Paper
10 July 2009 Inner Mongolia soil moisture retrieved from MODIS image and TVDI model
Libiao Guo, Yuhai Bao
Author Affiliations +
Proceedings Volume 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering; 748902 (2009) https://doi.org/10.1117/12.836357
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China
Abstract
The soil moisture is a sensitive index which is important in the research of weather, hydrograph, zoology, etc. And its importance embodied much more in the research of distribution of the vegetation and instructing the farming and herd. This paper use the MODIS data to retrieval the Inner Mongolia region's land surface temperature and vegetation index, establishing the temperature vegetation dryness index (TVDI) model by searching and regression the characteristics sequence of the data space, and then calculated the soil moisture of Inner Mongolia region. According to the validation between the retrieval and real survey data confirmed the scientific rationality and feasibility of the model using in the region. Considering the different characteristics of the climate and geographical distribution in the Inner Mongolia region, to make the research more objective and targeted, then divided the region into four sub-districts and retrieval the soil moisture independently. Finally, obtained the soil moisture ration information based on the different characteristics of the sub-districts, and the research provided some scientific basis and efforts for the agricultural and herd work in the Inner Mongolia region.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Libiao Guo and Yuhai Bao "Inner Mongolia soil moisture retrieved from MODIS image and TVDI model", Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 748902 (10 July 2009); https://doi.org/10.1117/12.836357
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Cited by 1 scholarly publication.
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KEYWORDS
Soil science

Climatology

Vegetation

Data modeling

MODIS

Agriculture

Image retrieval

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