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Evapotranspiration (ET) is a key variable for hydrology and irrigation water management, with significant importance in drought-stricken regions of the western US. This is particularly true for California, which grows much of the high-value perennial crops in the US. The advent of small Unmanned Aerial System (sUAS) with sensor technology similar to satellite platforms allows for the estimation of high-resolution ET at plant spacing scale for individual fields. However, while multiple efforts have been made to estimate ET from sUAS products, the sensitivity of ET models to different model grid size/resolution in complex canopies, such as vineyards, is still unknown. The variability of row spacing, canopy structure, and distance between fields makes this information necessary because additional complexity processing individual fields. Therefore, processing the entire image at a fixed resolution that is potentially larger than the plant-row separation is more efficient. From a computational perspective, there would be an advantage to running models at much coarser resolutions than the very fine native pixel size from sUAS imagery for operational applications. In this study, the Two-Source Energy Balance with a dual temperature (TSEB2T) model, which uses remotely sensed soil/substrate and canopy temperature from sUAS imagery, was used to estimate ET and identify the impact of spatial domain scale under different vine phenological conditions. The analysis relies upon high-resolution imagery collected during multiple years and times by the Utah State University AggieAirTM sUAS program over a commercial vineyard located near Lodi, California. This project is part of the USDA-Agricultural Research Service Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). Original spectral and thermal imagery data from sUAS were at 10 cm and 60 cm per pixel, respectively, and multiple spatial domain scales (3.6, 7.2, 14.4, and 30 m) were evaluated and compared against eddy covariance (EC) measurements. Results indicated that the TSEB2T model is only slightly affected in the estimation of the net radiation (Rn) and the soil heat flux (G) at different spatial resolutions, while the sensible and latent heat fluxes (H and LE, respectively) are significantly affected by coarse grid sizes. The results indicated overestimation of H and underestimation of LE values, particularly at Landsat scale (30 m). This refers to the non-linear relationship between the land surface temperature (LST) and the normalized difference vegetation index (NDVI) at coarse model resolution. Another predominant reason for LE reduction in TSEB2T was the decrease in the aerodynamic resistance (Ra), which is a function of the friction velocity ( u * ) that varies with mean canopy height and roughness length. While a small increase in grid size can be implemented, this increase should be limited to less than twice the smallest row spacing present in the sUAS imagery. The results also indicated that the mean LE at field scale is reduced by 10% to 20% at coarser resolutions, while the with-in field variability in LE values decreased significantly at the larger grid sizes and ranged between approximately 15% and 45%. This implies that, while the field-scale values of LE are fairly reliable at larger grid sizes, the with-in field variability limits its use for precision agriculture applications.
Ayman Nassar; Alfonso Torres-Rua; William Kustas; Hector Nieto; Mac McKee; Lawrence Hipps; David Stevens; Joseph Alfieri; John Prueger; Maria Mar Alsina; Lynn McKee; Calvin Coopmans; Luis Sanchez; Nick Dokoozlian. Influence of Model Grid Size on the Estimation of Surface Fluxes Using the Two Source Energy Balance Model and sUAS Imagery in Vineyards. Remote Sensing 2020, 12, 342 .
AMA StyleAyman Nassar, Alfonso Torres-Rua, William Kustas, Hector Nieto, Mac McKee, Lawrence Hipps, David Stevens, Joseph Alfieri, John Prueger, Maria Mar Alsina, Lynn McKee, Calvin Coopmans, Luis Sanchez, Nick Dokoozlian. Influence of Model Grid Size on the Estimation of Surface Fluxes Using the Two Source Energy Balance Model and sUAS Imagery in Vineyards. Remote Sensing. 2020; 12 (3):342.
Chicago/Turabian StyleAyman Nassar; Alfonso Torres-Rua; William Kustas; Hector Nieto; Mac McKee; Lawrence Hipps; David Stevens; Joseph Alfieri; John Prueger; Maria Mar Alsina; Lynn McKee; Calvin Coopmans; Luis Sanchez; Nick Dokoozlian. 2020. "Influence of Model Grid Size on the Estimation of Surface Fluxes Using the Two Source Energy Balance Model and sUAS Imagery in Vineyards." Remote Sensing 12, no. 3: 342.
In recent years, the deployment of satellites and unmanned aerial vehicles (UAVs) has led to production of enormous amounts of data and to novel data processing and analysis techniques for monitoring crop conditions. One overlooked data source amid these efforts, however, is incorporation of 3D information derived from multi-spectral imagery and photogrammetry algorithms into crop monitoring algorithms. Few studies and algorithms have taken advantage of 3D UAV information in monitoring and assessment of plant conditions. In this study, different aspects of UAV point cloud information for enhancing remote sensing evapotranspiration (ET) models, particularly the Two-Source Energy Balance Model (TSEB), over a commercial vineyard located in California are presented. Toward this end, an innovative algorithm called Vegetation Structural-Spectral Information eXtraction Algorithm (VSSIXA) has been developed. This algorithm is able to accurately estimate height, volume, surface area, and projected surface area of the plant canopy solely based on point cloud information. In addition to biomass information, it can add multi-spectral UAV information to point clouds and provide spectral-structural canopy properties. The biomass information is used to assess its relationship with in situ Leaf Area Index (LAI), which is a crucial input for ET models. In addition, instead of using nominal field values of plant parameters, spatial information of fractional cover, canopy height, and canopy width are input to the TSEB model. Therefore, the two main objectives for incorporating point cloud information into remote sensing ET models for this study are to (1) evaluate the possible improvement in the estimation of LAI and biomass parameters from point cloud information in order to create robust LAI maps at the model resolution and (2) assess the sensitivity of the TSEB model to using average/nominal values versus spatially-distributed canopy fractional cover, height, and width information derived from point cloud data. The proposed algorithm is tested on imagery from the Utah State University AggieAir sUAS Program as part of the ARS-USDA GRAPEX Project (Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment) collected since 2014 over multiple vineyards located in California. The results indicate a robust relationship between in situ LAI measurements and estimated biomass parameters from the point cloud data, and improvement in the agreement between TSEB model output of ET with tower measurements when employing LAI and spatially-distributed canopy structure parameters derived from the point cloud data.
Mahyar Aboutalebi; Alfonso F. Torres-Rua; Mac McKee; William P. Kustas; Hector Nieto; Maria Mar Alsina; Alex White; John H. Prueger; Lynn McKee; Joseph Alfieri; Lawrence Hipps; Calvin Coopmans; Nick Dokoozlian. Incorporation of Unmanned Aerial Vehicle (UAV) Point Cloud Products into Remote Sensing Evapotranspiration Models. Remote Sensing 2019, 12, 50 .
AMA StyleMahyar Aboutalebi, Alfonso F. Torres-Rua, Mac McKee, William P. Kustas, Hector Nieto, Maria Mar Alsina, Alex White, John H. Prueger, Lynn McKee, Joseph Alfieri, Lawrence Hipps, Calvin Coopmans, Nick Dokoozlian. Incorporation of Unmanned Aerial Vehicle (UAV) Point Cloud Products into Remote Sensing Evapotranspiration Models. Remote Sensing. 2019; 12 (1):50.
Chicago/Turabian StyleMahyar Aboutalebi; Alfonso F. Torres-Rua; Mac McKee; William P. Kustas; Hector Nieto; Maria Mar Alsina; Alex White; John H. Prueger; Lynn McKee; Joseph Alfieri; Lawrence Hipps; Calvin Coopmans; Nick Dokoozlian. 2019. "Incorporation of Unmanned Aerial Vehicle (UAV) Point Cloud Products into Remote Sensing Evapotranspiration Models." Remote Sensing 12, no. 1: 50.
A spatially distributed land surface temperature is important for many studies. The recent launch of the Sentinel satellite programs paves the way for an abundance of opportunities for both large area and long-term investigations. However, the spatial resolution of Sentinel-3 thermal images is not suitable for monitoring small fragmented fields. Thermal sharpening is one of the primary methods used to obtain thermal images at finer spatial resolution at a daily revisit time. In the current study, the utility of the TsHARP method to sharpen the low resolution of Sentinel-3 thermal data was examined using Sentinel-2 visible-near infrared imagery. Compared to Landsat 8 fine thermal images, the sharpening resulted in mean absolute errors of ~1 °C, with errors increasing as the difference between the native and the target resolutions increases. Part of the error is attributed to the discrepancy between the thermal images acquired by the two platforms. Further research is due to test additional sites and conditions, and potentially additional sharpening methods, applied to the Sentinel platforms.
Hanna Huryna; Yafit Cohen; Arnon Karnieli; Natalya Panov; William P. Kustas; Nurit Agam. Evaluation of TsHARP Utility for Thermal Sharpening of Sentinel-3 Satellite Images Using Sentinel-2 Visual Imagery. Remote Sensing 2019, 11, 2304 .
AMA StyleHanna Huryna, Yafit Cohen, Arnon Karnieli, Natalya Panov, William P. Kustas, Nurit Agam. Evaluation of TsHARP Utility for Thermal Sharpening of Sentinel-3 Satellite Images Using Sentinel-2 Visual Imagery. Remote Sensing. 2019; 11 (19):2304.
Chicago/Turabian StyleHanna Huryna; Yafit Cohen; Arnon Karnieli; Natalya Panov; William P. Kustas; Nurit Agam. 2019. "Evaluation of TsHARP Utility for Thermal Sharpening of Sentinel-3 Satellite Images Using Sentinel-2 Visual Imagery." Remote Sensing 11, no. 19: 2304.
William P. Kustas; Nurit Agam; Samuel Ortega-Farias. Forward to the GRAPEX special issue. Irrigation Science 2019, 37, 221 -226.
AMA StyleWilliam P. Kustas, Nurit Agam, Samuel Ortega-Farias. Forward to the GRAPEX special issue. Irrigation Science. 2019; 37 (3):221-226.
Chicago/Turabian StyleWilliam P. Kustas; Nurit Agam; Samuel Ortega-Farias. 2019. "Forward to the GRAPEX special issue." Irrigation Science 37, no. 3: 221-226.
Land cover has a strong effect on the evapotranspiration (ET) and the hydrologic cycle. Urbanization alters the land cover affecting the surface energy balance and ET by, for example, urban encroachment in agricultural areas. This study investigates the potential utility of high resolution ET in determining more accurately the impact of land cover on water use for an agricultural area. The approach was to apply the physically based two-source energy balance (TSEB) model to very high resolution (~8 m) aircraft thermal data and compare the ET pattern and distribution to TSEB output using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data acquired on 2 August 2012. Modeled flux components were validated using measurements collected from a network of 16 eddy covariance (EC) towers at the study site. The modeled ET using the aircraft data agreed satisfactorily with the flux tower measurements and had better performance than the TSEB model applied to the ASTER data. The percent errors between ET closed by the Bowen ratio (BR) and residual (RE) approaches were 3 and 1%, respectively. It is shown that the high resolution aircraft ET can more accurately determine the change in ET magnitude by having pure pixels of the main land cover types, namely urban, agriculture, and natural vegetation. As a result, the ET histogram exhibits a significant bi-modal distribution which can be used to accurately distinguish the impact on ET from urban versus agricultural land cover areas and potentially monitor the effect on ET over a landscape due to small changes in land cover. At the coarser 90 m resolution of ASTER, the TSEB ET estimates are more often a combination of urban and agricultural land cover ET near the urban-agriculture land cover boundaries. As a result, the bi-modal distribution in ET is almost nonexistent. This study demonstrates the potential utility of high resolution ET mapping for more accurately determining the magnitude of the ET differences between cropland and urban land cover. It also suggests that, with high resolution thermal imagery, TSEB is a potential tool for monitoring the impact on ET due to relatively small changes in land cover as a result of urban expansion. Such a tool would be useful for watershed management.
Jie Cheng; William P. Kustas. Using Very High Resolution Thermal Infrared Imagery for More Accurate Determination of the Impact of Land Cover Differences on Evapotranspiration in an Irrigated Agricultural Area. Remote Sensing 2019, 11, 613 .
AMA StyleJie Cheng, William P. Kustas. Using Very High Resolution Thermal Infrared Imagery for More Accurate Determination of the Impact of Land Cover Differences on Evapotranspiration in an Irrigated Agricultural Area. Remote Sensing. 2019; 11 (6):613.
Chicago/Turabian StyleJie Cheng; William P. Kustas. 2019. "Using Very High Resolution Thermal Infrared Imagery for More Accurate Determination of the Impact of Land Cover Differences on Evapotranspiration in an Irrigated Agricultural Area." Remote Sensing 11, no. 6: 613.
Yan Li; William P. Kustas; Chunlin Huang; Héctor Nieto; Erfan Haghighi; Martha C. Anderson; Francisco Domingo; Monica Garcia; Russell L. Scott. Evaluating Soil Resistance Formulations in Thermal‐Based Two‐Source Energy Balance (TSEB) Model: Implications for Heterogeneous Semiarid and Arid Regions. Water Resources Research 2019, 55, 1059 -1078.
AMA StyleYan Li, William P. Kustas, Chunlin Huang, Héctor Nieto, Erfan Haghighi, Martha C. Anderson, Francisco Domingo, Monica Garcia, Russell L. Scott. Evaluating Soil Resistance Formulations in Thermal‐Based Two‐Source Energy Balance (TSEB) Model: Implications for Heterogeneous Semiarid and Arid Regions. Water Resources Research. 2019; 55 (2):1059-1078.
Chicago/Turabian StyleYan Li; William P. Kustas; Chunlin Huang; Héctor Nieto; Erfan Haghighi; Martha C. Anderson; Francisco Domingo; Monica Garcia; Russell L. Scott. 2019. "Evaluating Soil Resistance Formulations in Thermal‐Based Two‐Source Energy Balance (TSEB) Model: Implications for Heterogeneous Semiarid and Arid Regions." Water Resources Research 55, no. 2: 1059-1078.
The energy delivered to the land surface via insolation is a primary driver of evapotranspiration (ET)—the exchange of water vapor between the land and atmosphere. Spatially distributed ET products are in great demand in the water resource management community for real-time operations and sustainable water use planning. The accuracy and deliverability of these products are determined in part by the characteristics and quality of the insolation data sources used as input to the ET models. This paper investigates the practical utility of three different insolation datasets within the context of a satellite-based remote sensing framework for mapping ET at high spatiotemporal resolution, in an application over the Sacramento–San Joaquin Delta region in California. The datasets tested included one reanalysis product: The Climate System Forecast Reanalysis (CFSR) at 0.25° spatial resolution, and two remote sensing insolation products generated with geostationary satellite imagery: a product for the continental United States at 0.2°, developed by the University of Wisconsin Space Sciences and Engineering Center (SSEC) and a coarser resolution (1°) global Clouds and the Earth’s Radiant Energy System (CERES) product. The three insolation data sources were compared to pyranometer data collected at flux towers within the Delta region to establish relative accuracy. The satellite products significantly outperformed CFSR, with root-mean square errors (RMSE) of 2.7, 1.5, and 1.4 MJ·m−2·d−1 for CFSR, CERES, and SSEC, respectively, at daily timesteps. The satellite-based products provided more accurate estimates of cloud occurrence and radiation transmission, while the reanalysis tended to underestimate solar radiation under cloudy-sky conditions. However, this difference in insolation performance did not translate into comparable improvement in the ET retrieval accuracy, where the RMSE in daily ET was 0.98 and 0.94 mm d−1 using the CFSR and SSEC insolation data sources, respectively, for all the flux sites combined. The lack of a notable impact on the aggregate ET performance may be due in part to the predominantly clear-sky conditions prevalent in central California, under which the reanalysis and satellite-based insolation data sources have comparable accuracy. While satellite-based insolation data could improve ET retrieval in more humid regions with greater cloud-cover frequency, over the California Delta and climatologically similar regions in the western U.S., the CFSR data may suffice for real-time ET modeling efforts.
Martha Anderson; George Diak; Feng Gao; Kyle Knipper; Christopher Hain; Elke Eichelmann; Kyle S. Hemes; Dennis Baldocchi; William Kustas; Yun Yang. Impact of Insolation Data Source on Remote Sensing Retrievals of Evapotranspiration over the California Delta. Remote Sensing 2019, 11, 216 .
AMA StyleMartha Anderson, George Diak, Feng Gao, Kyle Knipper, Christopher Hain, Elke Eichelmann, Kyle S. Hemes, Dennis Baldocchi, William Kustas, Yun Yang. Impact of Insolation Data Source on Remote Sensing Retrievals of Evapotranspiration over the California Delta. Remote Sensing. 2019; 11 (3):216.
Chicago/Turabian StyleMartha Anderson; George Diak; Feng Gao; Kyle Knipper; Christopher Hain; Elke Eichelmann; Kyle S. Hemes; Dennis Baldocchi; William Kustas; Yun Yang. 2019. "Impact of Insolation Data Source on Remote Sensing Retrievals of Evapotranspiration over the California Delta." Remote Sensing 11, no. 3: 216.
Accurate ground-based measurements of leaf area index (LAI) are needed for validation of remote sensing-based retrievals used in models estimating plant water use, stress, carbon assimilation and other land surface processes. Several methods for indirect LAI estimation with the Plant Canopy Analyzer (PCA, LAI-2200C, LI-COR, Lincoln, NE, USA) were evaluated using destructive (direct) leaf area measurements in three split-canopy vineyards and one double-vertical vineyard in California, as part of the Grape Remote sensing and Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). A method with the sensor facing the canopy, and four readings occurring evenly across the interrow space, had a coefficient of determination (R2) of 0.87 and relative root mean square error (RRMSE) of 16%, when compared to direct LAI measurements via destructive sampling. A previously used method, with the sensor facing down-row, showed lower correlation to direct LAI (R2 = 0.75, RRMSE = 33%) and underestimation which was mitigated by removing the outer sensor rings from analysis. A PCA method is recommended for rapid and accurate LAI estimation in split-canopy vineyards, though local calibration may be required. The method was tested within small units of ground surface area, which compliments high-resolution datasets such as those acquired by small unmanned aerial vehicles. The utility of ground-based LAI measurements to validate remote sensing products is discussed.
William A. White; Maria Mar Alsina; Héctor Nieto; Lynn G. McKee; Feng Gao; William P. Kustas. Determining a robust indirect measurement of leaf area index in California vineyards for validating remote sensing-based retrievals. Irrigation Science 2018, 37, 269 -280.
AMA StyleWilliam A. White, Maria Mar Alsina, Héctor Nieto, Lynn G. McKee, Feng Gao, William P. Kustas. Determining a robust indirect measurement of leaf area index in California vineyards for validating remote sensing-based retrievals. Irrigation Science. 2018; 37 (3):269-280.
Chicago/Turabian StyleWilliam A. White; Maria Mar Alsina; Héctor Nieto; Lynn G. McKee; Feng Gao; William P. Kustas. 2018. "Determining a robust indirect measurement of leaf area index in California vineyards for validating remote sensing-based retrievals." Irrigation Science 37, no. 3: 269-280.
Significant efforts have been made recently in the application of high-resolution remote sensing imagery (i.e., sub-meter) captured by unmanned aerial vehicles (UAVs) for precision agricultural applications for high-value crops such as wine grapes. However, at such high resolution, shadows will appear in the optical imagery effectively reducing the reflectance and emission signal received by imaging sensors. To date, research that evaluates procedures to identify the occurrence of shadows in imagery produced by UAVs is limited. In this study, the performance of four different shadow detection methods used in satellite imagery was evaluated for high-resolution UAV imagery collected over a California vineyard during the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) field campaigns. The performance of the shadow detection methods was compared and impacts of shadowed areas on the normalized difference vegetation index (NDVI) and estimated evapotranspiration (ET) using the Two-Source Energy Balance (TSEB) model are presented. The results indicated that two of the shadow detection methods, the supervised classification and index-based methods, had better performance than two other methods. Furthermore, assessment of shadowed pixels in the vine canopy led to significant differences in the calculated NDVI and ET in areas affected by shadows in the high-resolution imagery. Shadows are shown to have the greatest impact on modeled soil heat flux, while net radiation and sensible heat flux are less affected. Shadows also have an impact on the modeled Bowen ratio (ratio of sensible to latent heat) which can be used as an indicator of vine stress level.
Mahyar Aboutalebi; Alfonso F. Torres-Rua; William P. Kustas; Héctor Nieto; Calvin Coopmans; Mac McKee. Assessment of different methods for shadow detection in high-resolution optical imagery and evaluation of shadow impact on calculation of NDVI, and evapotranspiration. Irrigation Science 2018, 37, 407 -429.
AMA StyleMahyar Aboutalebi, Alfonso F. Torres-Rua, William P. Kustas, Héctor Nieto, Calvin Coopmans, Mac McKee. Assessment of different methods for shadow detection in high-resolution optical imagery and evaluation of shadow impact on calculation of NDVI, and evapotranspiration. Irrigation Science. 2018; 37 (3):407-429.
Chicago/Turabian StyleMahyar Aboutalebi; Alfonso F. Torres-Rua; William P. Kustas; Héctor Nieto; Calvin Coopmans; Mac McKee. 2018. "Assessment of different methods for shadow detection in high-resolution optical imagery and evaluation of shadow impact on calculation of NDVI, and evapotranspiration." Irrigation Science 37, no. 3: 407-429.
Vineyards’ canopy architecture and row structure pose unique challenges in modeling the radiation partitioning and energy exchange between the vine canopy and the interrow area. The vines are often pruned and manipulated to be strongly clumped, while mechanical harvesting requires wide rows, often with vine height to vine spacing ratio > 1. This paper estimates the intercepted radiation by the canopy, and the effect of this interception on the below canopy surface energy balance and evapotranspiration (ET). Measurements were conducted in an east–west oriented vineyard in CA during intensive observation periods as part of the grape remote sensing atmospheric profile and evapotrnspiration eXperiment (GRAPEX). Below canopy incoming shortwave radiation was measured at multiple positions across the interrow, and the surface energy balance/ET below the vine rows was measured for only one growing season (in 2015) using three micro-Bowen ratio (MBR) systems. These MBR systems were deployed across the interrow, in the north, center, and south of the interrow. A significant spatial and temporal variability in radiation was observed since the vines were not significantly pruned or manipulated and thus grew randomly into the interrow. However, when averaged across the interrow using the radiation sensor array, the values appeared to give reliable mean radiation extinction conditions that agreed with model estimates. The variation in the surface energy fluxes were dominated by the amount of transmitted radiation, while soil moisture was a second order effect. Daily estimates of ET from the three micro-Bowen ratio systems, weighted by their respective representative sampling area, yielded estimates similar to values computed by the correlation-based flux partitioning method, which utilizes high-frequency eddy covariance data measured above the canopy.
W. P. Kustas; N. Agam; J. G. Alfieri; L. G. McKee; J. H. Prueger; L. E. Hipps; A. M. Howard; Joshua Heitman. Below canopy radiation divergence in a vineyard: implications on interrow surface energy balance. Irrigation Science 2018, 37, 227 -237.
AMA StyleW. P. Kustas, N. Agam, J. G. Alfieri, L. G. McKee, J. H. Prueger, L. E. Hipps, A. M. Howard, Joshua Heitman. Below canopy radiation divergence in a vineyard: implications on interrow surface energy balance. Irrigation Science. 2018; 37 (3):227-237.
Chicago/Turabian StyleW. P. Kustas; N. Agam; J. G. Alfieri; L. G. McKee; J. H. Prueger; L. E. Hipps; A. M. Howard; Joshua Heitman. 2018. "Below canopy radiation divergence in a vineyard: implications on interrow surface energy balance." Irrigation Science 37, no. 3: 227-237.
For irrigated vineyards, accurate estimates of the sensible heat flux from the soil surface (HsHs) is essential for determining the contribution of soil evaporation (E) to evapotranspiration (ET) using thermal-based energy balance approaches. A key to an accurate estimate of HsHs is a robust physically-based soil resistance formulation. Here we compare the performance of two soil resistance formulations: a conventional resistance model (rKNrKN) derived from field and laboratory studies which has been extensively implemented in the thermal-based Two-Source Energy Balance (TSEB) model, and a recently developed physically-based soil resistance formulation (rHOrHO) that explicitly accounts for near-surface interactions affecting scalar fluxes at the soil surface in the presence of bluff-body roughness elements. Estimates of HsHs using the two resistance formulations were evaluated using in-situ observations from a drip-irrigated vineyard in the arid central Negev Highlands of Israel. The results indicate that the soil resistance model rHOrHO outperforms the rKNrKN formulation using standard model coefficients and provides robust estimates of HsHs independent of model calibration or parameter tuning. This offers an opportunity to advance the utility of TSEB model when applied to sparsely vegetated areas where ground-based calibration data are not available for adjusting coefficients in the rKNrKN formulation, and potentially improves its practical applications to heterogeneous landscapes by obviating its reliance on semi-empirical coefficients.
Yan Li; William P. Kustas; Chunlin Huang; Dilia Kool; Erfan Haghighi. Evaluation of soil resistance formulations for estimates of sensible heat flux in a desert vineyard. Agricultural and Forest Meteorology 2018, 260-261, 255 -261.
AMA StyleYan Li, William P. Kustas, Chunlin Huang, Dilia Kool, Erfan Haghighi. Evaluation of soil resistance formulations for estimates of sensible heat flux in a desert vineyard. Agricultural and Forest Meteorology. 2018; 260-261 ():255-261.
Chicago/Turabian StyleYan Li; William P. Kustas; Chunlin Huang; Dilia Kool; Erfan Haghighi. 2018. "Evaluation of soil resistance formulations for estimates of sensible heat flux in a desert vineyard." Agricultural and Forest Meteorology 260-261, no. : 255-261.
For monitoring water use in vineyards, it becomes important to evaluate the evapotranspiration (ET) contributions from the two distinct management zones: the vines and the interrow. Often the interrow is not completely bare soil but contains a cover crop that is senescent during the main growing season (nominally May–August), which in Central California is also the dry season. Drip irrigation systems running during the growing season supply water to the vine plant and re-wet some of the surrounding bare soil. However, most of the interrow cover crop is dry stubble by the end of May. This paper analyzes the utility of the thermal-based two-source energy balance (TSEB) model for estimating daytime ET using tower-based land surface temperature (LST) estimates over two Pinot Noir (Vitis vinifera) vineyards at different levels of maturity in the Central Valley of California near Lodi, CA. The data were collected as part of the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). Local eddy covariance (EC) flux tower measurements are used to evaluate the performance of the TSEB model output of the fluxes and the capability of partitioning the vine and cover crop transpiration (T) from the total ET or T/ET ratio. The results for the 2014–2016 growing seasons indicate that TSEB output of the energy balance components and ET, particularly, over the daytime period yield relative differences with flux tower measurements of less than 15%. However, the TSEB model in comparison with the correlation-based flux partitioning method overestimates T/ET during the winter and spring through bud break, but then underestimates during the growing season. A major factor that appears to affect this temporal behavior in T/ET is the daily LAI used as input to TSEB derived from a remote sensing product. An additional source of uncertainty is the use of local tower-based LST measurements, which are not representative of the flux tower measurement source area footprint.
W. P. Kustas; J. G. Alfieri; Héctor Nieto; T. G. Wilson; F. Gao; M. C. Anderson. Utility of the two-source energy balance (TSEB) model in vine and interrow flux partitioning over the growing season. Irrigation Science 2018, 37, 375 -388.
AMA StyleW. P. Kustas, J. G. Alfieri, Héctor Nieto, T. G. Wilson, F. Gao, M. C. Anderson. Utility of the two-source energy balance (TSEB) model in vine and interrow flux partitioning over the growing season. Irrigation Science. 2018; 37 (3):375-388.
Chicago/Turabian StyleW. P. Kustas; J. G. Alfieri; Héctor Nieto; T. G. Wilson; F. Gao; M. C. Anderson. 2018. "Utility of the two-source energy balance (TSEB) model in vine and interrow flux partitioning over the growing season." Irrigation Science 37, no. 3: 375-388.
Particularly in light of California’s recent multiyear drought, there is a critical need for accurate and timely evapotranspiration (ET) and crop stress information to ensure long-term sustainability of high-value crops. Providing this information requires the development of tools applicable across the continuum from subfield scales to improve water management within individual fields up to watershed and regional scales to assess water resources at county and state levels. High-value perennial crops (vineyards and orchards) are major water users, and growers will need better tools to improve water-use efficiency to remain economically viable and sustainable during periods of prolonged drought. To develop these tools, government, university, and industry partners are evaluating a multiscale remote sensing–based modeling system for application over vineyards. During the 2013–17 growing seasons, the Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project has collected micrometeorological and biophysical data within adjacent pinot noir vineyards in the Central Valley of California. Additionally, each year ground, airborne, and satellite remote sensing data were collected during intensive observation periods (IOPs) representing different vine phenological stages. An overview of the measurements and some initial results regarding the impact of vine canopy architecture on modeling ET and plant stress are presented here. Refinements to the ET modeling system based on GRAPEX are being implemented initially at the field scale for validation and then will be integrated into the regional modeling toolkit for large area assessment.
William P. Kustas; Martha C. Anderson; Joseph G. Alfieri; Kyle Knipper; Alfonso Torres-Rua; Christopher K. Parry; Héctor Nieto; Nurit Agam; William A. White; Feng Gao; Lynn McKee; John H. Prueger; Lawrence E. Hipps; Sebastian Los; Maria Mar Alsina; Luis Sanchez; Brent Sams; Nick Dokoozlian; Mac McKee; Scott Jones; Yun Yang; Tiffany G. Wilson; Fangni Lei; Andrew McElrone; Joshua Heitman; Adam M. Howard; Kirk Post; Forrest Melton; Christopher Hain. The Grape Remote Sensing Atmospheric Profile and Evapotranspiration Experiment. Bulletin of the American Meteorological Society 2018, 99, 1791 -1812.
AMA StyleWilliam P. Kustas, Martha C. Anderson, Joseph G. Alfieri, Kyle Knipper, Alfonso Torres-Rua, Christopher K. Parry, Héctor Nieto, Nurit Agam, William A. White, Feng Gao, Lynn McKee, John H. Prueger, Lawrence E. Hipps, Sebastian Los, Maria Mar Alsina, Luis Sanchez, Brent Sams, Nick Dokoozlian, Mac McKee, Scott Jones, Yun Yang, Tiffany G. Wilson, Fangni Lei, Andrew McElrone, Joshua Heitman, Adam M. Howard, Kirk Post, Forrest Melton, Christopher Hain. The Grape Remote Sensing Atmospheric Profile and Evapotranspiration Experiment. Bulletin of the American Meteorological Society. 2018; 99 (9):1791-1812.
Chicago/Turabian StyleWilliam P. Kustas; Martha C. Anderson; Joseph G. Alfieri; Kyle Knipper; Alfonso Torres-Rua; Christopher K. Parry; Héctor Nieto; Nurit Agam; William A. White; Feng Gao; Lynn McKee; John H. Prueger; Lawrence E. Hipps; Sebastian Los; Maria Mar Alsina; Luis Sanchez; Brent Sams; Nick Dokoozlian; Mac McKee; Scott Jones; Yun Yang; Tiffany G. Wilson; Fangni Lei; Andrew McElrone; Joshua Heitman; Adam M. Howard; Kirk Post; Forrest Melton; Christopher Hain. 2018. "The Grape Remote Sensing Atmospheric Profile and Evapotranspiration Experiment." Bulletin of the American Meteorological Society 99, no. 9: 1791-1812.
The ability to accurately monitor and anticipate changes in consumptive water use associated with changing land use and land management is critical to developing sustainable water management strategies in water-limited climatic regions. In this paper, we present an application of a remote sensing data fusion technique for developing high spatiotemporal resolution maps of evapotranspiration (ET) at scales that can be associated with changes in land use. The fusion approach combines ET map timeseries developed using an multi-scale energy balance algorithm applied to thermal data from Earth observation platforms with high spatial but low temporal resolution (e.g., Landsat) and with moderate resolution but frequent temporal coverage (e.g., MODIS (Moderate Resolution Imaging Spectroradiometer)). The approach is applied over the Sacramento-San Joaquin Delta region in California—an area critical to both agricultural production and drinking water supply within the state that has recently experienced stresses on water resources due to a multi-year (2012–2017) extreme drought. ET “datacubes” with 30-m resolution and daily timesteps were constructed for the 2015–2016 water years and related to detailed maps of land use developed at the same spatial scale. The ET retrievals are evaluated at flux sites over multiple land covers to establish a metric of accuracy in the annual water use estimates, yielding root-mean-square errors of 1.0, 0.8, and 0.3 mm day−1 at daily, monthly, and yearly timesteps, respectively, for all sites combined. Annual ET averaged over the Delta changed only 3 mm year−1 between water years, from 822 to 819 mm year−1, translating to an area-integrated total change in consumptive water use of seven thousand acre-feet (TAF). Changes were largest in areas with recorded land-use change between water years—most significantly, fallowing of crop land presumably in response to reductions in water availability and allocations due to the drought. Moreover, the time evolution in water use associated with wetland restoration—an effort aimed at reducing subsidence and carbon emissions within the inner Delta—is assessed using a sample wetland chronosequence. Region-specific matrices of consumptive water use associated with land use changes may be an effective tool for policymakers and farmers to understand how land use conversion could impact consumptive use and demand.
Martha Anderson; Feng Gao; Kyle Knipper; Christopher Hain; Wayne Dulaney; Dennis Baldocchi; Elke Eichelmann; Kyle Hemes; Yun Yang; Josue Medellin-Azuara; William Kustas. Field-Scale Assessment of Land and Water Use Change over the California Delta Using Remote Sensing. Remote Sensing 2018, 10, 889 .
AMA StyleMartha Anderson, Feng Gao, Kyle Knipper, Christopher Hain, Wayne Dulaney, Dennis Baldocchi, Elke Eichelmann, Kyle Hemes, Yun Yang, Josue Medellin-Azuara, William Kustas. Field-Scale Assessment of Land and Water Use Change over the California Delta Using Remote Sensing. Remote Sensing. 2018; 10 (6):889.
Chicago/Turabian StyleMartha Anderson; Feng Gao; Kyle Knipper; Christopher Hain; Wayne Dulaney; Dennis Baldocchi; Elke Eichelmann; Kyle Hemes; Yun Yang; Josue Medellin-Azuara; William Kustas. 2018. "Field-Scale Assessment of Land and Water Use Change over the California Delta Using Remote Sensing." Remote Sensing 10, no. 6: 889.
Savannas are among the most variable, complex and extensive biomes on Earth, supporting livestock and rural livelihoods. These water-limited ecosystems are highly sensitive to changes in both climatic conditions, and land-use/management practices. The integration of Earth Observation (EO) data into process-based land models enables monitoring ecosystems status, improving its management and conservation. In this paper, the use of the Two-Source Energy Balance (TSEB) model for estimating surface energy fluxes is evaluated over a Mediterranean oak savanna (dehesa). A detailed analysis of TSEB formulation is conducted, evaluating how the vegetation architecture (multiple layers) affects the roughness parameters and wind profile, as well as the reliability of EO data to estimate the ecosystem parameters. The results suggest that the assumption of a constant oak leaf area index is acceptable for the purposes of the study and the use of spectral information to derive vegetation indices is sufficiently accurate, although green fraction index may not reflect phenological conditions during the dry period. Although the hypothesis for a separate wind speed extinction coefficient for each layer is partially addressed, the results show that taking a single oak coefficient is more precise than using bulk system coefficient. The accuracy of energy flux estimations, with an adjusted Priestley–Taylor coefficient (0.9) reflecting the conservative water-use tendencies of this semiarid vegetation and a roughness length formulation which integrates tree structure and the low fractional cover, is considered adequate for monitoring the ecosystem water use (RMSD ~40 W m−2).
Ana Andreu; William P. Kustas; Maria Jose Polo; Arnaud Carrara; Maria P. González-Dugo. Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two-Source Energy Balance Model (TSEB) I. Remote Sensing 2018, 10, 567 .
AMA StyleAna Andreu, William P. Kustas, Maria Jose Polo, Arnaud Carrara, Maria P. González-Dugo. Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two-Source Energy Balance Model (TSEB) I. Remote Sensing. 2018; 10 (4):567.
Chicago/Turabian StyleAna Andreu; William P. Kustas; Maria Jose Polo; Arnaud Carrara; Maria P. González-Dugo. 2018. "Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two-Source Energy Balance Model (TSEB) I." Remote Sensing 10, no. 4: 567.
Dehesas are highly valuable agro-forestry ecosystems, widely distributed over Mediterranean-type climate areas, which play a key role in rural development, basing their productivity on a sustainable use of multiple resources (crops, livestock, wildlife, etc.). The information derived from remote sensing based models addressing ecosystem water consumption, at different scales, can be used by institutions and private landowners to support management decisions. In this study, the Two-Source Energy Balance (TSEB) model is analyzed over two Spanish dehesa areas integrating multiple satellites (MODIS and Landsat) for estimating water use (ET), vegetation ground cover, leaf area and phenology. Instantaneous latent heat (LE) values are derived on a regional scale and compared with eddy covariance tower (ECT) measurements, yielding accurate results (RMSDMODIS Las Majadas 44 Wm−2, Santa Clotilde RMSDMODIS 47 Wm−2 and RMSDLandsat 64 Wm−2). Daily ET(mm) is estimated using daily return interval of MODIS for both study sites and compared with the flux measurements of the ECTs, with RMSD of 1 mm day−1 over Las Majadas and 0.99 mm day−1 over Santa Clotilde. Distributed ET over Andalusian dehesa (15% of the region) is successfully mapped using MODIS images, as an approach to monitor the ecosystem status and the vegetation water stress on a regular basis.
Ana Andreu; William P. Kustas; Maria Jose Polo; Arnaud Carrara; Maria P. González-Dugo. Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two Source Energy Balance Model (TSEB) II—Integration of Remote Sensing Medium and Low Spatial Resolution Satellite Images. Remote Sensing 2018, 10, 558 .
AMA StyleAna Andreu, William P. Kustas, Maria Jose Polo, Arnaud Carrara, Maria P. González-Dugo. Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two Source Energy Balance Model (TSEB) II—Integration of Remote Sensing Medium and Low Spatial Resolution Satellite Images. Remote Sensing. 2018; 10 (4):558.
Chicago/Turabian StyleAna Andreu; William P. Kustas; Maria Jose Polo; Arnaud Carrara; Maria P. González-Dugo. 2018. "Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two Source Energy Balance Model (TSEB) II—Integration of Remote Sensing Medium and Low Spatial Resolution Satellite Images." Remote Sensing 10, no. 4: 558.
Wine grape quality and quantity are affected by vine growing conditions during critical phenological stages. Field observations of vine growth stages are too sparse to fully capture the spatial variability of vine conditions. In addition, traditional grape yield prediction methods are time consuming and require large amount grape samples. Remote sensing data provide detailed spatial and temporal information regarding vine development that is useful for vineyard management. In this study, Landsat surface reflectance products from 2013 and 2014 were used to map satellite-based Normalized Difference Vegetation Index (NDVI) and leaf area index (LAI) over two Vitis vinifera L. cv. Pinot Noir vineyards in California, USA. The spatial correlation between grape yield maps and the interpolated daily time series (LAI and NDVI) was quantified. NDVI and LAI were found to have similar performance as a predictor of spatial yield variability, providing peak correlations of 0.8 at specific times during the growing season, and the timing of this peak correlation differed for the two years of study. In addition, correlations with maximum and seasonal-cumulative vegetation indices were also evaluated, and showed slightly lower correlations with the observed yield maps. Finally, the within-season grape yield predictability was examined using a simple strategy in which the relationship between grape yield and vegetation indices were calibrated with limited ground measurements. This strategy has a strong potential to improve the accuracy and efficiency of yield estimation in comparison with traditional approaches used in the wine grape growing industry.
Liang Sun; Feng Gao; Martha C. Anderson; William P. Kustas; Maria M. Alsina; Luis Sanchez; Brent Sams; Lynn McKee; Wayne Dulaney; William A. White; Joseph G. Alfieri; John H. Prueger; Forrest Melton; Kirk Post. Daily Mapping of 30 m LAI and NDVI for Grape Yield Prediction in California Vineyards. Remote Sensing 2017, 9, 317 .
AMA StyleLiang Sun, Feng Gao, Martha C. Anderson, William P. Kustas, Maria M. Alsina, Luis Sanchez, Brent Sams, Lynn McKee, Wayne Dulaney, William A. White, Joseph G. Alfieri, John H. Prueger, Forrest Melton, Kirk Post. Daily Mapping of 30 m LAI and NDVI for Grape Yield Prediction in California Vineyards. Remote Sensing. 2017; 9 (4):317.
Chicago/Turabian StyleLiang Sun; Feng Gao; Martha C. Anderson; William P. Kustas; Maria M. Alsina; Luis Sanchez; Brent Sams; Lynn McKee; Wayne Dulaney; William A. White; Joseph G. Alfieri; John H. Prueger; Forrest Melton; Kirk Post. 2017. "Daily Mapping of 30 m LAI and NDVI for Grape Yield Prediction in California Vineyards." Remote Sensing 9, no. 4: 317.
Thermal and multispectral remote sensing data from low-altitude aircraft can provide high spatial resolution necessary for sub-field (≤ 10 m) and plant canopy (≤ 1 m) scale evapotranspiration (ET) monitoring. In this study, high-resolution (sub-meter-scale) thermal infrared and multispectral shortwave data from aircraft are used to map ET over vineyards in central California with the two-source energy balance (TSEB) model and with a simple model having operational immediate capabilities called DATTUTDUT (Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature). The latter uses contextual information within the image to scale between radiometric land surface temperature (TR) values representing hydrologic limits of potential ET and a non-evaporative surface. Imagery from 5 days throughout the growing season is used for mapping ET at the sub-field scale. The performance of the two models is evaluated using tower-based measurements of sensible (H) and latent heat (LE) flux or ET. The comparison indicates that TSEB was able to derive reasonable ET estimates under varying conditions, likely due to the physically based treatment of the energy and the surface temperature partitioning between the soil/cover crop inter-row and vine canopy elements. On the other hand, DATTUTDUT performance was somewhat degraded presumably because the simple scaling scheme does not consider differences in the two sources (vine and inter-row) of heat and temperature contributions or the effect of surface roughness on the efficiency of heat exchange. Maps of the evaporative fraction (EF = LE/(H + LE)) from the two models had similar spatial patterns but different magnitudes in some areas within the fields on certain days. Large EF discrepancies between the models were found on 2 of the 5 days (DOY 162 and 219) when there were significant differences with the tower-based ET measurements, particularly using the DATTUTDUT model. These differences in EF between the models translate to significant variations in daily water use estimates for these 2 days for the vineyards. Model sensitivity analysis demonstrated the high degree of sensitivity of the TSEB model to the accuracy of the TR data, while the DATTUTDUT model was insensitive to systematic errors in TR as is the case with contextual-based models. However, it is shown that the study domain and spatial resolution will significantly influence the ET estimation from the DATTUTDUT model. Future work is planned for developing a hybrid approach that leverages the strengths of both modeling schemes and is simple enough to be used operationally with high-resolution imagery.
Ting Xia; William P. Kustas; Martha C. Anderson; Joseph G. Alfieri; Feng Gao; Lynn McKee; John H. Prueger; Hatim M. E. Geli; Christopher M. U. Neale; Luis Sanchez; Maria Mar Alsina; Zhongjing Wang. Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes. Hydrology and Earth System Sciences 2016, 20, 1523 -1545.
AMA StyleTing Xia, William P. Kustas, Martha C. Anderson, Joseph G. Alfieri, Feng Gao, Lynn McKee, John H. Prueger, Hatim M. E. Geli, Christopher M. U. Neale, Luis Sanchez, Maria Mar Alsina, Zhongjing Wang. Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes. Hydrology and Earth System Sciences. 2016; 20 (4):1523-1545.
Chicago/Turabian StyleTing Xia; William P. Kustas; Martha C. Anderson; Joseph G. Alfieri; Feng Gao; Lynn McKee; John H. Prueger; Hatim M. E. Geli; Christopher M. U. Neale; Luis Sanchez; Maria Mar Alsina; Zhongjing Wang. 2016. "Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes." Hydrology and Earth System Sciences 20, no. 4: 1523-1545.
Water Energy Balance (WEB) Soil Vegetation Atmosphere Transfer (SVAT) modelling can be used to estimate soil moisture by forcing the model with observed data such as precipitation and solar radiation. Recently, an innovative approach that assimilates remotely sensed thermal infrared (TIR) observations into WEB-SVAT to improve the results has been proposed. However, the efficacy of the model-observation integration relies on the model's realistic representation of soil water processes. Here, we explore methods to improve the soil water processes of a simple WEB-SVAT model by adopting and incorporating an exponential root water uptake model with water stress compensation and establishing a more appropriate soil-biophysical linkage between root-zone moisture content, above-ground states and biophysical indices. The existing WEB-SVAT model is extended to a new Multi-layer WEB-SVAT with Dynamic Root distribution (MWSDR) that has five soil layers. Impacts of plant root depth variations, growth stages and phenological cycle of the vegetation on transpiration are considered in developing stages. Hydrometeorological and biogeophysical measurements collected from two experimental sites, one in Dookie, Victoria, Australia and the other in Ponca, Oklahoma, USA, are used to validate the new model. Results demonstrate that MWSDR provides improved soil moisture, transpiration and evaporation predictions which, in turn, can provide an improved physical basis for assimilating remotely sensed data into the model. Results also show the importance of having an adequate representation of vegetation-related transpiration process for an appropriate simulation of water transfer in a complicated system of soil, plants and atmosphere.
Minoo Hashemian; Dongryeol Ryu; Wade Crow; William P. Kustas. Improving root-zone soil moisture estimations using dynamic root growth and crop phenology. Advances in Water Resources 2015, 86, 170 -183.
AMA StyleMinoo Hashemian, Dongryeol Ryu, Wade Crow, William P. Kustas. Improving root-zone soil moisture estimations using dynamic root growth and crop phenology. Advances in Water Resources. 2015; 86 ():170-183.
Chicago/Turabian StyleMinoo Hashemian; Dongryeol Ryu; Wade Crow; William P. Kustas. 2015. "Improving root-zone soil moisture estimations using dynamic root growth and crop phenology." Advances in Water Resources 86, no. : 170-183.
Thermal and multispectral remote sensing data from low-altitude aircraft can provide high spatial resolution necessary for sub-field (≤ 10 m) and plant canopy (≤ 1m) scale evapotranspiration (ET) monitoring. In this study, high resolution aircraft sub-meter scale thermal infrared and multispectral shortwave data are used to map ET over vineyards in central California with the Two Source Energy Balance (TSEB) model and with a simple model called DATTUTDUT (Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature) which uses contextual information within the image to scale between radiometric land surface temperature (TR) values representing hydrologic limits of potential ET and a non-evaporative surface. Imagery from five days throughout the growing season is used for mapping ET at the sub-field scale. The performance of the two models is evaluated using tower-based energy flux measurements of sensible (H) and latent heat (LE) or ET. The comparison indicates that TSEB was able to derive reasonable ET estimates under varying conditions, likely due to the physically based treatment of the energy and the surface temperature partitioning between the soil/cover crop inter-row and vine canopy elements. On the other hand, DATTUTDUT performance was somewhat degraded presumably because the simple scaling scheme does not consider differences in the two sources (vine and inter-row) of heat and temperature contributions or the effect of surface roughness on the efficiency of heat exchange. Maps of the evaporative fraction (EF = LE/(H + LE)) from the two models had similar spatial patterns but different magnitudes in some areas within the fields on certain days. Large EF discrepancies between the models were found on two of the five days (DOY 162 and 219) when there were significant differences with the tower-based ET measurements, particularly using the DATTUTDUT model. These differences in EF between the models translate to significant variations in daily water use estimates for these two days for the vineyards. Model sensitivity analysis demonstrated the high degree of sensitivity of the TSEB model to the accuracy of the TR data while the DATTUTDUT model was insensitive as is the case with contextual-based models. However, study domain and spatial resolution will significantly influence the ET estimation from the DATTUTDUT model. Future work is planned for developing a hybrid approach that leverages the strengths of both modeling schemes and is simple enough to be used operationally with high resolution imagery.
Ting Xia; William P. Kustas; Martha C. Anderson; Joseph G. Alfieri; Feng Gao; Lynn McKee; John H. Prueger; Hatim M. E. Geli; Christopher M. U. Neale; Luis Sanchez; Maria Mar Alsina; Zhongjing Wang. Mapping evapotranspiration with high resolution aircraft imagery over vineyards using one and two source modeling schemes. Hydrology and Earth System Sciences Discussions 2015, 20, 1523 -1545.
AMA StyleTing Xia, William P. Kustas, Martha C. Anderson, Joseph G. Alfieri, Feng Gao, Lynn McKee, John H. Prueger, Hatim M. E. Geli, Christopher M. U. Neale, Luis Sanchez, Maria Mar Alsina, Zhongjing Wang. Mapping evapotranspiration with high resolution aircraft imagery over vineyards using one and two source modeling schemes. Hydrology and Earth System Sciences Discussions. 2015; 20 (4):1523-1545.
Chicago/Turabian StyleTing Xia; William P. Kustas; Martha C. Anderson; Joseph G. Alfieri; Feng Gao; Lynn McKee; John H. Prueger; Hatim M. E. Geli; Christopher M. U. Neale; Luis Sanchez; Maria Mar Alsina; Zhongjing Wang. 2015. "Mapping evapotranspiration with high resolution aircraft imagery over vineyards using one and two source modeling schemes." Hydrology and Earth System Sciences Discussions 20, no. 4: 1523-1545.