Soil moisture retrieval from MODIS data in Northern China Plain using thermal inertia model

Cai, Guorong; Xue, Yong; Hu, Yi; Wang, Y.; Guo, Jianping; Luo, Yi; Wu, Chengdong; Zhong, Shaobo; Qi, Shanshan

doi:10.1080/01431160601034886

Cited by 78 publications

(46 citation statements)

References 18 publications

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“…where the depth z is erroneously reported in Xue and Cracknell (1995) and Cai et al (2007) under the square root, whereas it is reported correctly in Watson (1975) and Sobrino et al (1998); -A c /B is also reported erroneously in Xue and Cracknell (1995) without the minus sign. In particular, within equation (8), the phase difference of the soil temperature for the n-order, δ n (equation (9)), is a function of the thermal inertia, P, and of the angular velocity of rotation of the Earth, ω, assuming a value of 7.27 × 10 -5 rad s -1 :…”

Section: The One-dimensional (1d) Thermal Diffusion Equationmentioning

confidence: 84%

Critical analysis of thermal inertia approaches for surface soil water content retrieval

Maltese

Bates

Capodici

et al. 2013

Hydrological Sciences Journal

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The "thermal inertia" method to retrieve surface soil water content maps on bare or sparsely-vegetated soils is analysed. The study area is a small experimental watershed, where optical and thermal images (in day and night time) and in situ data were simultaneously acquired. The sensitivity of thermal inertia to the phase difference between incoming radiation and soil temperature is demonstrated. Thus, to obtain an accurate value of the phase difference, the temporal distance between thermographs using a three-temperature approach is evaluated. We highlight when a cosine correction of the temperature needs to be applied, depending on whether the thermal inertia formulation includes two generic acquisition times, or not. Finally, the deviation in soil water content retrieval is quantifies for given values of each parameter by performing a sensitivity analysis on the basic parameters of the thermal inertia method that are usually affected by calibration errors.Key words thermal inertia; surface soil water content; remote sensing Analyse critique des approches fondées sur l'inertie thermique pour la cartographie de la teneur en eau de la surface du sol Résumé La méthode de « l'inertie thermique » pour la cartographie de la teneur en eau de la surface des sols nus ou à végétation clairsemée est analysée. La zone d'étude est un petit bassin versant expérimental, où des images optiques et thermiques (de jour et de nuit) et des données in situ ont été acquises simultanément. On a mis en évi-dence la sensibilité de l'inertie thermique à la différence de phase entre le rayonnement incident et la température du sol. Ainsi, pour obtenir une valeur précise de la différence de phase, nous avons évalué la distance temporelle entre thermographes en utilisant une approche à trois températures. Cet article montre la nécessité éventuelle d'une correction cosinusoïdale de la température, selon que la formulation de l'inertie thermique comprend ou non deux temps d'acquisition génériques. Enfin, l'article quantifie la variabilité de la teneur en eau du sol pour des valeurs données de chaque paramètre en effectuant une analyse de sensibilité sur les paramètres de base de la méthode de l'inertie thermique qui sont généralement affectés par des erreurs d'étalonnage.

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Section: The One-dimensional (1d) Thermal Diffusion Equationmentioning

confidence: 84%

Critical analysis of thermal inertia approaches for surface soil water content retrieval

Maltese

Bates

Capodici

et al. 2013

Hydrological Sciences Journal

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“…Additionally, it hinders the efficiency of radiant transfer of energy between the grains of a particulate surface. Diurnal temperature variations are also more sensitive to atmospheric humidity and precipitation, which reduces the accuracy of thermal inertia estimates [39][40][41][42]. Thermal inertia investigations of Earth must also account for vegetative cover, which obscures geologic surfaces in addition to effecting albedo and surface temperature.…”

Section: Apparent Thermal Inertiamentioning

confidence: 99%

“…For example, the inclusion of simple scaling factors [9] through a much more rigorous implementation to convert ATI to approximated actual thermal inertia [41]. Scheidt et al (2010) [9] includes two variables (n and c) in the calculation of ATI using: ATI = nc (1´a)/∆T, where n and c are correction factors to account for variations in solar flux with latitude and solar declination [79].…”

Section: Terrestrial Applicationsmentioning

confidence: 99%

“…Thermal inertia investigations of Earth must also account for vegetative cover, which obscures geologic surfaces in addition to effecting albedo and surface temperature. Despite these factors, thermal inertia has been used successfully on Earth, most commonly to map the moisture content of soils and for geologic interpretations [9,[39][40][41][42]. Cracknell and Xue (1996) [43] use data from the Advanced Very High Resolution Radiometer (AVHRR) sensor to create thermal inertia images to estimate surface heat flux after consulting local weather data.…”

Section: Apparent Thermal Inertiamentioning

confidence: 99%

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Satellite-Based Thermophysical Analysis of Volcaniclastic Deposits: A Terrestrial Analog for Mantled Lava Flows on Mars

2016

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Abstract:Orbital thermal infrared (TIR) remote sensing is an important tool for characterizing geologic surfaces on Earth and Mars. However, deposition of material from volcanic or eolian activity results in bedrock surfaces becoming significantly mantled over time, hindering the accuracy of TIR compositional analysis. Moreover, interplay between particle size, albedo, composition and surface roughness add complexity to these interpretations. Apparent Thermal Inertia (ATI) is the measure of the resistance to temperature change and has been used to determine parameters such as grain/block size, density/mantling, and the presence of subsurface soil moisture/ice. Our objective is to document the quantitative relationship between ATI derived from orbital visible/near infrared (VNIR) and thermal infrared (TIR) data and tephra fall mantling of the Mono Craters and Domes (MCD) in California, which were chosen as an analog for partially mantled flows observed at Arsia Mons volcano on Mars. The ATI data were created from two images collected~12 h apart by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument. The results were validated with a quantitative framework developed using fieldwork that was conducted at 13 pre-chosen sites. These sites ranged in grain size from ash-sized to meter-scale blocks and were all rhyolitic in composition. Block size and mantling were directly correlated with ATI. Areas with ATI under 2.3ˆ10´2 were well-mantled with average grain size below 4 cm; whereas values greater than 3.0ˆ10´2 corresponded to mantle-free surfaces. Correlation was less accurate where checkerboard-style mixing between mantled and non-mantled surfaces occurred below the pixel scale as well as in locations where strong shadowing occurred. However, the results validate that the approach is viable for a large majority of mantled surfaces on Earth and Mars. This is relevant for determining the volcanic history of Mars, for example. Accurate identification of non-mantled lava surfaces within an apparently well-mantled flow field on either planet provides locations to extract important mineralogical constraints on the individual flows using TIR data.

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“…Many methods for estimating ET and soil moisture based on remote sensing data were developed, such as SEBI (Surface Energy Balance Index) [2], SEBAL (Surface Energy Balance Algorithm for Land) [3], METRIC (Mapping EvapoTranspiration at high Resolution with Internalized Calibration) [4], a thermal inertia model for soil moisture [5], and so on. Reviews about these methods can be found [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Three Theoretical Methods for Determining Dry and Wet Edges of the LST/FVC Space: Revisit of Method Physics

et al. 2017

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Abstract:Land surface temperature and fractional vegetation coverage (LST/FVC) space is a classical model for estimating evapotranspiration, soil moisture, and drought monitoring based on remote sensing. One of the key issues in its utilization is to determine its boundaries, i.e., the dry and wet edges. In this study, we revisited and compared three methods that were presented by Moran et al. (1994), , and Sun (2016) for calculating the dry and wet edges theoretically. Results demonstrated that: (1) for the dry edge, the Sun method is equal to the Long method and they have greater vegetation temperature than that of the Moran method. (2) With respect to the wet edge, there are greater differences among the three methods. Generally, Long's wet edge is a horizontal line equaling air temperature. Sun's wet edge is an oblique line and is higher than that of the Long's. Moran's wet edge intersects them with a higher soil temperature and a lower vegetation temperature. (3) The Sun and Long methods are simpler in calculation and can circumvent some complex parameters as compared with the Moran method. Moreover, they outperformed the Moran method in a comparison of estimating latent heat flux (LE), where determination coefficients varied between 0.45~0.66 (Sun), 0.47~0.68 (Long), and 0.39~0.57 (Moran) among field stations.

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Soil moisture retrieval from MODIS data in Northern China Plain using thermal inertia model

Cited by 78 publications

References 18 publications

Critical analysis of thermal inertia approaches for surface soil water content retrieval

Critical analysis of thermal inertia approaches for surface soil water content retrieval

Satellite-Based Thermophysical Analysis of Volcaniclastic Deposits: A Terrestrial Analog for Mantled Lava Flows on Mars

Comparison of Three Theoretical Methods for Determining Dry and Wet Edges of the LST/FVC Space: Revisit of Method Physics

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