A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture

2009 ◽  
Vol 33 (2) ◽  
pp. 224-250 ◽  
Author(s):  
G. Petropoulos ◽  
T.N. Carlson ◽  
M.J. Wooster ◽  
S. Islam
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Energy ◽  
Land Surface ◽  
Vegetation Index ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Wide Range

Imagery from remote sensing systems, often combined with ancillary ground information, is able to provide repetitive, synoptic views of key parameters characterizing land surface interactions, including surface energy fluxes and surface soil moisture. Differing methodologies using a wide range of remote sensing data have been developed for this purpose. Approaches vary from purely empirical to more complex ones, including residual methods and those that have their basis in the biophysical properties characterizing a two-dimensional Ts/VI (surface temperature/ vegetation index) scatterplot domain derived from remote sensing observations. The present article aims to offer a comprehensive and systematic review of this latter group of methods, which differ in terms of the complexity and assumptions they entail as well as their requirement for field-based and other ancillary data. Prior to the review, the biophysical meanings and properties encapsulated in the Ts/VI feature space is elucidated, since these represent the building block upon which all the Ts/VI methods described herein are based. The overview of the Ts/VI methods is also very timely, as one such method is being scheduled in the operational retrieval of surface soil moisture content by the National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms due to be launched in the next 12 years starting from 2016.

scholarly journals An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data

2019 ◽  
Author(s):  
Bouchra Ait Hssaine ◽  
Olivier Merlin ◽  
Jamal Ezzahar ◽  
Nitu Ojha ◽  
Salah Er-raki ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Wide Range ◽  
The Mean

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1 km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1 km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014–2018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014–2018). The field was seeded for the 2014–2015 (S1), 2016–2017 (S2) and 2017–2018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015–2016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated αPT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved αPT remains at a mostly constant value (∼ 0.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181 W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62 W/m2 for S1, S2, S3 and B1 respectively.

scholarly journals Evaporative Fluxes and Surface Soil Moisture Retrievals in a Mediterranean Setting from Sentinel-3 and the “Simplified Triangle”

2020 ◽  
Vol 12 (19) ◽  
pp. 3192 ◽  
Author(s):  
George P. Petropoulos ◽  
Ionut Sandric ◽  
Dionissios Hristopulos ◽  
Toby Nahum Carlson
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Vegetation Index ◽  
Surface Soil ◽  
Correlation Coefficients ◽  
Feature Space ◽  
Surface Soil Moisture ◽  
Detailed Assessment ◽  
Mean Square Difference ◽  
Earth’S System

Earth Observation (EO) makes it possible to obtain information on key parameters characterizing interactions among Earth’s system components, such as evaporative fraction (EF) and surface soil moisture (SSM). Notably, techniques utilizing EO data of land surface temperature (Ts) and vegetation index (VI) have shown promise in this regard. The present study investigates, for the first time, the accuracy of one such technique, known as the “simplified triangle”, using Sentinel-3 EO data, acquired for 44 days in 2018 at three savannah FLUXNET sites in Spain. The technique was found to be able to predict both EF and SSM with reasonable accuracy when compared to collocated ground measurements. Comparisons performed for all days together showed relatively low Root Mean square Difference (RMSD) for both EF (0.191) and SSM (0.012 cm3 cm−3) and good correlation coefficients (R) of 0.721 and 0.577, respectively. Both EF and SSM were also largely in agreement with land cover and seasonal variability. The present study comprises the first detailed assessment of the “simplified triangle”, in this case, using Sentinel-3 data and in a Mediterranean setting. Findings, albeit preliminary, are of significant value regarding the use of the investigated technique as a tool of environmental management, and towards ongoing, worldwide efforts aiming at developing operationally relevant products based on the Ts/VI feature space and EO data based on new satellites such as Sentinel-3.

scholarly journals Estimate soil moisture using trapezoidal relationship between remotely sensed land surface temperature and vegetation index

2010 ◽  
Vol 7 (6) ◽  
pp. 8703-8740 ◽  
Author(s):  
W. Wang ◽  
D. Huang ◽  
X.-G. Wang ◽  
Y.-R. Liu ◽  
F. Zhou
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Surface Soil ◽  
Remotely Sensed ◽  
Surface Soil Moisture ◽  
Antecedent Precipitation ◽  
Walnut Gulch ◽  
Semi Arid Region

Abstract. The trapezoidal relationship between surface temperature (Ts) and vegetation index (VI) was used to estimate soil moisture in the present study. An iterative algorithm is proposed to estimate the vertices of the Ts~VI trapezoid theoretically for each grid, and then WDI is calculated for each grid using MODIS remotely sensed measurements of surface temperature and enhanced vegetation index (EVI). The capability of using WDI based on Ts~VI trapezoid to estimate soil moisture is evaluated using soil moisture observations and antecedent precipitation in the Walnut Gulch Experimental Watershed (WGEW) in Arizona, USA. The result shows that, Ts~VI trapezoid based WDI can well capture temporal variation in surface soil moisture, but the capability of detecting spatial variation is poor for such a semi-arid region as WGEW.

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