基于信息熵的山西太谷植被指数最佳分辨率尺度分析  

Scale analysis of optimal vegetation index resolution based on information entropy :An example applied in Taigu county,Shanxi province

作　　者：齐婧冰 樊风雷[1] QI Jing-bing FAN Feng-lei(School of Geography, South China Normal University, Guangzhou 510631, China)

机构地区：[1]华南师范大学地理科学学院,广东广州510631

出　　处：《广东农业科学》2017年第1期167-171,I0002,共6页Guangdong Agricultural Sciences

基　　金：国家自然科学基金(41201432)

摘　　要：尺度是理解地球系统复杂性的关键准则之一。由地学现象的本身出发,结合具体的遥感研究应用来选择遥感影像最佳分辨率具有重大现实意义。从信息论的角度出发,选取山西太谷作为实验区,利用信息熵方法测试该区域2010年各类植被指数不同分辨率下所包含的信息量(测试分辨率主要有30、60、120、240、480、960 m),获得各类植被指数图像的信息熵随图像分辨率的变化曲线,并据此判定最佳的分辨率尺度。结果表明,当各类植被指数图像分辨率为240 m时,植被指数的信息熵均开始趋于减小,此时图像的信息量基本达到饱和。因此,研究区植被指数的最佳分辨率为240 m。基于信息熵的方法来选择影像最佳分辨率,可以为植被遥感监测提供重要参考。Abstract： Scale is one of the key criteria for understanding the complexity of earth system, and it is crucial to select the optimal resolution of remote sensing image according to its application field and characteristics. Based on information theory, this paper, giving an example of Taigu county in Shanxi province, measured the topographic information of different resolution of 30 x 30, 60 x 60, 120 x 120, 240 x 240,480 x 480 and 960 x 960 of vegetation index image in 2010 by the method of entropy, and then obtained the changed curve of topographic information entropy with the changed resolution so as to determine the optimal resolution. The results showed that, when the resolution of vegetation index image reached to 240 m, the information entropy of vegetation index image began to decrease, at the same time the information content tended to saturation, so the optimal resolution of vegetation index image was 240 m in this region. The method, which is based on information entropy to determine optimal resolution of images, can suDolv an imnortant referencefor remote sensing monitoring of vegetation.

关 键 词：植被指数 植被遥感 信息熵 最佳分辨率 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]