Remote Sensing · 2016 · 112 citations · 32 references
Earth ObservationPrecision AgricultureEnvironmental MonitoringEngineeringWater StressForestryAgricultural EconomicsCanopy MicrometeorologyTerrestrial SensingEarth ScienceIrrigation ManagementAtmospheric ScienceForest MeteorologyL. CultivarsThermal Infrared Remote SensingPublic HealthCrop MonitoringClimate ChangeHydrometeorologySaturn Peach OrchardsCrop Water StatusGeographyCrop Water RelationIrrigationCrop Growth ModelingHydrologyAirborne Thermal ImageryWater PotentialClimatologyConserve WaterWater ResourcesDroughtRemote Sensing
In the current scenario of worldwide limited water supplies, conserving water is a major concern in agricultural areas. Characterizing within-orchard spatial heterogeneity in water requirements would assist in improving irrigation water use efficiency and conserve water. The crop water stress index (CWSI) has been successfully used as a crop water status indicator in several fruit tree species. In this study, the CWSI was developed in three Prunus persica L. cultivars at different phenological stages of the 2012 to 2014 growing seasons, using canopy temperature measurements of well-watered trees. The CWSI was then remotely estimated using high-resolution thermal imagery acquired from an airborne platform and related to leaf water potential (ѰL) throughout the season. The feasibility of mapping within-orchard spatial variability of ѰL from thermal imagery was also explored. Results indicated that CWSI can be calculated using a common non-water-stressed baseline (NWSB), upper and lower limits for the entire growing season and for the three studied cultivars. Nevertheless, a phenological effect was detected in the CWSI vs. ѰL relationships. For a specific given CWSI value, ѰL was more negative as the crop developed. This different seasonal response followed the same trend for the three studied cultivars. The approach presented in this study demonstrated that CWSI is a feasible method to assess the spatial variability of tree water status in heterogeneous orchards, and to derive ѰL maps throughout a complete growing season. A sensitivity analysis of varying pixel size showed that a pixel size of 0.8 m or less was needed for precise ѰL mapping of peach and nectarine orchards with a tree crown area between 3.0 to 5.0 m2.
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Canopy temperature as a crop water stress indicator
Ray D. Jackson, Sherwood B. Idso, R. J. Reginato et al. · Water Resources Research · 1981 · 1.9K citations
Normalizing the stress-degree-day parameter for environmental variability
Sherwood B. Idso, Ray D. Jackson, Paul J. Pinter et al. · Agricultural Meteorology · 1981 · 1.3K citations
Pablo J. Zarco‐Tejada, V. González-Dugo, José A. Jiménez-Berni · Remote Sensing of Environment · 2011 · 872 citations
Thermal Camera, Environmental Monitoring, Water Stress Detection +10