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Remote Sensing for Plant Water Content Monitoring: A Review.

Authors :
Quemada, Carlos
Pérez-Escudero, José M.
Gonzalo, Ramón
Ederra, Iñigo
Santesteban, Luis G.
Torres, Nazareth
Iriarte, Juan Carlos
Source :
Remote Sensing. Jun2021, Vol. 13 Issue 11, p2088. 1p.
Publication Year :
2021

Abstract

This paper reviews the different remote sensing techniques found in the literature to monitor plant water status, allowing farmers to control the irrigation management and to avoid unnecessary periods of water shortage and a needless waste of valuable water. The scope of this paper covers a broad range of 77 references published between the years 1981 and 2021 and collected from different search web sites, especially Scopus. Among them, 74 references are research papers and the remaining three are review papers. The different collected approaches have been categorized according to the part of the plant subjected to measurement, that is, soil (12.2%), canopy (33.8%), leaves (35.1%) or trunk (18.9%). In addition to a brief summary of each study, the main monitoring technologies have been analyzed in this review. Concerning the presentation of the data, different results have been obtained. According to the year of publication, the number of published papers has increased exponentially over time, mainly due to the technological development over the last decades. The most common sensor is the radiometer, which is employed in 15 papers (20.3%), followed by continuous-wave (CW) spectroscopy (12.2%), camera (10.8%) and THz time-domain spectroscopy (TDS) (10.8%). Excluding two studies, the minimum coefficient of determination (R2) obtained in the references of this review is 0.64. This indicates the high degree of correlation between the estimated and measured data for the different technologies and monitoring methods. The five most frequent water indicators of this study are: normalized difference vegetation index (NDVI) (12.2%), backscattering coefficients (10.8%), spectral reflectance (8.1%), reflection coefficient (8.1%) and dielectric constant (8.1%). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
13
Issue :
11
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
150828758
Full Text :
https://doi.org/10.3390/rs13112088