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RSS FeedsRemote Sensing, Vol. 11, Pages 456: A New Remote Sensing Dryness Index Based on the Near-Infrared and Red Spectral Space (Remote Sensing)

 
 

22 february 2019 21:01:02

 
Remote Sensing, Vol. 11, Pages 456: A New Remote Sensing Dryness Index Based on the Near-Infrared and Red Spectral Space (Remote Sensing)
 


Soil moisture, as a crucial indicator of dryness, is an important research topic for dryness monitoring. In this study, we propose a new remote sensing dryness index for measuring soil moisture from spectral space. We first established a spectral space with remote sensing reflectance data at the near-infrared (NIR) and red (R) bands. Considering the distribution regularities of soil moisture in this space, we formulated the Ratio Dryness Monitoring Index (RDMI) as a new dryness monitoring indicator. We compared RDMI values with in situ soil moisture content data measured at 0–10 cm depth. Results showed that there was a strong negative correlation (R = −0.89) between the RDMI values and in situ soil moisture content. We further compared RDMI with existing remote sensing dryness indices, and the results demonstrated the advantages of the RDMI. We applied the RDMI to the Landsat-8 imagery to map dryness distribution around the Fukang area on the Northern slope of the Tianshan Mountains, and to the MODIS imagery to detect the spatial and temporal changes in dryness for the entire Xinjiang in 2013 and 2014. Overall, the RDMI index constructed, based on the NIR–Red spectral space, is simple to calculate, easy to understand, and can be applied to dryness monitoring at different scales.


 
81 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 11, Pages 457: Retrieving the Lake Trophic Level Index with Landsat-8 Image by Atmospheric Parameter and RBF: A Case Study of Lakes in Wuhan, China (Remote Sensing)
Remote Sensing, Vol. 11, Pages 458: Spectral Heterogeneity Predicts Local-Scale Gamma and Beta Diversity of Mesic Grasslands (Remote Sensing)
 
 
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