Research on Temporal and Spatial Dynamic of Maize Drought Using Remote Sensing: A Case on Shuanghe Farm of Beijing
Yunxiang Jin, Sijian Zhao, Wei Sun, Lei Xu, Qian Nie, Qiao Zhang
Available Online November 2016.
- https://doi.org/10.2991/rac-16.2016.105How to use a DOI?
- maize, drought, anomaly vegetation index
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC-2016) PB - Atlantis Press SP - 652 EP - 657 SN - 1951-6851 UR - https://doi.org/10.2991/rac-16.2016.105 DO - https://doi.org/10.2991/rac-16.2016.105 ID - Jin2016/11 ER -