湖泊科学2019，Vol.31Issue(2)：517-528,12.DOI:10.18307/2019.0220
基于无人机和卫星遥感影像的升金湖草滩植被地上生物量反演
UAV and satellite remote sensing images based aboveground biomass inversion in the meadows of Lake Shengjin
摘要
Abstract
The aboveground biomass of wetland vegetation, as an essential indicator of the wetland ecosystem health, is of great significance for the overwintering reproduction, global carbon cycle and ecological purification of rare waterfowl. It is one of the research hotspots in ecology and remote sensing interpretation. The advantage of satellite remote sensing data lies in its wide coverage, but its spatial resolution is low. UAV remote sensing data have high spatial resolution but small acquisition range. At the same time, because of the influence of wetland area, observation system and external environment, it is more complicated and difficult to retrieve the aboveground biomass from remote sensing images. This research studies a kind of inversion method of aboveground biomass based on UAV and GF-1 data. Firstly, UAV visible images of four sample areas and the ground measured sample data are used to establish linear, power function, polynomial, and logarithmic regression model of biomass, visible light band, and a variety of visible light vegetation index. The accuracy of this method was evaluated by the coefficient of determination (R2) , mean absolute error (MAE) and root mean square error (RMSE) . The optimal model was selected for biomass inversion of UAV images. Then the biomass data inverted from the visible light band and the GF-1 WFV normalized difference vegetation index (NDVI) image are used to establish a regression model to obtain the aboveground biomass distribution map of the vegetation in Lake Shengjin meadows. The results show that the polynomial equation was determined using the red band has higher simulation accuracy for biomass inversion, R2= 0.86, MAE = 111.33 g/m2, RMSE = 145.42 g/m2, and the inversion results obtained by the red band biomass inversion method is highly consistent with the actual biomass distribution. The polynomial model, constructed by GF-1 WFV and biomass inversed by UAV, is the optimal model, and R2 reached 0.91. This study uses UAV and GF-1 data to conduct biomass inversion research. It integrates the advantages of each data and can obtain richer and more accurate information. It could improve inversion accuracy and provide data and technical support for wetland monitoring and wetland restoration management. Thus this work has important research significance and application value.关键词
湿地/地上生物量反演/无人机遥感/高分一号/植被指数/升金湖Key words
Wetlands/aboveground biomass inversion/UAV/GF-1/vegetation index/Lake Shengjin引用本文复制引用
高燕,梁泽毓,王彪,吴艳兰,刘诗雨..基于无人机和卫星遥感影像的升金湖草滩植被地上生物量反演[J].湖泊科学,2019,31(2):517-528,12.基金项目
安徽省教育厅重点项目(KJ2018A0007) （KJ2018A0007）
安徽省人力厅留学人员创新项目择优资助计划 （）
安徽省国土资源厅科技项目(2016KJ030002)联合资助 （2016KJ030002）
