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High Resolution Geospatial Evapotranspiration Mapping of Irrigated Field Crops Using Multispectral and Thermal Infrared Imagery with METRIC Energy Balance Model
- Source :
- Drones, Volume 4, Issue 3, Drones, Vol 4, Iss 52, p 52 (2020)
- Publication Year :
- 2020
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2020.
-
Abstract
- Geospatial crop water use mapping is critical for field-scale site-specific irrigation management. Landsat 7/8 satellite imagery with a widely adopted METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) energy balance model (LM approach) estimates accurate evapotranspiration (ET) but limits field-scale spatiotemporal (30 m pixel&minus<br />1, ~16 days) mapping. A study was therefore conducted to map actual ET of commercially grown irrigated-field crops (spearmint, potato, and alfalfa) at very high-resolution (7 cm pixel&minus<br />1). Six small unmanned aerial system (UAS)-based multispectral and thermal infrared imagery campaigns were conducted (two for each crop) at the same time as the Landsat 7/8 overpass. Three variants of METRIC model were used to process the UAS imagery<br />UAS-METRIC-1, -2, and -3 (UASM-1, -2, and -3) and outputs were compared with the standard LM approach. ET root mean square differences (RMSD) between LM-UASM-1, LM-UASM-2, and LM-UASM-3 were in the ranges of 0.2&ndash<br />2.9, 0.5&ndash<br />0.9, and 0.5&ndash<br />2.7 mm day&minus<br />1, respectively. Internal calibrations and sensible heat fluxes majorly resulted in such differences. UASM-2 had the highest similarity with the LM approach (RMSD: 0.5&ndash<br />0.9, ETdep,abs (daily ET departures): 2&ndash<br />14%, r (Pearson correlation coefficient) = 0.91). Strong ET correlations between UASM and LM approaches (0.7&ndash<br />0.8, 0.7&ndash<br />0.8, and 0.8&ndash<br />0.9 for spearmint, potato, and alfalfa crops) suggest equal suitability of UASM approaches as LM to map ET for a range of similar crops. UASM approaches (Coefficient of variation, CV: 6.7&ndash<br />24.3%) however outperformed the LM approach (CV: 2.1&ndash<br />11.2%) in mapping spatial ET variations due to large number of pixels. On-demand UAS imagery may thus help in deriving high resolution site-specific ET maps, for growers to aid in timely crop water management.
- Subjects :
- 010504 meteorology & atmospheric sciences
lcsh:Motor vehicles. Aeronautics. Astronautics
Multispectral image
0211 other engineering and technologies
Aerospace Engineering
02 engineering and technology
Sensible heat
irrigated field crops
multispectral imagery
01 natural sciences
symbols.namesake
Artificial Intelligence
Evapotranspiration
Calibration
Satellite imagery
actual evapotranspiration
Irrigation management
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Remote sensing
Pearson product-moment correlation coefficient
Computer Science Applications
METRIC energy balance model
Control and Systems Engineering
high spatiotemporal resolution
Metric (mathematics)
symbols
Environmental science
lcsh:TL1-4050
thermal infrared imagery
Information Systems
Subjects
Details
- Language :
- English
- ISSN :
- 2504446X
- Database :
- OpenAIRE
- Journal :
- Drones
- Accession number :
- edsair.doi.dedup.....121dddfa28eccc4bb8d85e606a93184e
- Full Text :
- https://doi.org/10.3390/drones4030052