中国农业气象 ›› 2014, Vol. 35 ›› Issue (01): 97-102.doi: 10.3969/j.issn.1000-6362.2014.01.015

• 论文 • 上一篇    下一篇

几种干旱遥感监测模型在陕北地区的对比和应用

李菁,王连喜,沈澄,李琪,李登科   

  1. 1南京市江宁区气象局,南京211100;2南京信息工程大学江苏省大气环境监测与污染控制高技术研究重点实验室/南京信息工程大学环境科学与工程学院,南京210044;3南京市气象局,南京210009;4陕西省农业遥感信息中心,西安710014
  • 收稿日期:2013-06-09 出版日期:2014-02-20 发布日期:2015-02-10
  • 作者简介:李菁(1986-),女,陕西汉中人,硕士,助理工程师,研究方向为短期天气预报、农业气象等。Email:lj74223@sina.cn
  • 基金资助:

    国家科技支撑计划“全球变化环境下作物产量的影响与适应监测评估技术”(2012BAH29B03)

Application and Comparison of Several Drought Monitoring Models in Northern Shaanxi

LI Jing,WANG Lian xi,SHEN Cheng,LI Qi,LI Deng ke   

  1. 1Jiangning Meteorological Bureau,Nanjing211100,China;2Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control/School of Environmental Science and Engineering,Nanjing University of Information Science and Technology,Nanjing210044;3Nanjing Meteorological Bureau,Nanjing210009;4Shaanxi Remote Sensing Information Center for Agriculture,Xi′an710014
  • Received:2013-06-09 Online:2014-02-20 Published:2015-02-10

摘要: 利用陕北20个测墒站不同土层深度的土壤湿度和对应的MODIS卫星资料,分析了3种干旱遥感指数即改进型能量指数(MEI)、垂直干旱植被指数(PDI)和地表含水量指数(SWCI),由此得到陕北旱情空间分布图,并对其分等定级。结果表明:3种遥感干旱监测模型监测土壤水分的最佳土层深度均为20cm,其次为10cm。对2008年4-9月的植物生长季土壤相对湿度进行动态反演表明,3种指数均能及时、准确得到大范围的土壤含水量情况及旱情,适宜在当地应用推广。

关键词: 干旱遥感, 土壤相对湿度, 地表含水量指数, 改进型能量指数, 垂直干旱植被指数

Abstract: Based on soil moisture and its MODIS data in different depth from 20 soil monitoring stations in north Shaanxi,three kinds of drought remote sensing indices,including the modify energy index(MEI),perpendicular drought index(PDI)and the surface water capacity index(SWCI),was calculated,and the spatial distribution of droughts with different grades was formed.The results showed that 20cm was the best depth for monitoring soil moisture by three drought remote sensing models,followed by 10cmA dynamic inverse of relative soil moisture during the growing season from April to September in 2008 showed that all of the three indices could monitor soil moisture and drought proper and timely in region.So they are suitable for this study area.

Key words: Drought remote sensing, Relative soil moisture, Surface water capacity index(SWCI), Modify energy index(MEI), Perpendicular drought index