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19 October 2012 Evaluation of spatial upscaling methods based on remote sensing data with multiple spatial resolutions
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Abstract
In most applications of remote sensing data, special spatial information is required from a finer to a coarser spatial resolution with appropriate upscaling methods. The purpose of this paper is to compare and evaluate current spatial upscaling methods using MODIS remote sensing data with multiple spatial resolutions. In the research, Northeast China was selected as the study area. MODIS data with spatial resolutions of 250 m (2 bands) and 500 m (7 bands) were used as the test data. Through using the selected upscaling methods, the Band 1 and Band 2 data of MODIS were scaled up from 250 m to 500 m spatial resolution. On the basis of land cover characteristics of Northeast China, the MODIS data located in the study area was classified into the five land cover types, including water, grasslands, forests, farmlands and bare lands using maximum likelihood method. The land cover classification results were further compared with MODIS Land Cover Type product. Finally, Structural Similarity (SSIM) was selected to evaluate the effects of these upscaling methods. The research can provide more useful information for spatial scaling transformation in remote sensing data applications.
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Ruizhi Ren, Lingjia Gu, Junsheng Cao, Haipeng Chen, and Jian Sun "Evaluation of spatial upscaling methods based on remote sensing data with multiple spatial resolutions", Proc. SPIE 8514, Satellite Data Compression, Communications, and Processing VIII, 85140A (19 October 2012); https://doi.org/10.1117/12.929374
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