Ronglin Tang

A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data

An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements.

Validating MODIS‐derived land surface evapotranspiration with in situ measurements at two AmeriFlux sites in a semiarid region

Reducing uncertainties in the estimation of land surface evapotranspiration (ET) from remote-sensing data is essential to better understand earth-atmosphere interactions. This paper demonstrates the applicability of temperature-vegetation index triangle (T-s-VI) method in estimating regional ET and evaporative fraction (EF, defined as the ratio of latent heat flux to surface available energy) from MODIS/Terra and MODIS/Aqua products in a semiarid region. We have compared the satellite-based estimates of ET and EF with eddy covariance measurements made over 4 years at two semiarid grassland sites: Audubon Ranch (AR) and Kendall Grassland (KG). The lack of closure in the eddy covariance measured surface energy components is shown to be more serious at MODIS/Aqua overpass time than that at MODIS/Terra overpass time for both AR and KG sites. The T-s-VI-derived EF could reproduce in situ EF reasonably well with BIAS and root-mean-square difference (RMSD) of less than 0.07 and 0.13, respectively. Surface net radiation has been shown to be systematically overestimated by as large as about 60 W/m(2). Satisfactory validation results of the T-s-VI-derived sensible and latent heat fluxes have been obtained with RMSD within 54 W/m(2). The simplicity and yet easy use of the T-s-VI triangle method show a great potential in estimating regional ET with highly acceptable accuracy that is of critical significance in better understanding water and energy budgets on the Earth. Nevertheless, more validation work should be carried out over various climatic regions and under other different land use/land cover conditions in the future.

Surface Soil Water Content Estimation from Thermal Remote Sensing based on the Temporal Variation of Land Surface Temperature

Soil water content (SWC) is a crucial variable in the thermal infrared research and is the major control for land surface hydrological processes at the watershed scale. Estimating the surface SWC from remotely sensed data using the triangle method proposed by Price has been demonstrated in previous studies. In this study, a new soil moisture index (Temperature Rising Rate Vegetation Dryness IndexTRRVDI) is proposed based on a triangle constructed using the mid-morning land surface temperature (LST) rising rate and the vegetation index to estimate the regional SWC. The temperature at the dry edge of the triangle is determined by the surface energy balance principle. The temperature at the wet edge is assumed to be equal to the air temperature. The mid-morning land surface temperature rising rate is calculated using Meteosat Second GenerationSpinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) LST products over 4 cloud-free days (day of year: 206, 211, 212, 242) in 2007. The developed TRRVDI is validated by in situ measurements from 19 meteorological stations in Spain. The results indicate that the coefficient of determination (R-2) between the TRRVDI derived using the theoretical limiting edges and the in situ SWC measurements is greater than that derived using the observed limiting edges. The R-2 values are 0.46 and 0.32; respectively (p < 0.05). Additionally, the TRRVDI is much better than the soil moisture index that was developed using one-time LST and fractional vegetation cover (FVC) with the theoretically determined limiting edges.

Estimation of Diurnal Cycle of Land Surface Temperature at High Temporal and Spatial Resolution from Clear-Sky MODIS Data

The diurnal cycle of land surface temperature (LST) is an important element of the climate system. Geostationary satellites can provide the diurnal cycle of LST with low spatial resolution and incomplete global coverage, which limits its applications in some studies. In this study, we propose a method to estimate the diurnal cycle of LST at high temporal and spatial resolution from clear-sky MODIS data. This method was evaluated using the MSG-SEVIRI-derived LSTs. The results indicate that this method fits the diurnal cycle of LST well, with root mean square error (RMSE) values less than 1 K for most pixels. Because MODIS provides at most four observations per day at a given location, this method was further evaluated using only four MSG-SEVIRI-derived LSTs corresponding to the MODIS overpass times (10:30, 13:30, 22:30, and 01:30 local solar time). The results show that the RMSE values using only four MSG-SEVIRI-derived LSTs are approximately two times larger than those using all LSTs. The spatial distribution of the modeled LSTs at the MODIS pixel scale is presented from 07:00 to 05:00 local solar time of the next day with an increment of 2 hours. The diurnal cycle of the modeled LSTs describes the temporal evolution of the LSTs at the MODIS pixel scale.

Evaluating one-and two-source energy balance models in estimating surface evapotranspiration from Landsat-derived surface temperature and field measurements

This article compares one- and two-source energy balance (OSEB and TSEB) models in the estimates of surface energy components using Landsat imagery and surface measurements acquired from an experimental field at Yucheng Station in Northern China. Compared to surface measurements, similar performance between the TSEB and OSEB models has been observed for estimated surface net radiation and soil heat flux. The root mean square difference (RMSD) is within 14–39 W m−2 in both the TSEB and OSEB models. The residual energy (E R) correction method yields the best agreement in comparisons of the sensible (H) and latent (LE) heat fluxes estimated using both the TSEB and OSEB models to the eddy covariance (EC) system measurements. The TSEB model is shown to greatly outperform the OSEB model in reproducing surface H and LE measurements. Cirrus clouds are likely responsible for the surface temperature retrieved from the enhanced thematic mapper plus (ETM+) sensor being lower than air temperature on days of the year (DOYs) 178 and 218 of 2009. This atmospheric stability is contrary to the unstable atmosphere that the EC measurements observe. If data on these two days are excluded and the E R correction method is applied, when comparing the estimated H and LE to the EC measurements, RMSD is within 55 W m−2 in the TSEB model and is larger than 97 W m−2 in the OSEB model.

Derivation of Daily Evaporative Fraction Based on Temporal Variations in Surface Temperature, Air Temperature, and Net Radiation

Based on surface energy balance and the assumption of fairly invariant evaporative fraction (EF) during daytime, this study proposes a new parameterization scheme of directly estimating daily EF. Daily EF is parameterized as a function of temporal variations in surface temperature, air temperature, and net radiation. The proposed EF parameterization scheme can well reproduce daily EF estimates from a soil-vegetation-atmosphere transfer (SVAT) model with a root mean square error (RMSE) of 0.13 and a coefficient of determination (R-2) of 0.719. When input variables from in situ measurements at the Yucheng station in North China are used, daily EF estimated by the proposed method is in good agreement with measurements from the eddy covariance system corrected by the residual energy method with an R-2 of 0.857 and an RMSE of 0.119. MODIS/Aqua remotely sensed data were also applied to estimate daily EF. Though there are some inconsistencies between the remotely sensed daily EF estimates and in situ measurements due to errors in input variables and measurements, the result from the proposed parameterization scheme shows a slight improvement to SEBS-estimated EF with remotely sensed instantaneous inputs.

Multiscale Validation of the 8-day MOD16 Evapotranspiration Product Using Flux Data Collected in China

Accurate estimates of terrestrial evapotranspiration (ET) are critical and significant to the field for modeling water and energy transfer between the land surface and atmosphere. This paper evaluates the 8-day MOD16 actual ET product using the ground-based eddy covariance (EC) system and large aperture scintillometer (LAS) measurements collected from 2008 to 2011 at seven sites in North and Northwest China. Overall, the 8-day MOD16 ET reproduces the temporal patterns of both the LAS and EC measurements but tends to underestimate and overestimate these measurements at high and low ET levels, respectively. It is also of limited use when surface is irrigated because under such condition significant underestimation is observed. Using the LAS measurements that also include a large source area does not generate a better agreement than using the EC measurements which comprise a small source area. The 8-day MOD16 ET averaged over

A Simple Method for Soil Moisture Determination From LST–VI Feature Space Using Nonlinear Interpolation Based on Thermal Infrared Remotely Sensed Data

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An improved NDVI-based threshold method for estimating land surface emissivity using MODIS satellite data

MODIS pixels agree better with both the EC and LAS measurements than that extracted at the

A new parameterization scheme for estimating surface energy fluxes with continuous surface temperature, air temperature, and surface net radiation measurements

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