Matlab Software for Supervised Habitat Mapping of Freshwater Systems Using Image Processing
نویسندگان
چکیده
We present a software package for the supervised classification of images useful cover-type mapping freshwater habitat (e.g., water surface, gravel bars, vegetation). The allows user to select representative subset pixels within specific area interest in image that has identified as interest. developed graphical interface (GUI) single using dot, line, or group defined polygon appears have spectral similarity. Histogram plots each band selected ground-truth aid determining whether accept reject it input data processes. A statistical model, classifier, is then built this pixel assign every best-fit based on reflectance Ideally, classifier incorporates both and spatial information. In our software, we implement quadratic discriminant analysis (QDA) choose three methods—mode filtering, probability label relaxation, Markov random fields—to incorporate context after computation type. This multi-step interactive process makes quantitatively robust, broadly applicable, easily usable rivers, their floodplains, wetlands often components these functionally linked systems. Indeed, approach helpful wide range applications systems but also estuarine coastal well. However, can many other applications, specifically automatic quantitative extraction represent surface rivers floodplains.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2021
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs13234906