Book ChapterDOI
Temperature and Vegetation Indices Based Surface Soil Moisture Estimation: A Remote Sensing Data Approach
V. Vani,K. Pavan Kumar,Mandla Venkata Ravibabu +2 more
- pp 281-289
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TLDR
Theoretical solutions of dry and wet edges were derived from this method as discussed by the authors, based on this method, they calculated Soil Moisture Index using more than 8 images for year from 2007 to may 2011 for a part of Murrumbidgee catchment in southern new south wales, Australia.Abstract:
In environmental and agricultural modelling soil moisture condition is one of the main parameter. To estimate surface soil moisture using an operational algorithm at fine spatial and temporal resolutions (thermal and optical sensors) with the help of Ts(Land Surface Temperature)/VI(Vegetation Index) space based triangle method. Theoretical solutions of dry and wet edges were derived from this method. Based on this method we calculated Soil Moisture Index using more than 8 images for year from 2007 to may 2011 for a part of Murrumbidgee catchment in southern new south wales, Australia. Insitu Soil moisture data for 20 agricultural stations were used for validating the satellite observed Soil Moisture Index. The Results indicated that the general pattern of the SMI variation follows the trend of field soil moisture measurement. Different soil backgrounds influenced the SMI computing using optical satellite image. Estimation of regional soil moisture in areas with less ground information (insitu observations) is achieved with the help of SMI model.read more
Citations
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Machine learning to estimate surface soil moisture from remote sensing data
TL;DR: In this article, an important experiment of soil moisture retrieval for investigating the capability of the machine learning methods was conducted in the early spring season in a semi-arid region of Iran.
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An integrated methodology for surface soil moisture estimating using remote sensing data approach
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TL;DR: In this article, the authors proposed an operational approach for estimating surface soil moisture from MODIS data by considering diverse environmental conditions, such as weather conditions, soil types, and soil types.
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Spatial Distribution of Soil Moisture in Mongolia Using SMAP and MODIS Satellite Data: A Time Series Model (2010–2025)
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The synergistic use of microwave coarse-scale measurements and two adopted high-resolution indices driven from long-term T-V scatter plot for fine-scale soil moisture estimation
TL;DR: In this paper, the authors proposed and evaluated a developed approach that overcomes three of the most fundamental limitation of remote sensing techniques, namely, computational complexity, computational efficiency, and computational complexity.
References
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Journal ArticleDOI
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Journal ArticleDOI
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Journal ArticleDOI
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Paul R. Houser,Paul R. Houser,W. James Shuttleworth,James S. Famiglietti,Hoshin V. Gupta,Kamran H. Syed,David C. Goodrich +6 more
TL;DR: The feasibility of synthesizing distributed fields of soil moisture by the novel application of four-dimensional data assimilation (4DDA) applied in a hydrological model is explored in this article.
Journal ArticleDOI
The surface temperature-vegetation index space for land cover and land-cover change analysis
Eric F. Lambin,Daniele Ehrlich +1 more
TL;DR: In this paper, the authors investigated the biophysical justification for such a combination, using 10 years of Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) data over the African continent.