Surface Soil Moisture Estimation Using a Neural Network Model in Bare Land and Vegetated Areas
Most of the approaches to retrieve surface soil moisture (SSM) by optical and thermal infrared (TIR) spectroscopies are purposed to calculate various characteristic bands/indices and then to establish the regression relationship between them in combination with the measurement data. However, due to...
Main Authors: | Dayou Luo, Xingping Wen, Ping He |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2023-01-01
|
Series: | Journal of Spectroscopy |
Online Access: | http://dx.doi.org/10.1155/2023/5887177 |
Similar Items
-
The ATI-ET Triangle Model: A Novel Approach to Estimate Soil Moisture Applied to MODIS Data
by: Dayou Luo, et al.
Published: (2022-10-01) -
Dual-Channel Convolutional Neural Network for Bare Surface Soil Moisture Inversion Based on Polarimetric Scattering Models
by: Qiang Yin, et al.
Published: (2021-11-01) -
Soil Moisture Retrieval in Bare Agricultural Areas Using Sentinel-1 Images
by: Mouad Ettalbi, et al.
Published: (2023-07-01) -
Spatial and temporal distribution characteristics of soil moisture in the non-freezing period under the bare land and vegetation cover in the Mu Us desert
by: Jia GAO, et al.
Published: (2022-11-01) -
Estimation of soil moisture using trapezoidal relationship between remotely sensed land surface temperature and vegetation index
by: W. Wang, et al.
Published: (2011-05-01)