Research on Temporal and Spatial Dynamic of Maize Drought Using Remote Sensing: A Case on Shuanghe Farm of Beijing

DOI

10.2991/rac-16.2016.105How to use a DOI?

Keywords

maize, drought, anomaly vegetation index

Abstract

Drought, which is one of main meteorological disasters, always affects maize production. Remote sensing has become an important and effective technology for maize drought monitoring and assessment. In this paper, maize planting region in Shuanghe farm of Beijing was selected as study areas. We calculated SPI (standardized precipitation index) using meteorological data during 1985 to 2014 and confirmed years of drought events. Then, based on 16 day composite MODIS NDVI products between 2000 and 2014, the model to monitor maize drought was established by anomaly vegetation index (AVI). The drought grades were classified into three levels including serious drought, medium drought and slight drought. The temporal and spatial changes of drought were monitoring in the growth period of maize. This study could offer scientific decision to agricultural production and disaster reduction to avoid disaster. It also could offer a novel technique method to risk assessment of disaster.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yunxiang Jin
AU  - Sijian Zhao
AU  - Wei Sun
AU  - Lei Xu
AU  - Qian Nie
AU  - Qiao Zhang
PY  - 2016/11
DA  - 2016/11
TI  - Research on Temporal and Spatial Dynamic of Maize Drought Using Remote Sensing: A Case on Shuanghe Farm of Beijing
BT  - Proceedings of the 7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention
PB  - Atlantis Press
SP  - 652
EP  - 657
SN  - 1951-6851
UR  - https://doi.org/10.2991/rac-16.2016.105
DO  - 10.2991/rac-16.2016.105
ID  - Jin2016/11
ER  -