Evaluation of LANDSAT image data for land-use mapping

Abstract

A computer aided extraction of land-use information from LANDSAT image data, gathered on 9 August 1975, was conducted. Specifically the study was designed to develop a method for supervised multispectral classification of LANDSAT data of a central European region and to verify the classification results on a pixel-by-pixel basis and by comparison of the land-use inventory with aerial photo interpretation in test areas. The method enables the integration and processing of additional data. For the test area Speyer in the Rhine valley with small size allotments and a variety of land-use it was found that the pixel-by-pixel comparison is rather difficult and has a high potential failure rate. Seven classes were considered. With the integration of subclasses to main classes higher classification accuracy can be reached. The highest classification accuracy could be obtained for agricultural land (97%); orchards, pasture (91%) and coniferous forest (84%) in the land-use inventory of Speyer. The study confirms that the degree of fit rises with the size of homogeneous land-use zones. The study results yield that for larger areas of homogeneous land-use in central Europe this method will reach acceptable classification accuracies for land-use inventories. The land-use information can be presented in colour coded thematic maps with the same scale and projection of existing maps.