Figures (5)  Tables (4)
    • Figure 1. 

      (a) Map of China indicating the location of Hainan. (b) Map of Hainan indicating the assessment areas for UGS drivers. (c) Satellite map of Haikou (www.google.com/maps) displaying the 190 urban functional units (UFUs, red boundaries) surveyed within the Haikou study region (purple line).

    • Figure 2. 

      Landuse of Haikou in (a) 2016 and (b) 2020 and (c) landuse change in Haikou City.

    • Figure 3. 

      Landuse and UGS in primary UFUs in Haikou in 2016 and 2020. Among them, IB: Industry and business districts, PA: Public affairs service districts, RL: Recreation and leisure districts, RD: Residential districts, TR: Transportation.

    • Figure 4. 

      Proportion of green space (area covered in vegetation) in secondary UFUs in 2016 and 2020 in Haikou city. * indicate significant differences between 2016 and 2020 based on Wilcoxon tests.

    • Figure 5. 

      Proportion of landuse in secondary UFUs in 2016 and 2020 in Haikou city. * indicate significant differences between 2016 and 2020 based on Wilcoxon tests.

    • Primary UFUsSecondary UFUsPolygons included
      Public affairs service districtsGovernmental Agencies18
      Colleges/universities7
      Primary/Middle Schools18
      Research institutes4
      Hospitals12
      Industry and business districtsIndustry12
      Hotels11
      Industrial offices9
      Supermarkets3
      Residential districtsLow-density residential areas
      (lower than six stories)
      5
      High-density residential areas (higher than six stories)43
      Recreation and leisure districtsParks7
      Museums5
      TransportationMain/secondary roads28
      Bus parking5
      Undeveloped landWetland3
      Total190

      Table 1. 

      The number of primary and secondary urban functional units (UFUs) sampled in Haikou.

    • ClassesDefinition
      Built-up landLand under construction inside the city area or its surroundings; including buildings and construction sites.
      Forest landForested areas, native or planted; composed of tall trees and a dense canopy.
      WaterAny water body or water resource in the area, including the sea, rivers, streams, dams, and ponds.
      GrasslandNatural or planted grassy areas dominated by graminoids and forbs.
      Bare landAny area of exposed soil. Found on sites under construction, underdeveloped roads, sandpits, or sand sources.

      Table 2. 

      Land use land cover classes and definitions.

    • Landuse20162020
      Producer accuracyUser accuracyProducer accuracyUser accuracy
      Water100%100%100%100%
      Bare land100%60%100%50%
      Forest area75%90%69%90%
      Grassland86%60%67%40%
      Built-up land76%100%74%100%
      Overall accuracy85.71%81.25%

      Table 3. 

      Summary of mapping accuracy assessment.

    • Land use and land coverPrimary UFUsConstruction age
      (β coefficient, n = 190)
      Housing price
      (β coefficient, n = 190)
      Population density
      (β coefficient, n = 190)
      R2
      Water areaIndustry and business−0.1420.127−0.0980.052
      Public service−0.000−0.1560.3020.041
      Recreation and leisure0.019−0.172−0.1360.058
      Residential−0.612***0.018−0.1880.430***
      Transportation0.095−0.1070.0990.033
      Bare land areaIndustry and business0.106−0.2530.384*0.223
      Public service0.0270.635***0.2030.656***
      Recreation and leisure0.089−0.038−0.0700.022
      Residential0.370*−0.0730.1620.172*
      Transportation−0.023−0.0250.2390.056
      Forest areaIndustry and business−0.0870.487−0.1460.271*
      Public service0.0420.252−0.2520.027
      Recreation and leisure0.187−0.176−0.1560.138
      Residential0.544***−0.0910.2160.373***
      Transportation−0.534**0.034−0.0750.319*
      Grassland areaIndustry and business−0.2410.195−0.1390.130
      Public service−0.045−0.772***−0.215**0.921***
      Recreation and leisure0.138−0.4420.0920.228
      Residential−0.878***−0.074−0.0970.776***
      Transportation0.1180.0230.0150.014
      Built-up areaIndustry and business−0.022−0.398*0.0230.161
      Public service0.0990.139−0.1540.016
      Recreation and leisure−0.1110.1810.1260.088
      Residential−0.0090.314*−0.0600.102
      Transportation0.205−0.145−0.1160.074
      Significance codes: * p < 0.05, ** p < 0.01, *** p < 0.001.

      Table 4. 

      Multivariate regression analysis results of Landuse area with construction age, housing prices, and population density in primary UFUs of Haikou City in 2020.