SOIL MOISTURE PREDICTION WITH MULTISPECTRAL VISIBLE AND NIR REMOTE SENSING

Water is a valuable resource and an understanding of soil moisture dynamics is critical in many land management, agricultural and engineering applications. Satellite and UAV remote sensing platforms present an opportunity for rapid, cost-efficient data collection; however, soil moisture remote sensi...

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Bibliographic Details
Published in:ISPRS annals of the photogrammetry, remote sensing and spatial information sciences remote sensing and spatial information sciences, 2022-05, Vol.V-3-2022, p.447-453
Main Authors: McGuirk, S. L., Cairns, I. H.
Format: Article
Language:English
Subjects:
Agricultural engineering
Atmospheric moisture
Data collection
Land management
Landsat
Landsat 5
Landsat satellites
Linear equations
Moisture content
Moisture effects
Remote sensing
Satellites
Soil dynamics
Soil moisture
Spectral bands
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Summary:Water is a valuable resource and an understanding of soil moisture dynamics is critical in many land management, agricultural and engineering applications. Satellite and UAV remote sensing platforms present an opportunity for rapid, cost-efficient data collection; however, soil moisture remote sensing presents unique challenges. Specifically, spectral bands near 1400nm and 1900nm associated with water are typically avoided in remote sensing data products due to strong interference by atmospheric moisture. Using soil reflectance data collected in the lab, this paper presents a number of linear equations which maybe be applied to predict soil moisture content from Landsat 5 MSS, 7 TM and 9 data, as well as other NIR sensors collecting data at 1720, 1782, 2140 and 2240nm.
ISSN:2194-9050
2194-9042
2194-9050
DOI:10.5194/isprs-annals-V-3-2022-447-2022