中国农业气象 ›› 2014, Vol. 35 ›› Issue (05): 593-599.doi: 10.3969/j.issn.1000-6362.2014.05.018

• 论文 • 上一篇    下一篇

河南麦区一次高温低湿型干热风灾害的遥感监测

李颖,韦原原,刘荣花,方文松,成林   

  1. 1中国气象局河南省农业气象保障与应用技术重点实验室,郑州450003;2河南省气象科学研究所,郑州450003;3郑州大学水利与环境学院,郑州450001
  • 收稿日期:2014-06-16 出版日期:2014-10-20 发布日期:2015-02-11
  • 作者简介:李颖(1984-),河南郑州人,博士,工程师,主要从事遥感技术及其应用研究。Email:walnutclip@163.com
  • 基金资助:

    “十二五”国家科技支撑计划课题(2011BAD32B01)

Remote Sensing Monitoring of a Dry hot Wind Disaster in Wheat Growing Area of Henan Province

LI Ying, WEI Yuan yuan, LIU Rong hua, FANG Wen song, CHENG Lin   

  1. 1Henan Key Laboratory of Agrometeorological Support and Applied Technique, CMA,Zhengzhou450003, China; 2Henan Institute of Meteorological Sciences, Zhengzhou450003;3College of Water Conservancy & Environmental Engineering,Zhengzhou University,Zhengzhou450001
  • Received:2014-06-16 Online:2014-10-20 Published:2015-02-11

摘要: 使用国产气象卫星FY3/MERSI数据构建NDVI、RVI、ARVI、EVI指数,对河南麦区2013年5月12-13日的一次大面积冬小麦干热风过程进行监测,通过对干热风发生前后小麦种植区像元植被指数频次分布和变化量空间分布的对比,以及干热风前后像元植被指数变化量与气象指标的相关分析,研究不同植被指数用于干热风监测评估的适用性和敏感性。结果表明,NDVI、RVI、ARVI指数在干热风灾害发生后具有明显一致的下降趋势,其下降幅度随干热风灾害程度的加重而增大,且与干热风灾害程度的相关性随灾害加重而增大,NDVI和RVI对干热风灾害程度的敏感性优于ARVI,适于大面积干热风灾害监测。研究结果可为推广卫星遥感技术在大面积干热风灾害监测评估中的应用提供科学依据。

关键词: MERSI, 植被指数, NDVI, RVI, ARVI, EVI

Abstract:  The domestic meteorological data FY3/MERSI was used to construct 4 types vegetation indices that including NDVI, RVI, ARVI and EVI to monitor a wide range of dry hot wind process in winter wheat growing area in Henan province 12-13 May, 2013.By comparing the frequency distribution and the variation spatial distribution of these pixel vegetation indexes before and after dry hot wind occurred, and analyzing the correlation between vegetation index variation and meteorological indices, authors studied the applicability and sensitivity of different vegetation index for monitoring and evaluation the dry hot wind disaster. The results showed that NDVI, RVI and ARVI had a consistent and significant downward trend when this dry hot wind occurred and its descent amount increased as the dry hot wind disaster grade rised. The correlation between vegetation index variation and dry hot wind disaster level also increased with the grade rised. In addition, NDVI and RVI were more sensitive than ARVI for the dry hot wind disaster, so that they are applicable to monitoring a large area of dry hot wind disaster. The research results can provide a scientific basis for promoting the application of satellite remote sensing technology to monitor and evaluate a large area of dry hot wind disaster.

Key words: MERSI, Vegetable index, NDVI, RVI, ARVI, EVI