Remote sensing estimation of urban surface evapotranspiration based on a modified Penman–Monteith model

Abstract. To date, remote sensing-based algorithms for inferring urban surface evapotranspiration (ET) remain little studied. Based on the modifications of the remote sensing Penman–Monteith (RS-PM) model, we propose an urban RS-PM model for estimating urban surface ET. Compared with the traditional RS-PM model, our urban RS-PM model is specifically developed for urban areas and is characterized by the following improvements: (1) excluding the interference of impervious surface components in urban areas by replacing the vegetation cover fraction index with land surface component fraction parameters inversed through linear spectral mixture analysis for calculating the area proportions of vegetation and soil; (2) considering the effect of the component fractions of vegetation or soil on all energy components of the surface energy balance by applying the modified multisource parallel model for estimating the component latent heat flux; and (3) optimizing the calculation of the component net radiation flux by considering the component surface characteristics. This urban RS-PM model was tested on an urban area of Xuzhou in the eastern Chinese province of Jiangsu. Landsat 8 operational land imager and thermal infrared sensor satellite images acquired between 2014 and 2016, together with their corresponding meteorological data and flux observation data, were used for estimating the ET of the study area for eight dates with the model. The results were validated by the latent heat flux data observed by an open path eddy covariance system. Validation shows the goodness of fit (R2), the root-mean-square error, the mean relative error, and the correlation coefficient (r) between estimated ET and observed ET for the eight dates were 0.8965, 24.14  W  ·  m  −  2, 18.5%, and 0.9546, respectively. The results prove that the urban RS-PM model is effective in estimating ET of urban areas with an acceptable accuracy.

[1]  Jan M. H. Hendrickx,et al.  New Mexico Scintillometer Network: Supporting Remote Sensing and Hydrologic and Meteorological Models , 2009 .

[2]  M. S. Moran,et al.  Determination of sensible heat flux over sparse canopy using thermal infrared data , 1989 .

[3]  A. Granier.  Une nouvelle méthode pour la mesure du flux de sève brute dans le tronc des arbres , 1985 .

[4]  Li Jia,et al.  Evaluating parameterizations of aerodynamic resistance to heat transfer using field measurements , 2007 .

[5]  W. Brutsaert.  Evaporation into the atmosphere , 1982 .

[6]  Chen Wei,et al.  Vegetation role in controlling the ecoenvironmental conditions for sustainable urban environments: a comparison of Beijing and Islamabad , 2018 .

[7]  J. Wallace,et al.  Evaporation from sparse crops‐an energy combination theory , 2007 .

[8]  Ashok K. Keshari,et al.  An operational model for estimating Regional Evapotranspiration through Surface Energy Partitioning (RESEP) , 2002 .

[9]  K. N. Dollman,et al.  - 1 , 1743 .

[10]  Frank Veroustraete,et al.  Estimating evapotranspiration of European forests from NOAA-imagery at satellite overpass time: Towards an operational processing chain for integrated optical and thermal sensor data products , 2005 .

[11]  Matthew F. McCabe,et al.  Partitioning of evapotranspiration using a stable isotope technique in an arid and high temperature agricultural production system , 2017 .

[12]  A. Palisoc,et al.  NASA Jet Propulsion Laboratory , 2020, Definitions.

[13]  Maosheng Zhao,et al.  Development of a global evapotranspiration algorithm based on MODIS and global meteorology data , 2007 .

[14]  T. J. Lyons,et al.  Remote estimation of regional evapotranspiration , 2002, Environ. Model. Softw..

[15]  J. Monteith.  Evaporation and environment. , 1965, Symposia of the Society for Experimental Biology.

[16]  S. Running,et al.  A continuous satellite‐derived global record of land surface evapotranspiration from 1983 to 2006 , 2010 .

[17]  J. Norman,et al.  Surface flux estimation using radiometric temperature: A dual‐temperature‐difference method to minimize measurement errors , 2000 .

[18]  Yanzhao Zhou,et al.  Assessing the impacts of an ecological water diversion project on water consumption through high-resolution estimations of actual evapotranspiration in the downstream regions of the Heihe River Basin, China , 2018 .

[19]  Jan Čermák,et al.  Measured sap flow and simulated transpiration from a poplar stand in Flanders (Belgium) , 1999 .

[20]  Defa Mao,et al.  Estimation of Regional Evapotranspiration by TM/ETM+ Data over Heterogeneous Surfaces , 2007 .

[21]  Shashi B. Verma,et al.  Micrometeorological methods for measuring surface fluxes of mass and energy , 1990 .

[22]  Massimo Menenti,et al.  S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance , 2000 .

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

[24]  R. Gillies.  A verification of the 'triangle' method for obtaining surface water content and energy fluxes from remote measurements of Normalized Difference Vegetation Index (NDVI) and surface radiant temperature , 1997 .

[25]  Toshio Koike,et al.  Improvement of surface flux parametrizations with a turbulence‐related length , 2002 .

[26]  W. Kustas,et al.  A verification of the 'triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface e , 1997 .

[27]  A. J. Dolman,et al.  Transpiration of an oak forest as predicted from porometer and weather data , 1988 .

[28]  A. Karnieli,et al.  A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region , 2001 .

[29]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

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

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

[32]  Maosheng Zhao,et al.  Improvements to a MODIS global terrestrial evapotranspiration algorithm , 2011 .

[33]  J. Norman,et al.  Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover , 1999 .

[34]  M. Ridd.  Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing: comparative anatomy for cities , 1995 .

[35]  M. Mccabe,et al.  Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data , 2008 .

[36]  Frank Veroustraete,et al.  Assessment of Evapotranspiration and Soil Moisture Content Across Different Scales of Observation , 2008, Sensors.

[37]  L. J. Lambán,et al.  Combination of lumped hydrological and remote-sensing models to evaluate water resources in a semi-arid high altitude ungauged watershed of Sierra Nevada (Southern Spain). , 2018, The Science of the total environment.

[38]  野村栄一,et al.  2 , 1900, The Hatak Witches.

[39]  Shaomin Liu,et al.  Validation of remotely sensed evapotranspiration over the Hai River Basin, China , 2012 .

[40]  W. Chow,et al.  Solar radiation model , 2001 .

[41]  Amélie Rajaud,et al.  A simple surface conductance model to estimate regional evaporation using MODIS leaf area index and the Penman‐Monteith equation , 2008 .

[42]  Nathaniel A. Brunsell,et al.  Validating remotely sensed land surface fluxes in heterogeneous terrain with large aperture scintillometry , 2011 .

[43]  Dennis D. Baldocchi,et al.  A comparison of methods for determining forest evapotranspiration and its components: sap-flow, soil water budget, eddy covariance and catchment water balance , 2001 .

[44]  E. Noordman,et al.  SEBAL model with remotely sensed data to improve water-resources management under actual field conditions , 2005 .

[45]  P. Gowda,et al.  Utility of remote sensing-based surface energy balance models to track water stress in rain-fed switchgrass under dry and wet conditions , 2017 .

[46]  S. Running,et al.  Regional evaporation estimates from flux tower and MODIS satellite data , 2007 .

[47]  Martha C. Anderson,et al.  A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation , 2007 .

[48]  Xiaolin Chen,et al.  Stratified spectral mixture analysis of medium resolution imagery for impervious surface mapping , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[49]  L. Jiang,et al.  An intercomparison of regional latent heat flux estimation using remote sensing data , 2003 .

[50]  R. Kormann,et al.  An Analytical Footprint Model For Non-Neutral Stratification , 2001 .

[51]  S. Idso,et al.  An analysis of infrared temperature observations over wheat and calculation of latent heat flux , 1986 .

[52]  Alan T. Murray,et al.  Monitoring the composition of urban environments based on the vegetation-impervious surface-soil (VIS) model by subpixel analysis techniques , 2002 .

[53]  Fei Wang,et al.  An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data , 2015, Remote. Sens..

[54]  S. Goetz,et al.  Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005 , 2008 .

[55]  C. Small.  Estimation of urban vegetation abundance by spectral mixture analysis , 2001 .

[56]  S. Running,et al.  A review of remote sensing based actual evapotranspiration estimation , 2016 .

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

[58]  Zhanqing Li,et al.  A simple method to estimate actual evapotranspiration from a combination of net radiation, vegetation index, and temperature , 2007 .

[59]  Alan T. Murray,et al.  Estimating impervious surface distribution by spectral mixture analysis , 2003 .

[60]  V. Singh,et al.  A Two-source Trapezoid Model for Evapotranspiration (TTME) from satellite imagery , 2012 .

[61]  Richard H. Cuenca,et al.  Plant Water Use and Crop Curves for Hybrid Poplars , 2000 .

[62]  Adriaan A. Van de Griend,et al.  Bare soil surface resistance to evaporation by vapor diffusion under semiarid conditions , 1994 .

[63]  W R Edwards,et al.  Precision weighing lysimetry for trees, using a simplified tared-balance design. , 1986, Tree physiology.

[64]  B. Hurk,et al.  The scintillation method tested over a dry vineyard area , 1995 .

[65]  Pamela L. Nagler,et al.  Integrating Remote Sensing and Ground Methods to Estimate Evapotranspiration , 2007 .

[66]  R. Kingsford,et al.  Incorporating an iterative energy restraint for the Surface Energy Balance System (SEBS) , 2017 .

[67]  Jan Čermák,et al.  Sapwood as the scaling parameter - defining according to xylem water content or radial pattern of sap flow? , 1998 .

[68]  D. Lu,et al.  Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies , 2004 .

[69]  K. G. McNaughton,et al.  Effects of spatial scale on stomatal control of transpiration , 1991 .

[70]  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 .

[71]  Yu Zhang,et al.  A Modified Multi-Source Parallel Model for Estimating Urban Surface Evapotranspiration Based on ASTER Thermal Infrared Data , 2017, Remote. Sens..

[72]  S. Liang.  Narrowband to broadband conversions of land surface albedo I Algorithms , 2001 .

[73]  K. Davis,et al.  Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data , 2010 .

[74]  M. Kanda,et al.  Roughness Lengths for Momentum and Heat Derived from Outdoor Urban Scale Models , 2007 .

[75]  Matthew F. McCabe,et al.  Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors , 2006 .

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

[77]  S. Islam,et al.  Estimation of surface evaporation map over Southern Great Plains using remote sensing data , 2001 .

[78]  William P. Kustas,et al.  Comparing Aircraft-Based Remotely Sensed Energy Balance Fluxes with Eddy Covariance Tower Data Using Heat Flux Source Area Functions , 2005 .

[79]  John H. C. Gash,et al.  Vapour flux density and transpiration rate comparisons in a stand of Maritime pine (Pinus pinaster Ait.) in Les Landes forest , 1990 .

[80]  B. Séguin,et al.  Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches , 2005 .

[81]  K. J. McAneney,et al.  Large-aperture scintillometry: the homogeneous case , 1995 .

[82]  B. Choudhury,et al.  Parameterization of land surface evaporation by means of location dependent potential evaporation and surface temperature range , 2007 .

[83]  J. Wallace,et al.  Soil evaporation from tiger-bush in south-west Niger , 1997 .

[84]  Mark A. Friedl,et al.  Relationships among Remotely Sensed Data, Surface Energy Balance, and Area-Averaged Fluxes over Partially Vegetated Land Surfaces , 1996 .

[85]  Shawn C. Kefauver,et al.  Effect of observation scale on remote sensing based estimates of evapotranspiration in a semi-arid row cropped orchard environment , 2016, Precision Agriculture.

[86]  Di Long,et al.  Integration of the GG model with SEBAL to produce time series of evapotranspiration of high spatial resolution at watershed scales , 2010 .

[87]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[88]  Weiwei Ma,et al.  Discriminating lava flows of different age within Nyamuragira's volcanic field using spectral mixture analysis , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[89]  Thomas J. Jackson,et al.  Comparing the utility of microwave and thermal remote-sensing constraints in two-source energy balance modeling over an agricultural landscape , 2006 .

[90]  Chenghu Zhou,et al.  A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data , 2009, Sensors.

[91]  Li Xiaolong,et al.  Transformation of surface water and groundwater and water balance in the agricultural irrigation area of the Manas River Basin, China , 2017 .

[92]  Changshan Wu,et al.  Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery , 2004 .

[93]  J. A. Tolk,et al.  ET mapping for agricultural water management: present status and challenges , 2008, Irrigation Science.

[94]  Ü. Rannik,et al.  Gap filling strategies for defensible annual sums of net ecosystem exchange , 2001 .

[95]  A. Holtslag,et al.  A remote sensing surface energy balance algorithm for land (SEBAL)-1. Formulation , 1998 .

[96]  D. Lu,et al.  Spectral Mixture Analysis of the Urban Landscape in Indianapolis with Landsat ETM+ Imagery , 2004 .

[97]  Zhongbo Su,et al.  Estimating areal evaporation from remote sensing , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

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

[99]  Z. Qin,et al.  A practical split‐window algorithm for retrieving land‐surface temperature from MODIS data , 2005 .

[100]  Miguel Angel Lopez,et al.  Evapotranspiration from areas of native vegetation in West-Central Florida , 1996 .

[101]  Hongbo Su,et al.  An enhanced two-source evapotranspiration model for land (ETEML): Algorithm and evaluation , 2015 .