Comparison of Leaf Area Index, Surface Temperature, and Actual Evapotranspiration Estimated Using the METRIC Model and In Situ Measurements

The verification of remotely sensed estimates of surface variables is essential for any remote sensing study. The objective of this study was to compare leaf area index (LAI), surface temperature (Ts), and actual evapotranspiration (ETa), estimated using the remote sensing-based METRIC model and in situ measurements collected at the satellite overpass time. The study was carried out at a commercial corn field in eastern South Dakota. Six clear-sky images from Landsat 7 and Landsat 8 (Path 29, Row 29) were processed and used for the assessment. LAI and Ts were measured in situ, and ETa was estimated using an atmometer and independent crop coefficients. The results revealed good agreement between the variables measured in situ and estimated by the METRIC model. LAI showed r2 = 0.76, and RMSE = 0.59 m2 m−2, the Ts comparison had an agreement of r2 = 0.87 and RMSE 1.24 °C, and ETa presented r2 = 0.89 and RMSE = 0.71 mm day−1.

[1]  Steven R. Evett,et al.  Automation of a Center Pivot Using the Temperature-Time- Threshold Method of Irrigation Scheduling , 2008 .

[2]  S. Evett,et al.  Canopy temperature based system effectively schedules and controls center pivot irrigation of cotton , 2010 .

[3]  Pablo J. Zarco-Tejada,et al.  Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[4]  M. Tasumi,et al.  Integrating satellite-based evapotranspiration with simulation models for irrigation management at the scheme level , 2008, Irrigation Science.

[5]  Jindi Wang,et al.  Crop Leaf Area Index Observations With a Wireless Sensor Network and Its Potential for Validating Remote Sensing Products , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[6]  James L. Wright,et al.  Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Applications , 2007 .

[7]  P. Gowda,et al.  A Decade of Remote Sensing and Evapotranspiration Research at USDA-ARS Conservation and Production Research Laboratory , 2015, Emerging Technologies for Sustainable Irrigation.

[8]  Saleh Taghvaeian,et al.  Remote sensing for evaluating crop water stress at field scale using infra-red thermography : potential and limitations , 2013 .

[9]  D. Z. Haman,et al.  Determination of Crop Water Stress Index for Irrigation Timing and Yield Estimation of Corn , 2000 .

[10]  H. Jones,et al.  Remote Sensing of Vegetation: Principles, Techniques, and Applications , 2010 .

[11]  Ivan T. Gallardo Using infrared canopy temperature and leaf water potential for irrigation scheduling in peppermint (Mentha piperita L.) , 1992 .

[12]  Richard G. Allen,et al.  Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Model , 2007 .

[13]  P. Zarco-Tejada,et al.  Mapping crop water stress index in a ‘Pinot-noir’ vineyard: comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle , 2014, Precision Agriculture.

[14]  Samuel C. Zipper,et al.  Using evapotranspiration to assess drought sensitivity on a subfield scale with HRMET, a high resolution surface energy balance model , 2014 .

[15]  J. Hicke,et al.  Global synthesis of leaf area index observations: implications for ecological and remote sensing studies , 2003 .

[16]  M. Meron,et al.  Evaluation of different approaches for estimating and mapping crop water status in cotton with thermal imaging , 2010, Precision Agriculture.

[17]  M. Meron,et al.  Crop water status estimation using thermography: multi-year model development using ground-based thermal images , 2014, Precision Agriculture.

[18]  Terry A. Howell,et al.  Surface Energy Balance Based Evapotranspiration Mapping in the Texas High Plains , 2008, Sensors.

[19]  Thomas J. Trout,et al.  Estimating maize water stress by standard deviation of canopy temperature in thermal imagery , 2016 .

[20]  Zhihao Qin,et al.  Estimation of Crop LAI using hyperspectral vegetation indices and a hybrid inversion method , 2015 .

[21]  Q. Lier,et al.  Canopy temperature versus soil water pressure head for the prediction of crop water stress , 2013 .

[22]  Ronglin Tang,et al.  An intercomparison of three remote sensing-based energy balance models using Large Aperture Scintillometer measurements over a wheat–corn production region , 2011 .

[23]  Kelly R. Thorp,et al.  Remote sensing of evapotranspiration over cotton using the TSEB and METRIC energy balance models , 2015 .

[24]  Martha C. Anderson,et al.  Thermal Remote Sensing of Drought and Evapotranspiration , 2008 .

[25]  Kenton W. Peterson,et al.  Evaluation of Atmometers within Urban Home Lawn Microclimates , 2015 .

[26]  M. Timmons,et al.  Temperature Variations Within Caged-Layer Housing as Affected by Inlet Flow Characteristics , 1986 .

[27]  B. Markham,et al.  Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors , 2009 .

[28]  L. Ahiablame,et al.  Assessing Accuracy of Vegetation Index Method to Estimate Actual Evapotranspiration , 2018 .

[29]  Christopher Hay,et al.  Estimation of Evapotranspiration from Fields with and without Cover Crops Using Remote Sensing and in situ Methods , 2012, Remote. Sens..

[30]  J. Lenters,et al.  Remote sensing and in situ-based estimates of evapotranspiration for subirrigated meadow, dry valley, and upland dune ecosystems in the semi-arid sand hills of Nebraska, USA , 2010 .

[31]  Marvin E. Jensen,et al.  Evaporation, Evapotranspiration, and Irrigation Water Requirements , 2016 .

[32]  F. J. García-Haro,et al.  Derivation of high-resolution leaf area index maps in support of validation activities: Application to the cropland Barrax site , 2009 .

[33]  W. Bustamante,et al.  Evapotranspiration and Crop Water Stress Index in Mexican Husk Tomatoes (Physalis ixocarpa Brot) , 2011 .

[34]  R. Colombo,et al.  Retrieval of leaf area index in different vegetation types using high resolution satellite data , 2003 .

[35]  Wolfram Spreer,et al.  Monitoring physiological responses to water stress in two maize varieties by infrared thermography , 2011 .

[36]  Amine Merzouki,et al.  Estimation of Leaf Area Index (LAI) in corn and soybeans using multi-polarization C- and L-band radar data , 2015 .

[37]  J. Huntington,et al.  Reduced evapotranspiration from leaf beetle induced tamarisk defoliation in the Lower Virgin River using satellite‐based energy balance , 2016 .

[38]  Justin L. Huntington,et al.  EEFlux : A Landsat-based Evapotranspiration mapping tool on the Google Earth Engine , 2015 .

[39]  J. M. Norman,et al.  Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery , 2011 .

[40]  Paul D. Colaizzi,et al.  Remote Sensing Based Energy Balance Algorithms for Mapping ET: Current Status and Future Challenges , 2007 .

[41]  K. Hubbard,et al.  Estimation of Land Surface Evapotranspiration with a Satellite Remote Sensing Procedure , 2011 .

[42]  Ayse Irmak,et al.  Improved methods for estimating monthly and growing season ET using METRIC applied to moderate resolution satellite imagery , 2011 .

[43]  Fan Chen,et al.  Estimating reference crop evapotranspiration with ETgages. , 2009 .

[44]  Huihui Zhang,et al.  Satellite-based crop coefficient and regional water use estimates for Hawaiian sugarcane , 2015 .

[46]  D. W. Stewart,et al.  Canopy structure, light interception, and photosynthesis in maize , 2003 .

[47]  R. Allen,et al.  FINE-TUNING COMPONENTS OF INVERSE-CALIBRATED, THERMAL-BASED REMOTE SENSING MODELS FOR EVAPOTRANSPIRATION , 2008 .

[48]  Teferi D. Tsegaye,et al.  ESTIMATING COTTON LEAF AREA INDEX NONDESTRUCTIVELY WITH A LIGHT SENSOR , 2005 .

[49]  Henning Kage,et al.  Integrating Wheat Canopy Temperatures in Crop System Models , 2016 .

[50]  A. Viña,et al.  Green leaf area index estimation in maize and soybean: Combining vegetation indices to achieve maximal sensitivity , 2012 .

[51]  G. Senay,et al.  Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin , 2015 .

[52]  Baanda A. Salim,et al.  Effects of deficit irrigation scheduling on yields and soil water balance of irrigated maize , 2008, Irrigation Science.

[53]  Christopher Hay,et al.  Comparative Analysis of METRIC Model and Atmometer Methods for Estimating Actual Evapotranspiration , 2017 .

[54]  Matthew Bardeen,et al.  Selecting Canopy Zones and Thresholding Approaches to Assess Grapevine Water Status by Using Aerial and Ground-Based Thermal Imaging , 2016, Remote. Sens..

[55]  I. Broner,et al.  Evaluation of a modified atmometer for estimating reference ET , 1991, Irrigation Science.

[56]  W. Bastiaanssen Remote sensing in water resources management: the state of the art. , 1998 .

[57]  Tae-Woong Kim,et al.  Evapotranspiration estimation using the Landsat-5 Thematic Mapper image over the Gyungan watershed in Korea , 2011 .

[58]  Marcos Carrasco-Benavides,et al.  Parameterization of the Satellite-Based Model (METRIC) for the Estimation of Instantaneous Surface Energy Balance Components over a Drip-Irrigated Vineyard , 2014, Remote. Sens..

[59]  Samuel Ortega-Farías,et al.  Estimation of Energy Balance Components over a Drip-Irrigated Olive Orchard Using Thermal and Multispectral Cameras Placed on a Helicopter-Based Unmanned Aerial Vehicle (UAV) , 2016, Remote. Sens..

[60]  Ayse Irmak,et al.  Satellite‐based ET estimation in agriculture using SEBAL and METRIC , 2011 .

[61]  S. Irmak,et al.  Using Modified Bellani Plate Evapotranspiration Gauges to Estimate Short Canopy Reference Evapotranspiration , 2005 .

[62]  T. P. Trooien,et al.  ESTIMATING REFERENCE EVAPOTRANSPIRATION WITH AN ATMOMETER , 2001 .

[63]  Wolfram Spreer,et al.  Use of thermography for high throughput phenotyping of tropical maize adaptation in water stress , 2011 .

[64]  Performance of atmometers in estimating reference evapotranspiration in a semi-arid environment , 2013 .

[65]  Christopher Hay,et al.  Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index , 2018 .

[66]  Zheng Niu,et al.  Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2 , 2013, Int. J. Appl. Earth Obs. Geoinformation.