Abstract
Optical remotely sensed images in mountainous areas are subject to radiometric distortions induced by topographic effects, which need to be corrected before quantitative applications. Based on Li model and Sandmeier model, this paper proposed an improved physics-based model for the topographic correction of Landsat Thematic Mapper (TM) images. The model employed Normalized Difference Vegetation Index (NDVI) thresholds to approximately divide land targets into eleven groups, due to NDVI’s lower sensitivity to topography and its significant role in indicating land cover type. Within each group of terrestrial targets, corresponding MODIS BRDF (Bidirectional Reflectance Distribution Function) products were used to account for land surface’s BRDF effect, and topographic effects are corrected without Lambertian assumption. The methodology was tested with two TM scenes of severely rugged mountain areas acquired under different sun elevation angles. Results demonstrated that reflectance of sun-averted slopes was evidently enhanced, and the overall quality of images was improved with topographic effect being effectively suppressed. Correlation coefficients between Near Infra-Red band reflectance and illumination condition reduced almost to zero, and coefficients of variance also showed some reduction. By comparison with the other two physics-based models (Sandmeier model and Li model), the proposed model showed favorable results on two tested Landsat scenes. With the almost half-century accumulation of Landsat data and the successive launch and operation of Landsat 8, the improved model in this paper can be potentially helpful for the topographic correction of Landsat and Landsat-like data.
Highlights
Mountain areas account for approximately 1/5 of the world’s land area, and provide diverse goods and services to human society [1]
The topographic correction effects were evaluated by comparing both with the original image and correction results from Sandmeier model and Li model
Topographic undulation modifies the configuration of STS geometry as well as solar irradiance reaching the surface, and makes topographic distortion and BRDF effect pronounced in remotely sensed images
Summary
Mountain areas account for approximately 1/5 of the world’s land area, and provide diverse goods and services to human society [1]. Compared to horizontal land surfaces, remotely sensed images of rugged areas possess pronounced topographic effect, which severely impacts the accuracy of the images’ quantitative applications [3]. As for the ubiquitous non-Lambertian targets in the real world [6], different STS geometry often means different bi-directional reflectance (effect of bidirectional reflectance distribution function, BRDF) [7]. This will very likely lead to phenomenon of the “same targets showing different reflectance and different targets showing same reflectance”, which severely reduces the accuracy of quantitative applications of remote sensing, such as biophysical parameter inversion and land use/cover change detection [8,9]. Topographic correction, aiming at elimination or at least reduction of terrain effect, is a necessity before the imagery of mountainous areas is used in quantitative analysis
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