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Vegetation survey in the former brown coal mining area of eastern Germany by integrating remote sensing and ground‐based methods
Author(s) -
Felinks Birgit,
Pilarski Monika,
Wiegleb Gerhard
Publication year - 1998
Publication title -
applied vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.096
H-Index - 64
eISSN - 1654-109X
pISSN - 1402-2001
DOI - 10.2307/1478953
Subject(s) - vegetation (pathology) , remote sensing , sampling (signal processing) , satellite imagery , scale (ratio) , habitat , satellite , environmental science , vegetation classification , ground truth , mosaic , physical geography , geography , cartography , ecology , computer science , medicine , archaeology , filter (signal processing) , pathology , aerospace engineering , machine learning , engineering , computer vision , biology
. In the former brown coal mining area of eastern Germany, now scheduled as a nature conservation area, an analysis of the spatial distribution of vegetation was considered as an important tool in landscape planning. Therefore a comprehensive vegetation survey by means of satellite imagery (Landsat‐TM), airborne imagery (CASI), and ground‐based methods, notably habitat mapping and vegetation sampling was carried out. With respect to the scales of resolution the classification results of the four methods are, to a certain degree, comparable. Differences in the outcome can be ascribed to the fact that methods of low resolution result in a discrete array of polygons whereas methods of high resolution depict a mosaic structure with an underlying, continuously changing gradient. Provided that the biological meaning of the remote sensing classification is known, a shift from single vegetation patterns to the landscape scale will be possible. Neither satellite nor airborne imagery is restricted to the purpose of mapping but may also serve for vegetation classification itself.