Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors

Abstract There is considerable interest in using remote sensing to characterize the hydrologic behavior of the land surface on a routine basis. Information on moisture fluxes between the surface and lower atmosphere reveals linkages and land–atmosphere feedback mechanisms, aiding our understanding of energy and water balance cycles. Techniques that combine information on land and atmospheric properties with remotely sensed variables would allow improved prediction for a number of hydrological variables. Over the last few decades, there has been a focus on better determining evapotranspiration and its spatial variability, but for many regions routine prediction is not generally available at a spatial resolution appropriate to the underlying surface heterogeneity. Over agricultural regions, this is particularly critical, since the spatial extent of typical field scales is not regularly resolved within the pixel resolution of satellite sensors. Understanding the role of landscape heterogeneity and its influence on the scaling behavior of surface fluxes as observed by satellite sensors with different spatial resolutions is a critical research need. To attend this task, data from Landsat-ETM (60 m), ASTER (90 m), and MODIS (1020 m) satellite platforms are employed to independently estimate evapotranspiration. The range of the satellite sensor resolutions allows analyses that span scales from (point-scale) in-situ tower measurements to the MODIS kilometer-scale. Evapotranspiration estimates derived at these multiple resolutions were assessed against eddy covariance flux measurements collected during the 2002 Soil Moisture Atmospheric Coupling Experiment (SMACEX) over the Walnut Creek watershed in Iowa. Together, these data allow a comprehensive scale intercomparison of remotely sensed predictions, which include intercomparisons of the evapotranspiration products from the various sensors as well as a statistical analysis for the retrievals at the watershed scale. A high degree of consistency was observed between the retrievals from the higher-resolution satellite platforms (Landsat-ETM and ASTER). The MODIS-based estimates, while unable to discriminate the influence of land surface heterogeneity at the field scale, effectively reproduced the watershed average response, illustrating the utility of this sensor for regional-scale evapotranspiration estimation.

[1]  Martha C. Anderson,et al.  Estimating subpixel surface temperatures and energy fluxes from the vegetation index-radiometric temperature relationship , 2003 .

[2]  A. C. Xavier,et al.  Monitoring leaf area index at watershed level through NDVI from Landsat-7/ETM+ data , 2004 .

[3]  Y. Kerr,et al.  Scaling up in Hydrology Using Remote Sensing , 1996 .

[4]  Wilfried Brutsaert,et al.  Aspects of bulk atmospheric boundary layer similarity under free‐convective conditions , 1999 .

[5]  Craig S. T. Daughtry,et al.  Estimation of the soil heat flux/net radiation ratio from spectral data , 1990 .

[6]  D. Stannard A THEORETICALLY BASED DETERMINATION OF BOWEN-RATIO FETCH REQUIREMENTS , 1997 .

[7]  J. Norman,et al.  Remote sensing of surface energy fluxes at 101‐m pixel resolutions , 2003 .

[8]  Matthew F. McCabe,et al.  Surface energy fluxes with the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) at the Iowa 2002 SMACEX site (USA) , 2005 .

[9]  T. Schmugge,et al.  Deriving land surface temperature from Landsat 5 and 7 during SMEX02/SMACEX , 2004 .

[10]  Zhao-Liang Li,et al.  Definition of component effective emissivity for heterogeneous and non-isothermal surfaces and its approximate calculation , 2004 .

[11]  J. Norman,et al.  Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature , 1995 .

[12]  A. C. Xavier,et al.  Mapping leaf area index through spectral vegetation indices in a subtropical watershed , 2004 .

[13]  William P. Kustas,et al.  Tower and Aircraft Eddy Covariance Measurements of Water Vapor, Energy, and Carbon Dioxide Fluxes during SMACEX , 2005 .

[14]  Z. Su The Surface Energy Balance System ( SEBS ) for estimation of turbulent heat fluxes , 2002 .

[15]  Wilfried Brutsaert,et al.  Evaporation into the atmosphere : theory, history, and applications , 1982 .

[16]  H. E. Jobson Evaporation Into the Atmosphere: Theory, History, and Applications , 1982 .

[17]  José A. Sobrino,et al.  A Comparative Study of Land Surface Emissivity Retrieval from NOAA Data , 2001 .

[18]  William P. Kustas,et al.  Estimates of Evapotranspiration with a One- and Two-Layer Model of Heat Transfer over Partial Canopy Cover , 1990 .

[19]  Beryl Graham,et al.  Digital Media , 2003 .

[20]  Jeff Dozier,et al.  A generalized split-window algorithm for retrieving land-surface temperature from space , 1996, IEEE Trans. Geosci. Remote. Sens..

[21]  Scaling, soil moisture and evapotranspiration in runoff models , 1994 .

[22]  W. Bastiaanssen,et al.  A remote sensing surface energy balance algorithm for land (SEBAL). , 1998 .

[23]  W. Kustas,et al.  The Soil Moisture–Atmosphere Coupling Experiment (SMACEX): Background, Hydrometeorological Conditions, and Preliminary Findings , 2005 .

[24]  Matthew F. McCabe,et al.  Modeling Evapotranspiration during SMACEX: Comparing Two Approaches for Local- and Regional-Scale Prediction , 2005 .

[25]  M. S. Moran,et al.  The scaling characteristics of remotely-sensed variables for sparsely-vegetated heterogeneous landscapes , 1997 .

[26]  R. Colwell Remote sensing of the environment , 1980, Nature.

[27]  Thomas J. Jackson,et al.  Effects of remote sensing pixel resolution on modeled energy flux variability of croplands in Iowa , 2004 .

[28]  A. Jacobsen,et al.  Estimation of the soil heat flux/net radiation ratio based on spectral vegetation indexes in high-latitude Arctic areas , 1999 .

[29]  Martha C. Anderson,et al.  Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans , 2004 .

[30]  W. Massman,et al.  AN ANALYTICAL ONE-DIMENSIONAL MODEL OF MOMENTUM TRANSFER BY VEGETATION OF ARBITRARY STRUCTURE , 1997 .

[31]  Z. Su The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes , 2002 .

[32]  J. Finnigan,et al.  Scale issues in boundary-layer meteorology: Surface energy balances in heterogeneous terrain , 1995 .

[33]  J. Monteith Evaporation and surface temperature , 2007 .

[34]  M. Wu,et al.  Principles of environmental physics , 2004, Plant Growth Regulation.

[35]  T. Meixner Spatial Patterns in Catchment Hydrology: Observations and Modelling , 2002 .

[36]  Terry Lyons,et al.  Effect of sharp vegetation boundary on the convective atmospheric boundary layer , 2002 .

[37]  J. Clevers,et al.  The robustness of canopy gap fraction estimates from red and near-infrared reflectances: A comparison of approaches , 1995 .

[38]  Matthew F. McCabe,et al.  Corrigendum to ¿Surface energy fluxes with the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) at the Iowa 2002 SMACEX site (USA)¿ [Remote Sensing of Environment 2005 99/1¿2;55¿65] , 2005 .

[39]  Zhao-Liang Li,et al.  Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data , 2002 .

[40]  Thomas J. Jackson,et al.  Soil moisture estimation using special satellite microwave/imager satellite data over a grassland region , 1997 .

[41]  J. Norman,et al.  Correcting eddy-covariance flux underestimates over a grassland , 2000 .

[42]  A S Monin,et al.  BASIC LAWS OF TURBULENT MIXING IN THE GROUND LAYER OF ATMOSPHERE , 1954 .

[43]  Shuichi Rokugawa,et al.  A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images , 1998, IEEE Trans. Geosci. Remote. Sens..

[44]  Murugesu Sivapalan,et al.  Scale issues in hydrological modelling , 1995 .

[45]  M. Mccabe,et al.  Evaluation of AMSR-E-Derived Soil Moisture Retrievals Using Ground-Based and PSR Airborne Data during SMEX02 , 2005 .

[46]  S. Idso,et al.  Analysis of an empirical model for soil heat flux under a growing wheat crop for estimating evaporation by an infrared-temperature based energy balance equation , 1987 .

[47]  Monique Y. Leclerc,et al.  Footprint prediction of scalar fluxes from analytical solutions of the diffusion equation , 1990 .

[48]  Eni G. Njoku,et al.  Effects of Surface Heterogeneity on Thermal Remote Sensing of Land Parameters , 1995 .

[49]  G. SCALE ISSUES IN HYDROLOGICAL MODELLING : A REVIEW , 2006 .

[50]  D. I. Cooper,et al.  Spatial source-area analysis of three-dimensional moisture fields from lidar, eddy covariance, and a footprint model , 2003 .

[51]  K. Mitchell,et al.  Assessment of the Land Surface and Boundary Layer Models in Two Operational Versions of the NCEP Eta Model Using FIFE Data , 1997 .

[52]  Scott J. Goetz,et al.  Inference of surface and air temperature, atmospheric precipitable water and vapor pressure deficit using Advanced Very High-Resolution Radiometer satellite observations: comparison with field observations , 1998 .

[53]  Martha C. Anderson,et al.  Upscaling ground observations of vegetation water content, canopy height, and leaf area index during SMEX02 using aircraft and Landsat imagery , 2004 .

[54]  William P. Kustas,et al.  Evaluating the effects of subpixel heterogeneity on pixel average fluxes. , 2000 .