首页 >  2003, Vol. 7, Issue (6) : 504-508

摘要

全文摘要次数: 3020 全文下载次数: 18
引用本文:

DOI:

10.11834/jrs.20030612

收稿日期:

2002-06-05

修改日期:

2003-01-17

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草地蝗虫发生遥感监测的一种新算法
南京师范大学地理科学学院,江苏南京210097
摘要:

草地蝗虫发生的遥感指标分析是建立草地蝗虫发生预报模型的基础。以Landsat-5 TM为遥感信息源,根据草地蝗虫发生的遥感机理,提出了一种基于比值的草地蝗虫发生监测的遥感新算法,即R/G=(TM4 TM7)/TM6。在青海湖地区,结合草地蝗虫发生的野外样点数据,应用此新算法以及常用的标准植被指数[归一化植被指数(NDVI)和土壤调节植被指数(SAVI)],分别进行了此3种指标对草地蝗虫发生的差异显著性检验。结果表明,在草地蝗虫密度≥5头/m^2时,常规的标准算法(NDVI,SAVI)优于新算法(RIG);而在草地蝗虫密度≥15头/m^2和≥25头/m^2时,RIG优于NDVI和SAVI,可用于草地蝗虫发生的遥感监测。

A New Algorithm for Grasshopper Outbreak Monitoring from Landsat-TM Imagery
Abstract:

The analysis of remote sensing indices to grasshopper outbreak is the base to develop the prediction model for grasshopper outbreak. A ratio-based formulae for grasshopper outbread from Landsat-5 TM imagery,namely,RIG = (TM4 + TM7)/ TM6,was presented,according to the mechanism of remote sensing of grasshopper outbreak. The new algorithm( RIG)and two kinds of standard algorithms (the normalized difference vegetation index-NDVI and the soil adjusted vegetation index-SAVI)were used to test significance levels for t-tests of differences between mean Values of grasshopper site and non-site respectively,combining with grasshopper outbreak information from field sampling in the region around Qinghai lake. The results showed that the RIG presented was superior to standard vegetation indices(NDVI and SAVI)used commonly at densities≥15 and≥25 grasshoppers / m2;while inferior to NDVI and SAVI at densities≥5 grasshoppers / m2 . Therefore,the RIG is able to monitor grasshopper outbreak.

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