Advances in the application of remote sensing and GIS for surveying mountainous land

摘要

Satellite remote sensing has been practised since 1972, starting with broad channels and moderate ground resolution (Landsat MSS). In the 1980s, Landsat TM and SPOT provided for improved spatial and spectral resolutions. Many satellite images were produced in these two decades, offering a synoptic view of landscapes that were rich in contrast and that included mountainous areas. The present paper describes advances made throughout the 1990s in research on and application of remote sensing and the use of OEMs to identify landforms and landscape forming processes has become an accepted survey technique. Advances were made in the field of multi-factor approaches to spatial prediction of shallow mass movements, the application of multiple endmember spectral mixture analysis to identify land cover types, and the definition of image time series, as well as their use in component identification and monitoring of land cover (including snow). The use of steerable imaging instruments in SPOT, synthetic aperture radar (SAR) and wide scan angles in thermal infrared scanning bring specific geometric problems that have yet to be solved. SAR in particular has received increasing attention in recent research. Examples of research on radargrammetry to correct for geometric distortions in the slant range are discussed. The simulation of SAR data, aided by topographic data (DEM) of mountainous terrain, is a means to obtain better understanding and reach high geometric precision. For thematic interpretation, a variety of techniques are used, including GPS registration for measuring earth crust movements and application of remote-sensing-based vegetation indices as land quality or LAI indicators, acting as basic input for crop growth models. Great impact on the application of remote sensing can be expected in the near future from: (1) improved spatial and spectral resolution for object identification; (2) application of off-nadir viewing in stereo-modelling; and (3) improved temporal resolution, serving the monitoring of land cover (including snow) and thermal condition.