DocumentCode :
3447014
Title :
Mapping farmland organic matter using HSI image and its effects of land-use types
Author :
Xiaohe, Gu ; Yansheng, Dong ; Kun, Wang
Author_Institution :
Beijing Res. Center for Inf. Technol. in Agric., Beijing, China
fYear :
2012
fDate :
2-4 Aug. 2012
Firstpage :
1
Lastpage :
4
Abstract :
Spatial distribution of farmland organic is essential for soil fertility adjustment, land-use change and sustainable development of agriculture. It is important to develop a rapid method for mapping farmland organic matter at county scale using remote sensing technology. The HJ-1A HSI image used in the paper has 115 bands, which result in good response to soil organic matter. With the support of in-situ sample data, the correlation between organic matter and characteristic variants of HSI image was analyzed. Then the optimized response wavebands and feature algorithm was selected. Through the application of multiple linear regressions, the model of retrieving farmland organic matter at a county scale was developed. Results indicated that the visible and near infrared bands of HSI image, especially 540-860 nm bands, had good response to farmland organic matter. The model of first order differential logarithm of HSI reflectivity could reach best accuracy, of which the determination coefficients (R) of training and testing samples were both higher than 0.7, while the RMSEs all around 0.2%. The spatial distribution of farmland organic matter was mapped by the model and HSI image. It is concluded that the HJ1A-HSI image has good response and coverage ability for farmland organic matter, which could provide an effective model of mapping organic matter on a county scale. The study also shows that land-use types have certain influence to farmland organic matter.
Keywords :
geophysical image processing; regression analysis; soil; sustainable development; terrain mapping; HJ-1A HSI image; agriculture sustainable development; farmland organic matter mapping; feature algorithm; first order differential logarithm; land use change; land use type; multiple linear regression; optimized response waveband; remote sensing technology; soil fertility adjustment; spatial distribution; Correlation; Linear regression; Reflectivity; Remote sensing; Soil; Testing; HSI; land-use type; mapping; multiple linear regressions; organic matter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Agro-Geoinformatics (Agro-Geoinformatics), 2012 First International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-2495-3
Electronic_ISBN :
978-1-4673-2494-6
Type :
conf
DOI :
10.1109/Agro-Geoinformatics.2012.6311723
Filename :
6311723
Link To Document :
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