毛乌素沙地南缘草地地上生物量遥感反演模型研究  

Study on Remote Sensing Inversion Model of Above-ground Biomass in Grassland on the Southern Edge of MuUs Sandy Land

作　　者：陈丽佳 温利明 路乾 刘维平 陈亚飞 王小龙 陆颖 丛帅 徐誉彰 任永丽 CHEN Li-jia;WEN Li-ming;LU Qian(Yinchuan Livestock Technology Promotion Service Center,Yinchuan,Ningxia 750001)

机构地区：[1]银川市畜牧技术推广服务中心,宁夏银川750001

出　　处：《安徽农业科学》2025年第3期53-57,共5页Journal of Anhui Agricultural Sciences

摘　　要：以毛乌素沙地南缘草地为研究对象,利用2023年7和8月获得的草地地上生物量数据和同期Landsat8 OLI影像,提取归一化植被指数(NDVI)、比值植被指数(RVI)、差值植被指数(DVI)、转换型植被指数(TVI)4种植被指数,并与地上生物量进行相关分析,建立回归模型,同时验证模型的准确度。结果表明:4种植被指数与地上生物量均呈极显著相关,RVI的相关系数高达0.914,其次是NDVI。最优模型为二次多项式回归模型,最差模型为指数回归模型。地上生物量实测值和预测值的平均误差系数为16.23%,回归拟合精度为83.77%。二次多项式回归模型监测草地地上生物量效果最佳。Based on the study of the grassland in south fringe of MuUs sandy land,normalized vegetation index(NDVI),ratio vegetation index(RVI),difference vegetation index(DVI)and transformation vegetation index(TVI)were extracted using grassland above-ground biomass data and Landsat8 OLI image which were acquired in July and August,2023.The correlation analysis was made between the four vegetation indexes and above-ground biomass,and regression models were established.Meanwhile,the accuracy of the model was verified.The results showed that there was an extremely significant correlation between the four vegetation indexes and above-ground biomass,with a correlation coefficient of 0.914 for RVI,followed by NDVI.The optimal model was a quadratic polynomial regression model,and the worst model was an exponential regression model.The average error coefficient between the measured and predicted values of above-ground biomass was 16.23%,and the regression fitting accuracy was 83.77%.The quadratic polynomial regression model had the best effect on monitoring the above-ground biomass of grassland.

关 键 词：地上生物量 植被指数 草地 遥感监测 毛乌素沙地 

分 类 号：S127[农业科学—农业基础科学]