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[1]LIN Chenghang,ZHU Shoujun,ZHOU Tao,et al.The Extraction of Vegetation Recovery Rate in Soil and Water Conservation Based on the Technology of Unmanned Aerial Vehicle (UAV) Remote Sensing[J].Research of Soil and Water Conservation,2018,25(06):211-215.

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The Extraction of Vegetation Recovery Rate in Soil and Water Conservation Based on the Technology of Unmanned Aerial Vehicle (UAV) Remote Sensing

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 25 Number of periods: 2018 06 Page number: 211-215 Column: Public date: 2018-10-26

Title:: The Extraction of Vegetation Recovery Rate in Soil and Water Conservation Based on the Technology of Unmanned Aerial Vehicle (UAV) Remote Sensing

Author(s):: LIN Chenghang¹, ZHU Shoujun^1,2, ZHOU Tao², BA Mingkun², ZHAO Yu²; 1. Institute of Soil and Water Conservation, Northwest A & F University, Yangling, Shaanxi 712100, China;
2. College of Natural Resources and Environment, Northwest A & F University, Yangling, Shaanxi 712100, China

Keywords:: UAV; remote sensing; land use classification; vegetation recovery rate

CLC:: V279⁺.2;P231.2

DOI:: -

Abstract:: 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.

References:: [1] 马泽忠,王福海,刘智华,等.低空无人飞行器遥感技术在重庆城口滑坡堰塞湖灾害监测中的应用研究[J].水土保持学报,2011,25(1):253-256.
[2] 张养安,宋晓强,段怡红.水土保持规划中低空遥感数据的获取及应用[J].水土保持通报,2017,37(5):338-341.
[3] 汪小钦,王苗苗,王绍强,等.基于可见光波段无人机遥感的植被信息提取[J].农业工程学报,2015,31(5):152-158.
[4] 喻权刚."3S"技术在黄土高原水土保持动态监测中的研究与实践[J].水土保持研究,2004,11(2):33-35.
[5] 魏子寅.基于无人机正射影像进行土地利用/土地覆盖分析[D].呼和浩特:内蒙古师范大学,2013.
[6] 韩文霆,郭聪聪,张立元,等.基于无人机遥感的灌区土地利用与覆被分类方法[J].农业机械学报,2016,47(11):270-277.
[7] 李宗南,陈仲新,王利民,等.基于小型无人机遥感的玉米倒伏面积提取[J].农业工程学报,2014,30(19):207-213.
[8] Agisoft PhotoScan User Manual[M].Sankt Petersburg, Russia:Agisoft LLC,2018.
[9] 杨超,苏正安,马菁,等.基于无人机影像快速估算矿山排土场边坡土壤侵蚀速率的方法[J].水土保持通报,2016,36(6):126-130.
[10] 张雅文,许文盛,韩培,等.无人机遥感技术在生产建设项目水土保持监测中的应用[J].中国水土保持科学,2017,2(15):132-139.
[11] 于海洋,张飞,曹雷.精河县土地利用/覆被变化及土地生态安全研究[J].水土保持研究,2017,24(6):348-353.
[12] 韩沐汶,庄逐舟,马超,等.基于生态绿当量的生态移民区生态效益评价[J].水土保持研究,2014,21(6):211-217.
[13] 史俊凤.生产建设项目水土保持监测的RS与GIS的应用研究[D].北京:北京林业大学,2016.
[14] 赵庚星,林戈.黄河口耕地遥感动态监测及其生态环境安全分析[J].水土保持学报,2004,18(2):37-40.

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