摘要
植被恢复情况是生产建设水土保持监测的主要内容,也是生态环境恢复的重要指标。为高效精准进行植被恢复率计算,应用无人机航测影像数据,利用ENVI非监督分类及目视判别手段,在实现影像土地利用分类的基础上提取植被面积,以期为生产建设项目水土保持监测提供可靠的依据。结果表明:(1)无人机在能见度较高且风速稳定天气条件下,可快速获取小区域地面高分辨率影像。(2)无人机正射影像图在Envi 5.1软件非监督分类的基础上采用目视解释法可实现水土保持土地利用现状分类。(3)通过对各地物分析剖解,在目视判决准则下可划分植被并提取植被面积。(4)利用无人机获取试验区域的正射影像图,其水平精度可达0.2m。高精度无人机遥感数据可用于小范围生产建设项目水土保持土地利用分类及植被恢复分析。
Vegetation restoration is the main aspect of soil and water conservation monitoring,and is the important indicator of ecological environment restoration.Vegetation area was extracted on the basis of image land use classification to efficiently and accurately calculate vegetation restoration rate,provide a reliable basis for soil and water conservation monitoring by using UAV aerial survey image data,unsupervised classification and visual discrimination method of ENVI.The result shows that:(1)UAV can quickly obtain high resolution images of the small areas with high visibility and stable wind conditions;(2)UAV orthophoto map can be used to classify land use status of water and soil conservation on the basis of unsupervised classification of Envi 5.1 software;(3)based on the analysis of objects in various regions,vegetation can be divided and vegetation area can be extracted in visual judgement criterion;(4)the horizontal precision of the orthophoto map of the test area obtained by using the UAV can reach 0.2 m resolution.High precision data obtained from UAV remote sensing can be used for land use classification and vegetation restoration analysis in small scale of soil and water conservation projects.
作者
林成行
朱首军
周涛
巴明坤
赵宇
LIN Chenghang;ZHU Shoujun;ZHOU Tao;BA Mingkun;ZHAO Yu(Institute of Soil and Water Conservation,Northwest A&F University,Yangling,Shaanxi 712100,China;College of Natural Resources and Environment,Northwest A&F University,Yangling,Shaanxi 712100,China)
出处
《水土保持研究》
CSCD
北大核心
2018年第6期211-215,共5页
Research of Soil and Water Conservation
基金
陕西省水土保持地方标准修编项目"<陕西省水土保持工程施工监理技术规程>编"(K4030216162)
关键词
无人机
遥感
土地利用分类
林草植被恢复率
UAV
remote sensing
land use classification
vegetation recovery rate