- Page 1: European Organization for Experimen
- Page 5 and 6: Mr. F. PAPI MONTANEL Spain Institut
- Page 7 and 8: Table of contents D. Holland, B. Gu
- Page 9 and 10: Oeepe - Project on Topographic Mapp
- Page 11 and 12: Figure 5 Local binary difference be
- Page 13 and 14: Summary The aim of this project was
- Page 15 and 16: 1.2 Work packages OEEPE members exp
- Page 17 and 18: To enable the work to commence, it
- Page 19 and 20: 3 Summaries of the reports The numb
- Page 21 and 22: Major point features such as railwa
- Page 23 and 24: This aim of the study was to compar
- Page 25 and 26: 3.4.4 A summary of the Work Package
- Page 27 and 28: 4.4 Challenges to existing products
- Page 29: 6 Recommendations Mapping organizat
- Page 32 and 33: 1 Introduction 1.1 Background The a
- Page 34 and 35: Figure 1: Area 1. Rural / urban sub
- Page 36 and 37: Table 1: Summary of the findings of
- Page 38 and 39: 2.4.2 Roads. All major roads could
- Page 40 and 41: Derek Ireson at Z/I Imaging. Experi
- Page 42 and 43: for comparison was digital ortho-im
- Page 44 and 45: features. The amount of distortion
- Page 46 and 47: Table 5 Flowline costs Process Aeri
- Page 48 and 49: 1. Z/I Imaging workstations for aer
- Page 50 and 51: 5.5 Examples of the use of IKONOS i
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1:50,000 - for full specification 1
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1 Aim and objectives The major aim
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3.2 Communication Figure 2 shows tw
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3.4 Drainage Figure 4 shows two sub
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OEEPE - Project Topographic Mapping
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spectral range 0.45 - 0.90 b/w pan
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Figure 1: original geometric relati
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4 Geometry of CARTERRA Geo The geom
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Figure 8: differences after correct
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Oeepe - Project on Topographic Mapp
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example, IKONOS MS imagery for one
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Binary difference For a moving (2w+
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Figure 1 shows how several features
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Figure 3. (a) k-means classificatio
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4.3.2 Type Figure 5a shows the loca
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Figures 7a and b show the local (th
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For the agricultural area, the reas
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5 Discussion 5.1 Geometric registra
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6 Conclusion The objective of this
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OEEPE - Project Topographic Mapping
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esult of the level of spatial gener
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The 44 classes were specified such
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when there is an abundance of small
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Table 1 (b). Relation of CORINE cla
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The four classes were chosen to rep
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mation available to the classifier.
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Oeepe - Project on Topographic Mapp
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Outline Background / Motivation Dat
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Available Satellite Data • IKONOS
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Available Map Data Scanned OS Landp
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Spectral Properties Spectral Bands
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CORINE 44 Landuse units 5 Main cato
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Variables Variables Options CORINE
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ERDAS • MS-Channels RGB,NIR • N
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Expert Classifier • Texture from
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Prelimnary Accuracy Assessment Inst
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Influence of image object sizes Sma
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Level 4 Form, texture and spatial r
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1,00 0,90 0,80 0,70 0,60 0,50 0,40
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Problems due to spectral resolution
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Conclusions 1. Interpretation key s
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OEEPE - Project Topographic Mapping
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Figure 1: Signature Mean Plot of th
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4 Conclusion The multispectral Ikon
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Image 1b : Unsupervised Classified
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Image 1d : Supervised Classified Im
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Image 1f : Landmap (Ordnance Survey
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Image 2b : Unsupervised Classified
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Image 2d : Supervised Classified Im
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Image 2f : Landmap (Ordnance Survey
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Harrison, A.R.; D’souza, G; and S
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LIST OF THE OEEPE PUBLICATIONS Stat
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20 Eichhorn, G.: Summary of Replies