Soil water content monitoring using joint application of PDI and TVDI drought indices
Heng Wang, Nian He, Rongheng Zhao, Xiaoyi Ma
Abstract
Remote sensing technology provides a viable way for large-scale soil water content (SWC) estimation. The perpendicular drought index (PDI) and temperature vegetation dryness index (TVDI) are two drought indices that can reflect SWC based on remote sensing data. These two indices have their own set of pros and cons when used independently for SWC estimation: PDI is primarily suitable for low vegetation coverage, whereas TVDI is more suitable for dense vegetation coverage. Thus, it might be inappropriate to employ a single model for the entire growth cycle. In this study, the relationship between PDI/TVDI and SWC at soil depths of 0–20 cm, 0–30 cm and 0–40 cm was analysed. We found that the estimation accuracy of the PDI/TVDI model was markedly affected by soil depth and the normalized difference vegetation index (NDVI). Two combination approaches (joint and combined models) based on PDI and TVDI indices were established. The root mean squared error (RMSE) of the joint/combined models were 1.49%/1.48% at 0–20 cm, 1.46%/1.48% at 0–30 cm and 1.86%/1.90% at 0–40 cm. Our results show that both combination models are suitable for regional SWC estimation.