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水土流失区生态修复后植被健康的遥感判别
引用本文:胡秀娟,徐涵秋,郭燕滨,张博博.水土流失区生态修复后植被健康的遥感判别[J].生态学杂志,2017,28(1):250-256.
作者姓名:胡秀娟  徐涵秋  郭燕滨  张博博
作者单位:1.福州大学环境与资源学院, 福州 350116;2.福州大学遥感信息工程研究所, 福州 350116;3.福建省水土流失遥感监测评估与灾害防治重点实验室, 福州 350116
基金项目:本文由国家科技支撑计划项目(2013BAC08B01-05)和福州大学科技发展基金项目(2014-XY-10)资助
摘    要:基于遥感技术和WorldView-2卫星影像,提出一个新型植被健康指数(VHI),以快速、大面积地监测与评价水土流失区的植被健康状况.该指数由归一化山地植被指数、氮素反射指数和黄光波段反射率3个因子构成,通过主成分变换将3个因子集成为VHI,以避免主观加权求和集成法所产生的偏差.将VHI应用于福建省长汀县河田盆地一带,对水土流失区的植被健康状况进行监测.结果表明: VHI可以很好地揭示植被的健康状况,其判别总精度可达91%.河田盆地健康等级为好、中、差的植被面积占植被总面积的比例分别为10.1%、49.2%和40.7%,说明研究区的植被健康总体状况仍不理想,主要因为水土流失区土壤贫瘠、新种植的植被生长不良.

关 键 词:生态  遥感  植被健康指数  主成分分析  河田盆地
收稿时间:2016-06-15

Remote sensing detection of vegetation health status after ecological restoration in soil and water loss region
HU Xiu-juan,XU Han-qiu,GUO Yan-bin,ZHANG Bo-bo.Remote sensing detection of vegetation health status after ecological restoration in soil and water loss region[J].Chinese Journal of Ecology,2017,28(1):250-256.
Authors:HU Xiu-juan  XU Han-qiu  GUO Yan-bin  ZHANG Bo-bo
Institution:1.College of Environment and Resources, Fuzhou University, Fuzhou 350116, China;2.Institute of Remote Sensing Information Engineering, Fuzhou University, Fuzhou 350116, China;3.Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Protection, Fuzhou University, Fuzhou 350116, China
Abstract:This paper proposed a vegetation health index (VHI) to rapidly monitor and assess vegetation health status in soil and water loss region based on remote sensing techniques and WorldView-2 imagery. VHI was constructed by three factors, i.e., the normalized mountain vegetation index, the nitrogen reflectance index and the reflectance of the yellow band, through the principal component transformation, in order to avoid the deviation induced by subjective method of weighted summation. The Hetian Basin of Changting County in Fujian Province, China, was taken as a test area to assess the vegetation health status in soil and water loss region using VHI. The results showed that the VHI could detect vegetation health status with a total accuracy of 91%. The vegetation of Hetian Basin in good, moderate and poor health status accounted for 10.1%, 49.2% and 40.7%, respectively. The vegetation of the study area was still under an unhealthy status because the soil was poor and the growth of newly planted vegetation was not good in the soil and water loss region.
Keywords:ecology  remote sensing  vegetation health index (VHI)  principal component analysis  Hetian Basin
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