利用NDVI时间序列数据分析植被长势对气候因子的响应
收稿日期: 2003-06-01
修回日期: 2004-02-01
网络出版日期: 2004-05-25
基金资助
中国科学院知识创新工程重大项目(KZCX1-SW-01-02)、国家重点基础研究发展规划项目(2002CB412500)、国家高技术研究发展计划(2003AA131170和(2003AA131020)资助。
SVI and VCI Based on NDVI Time-Series Dataset Used to Monitor Vegetation Growth Status and Its Response to Climate Variables
Received date: 2003-06-01
Revised date: 2004-02-01
Online published: 2004-05-25
本文利用1982~2000年旬合成NDVI时间序列数据,计算2000年3月和5月各旬NDVI偏离历年均值及时间序列NDVI的标准差,进而确定不同土地覆盖类型的Z值在空间域内正态分布特征参数,利用概率密度函数方法将Z值归一化,得到植被长势评价指标标准植被指数(SVI),利用SVI分析2000年3月和5月上旬植被生长状况,在此基础上,利用10个气象站观测的降水量和平均气温资料,分析了各个气象站点19年时间序列的SVI和VCI与降水量和平均气温之间的相关程度,结果表明: (1)在华北平原大部分冬小麦耕作区,3月份小麦生长较好,到5月份,生长与历年相比较差;从3月上旬到5月下旬,生长不良的植被面积有扩张趋势; (2)SVI与植被状态指数( VCI ),表明SVI与VCI之间相关显著,SVI作为植被生长状况评价指标是有效的; (3)SVI和VCI与降水量和气温之间尽管表现出一定的相关性,但相关程度都不很显著,表明植被长势是由多因素共同作用的结果,在不同地区、不同时期以及不同植被覆盖条件下,植被长势所受主要控制因子存在很大的差别;(4)在森林覆盖类型区,3月份的植被长势与该月份之前总降水量存在的关系更显著,而与当月降水和当月平均气温关系并不明显,到5月上旬,由于森林覆盖条件下植被绿度达到饱和,引起建立在光谱植被指数基础上的长势评价指标对气温和降水均不敏感;(5)自然植被条件下的灌丛、草原和草甸覆盖区,相对于降水量,植被长势对气温变化的响应更敏感;(6)农作物覆盖条件下,SVI与降水和气温的关系都不明显,而VCI在不同的季节所受影响的主要气候因子不同,3月份,气温成为作物生长的主要限制因子,而到5月份,水分条件成为作物生长的主要限制条件,特别是在华北平原的冬小麦耕种区;(7)利用时间序列NDVI数据在时间域内构建的指标,进行干旱监测存在明显局限性,因为指标对降水量的敏感性在不同季节不同;(8)VCI和SVI与降水和气温的相关分析说明VCI 对气候环境的变化更敏感。
齐述华,王长耀,牛铮,刘正军 . 利用NDVI时间序列数据分析植被长势对气候因子的响应[J]. 地理科学进展, 2004 , 23(3) : 91 -99 . DOI: 10.11820/dlkxjz.2004.03.012
In this paper, the 20-year NDVI time-series dataset composed every ten days was used to induce SVI (Standard Vegetation Index) and VCI (Vegetation Condition Index). The vegetation growth status spatial pattern for China, at the first ten days of March and May in 2000 , was studied with SVI. Results showed that the winter maize was eugonic in March, but in May winter maize was not in good status; and the area where vegetation was not in good status compared with the past years was enlarged from March to May. Considering the validity of VCI in monitoring vegetation growth status has been approved by some studies and the maganificent correlation between SVI and VCI, we reached the conclusion safely that SVI is valid in monitoring vegetation growth condition. A 20-year rain and average air temperature dataset collected at 10 meterological stations located at differrent vegetation cover type was used to study the VCI and SVI’s response sensitivity to climate variables. Results showed that: (1) The dominant factor on vegetation growth is spatio-temporal and land cover type specified; (2) For forestory cover type, SVI and VCI exhibit some relation with the total precipitation before due time at the first ten days of March, while in May irrelevance between SVI or VCI and climate variables was found that can be explained by NDVI saturation phenomena always happening on forest cover area; (3) For meadow/grassland and shrub, air temperature exhibits a little more remarkable relativity than precipitation especially for VCI; (4) For crop area, according VCI, vegetation growth status has more remarkable relativity with air temperature in March, while precipitation has become the preponderant factor on growth status at May especially for winter wheat area; (5) The drought indice based on time-domain spectral vegetation index were not always valid because their response to precipitation was spatialy and temporaly specified; (6) VCI is more excellent at indicating climatic changes.
Key words: global change; NDVI; SVI; VCI; vegetation
[1] Benedetti, R., and P. Rossini. On the use of NDVI profilesas a tool for agricultural statiscs: the case study of wheat yield estimate and forecast in Emilia Romagna, Remote Sensing of Enviroment, 1993, 45: 311~326.
[2] Moulin, S. A., A. Bondeau, and R. Delecolle. Combining agricultural crop models and satellite observations: from field to regional scales, International Jounal of Remote Sensing, 1998, 19:1021~1036.
[3] Tucker, C.J., Dregne, H.E., Newcomb, W W.. Expantion and contraction of the sahara Desert from 1980 to 1990, Science, 1991, 253: 299~301.
[4] 李晓兵, 史培军. 基于NOAA AVHRR数据的中国主要植被类型NDVI变化规律研究. 植物学报,1999, 41(3):314~324.
[5] Tucker C.J., J.R.G. Townshend, and T.E.Goff. Africanland-cover classification using satellite data. Science, 1985, 227:369~375.
[6] Tucker, C.J. and B.J.Choudhury. Satellite remote sensing of drought conditions, Remote Sensing of Enviroment, 1987, 23:243~251.
[7] Bawa, K., J. Rose, K. N. Ganeshaiah, N. Barve, M. C. Kiran, and R. Umashaanker. Assessing biodiversity from space: an example from the Western Ghats, India. Conservation Ecology, 2002, 6(2): 7.
[Online] URL: http://www.consecol.org/vol6/iss2/art7.
[8] Albert J. Peters, Elizabeth A. Walter-Shea, Lei Ji, Andrés Viπa, Michael Hayes, and Mark D. Svoboda. Drought Monitoring with NDVI-Based Standardized Vegetation Index. Photogrammetric Engineering & Remote Sensing, 2002, 68(1).
[9] Kogan F.N. Remote Sensing of weather impacts on vegetation, International Jounal of Remote Sensing, 1990,11:1405~1419.
[10] 冯强. 中国干旱遥感监测系统的研究, 中国科学院遥感应用研究所博士后出站报告. 2001.
[11] Burgan,R.E., and R.A. hartford. Monitoring vegetation greenness with satellite data, Gen. Tech. Rep. INT-297, U.S. Department of Agriculture, Forest Service, Intermountain Research Station, Ogden, Utah, 1993, 13p.
[12] Unganai LS, Kogan FN. Drought monitoring and corn yield estimation in Southern Africa from AVHRR data. Remote Sensing of Enviromen, 1998, 63 (3): 219~232 .
[13] 温刚, 符淙斌. 中国东部季风区植被物候季节变化对气候响应的大尺度特征: 年际比较. 气候与环境研究, 2001, 6 (1): 1~11.
[14] Kazuhito Ichii, Akira Kawabata and Yasushi Yamaguchi. Global decadal changes in NDVI and its relationships to climate variables, IGARSS 2001, IEEE.
[15] Zhou, L., R. K. Kaufmann, Y. Tian, R. B. Myneni, and C. J. Tucker, Relation between interannual variations in satellite measures of northern forest greenness and climate between 1982 and 1999. Journal of Geophysical Research, 2002, 108 (D1): 4004.
[16] Holben, B. Characteristics of maximum-value composite images from temporal AVHRR data. Int. J. Remote Sens. 1986 (7): 1417~1434.
[17] Cihar J, Huang F. Effect of Atmospheric Correction and Viewing Angle Restriction on AVHRR Composites. Can. J. Remote Sens. 1994, 20(2): 132~137.
[18] 刘正军. 高维遥感数据土地覆盖特征提取与分类研究. 中国科学院遥感应用研究所博士学位论文, 2003. 19] 宋连春, 邓振镛, 董安祥. 全球变化热门丛书——干旱. 北京: 气象出版社, 2003,19.
/
〈 |
|
〉 |