无人机多光谱影像的天然草地生物量估算  

Estimating aboveground biomass of natural grassland based on multispectral images of Unmanned Aerial Vehicles

作　　者：孙世泽[1,2,3] 汪传建 尹小君[1,2,3] 王伟强 刘伟[1,2,3] 张雅 赵庆展[1,2,3] SUN Shize;WANG Chuanjian;YIN Xiaojun;WANG Weiqiang;LIU Wei;ZHANG Ya;ZHAO Qingzhan(College of Information Science and Technology,Shihezi University,Shihezi 832000,China;Geospatial Information Engineering Research Center,Xinjiang Production and Construction Corps,Shihezi 832000,China;Geospatial Information Engineering Laboratory,Xinjiang Production and Construction Corps,Shihezi 832000,China)

机构地区：[1]石河子大学信息科学与技术学院,石河子832000 [2]兵团空间信息工程技术研究中心,石河子832000 [3]兵团空间信息工程实验室,石河子832000

出　　处：《遥感学报》2018年第5期848-856,共9页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家自然科学基金(编号:41461088);兵团空间信息创新团队(编号:2016AB001);新疆兵团工业科技计划项目(编号:2015BA006)~~

摘　　要：地上草地生物量是衡量天然草地生态系统的重要指标,是草地资源合理利用和载畜平衡监测的重要依据。为了快速、准确、有效地估算天然草地地上生物量,掌握其变化规律,以天山北坡天然牧场为研究区,分析其地上生物量的时空分布特征。根据研究区阴坡与阳坡不同的草地类型和植被种类,利用多旋翼无人机获取的高分辨率多光谱影像(含近红外波段),结合地面实测数据,在进行天然草地地上生物量与植被指数相关性分析的基础上,运用回归分析方法,建立生物量和多种植被指数的估算模型。结果表明:考虑地形因子(阴阳坡)之后,植被地上生物量与各植被指数的相关性系数显著提高;不同坡向,同一植被指数拟合精度差异较大;同一坡向,各个植被指数的敏感性也有所不同。总体上,比值植被指数(RVI)与阴阳坡草地生物量拟合效果最好,模型精度均达到75%以上。利用植被指数建立的生物量估算方法结果与实际相符,可为天然草地生态系统检测和草地资源合理利用提供方法和依据。The aboveground biomass of grasslands is an important measurement index for grassland ecosystems and an important basis for the optimal use of grassland resources. In addition, identification of aboveground biomass can be used in monitoring the balance between grassland forage supply and livestock demand. To estimate the aboveground biomass of natural grasslands and determine the variation trend rapidly, accurately, and effectively, we selected the natural rangeland in the northern hillside of Tianshan Mountain as a typical study area and analyzed the spatio-temporal change characteristic of its aboveground biomass.With their rapid development, Unmanned Aerial Vehicles（UAVs） have been extensively used in remote sensing because of their convenient operation, lower cost, and shorter revisit cycle compared with satellites. In addition, the lightweight sensors of UAV allow low-altitude remote sensing, which could capture high-spatial, high-spectral resolution images. We conducted a survey of the different grassland types and vegetation varieties in shady and sunny slopes of the rangeland. We used a multi-rotor UAV equipped with Micro-MCA12 Snap to obtain high-resolution multispectral images and collected field survey data. We established a relational model based on the correlation between the aboveground biomass and Vegetation Indexes（VIs） by regression analysis. Results showed poor correlations between the aboveground biomass and VIs, but these correlations improved remarkably after considering the terrain factors. The effectiveness of the VIs varied in different grassland types and vegetation fractions. Accuracy analysis showed large differences in the fitting accuracy of the different slope aspects and small differences in the effectiveness of the same slope aspect. In sum, the highest effectiveness between the Ratio Vegetation Index（RVI） and the aboveground biomass was obtained in the southern and northern slopes, with an estimation precision of more than 75%. The main conclusions are the following.�

关 键 词：天然草地 生物量 多光谱影像 阴阳坡 估算模型 无人机 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]