J Integr Plant Biol. ›› 2003, Vol. 45 ›› Issue (10): 1139-1145.

• Research Articles •     Next Articles

Intra-annual Vegetation Change Characteristics in the NDVI-Ts Space: Application to Farming-Pastoral Zone in North China

CHEN Yun-Hao, LI Xiao-Bing*, SHI Pei-Jun, DOU Wen, LI Xia   


Land use/land cover change (LUCC) mapping and analysis using multi-temporal normalize difference vegetation index (NDVI) data have been well documented. Recent empirical studies have documented that many new methods with high accuracy of retrieved land surface temperature (Ts) have been developed. Thus, the combination of land surface temperature and NDVI has the greatest potential to improve the surface vegetation dynamic monitoring. In this study, the following objectives are pursued to: (1) introduce the practical method to produce the Ts, NDVI and Ts/NDVI based on remotely sensed data; (2) investigate the different retrieved result of vegetation cover information from NDVI, Ts and Ts/NDVI data sets, and analyze the intra-annual time trajectories of different vegetation cover categories in the NDVI-Ts space for farming-pastoral zone in North China, and (3) quantitative analysis the difference in using NDVI, Ts and Ts/NDVI data sets to express information based on the indices (information entropy and averaged information grads), and evaluate the relative role of Ts/NDVI data set in the discrimination of different vegetation cover categories through comparison to traditional NDVI data set.

中国北方草地与农牧交错带植被的N D V I-T s 空间的年内变化特征
陈云浩 李晓兵  史培军 窦 闻 李 霞
(北京师范大学资源科学研究所,北京师范大学环境演变与自然灾害教育部重点实验室,北京 100875)

摘要: 利用多时相或时序植被指数(normalize difference vegetation index,NDVI)数据进行地表覆盖研
究已取得了大量成果。随着陆地表面温度(land surface temperature, Ts)遥感反演精度的不断提高,将Ts与NDVI结合起来进行地表植被动态变化的监测已成为可能。本文主要包括以下三部分内容:1)介绍了基于卫星遥感数据的NDVI、TsTs/NDVI计算方法。2)讨论NDVI、TsTs/NDVI数据对植被覆盖信息表达的差异,并分析了中国北方草地与农牧交错带植被在NDVI-Ts空间的年内变化特征。3)利用信息熵和平均梯度,定量分析了NDVI、TsTs/NDVI数据在信息表达丰富度方面的差异,并对在不同地表植被覆盖下,Ts/NDVI数据对信息提高程度的敏感性进行了讨论。
关键词: 植被指数;陆地表面温度;NDVI-Ts空间;信息熵

通讯作者。E-mail: <xbli@irs.bnu.edu.cn>。

Key words: vegetation index, land surface temperature, NDVI-Ts space, information entropy

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