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Proceedings Paper

Simulation of regional rice growth by combination remote sensing data and crop model
Author(s): Jianmao Guo; Yanghua Gao; Junwei Liu; Dunyue Fei; Qian Wang
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Paper Abstract

Remote sensing monitoring the macroscopic vegetation situation and reflecting environmental factors influence the results and the process of crops; Crop growth simulation model using environmental factors simulate the process of crop growth, revealing the cause and essence of the process, both of them have advantages and disadvantages. Thus developing the study of combine remote sensing yield estimation and dynamic crop growth model is essential, it is a significant scientific issue studying the approach and method which can combine these two advanced technologies. In this paper, using multi-temporal remote sensing information and crop model ORYZA2000 combined method realizing the rice growth simulation in pixel scale, after the comparison between simulated result and the actual statistic value, accuracy is high and result is good. The combination of remote sensing information and crop simulation model is a complex issue, its result will be affected by many factors, combined with the field test in this study is a simplification of the actual situation, this will certainly affect the result’s accuracy.. This method has great practical significance and at the same time has positive application prospect. It can be used to monitor and evaluate crop growth condition, forecast crop yield and so on, thus can be used in decision support service on different regional scales and guiding agricultural production.

Paper Details

Date Published: 8 November 2014
PDF: 6 pages
Proc. SPIE 9260, Land Surface Remote Sensing II, 92602J (8 November 2014); doi: 10.1117/12.2068302
Show Author Affiliations
Jianmao Guo, Chongqing Institute of Meteorological Sciences (China)
Nanjing Univ. of Information Science & Technology (China)
Yanghua Gao, Chongqing Institute of Meteorological Science (China)
Junwei Liu, Nanjing Univ. of Information Science & Technology (China)
Dunyue Fei, Nanjing Univ. of Information Science & Technology (China)
Qian Wang, Nanjing Univ. of Information Science & Technology (China)


Published in SPIE Proceedings Vol. 9260:
Land Surface Remote Sensing II
Thomas J. Jackson; Jing Ming Chen; Peng Gong; Shunlin Liang, Editor(s)

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