Unmanned Aerial Remote Sensing System (UARSS)-Derived Normalized Difference Vegetation Index (NDVI) To Soil Moisture Mapping

Abstract

Satellite remote sensing systems have been widely applied to soil moisture monitoring but are unsuitably applied to that of small areas, which merely cover several hectares, due to their low spatial or temporal resolutions. In order to address the soil moisture mapping of the small areas in Kinmen, Taiwan, a multispectral sensor carried on an unmanned aerial vehicle (UAV) were adopted to derive the thematic maps (0.2 m resolution) of Normalized Difference Vegetation Index (NDVI). In this research, a total of 12 in situ sampling points was schemed for a monthly data acquisition of soil moistures at two depths, including 10 cm and 20 cm, and NDVI to establish an empirical model between soil moisture and NDVI. Before the empirical model establishment, a pre-processing of relative radiance correction is necessary for the digital number adjustment of the multi-temporal UAV images. Finally, the performance of the established empirical model in soil moisture estimation is also evaluated in this research.



Author Information
Tung-Ching Su, National Quemoy University, Taiwan

Paper Information
Conference: ACSEE2017
Stream: Environmental Sustainability & Environmental Management: Land Use & Misuse

This paper is part of the ACSEE2017 Conference Proceedings (View)
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Posted by James Alexander Gordon