Title | ||
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Soil thermal inertia estimation by combining afternoon and morning AVHRR data with a modified diurnal land surface temperature change model |
Abstract | ||
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A modified diurnal land surface temperature change model was developed for soil thermal inertia retrieval by using NOAA/AVHRR remotely sensed data. The modified thermal inertia model was used to estimate surface soil moisture contents in the Guanzhong Plain of Shaanxi Province in the Northwest China. The results showed that the retrieved values of soil thermal inertia converged when the Fourier series were set to 10 or greater than 10, and the values were in the range of ground measured values published in some related articles. For applications of the model, soil thermal inertia can be reversed by applying the second Fourier series approximation. Based on the significance and the range of the estimated surface soil moisture, we found the exponential model between soil thermal inertia and soil moisture had the best performance in estimating soil moisture contents |
Year | DOI | Venue |
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2004 | 10.1109/IGARSS.2004.1370087 | IGARSS |
Keywords | Field | DocType |
exponential model,remote sensing,suface soil moisture retrieval,moisture,shaanxi province,fourier series,diurnal land surface temperature change model,guanzhong plain,morning avhrr data,hydrological techniques,noaa/avhrr remotely sensed data,afternoon avhrr data,soil thermal inertia estimation,land surface temperature,soil thermal inertia,surface soil moisture content,soil,northwest china,soil moisture | Land surface temperature,Soil science,Moisture,Exponential function,Computer science,Remote sensing,Thermal inertia,Fourier series,Water content,Morning | Conference |
Volume | Issue | ISSN |
6 | null | 2153-6996 |
ISBN | Citations | PageRank |
0-7803-8742-2 | 0 | 0.34 |
References | Authors | |
0 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Peng Xin Wang | 1 | 14 | 6.53 |
Xiaowen Li | 2 | 372 | 112.54 |
Wei Sun | 3 | 0 | 0.34 |
Xingmin Li | 4 | 18 | 4.01 |
Shuyu Zhang | 5 | 0 | 0.68 |
Anlin Liu | 6 | 0 | 0.34 |