Proceedings of the Symposium on Global and Environmental Monitoring: Proceedings of the Symposium on Global and Environmental Monitoring

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Persistent identifier:: 856665355

Title:: Proceedings of the Symposium on Global and Environmental Monitoring

Sub title:: techniques and impacts ; September 17 - 21, 1990, Victoria Conference Centre, Victoria, British Columbia, Canada

Year of publication:: 1990

Place of publication:: Victoria, BC

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 856665355

Language:: English

Document type:: Multivolume work

Volume

Persistent identifier:: 856669164

Title:: Proceedings of the Symposium on Global and Environmental Monitoring

Sub title:: techniques and impacts; September 17 - 21, 1990, Victoria Conference Centre, Victoria, British Columbia, Canada

Scope:: XIV, 912 Seiten

Year of publication:: 1990

Place of publication:: Victoria, BC

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 856669164

Illustration:: Illustrationen, Diagramme, Karten

Signature of the source:: ZS 312(28,7,1)

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: International Society for Photogrammetry and Remote Sensing, Commission of Photographic and Remote Sensing Data

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:: [WA-3 DEMOGRAPHIC AND URBAN APPLICATIONS]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: PSEUDOCOLOR PHOTOMAPS PRODUCTION USING NEURAL NETWORKS. Karel Charvát, Vladimir Cervenka

Document type:: Multivolume work

Structure type:: Chapter

PSEUDOCOLOR PHOTOMAPS PRODUCTION USING NEURAL NETWORKS Karel Charvát, Vladimir Cervenka Geodetic and Cartographic Enterprise, Prague Remote Sensing Centre Introduction Gathering of information on the land use belongs to the main goals of remote sensing methods. This task is of special importance in regions with complicated structural zoning, e.g. in urban aglomerations and their surrounding. At present, Thematic Mapper (TM) data are frequently exploited for these purposes. Therefore, a great attention has been also paid to the development of their interpretation. Individual methods differ each other as for the complexity and the level of automation. There are a simple methods based on visual interpretation and also fully automated processes based on the principles of artificial intelligence. Selection of a suitable method can be made from different points of view. The most important of them will often be the costs of processing. Lower price is one of the main reasons for using the combinations of visual and computer methods. A simple method of production of 1 : 50 000 pseudocolor photomaps was described in [1]. The principle of this methods consisted in the production of a pseudocolor composite and its superimposition into the line map. The process described was divided into four steps: a) transformation of the primary TM data into three color components, b) histogram equalization of separate color components, c) refining of the pixel size, d) color composite production from three components and its superimposition into the map. There will be described a new improved technology in this paper. It applies modern principles of artificial intelligence, especially from the branche of neural networks. Transformation of the primary data into three color components Usual way of color composite production consist in the selection of three spectral bands, their conversion into the analogue form on the film material and common projection with red, green and blue filter by means of the multispectral projector. However, this way is not suitable for TM data, because only a part of the information, contained in six or seven TM bands, can be exploited. Therefore, it seems to be useful to transform all disponsible spectral bands into three "synthetic" ones. The use of the transformation called "Tasseled Cap" for this purpose has been described in [1]. The results obtained by this transformation was satisfactory but this method had also some disadvantages. At first, the data had different dynamics in the individual bands, and in some cases the part of information had been lost. A new transformation will be described here. It enables to comprimate effectively the whole information contained in original'TM data into three new synthetic channels, as well as its decomprimation back into the original channels. This 224

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