# Analysis and Applications of GlobeLand30: A Review
## 4 Application Analysis
### Status and Change Analysis  
The status and change of land cover at global, regional or local scales has been studied using GlobeLand30 and with spatial statistical analysis approaches. At the global scale, [PERSON] et al. [63] used GlobeLand30's water layer data to analyze the distribution of global open water and change from 2000 to 2010. Two indicators, namely, water body percentage and the coefficient of spatial variation, were calculated to reflect the characteristics of spatial distribution pattern and dynamic change for global open water resources. Results show that the total area of land surface water is roughly 3.68 million km\({}^{2}\) (2010), which occupies 2.73% of the Earth's land surface. Similarly, [PERSON] et al. [52] calculated global artificial surface areas at country and continental scales, and analyzed its change between 2000 and 2010. The result shows that the total area of the global built-up areas is 1.1875 million km\({}^{2}\) in 2010, covering 0.88% of the total area of the global land surface; the area of global built-up areas increased to 57,400 km\({}^{2}\) with the variation rate of 5.08% from 2000 to 2010. China and the United States are the top two countries with the largest increased built-up areas, which account for roughly 50% of that of the global total. In addition, 50.26% of the total increased built-up areas comes from arable land.  
Areas, landscape indexes, and conversion matrix were used to analyze the status and change of land covers at the country/regional scale. [PERSON] [64] calculated the Shannon index from GlobeLand30 to reveal the diversity of land cover types in administrative regions of Ukraine.  
[PERSON] et al. [65] derived the conversion matrix, change rate, and landscape indices from GlobeLand30 to analyze land cover change, especially the loss of cultivated land for the Bohai Rim, China between 2000 and 2010. Results indicate that cultivated land obviously reduced and was mainly converted to artificial surfaces, grasslands, water, and forests in this region, and the fragmentation of cultivated land increased. [PERSON] et al. [32] calculated and compared the areas of forest, shrub, grassland, wetland, cropland, artificial surface, bare land and ice/snow in GlobeLand30 and a new NepalCover-2010. The landscape indices were used to demonstrate the spatial pattern of land cover types.  
At the local scale, landscape metrics were derived from GlobeLand30 to quantify the landscape structure and to reveal the spatial details of land covers. Six landscape metrics are calculated for 25 cities in Yangtze River Delta, China from the artificial surface class of GlobeLand30, including total urban area (CA), number of urban patches (NP), largest patch index (LPI), mean perimeter-area ratio (PARA MN), mean Euclidean nearest neighbor distance (ENN MN), and traffic coupling factor (CF) with a spatial pattern analysis program FRAGSTATS 4.2 [66; 67]. These metrics were used to analyze the relationship between urban forms and air quality. [PERSON], [PERSON] et al. [68] derived seven landscapes from GlobeLand30 in Nanjing, China for each of the nine PM2.5 stations with radii of 0.5, 1.0, 2.0, 3.0, 4.0, 5.0, and 6.0 km and applied FRAGSTATS to compute the metrics, such as green cover, forest cover, grassland cover, and edge length. These metrics were then used to quantify the spatiotemporal change of PM2.5 concentration and its empirical relationship with vegetation and landscape structure.