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Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data
[article]
2018
arXiv
pre-print
In this paper, we investigate the potential of estimating the soil-moisture content based on VNIR hyperspectral data combined with LWIR data. Measurements from a multi-sensor field campaign represent the benchmark dataset which contains measured hyperspectral, LWIR, and soil-moisture data conducted on grassland site. We introduce a regression framework with three steps consisting of feature selection, preprocessing, and well-chosen regression models. The latter are mainly supervised machine
arXiv:1804.09046v3
fatcat:frtmgrn54bhzhiwxkte75kfbre