MODIS干旱指数对华北干旱的敏感性分析

干旱区地理 ›› 2012, Vol. 35 ›› Issue (5): 708-716.

MODIS干旱指数对华北干旱的敏感性分析

白力改^1,3,燕琴²,张丽³,谭志祥⁴

1 北华航天工业学院建筑工程系，河北廊坊 065000； 2 中国测绘科学研究院对地观测技术国家测绘局重点实验室，北京 100830； 3 中国科学院数字地球重点实验室中国科学院对地观测与数字地球科学中心，北京 100094； 4 中国矿业大学，江苏省资源环境信息工程重点实验室，江苏徐州 221116

收稿日期:2011-12-24 修回日期:2012-02-21 出版日期:2012-09-25
通讯作者: 张丽，副研究员，主要从事资源与环境遥感研究.Email:lizhang@ceode.ac.cn
作者简介:白力改(1984-)，女，河北石家庄人，硕士，主要从事遥感干旱监测与应用研究.Email: blgbb@163.com
基金资助:
中国科学院对地观测与数字地球科学中心主任创新基金（Y2ZZ19101B）

Sensitivity analysis of response of MODIS derived drought indices to drought in North China

BAI Ligai^1,3,YAN Qin²,ZHANG Li³,TAN Zhixiang⁴

1 Department of Construction Engineering, North China Institute of Aerospace Engineering, Langfang 065000,Hebei，China； 2 Key Laboratory of Earth Observing Technology of State Bureau of Surveying and Mapping, Chinese Academy of Surveying and Mapping, Beijing 100830, China； 3 Key Laboratory of Digital Earth, Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China； 4 Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116,Jiangsu,China

Received:2011-12-24 Revised:2012-02-21 Online:2012-09-25
Contact: ZHANG Li

摘要/Abstract

摘要： 针对近年来干旱发生频繁的华北地区，通过利用2000-2009年MODIS数据和气象观测站降水资料，建立草地和农田距平植被指数(AVI)与不同时间尺度标准化降水指数(SPI)之间的相关统计模型，比较AVI和距平水分指数(AWI)对干旱响应的敏感性。结果表明：(1)植被生长季AVI与不同时间尺度SPI的相关关系不同。草地AVI与1个月尺度的SPI(即1-SPI)相关系数较低，而与3-SPI相关最显著；而农田区AVI与SPI的相关性较低，总体上农田AVI与3-SPI的相关性较高；(2) AWI与AVI类似，也对SPI存在时滞响应，均与3-SPI有着极显著的相关关系，并且在干旱发生较严重的6~8月份AWI与3-SPI的相关性好于AVI与3-SPI的相关性；(3)运用AWI反演的华北地区2009年夏季干旱分布图较好地反映了旱情的时空分布，与相关气象资料结果相符合。

关键词: 华北, 干旱, 距平植被指数(AVI), 距平水分指数(AWI), 标准化降水指数(SPI)

Abstract: Drought occurred frequently in recent years in North China. In this study, MOD09A1，8day surface reflectance derived from MODIS(moderateresolution imaging spectroradiometer)images provided by NASA and monthly precipitation data from ground observations obtained by China Meteorological Data Sharing Service System, which were used to study temporal responses of MODISderived drought index to climatic factors in North China. Anomaly Vegetation Index(AVI) was computed from the time series data of NDVI (based on infrared and near infrared bands) and Anomaly Water Index(AWI) was calculated from NDWI (based on near infrared and short infrared wave bands) of MODIS. Given the consequences and pervasiveness of drought, it is important to assess the specialized indices that were used to assess drought sensitivity. The standardized precipitation index (SPI) has several characteristics that are an improvement in previous indices. In this paper, 1-SPI, 2-SPI, 3-SPI, 6-SPI and 12-SPI were calculated. The correlations and lag relationships between AVI from April to October (the growing season) during 2000 to 2009 and the multipletime scale SPI in North China grassland and cropland sites were investigated based on MODIS and climate data. Besides, the relations between AVI and AWI in different periods were also analyzed. According to the sensitivity analysis of the response of AVI and AWI to drought, summer drought from June to September in 2009 in North China were monitored and analyzed by AWI. The results show: (1) the correlations are different between AVI and SPI at different time scales during vegetation growing seasons. For the grassland, the correlations are insignificant between AVI and 1-SPI, but significant between AVI and 3-SPI. However, the correlation is lower between AVI and SPI for cropland than that for grassland. In general, the correlation is higher between AVI and 3-SPI for cropland. (2) Similarly to AVI, AWI shows lag response to SPI, and has better correlation with 3-SPI. The correlation between AWI and 3-SPI is better than that between AVI and 3-SPI during period from June to August when serious drought occurs. Therefore, AWI is more sensitive to drought than AVI in North China. (3) The timeseries drought monitoring maps in North China for 2009 derived from AWI reflects the temporal and spatial dynamics of drought, which are consistent with the relevant meteorological results.

Key words: North China, drought, anomaly vegetation index(AVI), anomaly water index(AWI), standardized precipitation index(SPI)

中图分类号:

TP79

白力改,燕琴,张丽,谭志祥. MODIS干旱指数对华北干旱的敏感性分析[J]. 干旱区地理, 2012, 35(5): 708-716.

BAI Ligai,YAN Qin,ZHANG Li,TAN Zhixiang. Sensitivity analysis of response of MODIS derived drought indices to drought in North China[J]. , 2012, 35(5): 708-716.

参考文献

1    陈维英，肖乾广，盛永伟．距平植被指数在1992年特大干旱监测中的应用〔J〕．环境遥感， 1994，9(2)：106-112．

2    居为民，孙涵，汤志成．气象卫星遥感在干旱监测中的应用〔J〕．灾害学，1996，11(4)：25-29．

3    晏明，张磊．距平植被指数在吉林省农作物干旱监测中的应用〔J〕．现代农业科技，2010,(11)：15-16．

4    冯强，田国良，王昂生,等．基于植被状态指数的全国干旱遥感监测的试验研究〔J〕．干旱区地理，2004，27(2)：132-136．

5    冯强，田国良，王昂生，等．基于植被状态指数的全国干旱遥感监测的试验研究(Ⅱ) 〔J〕．干旱区地理，2004，27(4)：477-484.

6    UNGANAI L S， KOGAN F N．Drought monitoring and corn yield estimation in Southern Africa from AVHRR data〔J〕．Remote Sensing of Environment，1998，(63)： 219-232．

7    戴声佩，张勃，王强,等．祁连山草地植被NDVI变化及其对气温降水的旬响应特征〔J〕．资源科学，2010，32(9)：1769-1776．

8    GAO B．NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space〔J〕. Remote Sensing of Environment，1996，(58)： 257-266．

9    CHEN D，HUANG J， THOMAS J J． Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS nearand shortwave infrared bands〔J〕． Remote Sensing of Environment，2005，(98)： 225-236．

10 刘小磊，覃志豪．NDWI与NDVI指数在区域干旱监测中的比较分析-以2003年江西夏季干旱为例〔J〕．遥感技术与应用，2007， 22(5)：608-612．

11 张峰．基于MODIS数据的浙江省旱情监测及其时空分析〔D〕．乌鲁木齐：新疆农业大学，2009．

12 司翠，吴昊．干旱灾害对华北地区农业经济影响研究〔J〕．经济研究,2009(4)：68-69．

13 CACCAMO G，CHISHOLM L A，BRADSTOCK R A，et al．Assessing the sensitivity of MODIS to monitor drought in high biomass ecosystems〔J〕．Remote Sensing of Environment,2011，(115)：2626–2639．

14 MCKEE T B，DOESKEN　N J，KLEIST J．The relationship of drought frequency　and duration to time scales〔R〕．California：Eighth Conference on Applied Climatology，1993．

15 袁文平，周广胜．标准化降水指标与Ｚ指数在我国应用的对比〔J〕．植物生态学报，2004，28(4)：523-529.

16 JI L，PETERS A J．Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices〔J〕．Remote Sensing of Environment，2003：85-98.

17 樊任华．基于MODIS数据的草地干旱指数对比研究〔D〕．南昌：南昌大学，2008．

18 梁芸，金文岩，郭铌,等．陇东地区植被指数NDVI与降水的关系研究〔J〕．干旱地区农业研究，2009，27(6)：247-25．

19 王宏，李晓兵，李霞,等．中国北方草原对气候干旱的响应〔J〕．生态学报，2008，28 (1)：172-182．

20 JINYOUNG R，JUNGHO I，GREGORY J　C．Monitoring agricultural drought for arid and humid regions using multisensor　remote sensing data〔J〕．Remote Sensing of Environment，2010，(114)：2875-2887．

21 郭军，李明财，刘德义．天津地区归一化植被指数时间动态及其与气候因子的关系〔J〕．生态学杂志，2009，28(6)：1055-1059．

22 张文江，陆其峰，高志强,等．基于水分距平指数的2006年四川盆地东部特大干旱遥感响应分析〔J〕．地球科学，2008，38(2)：251-260．

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