Acta Agrestia Sinica ›› 2019, Vol. 27 ›› Issue (6): 1766-1773.DOI: 10.11733/j.issn.1007-0435.2019.06.037

Previous Articles     Next Articles

Multi-scales Analysis of the Impacting Factors of Grassland NDVI Based on Remote Sensing and Unmanned Aerial Vehicle Data

PAN Ying1, ZHANG Yan-jie2, WU jun-xi1,3, ZHANG Xian-zhou1,3, YU Cheng-qun1,3   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
    2. College of Agronomy and Biological Sciences, Dali University, Dali, Yunnan Province 671003, China;
    3. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2019-06-05 Revised:2019-09-23 Online:2019-12-15 Published:2019-12-31

基于遥感和无人机数据的草地NDVI影响因子多尺度分析

潘影1, 张燕杰2, 武俊喜1,3, 张宪洲1,3, 余成群1,3   

  1. 1. 中国科学院地理科学与资源研究所, 北京 100101;
    2. 大理大学农学与生物科学学院, 大理 671003;
    3. 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室, 北京 100101
  • 通讯作者: 武俊喜,E-mail:wujx@igsnrr.ac.cn
  • 作者简介:潘影(1983-),男,安徽滁州人,副研究员,主要从事草地生态研究,E-mail:panying@igsnrr.ac.cn
  • 基金资助:
    国家重点研发计划(2016YFC0502004);国家自然科学面上基金(31570460)共同资助

Abstract: In order to clarify the impacting factors of grassland vegetation on different scales,this paper research on the impacting factors of NDVI of grassland ecosystem at both village and plot scales in a Tibetan village,based on multiple data sources including Landsat remote sensing images and unmanned aerial vehicle multispectral images. The results showed that,altitude,slope,aspect and relief degree of land surface all have impacts on vegetation index,with a nonlinear model with an interpreting level of 37.20%. The variance analysis showed heterogeneity in vegetation indices also existed within one same land use type. The heterogeneity within the same land use type was subdivided by unmanned aerial vehicle multispectral images,we found that the indiscernible the punctiform or linear ground objects (e.g. stone packs,channels and field roads) impact on the vegetation indices largely. The buffer analysis showed that,the negative impacts of non-concreted channels and field road on the around vegetation ranged from 1 to 3 meters,while the negative impacts of concreted channels and field road were more than 4 meters. Our research showed,the convenience of achieving high resolution images by unmanned aerial vehicle would boost the deepen the study of how human activities and landscape fragmentation impacting on the vegetation and ecosystem functions,at the fine scale.

Key words: Tibet, Unmanned aerial vehicle, Remote sensing, Vegetation index, Multiple scales

摘要: 为探索不同尺度草地植被的影响因子,本研究基于Landsat遥感影像和无人机多光谱影像等,在村落和地块2个尺度分析西藏草地归一化植被指数(Normalized Difference Vegetation Index,NDVI)的影响因子。结果表明:村落尺度的海拔、坡度、坡向、地表起伏度皆对NDVI有显著的非线性影响,解释比例为37.20%;方差分析表明,地形等因子相近的同类土地利用内部NDVI差异仍较大;运用无人机影像细分同种土地利用类型内部异质性,发现遥感影像中无法辨别的点状、线状地物(石堆、水渠、田间路等)对草地NDVI有一定影响;缓冲区分析表明,非硬化水渠和道路对NDVI的负面影响在1~3 m,硬化水渠和路面对草地的负面影响超过4 m。无人机获取高分辨率多光谱影像的便捷性可以推进更小尺度下人类活动强度以及景观破碎化对植被和生态系统功能影响研究的深入。

关键词: 西藏, 无人机, 遥感, 植被指数, 多尺度

CLC Number: