TROPICAL GEOGRAPHY ›› 2019, Vol. 39 ›› Issue (4): 538-545.doi: 10.13284/j.cnki.rddl.003156

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Rapid Diagnosis of Ancient Heritiera littoralis Community Health Using UAV Remote Sensing

Sun Zhongyu1, Huang Yuhui2, Yang Long1, Wang Chongyang1, Sun Hongbin3, Wang Zuolin 3, Zhang Weiqiang2 and Gan Xianhua2   

  1. (1. Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, China; 2. Guangdong Provincial Key Laboratory of Forest Culture, Protection and Utilization, Guangdong Academy of Forestry, Guangzhou 510520, China; 3. Shenzhen Wild Animal Rescue Center, Shenzhen 518040, China)
  • Online:2019-07-10 Published:2019-07-10

Abstract:

We evaluated the health of ancient Heritiera littoralis communities in landward terrestrial, seaward terrestrial, and halophytic marsh habitats using UAV remote sensing combined with ground surveys. Remote sensing indicators such as canopy height, forest window characteristics, photosynthetic effective radiation cross section ratio, Normalized Difference Vegetation Index (NDVI), Nitrogen Reflection Index (NRI), Yellow band Index (YI), and Forest Health Index (FHI) were used to indicate the health of ancient H. littoralis communities. The sky-ground combined survey indicated that: 1) Ancient H. littoralis tree holes were larger and more common in the halophytic marsh habitat due to their age. Moreover, the halophytic marsh habitat had the lowest biodiversity, with the highest biodiversity found in the seaward terrestrial habitat. 2) The lowest canopy height was found in the halophytic marsh habitat, with few large canopy gaps and the lowest shape complexity and photosynthetic effective radiation cross section ratio. The above indexes displayed little difference between the landward and seaward terrestrial habitats. NDVI, NRI, YI, and FHI values all tended to be lower in halophytic marshes than in landward and seaward terrestrial habitats, with no significant difference between the landward and seaward terrestrial habitats. 3) The UAV remote sensing survey results exhibited good correlation with the ground survey results, objectively reflecting the health of ancient H. littoralis communities in different habitats. After further improvements for specific communities, the evaluation system based on UAV remote sensing could be a rapid, non-destructive, and quantitative method for diagnosing ancient tree health.

Key words: UAV remote sensing, quantitative assessment, rapid diagnosis, community health, vegetation index