EFFECTS OF GF-6 SATELLITE RED-EDGE BANDS ON PEANUT DROUGHT MONITORING

文献类型： 外文期刊

第一作者： Zhang Yan

作者： Zhang Yan;Liu Ting;He Jia;Wang Laigang;Guo Yan;Zhang Hongli;Yang Xiuzhong;Li Pei

作者机构：

关键词： Remote Sensing; GF-6 WFV; Red-Edge Band; Peanut; Drought; Monitoring

期刊名称：XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION III

ISSN： 2194-9042

年卷期： 2022 年 5-3 卷

页码：

收录情况： SCI

摘要： Red-edge band is an indicator band to describe the health status of crops. In order to explore the impact of the red-edge bands on the accuracy of agricultural drought monitoring, this study used GF-6 WFV and Landsat8 to calculate the Red-edge Normalized Difference Vegetation Index (NDVI705), Vogelmann red-edge index 1 (VOG1), Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) to construct temperature vegetation drought index (TVDI), this index integrated vegetation index and land surface temperature information, the soil relative humidity data and the measured drought grade data were respectively used for correlation analysis and classification accuracy verification of the TVDI results. The results showed that dry edge equation fit with red edge bands were higher than that of non-red edge bands. The dry edge equation based on VOG1 index has the highest fit, with a maximum coefficient determination of 0.92; TVDI constructed by the above vegetation index have significant negative correlation with soil relative humidity. The TVDI based on the VOG1 index has a better correlation with the relative soil humidity, with a maximum correlation coefficient of 0.85; and realized the dynamic monitoring of peanut drought grade, the overall accuracy rate of peanut drought grade monitoring reached 92.59%, and the result of TVDI classification was in good agreement with the actual drought grade measurement result. The red edge bands of GF-6 satellite can effectively improve the accuracy of peanut drought monitoring and better characterize peanut drought information. This research provides a data reference for the application of GF-6 WFV data in agricultural drought monitoring.

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