Soil Moisture Remote Sensing across Scales-Reference-Cited by-同舟云学术

Soil Moisture Remote Sensing across Scales

Published:2019-01-19 Issue:2 Volume:11 Page:190
ISSN:2072-4292
Container-title:Remote Sensing
language:en
Short-container-title:Remote Sensing

Author:

Rodríguez-Fernández Nemesio,Al Bitar Ahmad,Colliander Andreas,Zhao Tianjie

Abstract

Soil moisture plays an important role in the water, carbon, and energy cycles. We summarize the 13 articles collected in this Special Issue on soil moisture remote sensing across scales in terms of the spatial, temporal, and frequency scales studied. We also review these papers regarding the data, the methods, and the different applications discussed.

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Link

http://www.mdpi.com/2072-4292/11/2/190/pdf

Reference18 articles.

1. Soil Moisture Mapping from Satellites: An Intercomparison of SMAP, SMOS, FY3B, AMSR2, and ESA CCI over Two Dense Network Regions at Different Spatial Scales

2. The Evaluation of SMAP Enhanced Soil Moisture Products Using High-Resolution Model Simulations and In-Situ Observations on the Tibetan Plateau

3. Evaluation of SMOS, SMAP, ASCAT and Sentinel-1 Soil Moisture Products at Sites in Southwestern France

4. 4th Satellite Soil Moisture Validation and Application Workshop;Wagner;Glob. Energy Water Exchang. Newsl.,2017

5. Use of SMOS L3 Soil Moisture Data: Validation and Drought Assessment for Pernambuco State, Northeast Brazil

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1. Multipath phase based vegetation correction scheme for improved field-scale soil moisture retrieval over agricultural cropland using GNSS-IR technique;Advances in Space Research;2024-04

2. Reviews and syntheses: Recent advances in microwave remote sensing in support of terrestrial carbon cycle science in Arctic–boreal regions;Biogeosciences;2023-07-21

3. Evaluation of L-band GPS signal attenuation to multiple vegetations using ground-based measurements;International Journal of Remote Sensing;2023-06-19

4. Surface Soil Moisture Retrieval of China Using Multi-Source Data and Ensemble Learning;Remote Sensing;2023-05-26

5. An Overview of Soil Moisture and Salinity Sensors for Digital Agriculture Applications;Digital Agriculture, Methods and Applications;2022-12-07