干旱区研究 ›› 2021, Vol. 38 ›› Issue (2): 526-535.doi: 10.13866/j.azr.2021.02.24

• 生态与环境 • 上一篇    下一篇

科尔沁沙丘草甸相间地区土地利用与覆被识别

曹文梅1(),刘廷玺1(),王喜喜2,王冠丽1,李东方1,童新1   

  1. 1.内蒙古农业大学水利与土木建筑工程学院,内蒙古自治区水资源保护与利用重点实验室,内蒙古 呼和浩特 010018
    2.美国欧道明大学,诺福克 23529
  • 收稿日期:2020-08-11 修回日期:2020-11-11 出版日期:2021-03-15 发布日期:2021-04-25
  • 通讯作者: 刘廷玺
  • 作者简介:曹文梅(1992-),女,博士,研究方向为干旱区群落生态学. E-mail:cwm_0303@126.com
  • 基金资助:
    国家自然科学基金重点国际(地区)合作研究项目和地区项目(51620105003);国家自然科学基金重点国际(地区)合作研究项目和地区项目(51769020);内蒙古自然科学基金重大项目、教育部创新团队发展计划项目(IRT_17R60);科技部重点领域科技创新团队(2015RA4013);内蒙古自治区草原英才产业创新创业人才团队资助

Land use and land cover classifications of Horqin Sandy Land dune-meadow areas

CAO Wenmei1(),LIU Tingxi1(),WANG Xixi2,WANG Guanli1,LI Dongfang1,TONG Xing1   

  1. 1. Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Inner Mongolia Water Resource Protection and Utilization Key Laboratory, Hohhot 010018, Inner Mongolia, China
    2. Civil and Environmental Engineering, Old Dominion University, Norfolk 23529, Virginia, USA
  • Received:2020-08-11 Revised:2020-11-11 Online:2021-03-15 Published:2021-04-25
  • Contact: Tingxi LIU

摘要:

为了实现基于单独光学遥感数据对科尔沁沙丘草甸相间地区土地利用与覆被(LULC)类型的识别,选用2018年64景Sentinel-2影像,结合影像分割技术,利用植被物候信息和生境特征,建立了基于群落水平的LULC决策树识别规则,总体分类精度为0.91,Kappa系数为0.89。分类结果显示:研究区旱地分布面积最大,占33.79%,灌木群落次之,占25.03%,高多样性半灌木群落和乔木林相近,分别为14.54%和10%,低多样性半灌木群落、草甸地和流动沙地分别占5%左右,剩余类型的总占比小于5%。该方法不仅可以准确反映研究区覆被类型的空间分布情况,还能给出不同覆被类型的生长发育状况,可为该区域物质循环研究提供基础数据,同时为该区域历史LULC识别提供阈值参考。

关键词: 遥感, 土地利用与覆被, 多尺度分割, 决策树, 分类, 哨兵2号卫星, 多时相, 科尔沁沙地

Abstract:

In this study, we determine land use/land cover (LULC) types using only optical remote sensing data in a dune-meadow area of Horqin Sandy Land in northeast China. We used 64 Sentinel-2 remote sensing images from 2018. An LULC decision tree recognition rule was established by combining image segmentation technology, vegetation phenology information, and habitat characteristics. The overall classification accuracy was 0.91, and the Kappa coefficient was 0.89. The classification results show that most of the study region was dryland area, accounting for 33.79%, followed by shrub communities at 25.03%. High-diversity semi-shrub communities and arbor forests accounted for 14.54% and 10%, respectively, while low-diversity semi-shrub communities, meadowlands, and mobile sand lands account for about 5% each. The total proportion of other LULC types was less than 5%. The results show that this interpretation method better reflects the spatial distribution of the LULC while also providing growth and development data for different cover types. These data can be used to study material cycles and provide threshold references for historical LULC identification of Horqin Sandy Land.

Key words: remote sensing, land use/land cover, multi-resolution segmenation, decision-trees, classification, Sentinel 2-A/B, time series, Horqin Sandy Land