首页|协同空—天遥感的荒漠草原植被覆盖度反演方法研究

协同空—天遥感的荒漠草原植被覆盖度反演方法研究

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草地植被覆盖度是评价草地健康状况及监测环境变化的重要生态参量.目前大区域尺度植被覆盖度提取主要基于卫星遥感数据,无人机遥感数据作为卫星数据估算草地覆盖度的一种补充手段,可提高模型估算精度.基于无人机遥感数据和BJ3卫星数据,采用回归分析法、像元二分法和随机森林三种植被覆盖度反演方法,对鄂托克旗荒漠草原植被覆盖度进行反演与验证.结果表明:利用植被指数建立的回归分析模型中最优反演模型为归一化植被指数(Normalized Difference Vegetation Index,NDVI)的二次多项式模型,R2=0.752;直接利用无人机遥感数据波段值建立的随机森林模型R2=0.893、RMSE=0.072,相较于NDVI的二次多项式模型、像元二分模型R2分别提升0.141、0.151.利用空—天遥感数据和随机森林方法,能够快速、准确获取卫星尺度上研究区的植被覆盖度,为大区域荒漠草原植被覆盖度反演提供支持.
Research on the Inversion Method of Desert Grassland Fractional Vegetation Cover based on Collaborative UAV-Satellite Remote Sensing
Grassland Fractional Vegetation Cover is an important ecological parameter for evaluating the health status of grassland and monitoring environmental changes.At present,the extraction of Fractional Vegetation Cover at large regional scale is mainly based on satellite remote sensing data,and Unmanned Aerial Vehicle Re-mote Sensing(UAVRS)data,as a supplementary means of estimating grassland cover from satellite data,can improve the accuracy of model estimation.Based on the UAVRS data and BJ3 satellite data,three vegetation cover inversion methods,namely regression analysis method,pixel dichotomy method and random forest were used to invert and validate the vegetation cover of desert grassland in Otog Banner.The results showed that the best inversion model among the regression analysis models established by the vegetation index was the quadratic polynomial model of Normalized Difference Vegetation Index(NDVI),with R2=0.752;the R2 and RMSE ob-tained from the random forest model directly using the waveband values of UAVRS data were 0.893 and 0.072,compared with the quadratic polynomial model of NDVI and the pixel dichotomy model,R2 is improved by 0.141 and 0.151.Using the UAVRS data and the random forest method,it is possible to quickly and accurately obtain the vegetation cover of the study area on the satellite scale,which can provide support for the inversion of desert grassland vegetation cover in the large region.

Unmanned Aerial Vehicle Remote Sensing(UAVRS)BJ3 satellite dataFractional vegetation coverDesert grassland

宁可欣、孙晨曦、万华伟、帅艳民

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辽宁工程技术大学测绘与地理科学学院,辽宁阜新 1230000

生态环境部卫星环境应用中心,北京 100094

浙江师范大学地理与环境科学学院,浙江金华 321004

中国科学院新疆生态与地理研究所,新疆乌鲁木齐 830011

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无人机遥感 BJ3卫星数据 植被覆盖度 荒漠草原

2024

遥感技术与应用
中国科学院遥感联合中心

遥感技术与应用

CSTPCD北大核心
影响因子:0.961
ISSN:1004-0323
年,卷(期):2024.39(5)