基于无人机遥感的高寒草原沙化模型及等级划分

	基于无人机遥感的高寒草原沙化模型及等级划分
其他题名	Desertification Model and Classification of Alpine Steppe Based on Unmanned Aerial Vehicle (UAV) Remote Sensing
	花蕊 1; 周睿 2; 王婷 3; 许铭 4; 唐庄生 5; 花立民 6
	2019
发表期刊	中国沙漠
ISSN	1000-694X
卷号	39 期号:1 页码:26-33
摘要	The alpine steppe is a major type of the grassland ecosystem in the Qinghai-Tibet Plateau and plays an important role in soil erosion control and wild animal conservation. In recent years,the desertification of alpine steppe is expanding because of the global climate change and human disturbance. Therefore,it is very important to monitor the area and extent of grassland desertification at a spatial-temporal scale for control. The study used two models of unmanned aerial vehicle (DJ Phantom 3 and Matrice100) and ground survey technology to investigate the desertification status of alpine steppe of Maduo County in Sanjiangyuan National Park,which located in Qinghai Province. The purpose of this study is to select the proper vegetation indices of UAV that suit to build desertification model and classification criteria for alpine steppe desertification. The results showed as following: (1) Based on the respective correlation between Visible-Band Difference Vegetation Index (VDVI) ,Enhanced Normalized Difference Vegetation Index (ENDVI) ,Normalized Green-Red Difference Index (NG RDI) and Grassland Desertification Index (GDI) ,the optimal vegetation index of UAV is VDVI (R = 0.9055) . (2) Built the grassland desertification model,VDVI = 0.3024GDI2-0.0335GDI+0.0119(R~2 = 0.9326) ,the relative error is 1.779% (RMSE = 0. 165,R~2 = 0.7447) ,which means the higher fitting precision. (3) The desertification of the alpine steppe in the study area is divided into five grades,involving no obvious desertification(VDVI>0.2247) ,mild desertification(0. 1493
其他摘要	高寒草原是青藏高原草地生态系统的主要组成,在防风固沙、野生动物保育等方面具有重要作用。近年来,在全球气候变化和人为干扰加剧的背景下,高寒草原沙化加剧,基于时空尺度监测范围及程度是防治高寒草地沙化的前提。以青海三江源区玛多县的高寒草原为研究区,结合大疆精灵3和经纬M100旋翼无人机和地面调查,探讨基于无人机遥测的植被指数在草地沙化调查方面的适宜性,以此为基础制定了高寒草原沙化模型及等级划分标准。结果显示: (1)通过对VDVI(Visible-Band Difference Vegetation Index) 、ENDVI(Enhanced Normalized Difference Vegetation Index)和NGRDI(Normalized Green-Red Difference Index)指数与草地沙化指数GDI(Grassland Desertification Index)的相关分析,选取出高寒草地沙化研究最优植被指数为VDVI(R= 0.9055) ; (2) GDI与VDVI的关系模型为VDVI = 0.3024GDI2-0.0335GDI+0.0119(R~2 = 0.9326) 。模型相对误差为1.779% (RMSE = 0.165,R~2 = 0.7447) ,拟合精度较高; (3)基于无人机遥感植被指数的聚类分析,将研究区高寒草原沙化划分为5个等级,即无明显沙化(VDVI>0.2247) 、轻度沙化(0.1493
关键词	无人机沙化植被指数高寒草原 UAV desertification vegetation index alpine steppe
收录类别	CSCD
语种	中文
WOS关键词	Geology
WOS研究方向	Science & Technology
WOS类目	GEOSCIENCES MULTIDISCIPLINARY
CSCD记录号	CSCD:6423842
引用统计	被引频次：6[CSCD] [CSCD记录]
文献类型	期刊论文
专题	任务一_子任务一循证社会科学证据集成任务一
作者单位	1.甘肃农业大学草业学院, 草业生态系统教育部重点实验室, 兰州, 甘肃 730070, 中国 2.甘肃农业大学草业学院, 草业生态系统教育部重点实验室, 兰州, 甘肃 730070, 中国 3.甘肃农业大学草业学院, 草业生态系统教育部重点实验室, 兰州, 甘肃 730070, 中国 4.甘肃农业大学草业学院, 草业生态系统教育部重点实验室, 兰州, 甘肃 730070, 中国 5.甘肃农业大学草业学院, 草业生态系统教育部重点实验室, 兰州, 甘肃 730070, 中国 6.甘肃农业大学草业学院, 草业生态系统教育部重点实验室, 兰州, 甘肃 730070, 中国
推荐引用方式 GB/T 7714	花蕊,周睿,王婷,等. 基于无人机遥感的高寒草原沙化模型及等级划分[J]. 中国沙漠,2019,39(1):26-33.
APA	花蕊,周睿,王婷,许铭,唐庄生,&花立民.(2019).基于无人机遥感的高寒草原沙化模型及等级划分.中国沙漠,39(1),26-33.
MLA	花蕊,et al."基于无人机遥感的高寒草原沙化模型及等级划分".中国沙漠 39.1(2019):26-33.