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

Prince, Stephen D.; Goetz, Scott J.; Dubayah, Ralph; Czajkowski, Kevin; Thawley, M.M.

doi:10.1016/s0022-1694(98)00210-8

Cited by 154 publications

(118 citation statements)

References 69 publications

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“…According to this method, remotely sensed T s tends to approach air temperature with increasing Remote Sens. 2017, 9, 26 3 of 25 of vegetation cover, and the radiometric temperature of a full vegetated canopy is in equilibrium with the temperature of the air within the canopy [39,41]. This provides a meaningful insight in the interpretation of the T s − V I triangle method mentioned above.…”

Section: Disadvantagesmentioning

confidence: 90%

“…2017, 9, 26 3 of 25 the temperature of the air within the canopy [39,41]. This provides a meaningful insight in the interpretation of the − triangle method mentioned above.…”

Section: Study Area and Field Measurementsmentioning

confidence: 96%

“…The temperature-vegetation index (TVX) method, proposed by Nemani and Running [52] and Goward et al [53], was mainly used to estimate near surface air temperature (T a ) in previous studies. It is assumed that because of the combined impact of vegetation cover on the average surface thermal characteristics and on the evaporative control of energy portioning, remotely sensed land surface temperature tends to approach air temperature with increasing vegetation cover, and the radiometric temperature of a full vegetated canopy is in equilibrium with the temperature of the air within the canopy [39,41]. Other assumptions involved in the TVX method are that both uniform atmospheric forcing and soil moisture conditions must take place [38].…”

Section: Basic Frameworkmentioning

confidence: 99%

“…(3) Numerous studies show that observed near surface air temperature can be used to represent the lowest T s over study area. For example, one principle of the TVX method is that the radiometric temperature of a fully vegetated canopy is in equilibrium with the air temperature within the canopy [39,41,45,61]. Even some T s − V I triangle/trapezoid models that were performed based on theoretical boundaries also assumed that the near surface T a could be taken as the horizontal wet edge [30,32,50].…”

Section: Determination Of the Dry And Wet Edgesmentioning

confidence: 99%

See 3 more Smart Citations

A New Contextual Parameterization of Evaporative Fraction to Reduce the Reliance of the Ts − VI Triangle Method on the Dry Edge

Zhu

Jia

et al. 2017

Remote Sensing

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Abstract:In this study, a new parameterization scheme of evaporative fraction (EF) was developed from the contextual information of remotely sensed radiative surface temperature (T s ) and vegetation index (VI). In the traditional T s − V I triangle methods, the Priestley-Taylor parameter ∅ of each pixel was interpolated for each VI interval; in our proposed new parameterization scheme (NPS), it was performed for each isopiestic line of soil surface moisture. Specifically, ∅ of mixed pixels was determined as the weighted-average value of bare soil ∅ and full-cover vegetation ∅. The maximum T s of bare soil (T smax ) is the sole parameter needed as the constraint of the dry edge. This has not only bypassed the task involved in the determination of the maximum T s of fully vegetated surface (T cmax ), but also made it possible to reduce the reliance of the T s − V I triangle methods on the determination of the dry edge. Ground-based measurements taken during 21 days in 2004 were used to validate the EF retrievals. Results show that the accuracy achieved by the NPS is comparable to that achieved by the traditional T s − V I triangle methods. Therefore, the simplicity of the proposed new parameterization scheme does not compromise its accuracy in monitoring EF.

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Section: Disadvantagesmentioning

confidence: 90%

“…2017, 9, 26 3 of 25 the temperature of the air within the canopy [39,41]. This provides a meaningful insight in the interpretation of the − triangle method mentioned above.…”

Section: Study Area and Field Measurementsmentioning

confidence: 96%

Section: Basic Frameworkmentioning

confidence: 99%

Section: Determination Of the Dry And Wet Edgesmentioning

confidence: 99%

See 2 more Smart Citations

A New Contextual Parameterization of Evaporative Fraction to Reduce the Reliance of the Ts − VI Triangle Method on the Dry Edge

Zhu

Jia

et al. 2017

Remote Sensing

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“…Therefore, the TVX method is suitable for daytime and full-cover normalized difference vegetation index (NDVI) and is highly sensible to uncertainty in the estimated LST and the maximum NDVI to improve the quality of remote sensing-based estimation of Ta. dTsa is primarily controlled by the surface energy balance but also depends on factors associated with the energy balance (e.g., wind speed, soil moisture, and surface roughness) [Prince et al, 1998]. Using energy balance theory to retrieve dTsa from remote sensing is quite difficult due to uncertainty in subparameters.…”

Section: Introductionmentioning

confidence: 99%

Retrieval of the land surface‐air temperature difference from high spatial resolution satellite observations over complex surfaces in the Tibetan Plateau

et al. 2015

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The temperature difference between the surface and the air (dTsa) directly indicates the intensity and heat fluxes of land-atmosphere interaction. Considering the effects of surface characteristics and air condition on the surface temperature, using 1 km data from the MOD02 thermal infrared bands of the EOS/moderate-resolution imaging spectroradiometer (MODIS) on satellite Aqua, other MODIS products and temperatures observed from weather stations at 14:00 China standard time (CST), the study analyzes the relationships between dTsa and brightness temperature in the infrared atmospheric window band (Bt31 and Bt32), the water vapor band (Bt28), the atmospheric temperature band (Bt25), and the CO 2 band (Bt34). A model estimating dTsa is built. The model coefficients are estimated for 96 stations representing 96 sets of surface and atmospheric conditions, and 71 sets of coefficients among them passing 90% confidence levels of estimating dTsa are selected as references. Combined with the probabilistic neural network (PNN) method and nine parameters reflecting surface characteristics in one season and month, the Tibetan Plateau surface is classified as 71 types with 71 sets of coefficients. PNN is certified an efficient classification method for multiple parameters and mass data. Based on PNN and estimated model, estimated dTsa shows 1.36°C root-mean-square error and a standard deviation of 0.74°C, and dTsa distribution exhibits all centers with peak value and valley value of European Centre for Medium-Range Weather Forecasts, MYD07, and simple regression model results, showing its superiority. The model is worthy of further exploration and application in an effort to advance the retrieval of surface energy fluxes from remote sensing.

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Large Area Surface Energy Balance Estimation Using Satellite Imagery

Arasteh

2004

Water Encyclopedia

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All climatic and hydrologic phenomena in the atmosphere and on the earth's surface are affected by the energy balance at the surface. The energy balance is one of the main subjects in climatology, hydrology, civil and traffic engineering, biology, and health. Photosynthesis and other metabolic processes in green plants, evaporation from free water and soil surfaces, and atmospheric and oceanic circulation are functions of the surface energy balance. Due to the nonuniform properties of the earth's surface (albedo, heat capacity, soil cover, etc.), the Earth's surface, phenomena must be monitored on continuous and simultaneous spatial scales. Satellite imagery provides a large view of the earth's surface. Such a spatially continuous, but time discrete, data acquisition system provides a suitable framework for distributed modeling, provided that the phenomenon to be modeled has spectral behavior. For energy balance processing, visible (VIS), near infrared (NIR), and thermal infrared (TIR) channels are used. Some primary surface parameters such as surface albedo, surface temperature, air temperature, surface roughness, land cover, and land use may be provided by remote sensing. In this article, inferring energy balance components using remotely sensed data and some common methods in this respect are introduced. Then, the energy components of the Hamoon Wetlands are described as a case study, and some Internet sources of the satellite‐based global energy budget are introduced.

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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

Cited by 154 publications

References 69 publications

A New Contextual Parameterization of Evaporative Fraction to Reduce the Reliance of the Ts − VI Triangle Method on the Dry Edge

A New Contextual Parameterization of Evaporative Fraction to Reduce the Reliance of the Ts − VI Triangle Method on the Dry Edge

Retrieval of the land surface‐air temperature difference from high spatial resolution satellite observations over complex surfaces in the Tibetan Plateau

Large Area Surface Energy Balance Estimation Using Satellite Imagery

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