TROPICAL GEOGRAPHY ›› 2019, Vol. 39 ›› Issue (4): 531-537.doi: 10.13284/j.cnki.rddl.003152

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Spatial Pattern and Landforms Effects of Elm (Ulmus pumila) Sparse Forest Based on High Spatial-Resolution Aerial Images from Unmanned Aerial Vehicle (UAV)

Wu Yin 1,2, Han Dong 1, Yao Xueling1, Zhang Jing 2 and Wang Feng1   

  1. (1. Institute of Desertification Studies, Chinese Academy of Forestry, Beijing 100091, China; 2 Beijing Key Laboratory of Resource Environment and Geographic Information System, Capital Normal University, Beijing 100048, China)
  • Online:2019-07-10 Published:2019-07-10


The purpose of this study is to explore the spatial characteristics of quantity, density, and structure of the elm (Ulmus pumila) on different micro-landforms based on the high spatial-resolution Digital Elevation Model (DEM) through Unmanned Aerial Vehicles (UAVs) and detailed ground investigation. The study sites are located at the long-term monitoring plot in Elm Sparse Forest Grassland Ecosystem (ESFOGE-Plot), Otindag sandy land, Inner Mongolia, China. The micro-landforms of ESFOGE-Plot were classified into plain, lowland, sunny slope, shady slope, and ridge by decision tree method considering five factors: slope, aspect, slope of aspect, height, and elevation. The results showed that: 1) the areas covered by plain, lowland, sunny slope, shady slope, and ridge on the ESFOGE-Plot were 52.89%, 17.25%, 12.47%, 10.05%, and 7.35%, respectively. 2) The number of elm trees per hectare on the five corresponding landforms were 28.9, 17.0, 41.2, 141.7, and 65.2, respectively. 3) The Diameter at Breast Height (DBH), canopy diameter, and tree height of elm trees on the sunny slope were 18.9 ± 7.52 cm, 5.19 ± 2.33 m, and 4.89 ± 2.33 m, respectively. 4) The density of elm trees on the shading slope was highest while the average size of elm trees on the sunny slope was largest. The micro-landforms based on comprehensive terrain factors better represent the spatial pattern of elm trees. It is demonstrated that UAVs are an efficient tool to study the spatial pattern of vegetation.

Key words: unmanned aerial vehicle, vegetation pattern, micro-landforms, elm (Ulmus pumila) sparse forest, Otingdag sandy land