Supervised Classifications of Optical Water Types in Spanish Inland Waters
نویسندگان
چکیده
Remote sensing of lake water quality assumes there is no universal method or algorithm that can be applied in a general way on all inland waters, which usually have different in-water components affecting their optical properties. Depending the place and time year, dynamics, particular water, non-tailor-designed algorithms lead to large errors lags quantification parameters, such as suspended mineral sediments, dissolved organic matter, chlorophyll-a concentration. Selecting most suitable for each type not simple matter. One make selecting easier occasion by knowing ahead being handled. This approach used, instance, Lake Water Quality production chain Copernicus Global Land Service. The objective this work determine supervised classification might give accurate results. We use dataset manually labeled pixels lakes reservoirs Eastern Spain. High-resolution images from Multispectral Instrument sensor board ESA Sentinel-2 satellite, atmospherically corrected with Case 2 Regional Coast Colour algorithm, are used basis extracting dataset. Three families classifiers been implemented compared: K-nearest neighbor, decision trees, support vector machine. Based results, appropriate our study area random forest classifier, was selected series derive temporal types per lake. An evaluation results presented, an analysis made using expert knowledge.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2022
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs14215568