摘要
基于光谱信息的森林地上生物量遥感模型多存在精度不高的问题,如何更准确地获取森林地上生物量是遥感领域的研究热点。该研究以位于塔里木河下游的河岸胡杨林为例,探讨在无人机摄影测量技术支持下,使用高分辨率卫星遥感技术,通过面向对象影像分析和回归分析等技术,获取区域尺度下胡杨冠幅、树高和密度等森林结构参数,在此基础上,通过生长方程计算得到区域尺度森林地上生物量。在30、50、100和250 m 4个空间尺度上,与无人机数据的估算结果相比,高分辨率卫星遥感数据的地上生物量估算结果高22%~26%,其误差主要来自于树冠生物量部分。随着空间尺度增大,基于卫星遥感的地上生物量回归模型R^(2)也随之增大,其中在100 m尺度上,地上生物量回归模型R^(2)为0.851,表明使用高分辨率卫星遥感技术可以在较大的区域尺度上获得较高的森林地上生物量估算精度。地上生物量回归模型的标准化系数分析表明,对森林地上生物量估算精度影响最大的因素是密度和树高,冠幅影响最小,并且随着空间尺度增大,密度的影响有增加趋势,树高的影响有减少趋势。研究结果可为使用无人机和卫星遥感技术研究森林地上生物量提供参考。
Currently,there is still some limitations on the Above Ground Biomass(AGB)of forest using spectral information from remote sensing technology.In this study,taking Populus euphratica forest in the lower reaches of Tarim River as an example,the Unmanned Aerial Vehicle(UAV)low altitude remote sensing and Very High-Resolution(VHR)satellite remote sensing were used to estimate the forest AGB using forest structure information.Some more advanced UAV and image segmentation techniques were used to improve the accuracy of crown diameter,thereby to improve the accuracy of AGB estimation in the future.The AGB of Populous euphratica was divided into trunk biomass and crown biomass.An allometric equation was used to calculate with the parameters of tree height,Diameter at Breast Height(DBH),and crown diameter.The actual procedure was as follows:Digital Surface Model(DSM)and Digital Terrain Model(DTM)were firstly obtained using UAV oblique photogrammetry and Geographic Information System(GIS)interpolation,together with the Canopy Height Model(CHM).Secondly,an Object-Oriented Image Analysis(OBIA)was used to acquire the tree height and crown diameter.Finally,an allometric equation was used to calculate the AGB by UAV measured data.The VHR WorldView-2(WV2)Normalized Difference Vegetation Index(NDVI)image was calculated by the OBIA and GIS overlay technologies,thereby to extract the crown diameter as result.Specifically,the WV2 tree height was obtained from the regression model that built between 32 general features and UAV-measured tree height.The AGB by WV2 measured was calculated using an allometric equation.A comparison of UAV-and field-measured data showed that:The coefficients of determination(R^(2))of crown diameter,height,density,and AGB were 0.783,0.866,0.941 and 0.816,respectively.A high goodness-of-fit was also proved that the UAV-measurement can be expected to replace the field-measurent in plot size.Tree height from the WV2-measured was overestimated by 2.2%-3.2%,resulting in the trunk biomass was higher by 10%-13%,compared with the UAV-measured data.The crown diameter of WV2-measured was significantly overestimated by 27%-30%,resulting in the canopy biomass was overestimated by 58%-71%.Therefore,the density was underestimated by 1.8%-6.5%.The AGB of WV2-measured was overestimated by 22%-26%,compared with the UAV-measured data,where the error mainly came from the canopy biomass.A comparison of WV2-and UAV-measured data on the four scale grid size of 30 to 250 m showed that the R^(2) of crown diameter,height,density,and AGB increased with the increasing of statistical grid size,whereas,the R^(2) of AGB was 0.851 at the scale of 100 m,which was usually used as a AGB statistical standard size.The forest structure information can be obtained by the VHR remote sensing through the OBIA with the support of UAV-measured data,and a good AGB accuracy can be obtained on a coarse scale.The linear regression models were established between AGB and crown diameter,height,density obtained by the UAV-and WV2-measured data.The coefficients of tree density and tree height were larger than those of crown diameter,indicating that tree density and tree height were the most important factors affecting the AGB on four scales,while the crown diameter has the least effect.There was an increasing trend in the influence of density,whereas a decreasing trend in the effect of tree height,with the increase of statistical grid size.
作者
杨雪峰
昝梅
木尼热·买买提
Yang Xuefeng;Zan Mei;Munire·Maimaiti(College of Geography Science and Tourism,Xinjiang Normal University,Urumqi 830054,China;Xinjiang Laboratory of Lake Environment and Resources in Arid Zone,Urumqi 830054,China)
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2021年第1期77-83,共7页
Transactions of the Chinese Society of Agricultural Engineering
基金
新疆维吾尔自治区自然科学基金资助面上项目(2018D01A32)。
关键词
无人机
遥感
地上生物量
森林结构
胡杨
卫星遥感
UAV
remote sensing
above ground biomass
structure of forest
Populus euphratica
satellite remote sensing