Paper
10 July 2009 Study on the shelterbelt effects on crop condition using RS and GIS
Rongxin Deng, Shuwen Zhang, Ying Li, Wenjuan Wang
Author Affiliations +
Proceedings Volume 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering; 74910N (2009) https://doi.org/10.1117/12.836836
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China
Abstract
The Northeast shelterbelt is a part of the Shelter Forest System Program in Three-North Regions of China, and the Jilin Province is an important food production basis, the research on the shelterbelt effects on crop condition in this region is very necessary to evaluating the protective effect and crop increasing. For this purpose, it choose Dehui, Yushu, Fuyu and Nong'an of the Jilin province as the research areas, and select the shelterbelt protected ground and no shelterbelt protected ground as the research spot respectively, taken the MODIS NDVI of 16 days compositional data productions from March to October in 2008, using GIS analysis technique, analyzing the crop condition in this temporal series. Through comparing the NDVI temporal changing line, peak value and the sum of the NDVI, it found that the shelterbelt has an obvious effect on the crop condition. It can conclude that, through reducing the wind speed, changing the local climate environment, the shelterbelt can improve the crop condition. In addition, comparing to the traditional research methods, it's much more effective, and less time consuming to analyzing the shelterbelt by RS and GIS, and it can help study the shelterbelt's protective effect on a larger temporal and spatial scale.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rongxin Deng, Shuwen Zhang, Ying Li, and Wenjuan Wang "Study on the shelterbelt effects on crop condition using RS and GIS", Proc. SPIE 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering, 74910N (10 July 2009); https://doi.org/10.1117/12.836836
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KEYWORDS
Remote sensing

Geographic information systems

Analytical research

Agriculture

Vegetation

Climatology

MODIS

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