A new mathematical formulation for remote sensing of soil moisture based on the Red-NIR space-Reference-Cited by-同舟云学术

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A new mathematical formulation for remote sensing of soil moisture based on the Red-NIR space

Published:2020-08-15 Issue:20 Volume:41 Page:8034-8047
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Foroughi Hassan¹²,Naseri Abd Ali¹,Boroomand Nasab Saeed¹,Hamzeh Saeid³,Sadeghi Morteza⁴,Tuller Markus⁵,Jones Scott B.²

Affiliation:

1. Department of Irrigation and Drainage, Shahid Chamran University of Ahvaz , Ahvaz, Iran

2. Department of Plants, Soils, and Climate, Utah State University , Logan, UT, USA

3. Department of Remote Sensing and GIS, Tehran University , Tehran, Iran

4. Department of Civil, Environmental & Geo-Engineering, University of Minnesota , Minneapolis, MN, USA

5. Department of Environmental Science, The University of Arizona , Tucson, AZ, USA

Funder

National Science Foundation

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2020.1770365

Reference29 articles.

1. Two new soil moisture indices based on the NIR-red triangle space of Landsat-8 data

2. Spatially constrained inversion of radiative transfer models for improved LAI mapping from future Sentinel-2 imagery

3. Mapping soil moisture with the OPtical TRApezoid Model (OPTRAM) based on long-term MODIS observations

4. Ground, Proximal, and Satellite Remote Sensing of Soil Moisture

5. A New Optical Remote Sensing Technique for High-Resolution Mapping of Soil Moisture

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1. Ensembles of multiple models for soil moisture retrieval from remote sensing data over agricultural areas: A deep learning-based framework;Remote Sensing Applications: Society and Environment;2024-08

2. Estimation of soil moisture using WCM model and Sentinel satellite imagery for irrigation scheduling of sugarcane fields;Journal of Geospatial Information Technology;2023-03-01

3. Soil Organic Matter Detection Based on Pyrolysis and Electronic Nose Combined with Multi-Feature Data Fusion Optimization;Agriculture;2022-09-24

4. Remote Sensing Recognition and Classification of Forest Vegetation Based on Image Feature Depth Learning;Mobile Information Systems;2022-06-28

5. A Proposed Methodology to Map Soil Moisture in Support of Farm-Level Decision Making Under Changing Climatic Conditions;Sustainable Agriculture and Food Security;2022

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