204 and 205:
5.2 Test Site Fjärdhundra 5.2.1 Ar
- Page 206 and 207:
5.2.2 Qualitative Comparison Simila
- Page 208 and 209:
206 140,0 120,0 100,0 80,0 60,0 40,
- Page 210 and 211:
Detection of buildings was not a bi
- Page 212 and 213:
210 120,00 100,00 80,00 60,00 40,00
- Page 214 and 215:
6 Conclusion - Phase I The results
- Page 216 and 217:
Index of Figures Figure 1: Data set
- Page 219:
EuroSDR-Project Commission 2 “Ima
- Page 222 and 223:
have developed semi-automated tools
- Page 224 and 225:
GDF includes topology, road classes
- Page 226 and 227:
cautiously than the rest. Two group
- Page 228 and 229:
optimize their parameters for each
- Page 230 and 231:
228 road cluster is refined by remo
- Page 232 and 233:
5 Analysis of Results We focus the
- Page 234 and 235:
232 Figure 4: Ikonos1 - Gerke_W (le
- Page 236 and 237:
• Ikonos3_Sub1 and Sub2: These tw
- Page 238 and 239:
236 Figure 9: Ikonos3_Sub2 - Bacher
- Page 240 and 241:
approaches. Unfortunately just obta
- Page 242 and 243:
Bacher, U. and Mayer, H. (2005): Au
- Page 245 and 246:
Appendices Appendix 1: Project Prop
- Page 247 and 248:
Implementation The project should b
- Page 249 and 250:
Brown University (Cooper), Univ. of
- Page 251 and 252:
Appendix 2: Questionnaire for Produ
- Page 253 and 254:
All spectral channels used: yes n
- Page 255 and 256:
14. How are road classes defined?
- Page 257:
C. Customers and applications List
- Page 260 and 261:
General information Corresponding P
- Page 262 and 263:
5. How is the smoothness of road tr
- Page 264 and 265:
DSM from LIDAR for segmentation of
- Page 266 and 267:
- DTM as typically existing in Euro
- Page 268 and 269:
no [4] Remark: could be useful to g
- Page 270 and 271:
Optimal exploitations in practical
- Page 273 and 274:
Appendix 5: README File EuroSDR Tes
- Page 275:
- percentage correctness - geometri
- Page 279:
Appendix 7: Documentation by Hedman
- Page 282 and 283:
polyline formation process. Only th
- Page 284 and 285:
Landesvermessungsamt Baden-Württem
- Page 286:
45 Murray, K. (ed.): OEEPE Workshop