Arid Zone Research ›› 2021, Vol. 38 ›› Issue (2): 526-535.doi: 10.13866/j.azr.2021.02.24

• Ecology and Environment • Previous Articles     Next Articles

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 E-mail:cwm_0303@126.com;txliu1966@163.com

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