Improving estimates of fractional vegetation cover based on UAV in alpine grassland on the Qinghai-Tibetan Plateau
Improving estimates of fractional vegetation cover based on UAV in alpine grassland on the Qinghai-Tibetan Plateau
复制标题
基于无人机改进青藏高原高寒草原植被覆盖度估算
DOI：
10.1080/01431161.2016.1165884
复制
发表时间：
2016-01-01
影响因子：
3.4
通讯作者：
Wang, Xiaoyun
中科院分区：
文献类型：
--
作者：
Chen, Jianjun;Yi, Shuhua;Wang, Xiaoyun
植被覆盖度是生态系统平衡、土壤侵蚀和气候变化研究中的重要参数。遥感反演是估算FVC的常用方法。然而，地面调查（样方一级）和卫星遥感图像（卫星图像像素比例）之间存在着重大差距。在这项研究中，我们评估的差距与无人机（UAV）航空影像的高寒草地在青藏高原（QTP）。结果表明：（1）在卫星图像像素尺度上，最准确的FVC估计来自无人机（FVCUAV），当FVC使用地面调查时，（FVCground），精度随样方数目的增加而增加，与下垫面条件的异质性成反比;（2）在卫星影像像素尺度上，无人机方法比传统的地面调查方法更有效;（3）FVCUAV与植被指数（维斯）的决定系数（R-2）显著大于FVCground与维斯的决定系数（p < 0.05，n = 5）。我们的研究结果表明，使用无人机估计FVC在卫星图像像素级提供更准确的结果，是比传统的地面调查方法更有效。
Fractional vegetation cover (FVC) is an important parameter in studies of ecosystem balance, soil erosion, and climate change. Remote-sensing inversion is a common approach to estimating FVC. However, there is an important gap between ground-based surveys (quadrat level) and remote-sensing imagery (satellite image pixel scale) from satellites. In this study we evaluated that gap with unmanned aerial vehicle (UAV) aerial images of alpine grassland on the Qinghai-Tibetan Plateau (QTP). The results showed that: (1) the most accurate estimations of FVC came from UAV (FVCUAV) at the satellite image pixel scale, and when FVC was estimated using ground-based surveys (FVCground), the accuracy increased as the number of quadrats used increased and was inversely proportional to the heterogeneity of the underlying surface condition; (2) the UAV method was more efficient than conventional ground-based survey methods at the satellite image pixel scale; and (3) the coefficient of determination (R-2) between FVCUAV and vegetation indices (VIs) was significantly greater than that between FVCground and VIs (p < 0.05, n = 5). Our results suggest that the use of UAV to estimate FVC at the satellite image pixel scale provides more accurate results and is more efficient than conventional ground-based survey methods.