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Remote sensing for resources development and environmental management (Volume 1)

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Bibliographic data

fullscreen: Remote sensing for resources development and environmental management (Volume 1)

Multivolume work

Persistent identifier:
856342815
Title:
Remote sensing for resources development and environmental management
Sub title:
proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986
Year of publication:
1986
Place of publication:
Rotterdam
Boston
Publisher of the original:
A. A. Balkema
Identifier (digital):
856342815
Language:
English
Additional Notes:
Volume 1-3 erschienen von 1986-1988
Editor:
Damen, M. C. J.
Document type:
Multivolume work

Volume

Persistent identifier:
856343064
Title:
Remote sensing for resources development and environmental management
Sub title:
proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986
Scope:
XV, 547 Seiten
Year of publication:
1986
Place of publication:
Rotterdam
Boston
Publisher of the original:
A. A. Balkema
Identifier (digital):
856343064
Illustration:
Illustrationen, Diagramme
Signature of the source:
ZS 312(26,7,1)
Language:
English
Usage licence:
Attribution 4.0 International (CC BY 4.0)
Editor:
Damen, M. C. J.
Publisher of the digital copy:
Technische Informationsbibliothek Hannover
Place of publication of the digital copy:
Hannover
Year of publication of the original:
2016
Document type:
Volume
Collection:
Earth sciences

Chapter

Title:
1 Visible and infrared data. Chairman: F. Quiel, Liaison: N J. Mulder
Document type:
Multivolume work
Structure type:
Chapter

Chapter

Title:
Comparison of classification results of original and preprocessed satellite data. Barbara Kugler & Rüdiger Tauch
Document type:
Multivolume work
Structure type:
Chapter

Contents

Table of contents

  • Remote sensing for resources development and environmental management
  • Remote sensing for resources development and environmental management (Volume 1)
  • Cover
  • Title page
  • Title page
  • Title page
  • Preface
  • Organization of the Symposium
  • Working Groups
  • Table of contents
  • 1 Visible and infrared data. Chairman: F. Quiel, Liaison: N J. Mulder
  • Structural information of the landscape as ground truth for the interpretation of satellite imagery. M. Antrop
  • Interpretation of classification results of a multiple data set. Helmut Beissmann, Manfred F. Buchroithner
  • Digital processing of airborne MSS data for forest cover types classification. Kuo-mu Chiao, Yeong-kuan Chen & Hann-chin Shieh
  • Methods of contour-line processing of photographs for automated forest mapping. R. I. Elman
  • Detection of subpixel woody features in simulated SPOT imagery. Patricia G. Foschi
  • A GIS-based image processing system for agricultural purposes (GIPS/ALP) - A discussion on its concept. J. Jin King Liu
  • Image optimization versus classification - An application oriented comparison of different methods by use of Thematic Mapper data. Hermann Kaufmann & Berthold Pfeiffer
  • Thematic mapping and data analysis for resource management using the Stereo ZTS VM. Kurt H. Kreckel & George J. Jaynes
  • Comparison of classification results of original and preprocessed satellite data. Barbara Kugler & Rüdiger Tauch
  • Airphoto map control with Landsat - An alternative to the slotted templet method. W. D. Langeraar
  • New approach to semi-automatically generate digital elevation data by using a vidicon camera. C. C. Lin, A. J. Chen & D. C. Chern
  • Man-machine interactive classification technique for land cover mapping with TM imagery. Shunji Murai, Ryuji Matsuoka & Kazuyuli Motohashi
  • Space photomaps - Their compilation and peculiarities of geographical application. B. A. Novakovski
  • Processing of raw digital NOAA-AVHRR data for sea- and land applications. G. J. Prangsma & J. N. Roozekrans
  • Base map production from geocoded imagery. Dennis Ross Rose & Ian Laverty, Mark Sondheim
  • Per-field classification of a segmented SPOT simulated image. J. H. T. Stakenborg
  • Digital classification of forested areas using simulated TM- and SPOT- and Landsat 5/TM-data. H.- J. Stibig, M. Schardt
  • Classification of land features, using Landsat MSS data in a mountainous terrain. H. Taherkia & W. G. Collins
  • Thematic Mapping by Satellite - A new tool for planning and management. J. W. van den Brink & R. Beck, H. Rijks
  • 2 Microwave data. Chairman: N. Lannelongue, Liaison: L. Krul
  • 3 Spectral signatures of objects. Chairman: G. Guyot, Liaison: N. J. J. Bunnik
  • 4 Renewable resources in rural areas: Vegetation, forestry, agriculture, soil survey, land and water use. Chairman: J. Besenicar, Liaisons: M. Molenaar, Th. A. de Boer
  • Cover

Full text

45 
Row- and 
Column- 
Doubling 
Rectification and 
Resampling with 
Bilinear Inter 
polation 
Classifi 
cation 
results of doubled 
and geometrically 
:ied Data 
Doubled 
2d 
4.03 
9.02 
8.25 
28.54 
34.90 
15.04 
I (%) 
lich disappear in 
result of doubled 
ling of data before 
ment of classifica- 
lds of data prepro- 
the results. The 
ns are briefly dis- 
influences of the 
rast enhanced data 
: linear histogram 
;d out separately, 
neighbourhood re- 
ange in respect to 
is is valid for re- 
nhanced data. 
interpolated data 
t to the result of 
l occurs in isolated 
classes with a lot 
of highly structured areas show the greatest chang 
ing. The use of contrast enhanced data for rectifica 
tion and resampling instead of original data seems to 
show a slightly better accuracy. 
Classification of resampled data by bilinear interpo 
lation may be improved if a row- and column 
doubling before rectifying is carried out. 
The above experiences indicate that contrast enhancement 
influences classification results slightly, either if data are 
geometrically preprocessed or not. Moreover classification 
of nearest neighbour resampled data leads to a result, 
which is only little influenced by preprocessing, even if a 
great geometric transformation (from satellite image to 
map grid) is performed. 
If bilinear interpolation for resampling is used the classi 
fication results will tend to more differences in respect to 
those of the original data. 
Bilinear interpolated data may be used for classification 
if a doubling of data before rectifying is carried out. The 
improvement of classification result is obvious, but study 
ing of classification accuracy needs more detailed investi 
gations. 
In the whole, the investigations dealed in this paper show 
the influences of various preprocessing methods. Therefore 
the purposes for the digital classification of different kinds 
of image preprocessing must be considered carefully. 
REFERENCES 
Forster, B.C., Trinder,3.C., 1984. Effects of Resampling of 
Landsat Data on Classification Accuracy. Aust. Л. Geod. 
Photo. Surv., 40, Липе 84: 53-67 
Kähler, M., Milkus, I., 1986. Berlin from Space - A Digital 
ly Produced Satellite Image Map. Intern. Symp. on 
Mapping from Modern Imagery, Edingburgh September 
1986 (in print) 
Realnutzungskartierung und Flächenbilanzierung, Maßstab 
1:50000, im Bereich des Raumordnungsverbandes Rhein- 
Neckar. ifp-Institut für Planungsdaten und StadtBauPlan 
Frankfurt am Main/Darmstadt 1976
	        

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Damen, M. .C. .J. Remote Sensing for Resources Development and Environmental Management. A. A. Balkema, 1986.
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