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Remote sensing information extraction is the key step of remote sensing application, and the automatic and high-precise extraction of water information from remotely sensed images is of great significance and urgently required in many research fields. This paper presents a step-by-step iterative transformation mechanism to extract water information, which uses spatial scale transformation mechanism...
Extracting water body information accurately from remotely sensed imagery is significant for surveying, planning and protecting water resources, and particularly flood disaster management such as monitoring, evaluation, emergency response and so on. Landsat ETM+ imagery has such features as high spatial resolution and multi-spectral resolution, which provides a rich, reliable and accurate source of...
A novel conceptual approach to address the mixture problem in agricultural remote sensing is presented in this study. The method, referred to as Signal Unmixing, combines both in situ and hyperspectral data in an adapted spectral mixture analysis algorithm and allows the extraction of pure and complete hyperspectral vegetation spectra (400-2400 nm) from mixed image pixels. The technique is evaluated...
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