Component radiative temperatures over sparsely vegetated surfaces and their potential for upscaling land surface temperature

Li, Mingsong; Zhou, Ji; Zhixing, Peng; Liu, Shaomin; Göttsche, Frank-M.; Zhang, Xiaodong; Song, Lisheng

doi:10.1016/j.agrformet.2019.05.031

Cited by 12 publications

(4 citation statements)

References 63 publications

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“…Additionally, thermal infrared radiometers and imagers were installed at the Mixed Forest and Sidaoqiao stations to measure different component temperatures, i.e., the brightness temperature of different land cover types under different illumination conditions (Li et al, 2019). The soil parameters and groundwater table were also observed around the stations.…”

Section: Natural Oasis and Desert Areas In The Lower Reachesmentioning

confidence: 99%

A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin

Liu,

Xu,

Che

et al. 2023

Earth Syst. Sci. Data

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Abstract. Oases and deserts generally act as a landscape matrix and mosaic in arid and semiarid regions. The significant difference in thermal and dynamic characteristics between an oasis and desert surface will result in oasis–desert interaction. Specifically, this refers to the interaction between an oasis and desert system via the exchange of momentum, energy, water, and carbon, which can lead to a series of microclimate effects that affect the structure of the atmospheric boundary layer, changes in carbon sources and sinks in an oasis, and the local ecological environment. Therefore, studying water, heat, and carbon exchange is significant to achieve the goals of carbon peaking and carbon neutrality in oasis–desert areas and support the ecological security and sustainable development of oases. To monitor energy, water vapor, and carbon exchange between the land surface and atmosphere, a land surface process integrated observatory network was established in the oasis–desert area in the middle and lower reaches of the Heihe River basin, the second largest endorheic basin in China. In this study, we present a suite of observational datasets from artificial and natural oasis–desert systems that consist of long-term energy, water vapor, carbon and methane fluxes as well as auxiliary data involving hydrometeorology, vegetation, and soil parameters from 2012 to 2021. Half-hourly turbulent flux data were acquired by an eddy covariance system and scintillometer. The hydrometeorological data (including radiation, soil heat flux, and soil temperature profiles; gradients of air temperature and humidity and of wind speed and direction; and air pressure, precipitation, and soil moisture profiles) were observed from automatic weather stations with a 10 min average period as well as the groundwater table data. Moreover, vegetation and soil parameters were also supplemented in the datasets. Careful data processing and quality control were implemented during data production, including data collection, processing, archiving, and sharing. The current datasets can be used to explore the water–heat–carbon process and its mechanism of influence; to calibrate and validate related remote-sensing products; to simulate energy, water vapor, and carbon exchange in oasis and desert areas; and to provide references and representatives for other similar artificial and natural oases along the “Silk Road”. The data are available from the National Tibetan Plateau Third Pole Environment: https://doi.org/10.11888/Terre.tpdc.300441 (Liu et al., 2023).

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Section: Natural Oasis and Desert Areas In The Lower Reachesmentioning

confidence: 99%

A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin

Liu,

Xu,

Che

et al. 2023

Earth Syst. Sci. Data

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“…3 Comparison of the spatial heterogeneity of LSHCs between the site measurements and remote sensing data based on the CV in the midstream flux observation matrix (3 km × 3 km) from June to September in 2012. LAI refers to the Leaf Area Index, SM refers to the Soil Moisture, Rn refers to the Net Radiation, LST refers to the Land Surface Temperature, and ET refers to the evapotranspiration the spatial heterogeneity of land surface moisture conditions (Li et al, 2019;Zhang et al, 2019), thus, the SM data were not used for later analysis. Fig.…”

Section: Flow Chartmentioning

confidence: 99%

Evaluating Spatial Heterogeneity of Land Surface Hydrothermal Conditions in the Heihe River Basin

Zhang

Liu

et al. 2020

Chin. Geogr. Sci.

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Land surface hydrothermal conditions (LSHCs) reflect land surface moisture and heat conditions, and play an important role in energy and water cycles in soil-plant-atmosphere continuum. Based on comparison of four evaluation methods (namely, the classic statistical method, geostatistical method, information theory method, and fractal method), this study proposed a new scheme for evaluating the spatial heterogeneity of LSHCs. This scheme incorporates diverse remotely sensed surface parameters, e.g., leaf area index-LAI, the normalized difference vegetation index-NDVI, net radiation-Rn, and land surface temperature-LST. The LSHCs can be classified into three categories, namely homogeneous, moderately heterogeneous and highly heterogeneous based on the remotely sensed LAI data with a 30 m spatial resolution and the combination of normalized information entropy (S') and coefficient of variation (CV). Based on the evaluation scheme, the spatial heterogeneity of land surface hydrothermal conditions at six typical flux observation stations in the Heihe River Basin during the vegetation growing season were evaluated. The evaluation results were consistent with the land surface type characteristics exhibited by Google Earth imagery and spatial heterogeneity assessed by high resolution remote sensing evapotranspiration data. Impact factors such as precipitation and irrigation events, spatial resolutions of remote sensing data, heterogeneity in the vertical direction, topography and sparse vegetation could also affect the evaluation results. For instance, short-term changes (precipitation and irrigation events) in the spatial heterogeneity of LSHCs can be diagnosed by energy factors, while long-term changes can be indicated by vegetation factors. The spatial heterogeneity of LSHCs decreases when decreasing the spatial resolution of remote sensing data. The proposed evaluation scheme would be useful for the quantification of spatial heterogeneity of LSHCs over flux observation stations toward the global scale, and also contribute to the improvement of the accuracy of estimation and validation for remotely sensed (or model simulated) evapotranspiration.

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“…In fact, like the bidirectional reflectance in visible and near‐infrared (VNIR) region, thermal infrared (TIR) radiation has been proven to own a significant directional signature (Lagouarde et al, ; Lagouarde et al, ; Lagouarde et al, ; Zhang et al, ). This thermal radiation directionality (TRD) effect is mainly resulted from two reasons: (1) the land surface emissivity is angularly dependent (Cao et al, ; Cuenca & Sobrino, ; García‐Santos et al, ; García‐Santos et al, ; Hu et al, ; Sobrino et al, ) and (2) various components of heterogeneous surface have different temperatures (Bian et al, ; Bian et al, ; Li et al, ; Timmermans et al, ). As a result, there are different observation values of thermal radiation or LST under different viewing and illumination geometries (Ermida et al, ; Ermida et al, ).…”

Section: Introductionmentioning

confidence: 99%

“…The second is the contributions of sunlit components are identical (Wanner et al, ). For thermal radiation, the radiances of shaded components cannot equal to zero, and the shaded soil is even hotter than the sunlit vegetation (Ermida et al, ; Li et al, ; Rasmussen et al, ). On the other hand, the radiation contributions of sunlit vegetation and sunlit soil are not identical in the majority of cases (Bian et al, ; Bian et al, ; Cao, Gastellu‐Etchegorry, et al, ; Ermida et al, ; Rasmussen et al, ; Timmermans et al, ).…”

Section: Introductionmentioning

confidence: 99%

On the Derivation of Geometric Optical Kernels for Directional Thermal Radiation

Tang

et al. 2020

Earth and Space Science

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The derivation of widely used geometric optical (GO) kernels in bidirectional reflectance distribution function models, that is, LiSparseReciprocal kernel (K GOLSR ) and LiDenseReciprocal kernel, was based on two important assumptions: (1) The shaded components are perfect black and (2) the contributions of two sunlit components are identical. Different from the bidirectional reflectance, thermal radiation directionality effect mainly results from component temperature differences, suggesting the above assumptions are not applicable in most situations. Therefore, this study derived GO kernels for thermal radiation based on temperature differences rather than illumination differences. Specifically, four GO kernels, that is, K GO4 with considering sunlit/shaded vegetation and sunlit/shaded soil, K GO3 with considering sunlit/shaded soil and vegetation, K GO2 with considering vegetation and soil, and K GOg only considering the hottest sunlit soil, have been developed. By using a comprehensive simulated data set, their performances have been thoroughly evaluated and the comparison with K GOLSR has also been analyzed in depth. Results showed that (1) K GO4 had the highest accuracy and K GO3 was the second; in the case of only two available angles, K GOg performed best.(2) Variables such as component temperature, component emissivity, solar zenith angle, and the percentage of tree crown cover mainly affected the comparison result between K GOLSR and K GO2 ; K GOLSR would have a better performance for a scene with a stronger vegetation effect. Moreover, the best values of two structure characteristics, that is, the crown shape parameter b/r and relative height h/b, for these five kernels have been determined, which can provide instruction for practical application. Plain Language SummaryLand surface temperature is a key variable for a variety of geoscientific studies. However, because of the heterogeneity of land surface, this important parameter has a significant angular effect. Previous studies mainly learned from directional reflectance models. Therefore, in this study, we developed four geometric optical kernels for correcting directional effect of land surface temperature from the inherent characteristic of thermal radiation. These new kernels not only own clearer physical meaning but also have higher accuracies. Moreover, we also determined the best values of two structure characteristics to provide instruction for practical application.

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Component radiative temperatures over sparsely vegetated surfaces and their potential for upscaling land surface temperature

Cited by 12 publications

References 63 publications

A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin

A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin

Evaluating Spatial Heterogeneity of Land Surface Hydrothermal Conditions in the Heihe River Basin

On the Derivation of Geometric Optical Kernels for Directional Thermal Radiation

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