A Three-Dimensional Index for Characterizing Crop Water Stress

The application of remotely sensed estimates of canopy minus air temperature (Tc-Ta) for detecting crop water stress can be limited in semi-arid regions, because of the lack of full ground cover (GC) at water-critical crop stages. Thus, soil background may restrict water stress interpretation by the...

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Main Authors: Jessica A. Torrion, Stephan J. Maas, Wenxuan Guo, James P. Bordovsky, Andy M. Cranmer
Format: Article
Language:English
Published: MDPI AG 2014-05-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/6/5/4025
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spelling doaj-43e2bea4ada449728c0a1b0c918499942020-11-24T22:37:16ZengMDPI AGRemote Sensing2072-42922014-05-01654025404210.3390/rs6054025rs6054025A Three-Dimensional Index for Characterizing Crop Water StressJessica A. Torrion0Stephan J. Maas1Wenxuan Guo2James P. Bordovsky3Andy M. Cranmer4Northwestern Ag Research Center, Montana State University, Kalispell, MT 59901, USADepartment of Plant and Soil Science, Texas Tech University, 3810 4th Street, Lubbock, TX 79415, USAMonsanto Company, 700 Chesterfield Pkwy W, Chesterfield, MO 63017, USATexas A&M AgriLife Research and Extension Center, 823 W US 70, Plainview, TX 79072, USATexas A&M AgriLife Research and Extension Center, 823 W US 70, Plainview, TX 79072, USAThe application of remotely sensed estimates of canopy minus air temperature (Tc-Ta) for detecting crop water stress can be limited in semi-arid regions, because of the lack of full ground cover (GC) at water-critical crop stages. Thus, soil background may restrict water stress interpretation by thermal remote sensing. For partial GC, the combination of plant canopy temperature and surrounding soil temperature in an image pixel is expressed as surface temperature (Ts). Soil brightness (SB) for an image scene varies with surface soil moisture. This study evaluates SB, GC and Ts-Ta and determines a fusion approach to assess crop water stress. The study was conducted (2007 and 2008) on a commercial scale, center pivot irrigated research site in the Texas High Plains. High-resolution aircraft-based imagery (red, near-infrared and thermal) was acquired on clear days. The GC and SB were derived using the Perpendicular Vegetation Index approach. The Ts-Ta was derived using an array of ground Ts sensors, thermal imagery and weather station air temperature. The Ts-Ta, GC and SB were fused using the hue, saturation, intensity method, respectively. Results showed that this method can be used to assess water stress in reference to the differential irrigation plots and corresponding yield without the use of additional energy balance calculation for water stress in partial GC conditions.http://www.mdpi.com/2072-4292/6/5/4025cottonwater stressirrigationremote sensingsoil brightnessground covertemperaturefusion technique
collection DOAJ
language English
format Article
sources DOAJ
author Jessica A. Torrion
Stephan J. Maas
Wenxuan Guo
James P. Bordovsky
Andy M. Cranmer
spellingShingle Jessica A. Torrion
Stephan J. Maas
Wenxuan Guo
James P. Bordovsky
Andy M. Cranmer
A Three-Dimensional Index for Characterizing Crop Water Stress
Remote Sensing
cotton
water stress
irrigation
remote sensing
soil brightness
ground cover
temperature
fusion technique
author_facet Jessica A. Torrion
Stephan J. Maas
Wenxuan Guo
James P. Bordovsky
Andy M. Cranmer
author_sort Jessica A. Torrion
title A Three-Dimensional Index for Characterizing Crop Water Stress
title_short A Three-Dimensional Index for Characterizing Crop Water Stress
title_full A Three-Dimensional Index for Characterizing Crop Water Stress
title_fullStr A Three-Dimensional Index for Characterizing Crop Water Stress
title_full_unstemmed A Three-Dimensional Index for Characterizing Crop Water Stress
title_sort three-dimensional index for characterizing crop water stress
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2014-05-01
description The application of remotely sensed estimates of canopy minus air temperature (Tc-Ta) for detecting crop water stress can be limited in semi-arid regions, because of the lack of full ground cover (GC) at water-critical crop stages. Thus, soil background may restrict water stress interpretation by thermal remote sensing. For partial GC, the combination of plant canopy temperature and surrounding soil temperature in an image pixel is expressed as surface temperature (Ts). Soil brightness (SB) for an image scene varies with surface soil moisture. This study evaluates SB, GC and Ts-Ta and determines a fusion approach to assess crop water stress. The study was conducted (2007 and 2008) on a commercial scale, center pivot irrigated research site in the Texas High Plains. High-resolution aircraft-based imagery (red, near-infrared and thermal) was acquired on clear days. The GC and SB were derived using the Perpendicular Vegetation Index approach. The Ts-Ta was derived using an array of ground Ts sensors, thermal imagery and weather station air temperature. The Ts-Ta, GC and SB were fused using the hue, saturation, intensity method, respectively. Results showed that this method can be used to assess water stress in reference to the differential irrigation plots and corresponding yield without the use of additional energy balance calculation for water stress in partial GC conditions.
topic cotton
water stress
irrigation
remote sensing
soil brightness
ground cover
temperature
fusion technique
url http://www.mdpi.com/2072-4292/6/5/4025
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