Remote Sensing for Studying of Soil Moisture: Techniques and Available Data Sources
DOI:
https://doi.org/10.14456/rmutlengj.2022.8Keywords:
Soil Moisture, Remote Sensing, Soil Moisture Data SourcesAbstract
This study aims to explore soil moisture data sources and review various techniques for obtaining soil moisture data from remote sensing technology. Results reveal available data sources that allow users to access, download and manipulate the soil moisture data via the internet. Remote sensing techniques and their related methods for extracting the soil moisture data are also mentioned. According to the demonstrated result, the use of soil moisture data can be applied to the engineering and environmental application, burning area, and air pollution (PM10 and PM2.5) management and disaster monitoring efficiently.
References
Kerr YH, Wigneron J-P, Al Bitar A, Mialon A, Srivastava PK. Soil moisture from space. In:
Satellite Soil Moisture Retrieval.J Techniques and Applications. Elsevier; 2016. p. 3–27.
Kim S, Zhang R, Pham H, Sharma A. A review of satellite-derived soil soisture and Its Usage for flood estimation. Remote Sens Earth Syst Sci. 2019 Dec 1;2(4):225–46.
Lillesand T, Kiefer RW. Remote sensing and image interpretation 4th Edition.2000
American Society for photogrammetry and Remote Sensing. Manual of Photogrammetry. 5th ed. American Society for Photogrammetry and Remote Sensing (ASPRS);2004.
Jensen JR. Remote sensing of the environment: an earth resource perspective. 2nd ed. Pearson; 2007.
Brocca L, Ciabatta L, Massari C, Camici S, Tarpanelli A. Soil moisture for hydrological applications: Open questions and new opportunities. Water. 2017 Feb;9(2):140.
Juglea S, Kerr Y, Mialon A, Lopez-Baeza E, Braithwaite D, Hsu K. Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station. Hydrol Earth Syst Sci. 2010 Aug 10;14(8):1509–25.
Kerr YH. Soil moisture from space: Where are we? Hydrogeol J. 2007 Jan 25;15(1):117–20.
Pellarin T, Louvet S, Gruhier C, Quantin G, Legout C. A simple and effective method for correcting soil moisture and precipitation estimates using AMSR-E measurements. Remote Sens Environ. 2013 Sep;136:28–36.
Mohanty BP, Cosh MH, Lakshmi V, Montzka C. Soil moisture remote sensing: state-of-the-science. Vadose Zone J. 2017;16(1):1-9.
National Aeronautics and Space Administration (NASA). Overview. California Institute of Technology.Available from: https: // smap.jpl.nasa.gov/observa tory/overview/[Accessed 31th March 2021].
National Aeronautics and Space Administration (NASA). Data Products. California Institute of Technology Available from: https://smap. jpl. nasa. gov/data/ [Accessed 31th March 2021].
Geo - Informatics and Space Technology Development Agency (Public Organization) (GISTDA). Available from: http://droughtv2.gistda.or.th [Accessed 31th March 2021]
UN-SPIDER. In Detail: Recommended Practice: Drought monitoring using the Standardized Precipitation Index (SPI). Available from: https:// un-spider.org/ advisory - support/recommended- practices/recommended-practice-drought-monitoring-spi/ in-detail? [Accessed 31th March 2021].
Prommuean S, Waewsak J, Katathikarnkul S, Konruang S. The study of soil moisture using remote sensing data and ground-Based measurement: A case study in Phatthalung
Province. ASEAN J Sci Technol Rep. 2018 Oct 25;21(3):224–32.
Marino P, Peres DJ, Cancelliere A, Greco R, Bogaard TA. Soil moisture information can
improve shallow landslide forecasting using the hydrometeorological threshold approach.
Landslides. 2020 Sep 1;17(9):2041–54.
Brocca L, Ponziani F, Moramarco T, Melone F, Berni N, Wagner W. Improving landslide
forecasting using ASCAT-Derived soil moisture data: A case study of the torgiovannetto
landslide in Central Italy. Remote Sens. 2012 May 4;4(5):1232–44.
Zhuo L, Dai Q, Han D, Chen N, Zhao B, Berti M. Evaluation of remotely sensed soil moisture for landslide hazard assessment. IEEE J Sel Top Appl Earth Obs Remote Sens. 2019 Jan;12(1): 162–73.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 RMUTL.Eng.J.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.