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草业学报 ›› 2017, Vol. 26 ›› Issue (3): 1-12.DOI: 10.11686/cyxb2016165

• 研究论文 • 上一篇    下一篇

基于UAV技术和MODIS遥感数据的高寒草地盖度动态变化监测研究—以黄河源东部地区为例

葛静, 孟宝平, 杨淑霞, 高金龙, 冯琦胜, 梁天刚*, 黄晓东, 高新华, 李文龙, 张仁平, 王云龙   

  1. 草地农业生态系统国家重点实验室,兰州大学草地农业科技学院,甘肃 兰州 730020
  • 收稿日期:2016-04-19 修回日期:2016-06-28 出版日期:2017-03-20 发布日期:2017-03-20
  • 作者简介:葛静(1992-),女,甘肃平凉人,在读硕士。E-mail:gej12@lzu.edu.cn*通信作者Corresponding author. E-mail: tgliang@lzu.edu.cn
  • 基金资助:
    国家自然科学基金项目(31372367,31228021,41401472),农业部公益性行业(农业)科研专项项目(201203006),中国气象局气候变化专项项目(CCSF201603)和长江学者和创新团队发展计划(IRT13019)资助

Dynamic monitoring of alpine grassland coverage based on UAV technology and MODIS remote sensing data-A case study in the headwaters of the Yellow River

GE Jing, MENG Bao-Ping, YANG Shu-Xia, GAO Jin-Long, FENG Qi-Sheng, LIANG Tian-Gang*, HUANG Xiao-Dong, GAO Xin-Hua, LI Wen-Long, ZHANG Ren-Ping, WANG Yun-Long   

  1. State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China
  • Received:2016-04-19 Revised:2016-06-28 Online:2017-03-20 Published:2017-03-20

摘要: 利用黄河源东部地区野外实测样地数据和MODIS卫星遥感资料,结合农业多光谱相机(agricultural digital camera,ADC)、普通数码相机(Canon)、无人机(unmanned aerial vehicle,UAV)等设备获取的高寒草地盖度数据,构建了基于MODIS NDVI、EVI的草地盖度反演模型,比较分析了不同草地盖度监测方法的精度,确立了黄河源区草地盖度遥感监测的最优反演模型,并分析了研究区近16年草地植被盖度的动态变化。结果表明,1) MODIS NDVI与基于UAV相片计算的草地盖度间的相关性优于MODIS EVI,而MODIS EVI与ADC和Canon照片计算的草地盖度之间的相关性则优于MODIS NDVI;2) 就Canon和ADC方法构建的草地盖度反演模型而言,前者精度远高于后者,普通数码相机方法更适宜于高寒草地植被盖度的估算;3) 对比分析两种植被指数与Canon相机、ADC和大疆(DJI)无人机航拍(航高30和100 m两种方法)相片计算的草地盖度之间的关系表明,MODIS NDVI对航高30 m UAV航拍相片计算的盖度数据的响应最敏感,基于UAV航高30 m的相片和NDVI构建的草地盖度反演模型最优;4) 黄河源东部地区2000-2015年间草地盖度稳定不变的区域达71.46%,多分布在东南部;呈增加趋势的区域占研究区草地面积的22.01%,由西向东、由北向南增加幅度呈减少趋势;盖度减少区域零星分布在黄河源北部和南部的部分地区,仅占研究区草地面积的6.53%。

Abstract: In this study, MODIS NDVI and EVI data from 41 field measurements in the eastern headwaters of the Yellow River were used. In combination with the alpine grassland coverage data obtained by an Agricultural Digital Camera (ADC), ordinary digital camera (i.e., Canon 70D) and Unmanned Aerial Vehicles (UAV) images, grassland coverage inversion models were constructed using MODIS vegetation indices. The optimal remote sensing model was used to analyze the grassland coverage dynamics from 2000 to 2015. The results indicated that: 1) the correlation between MODIS NDVI and grassland coverage calculated by UAV images was better than that of MODIS EVI and UAV, and the correlation between MODIS EVI and grassland coverage calculated by ADC and Canon images was higher than that of MODIS NDVI and ADC and the Canon 70D. 2) Compared to ADC, the accuracy of the models established using the Canon 70D was much higher, indicating that ordinary digital cameras may be more reliable for calculating the alpine grassland vegetation coverage. 3) Compared with the grassland coverage calculated with the Canon, images from the ADC and UAV under 30 m and 100 m flight height with the two MODIS vegetation indices respectively, the MODIS NDVI was more sensitive to grassland vegetation coverage retrieved by UAV under 30 m flight height; the optimal model was y=65.4132ln(NDVI)+109.1763 (R2=0.7575, RMSEP=8.4780). 4) Vegetation coverage during the study period in the southeast area of the study area was stable at 71.5%. Increases in vegetation cover occurred primarily in the western and northern regions while decreases in vegetation were mostly found in northern and southern regions of the study area.