AUTHOR=Fu Yanhua , Zhang Yalin 

TITLE=Research on temporal and spatial evolution of land use and landscape pattern in Anshan City based on GEE

JOURNAL=Frontiers in Environmental Science

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2022.988346

DOI=10.3389/fenvs.2022.988346

ISSN=2296-665X

ABSTRACT=Taking the main urban area of Anshan City, where mining areas concentrate as the study area, based on Google Earth Engine (GEE) platform, the study acquired and processed the Landsat TM/OLI surface reflectivity (SR) data and digital elevation (DEM) data in 2008, 2014 and 2020. At the same time, the random forest classification algorithm of the GEE platform was used to classify land use. On this basis, the land use transfer matrix and land use dynamic degree were used to quantify the land use changes in Anshan urban area. In addition, with application of moving window, the landscape pattern index was used to characterize the spatial variation characteristics of landscape pattern in Anshan urban area. The results show that: 1. From 2008 to 2020, the construction land in Anshan urban area continued to decline, the forest land continued to expand, and the construction land was shifted to the forest land and cultivated land. The most dramatic degree of variation in water, with an annual rate of change of 8.1%. Mining land increased before 2014 and remained almost unchanged after 2014, which is in line with the actual situation. 2. During the study period, the landscape fragmentation degree and landscape heterogeneity in the urban area of Anshan kept increasing. In 2008, the high-value areas of landscape fragmentation and heterogeneity were mining areas. Under the influence of urbanization and mining activities, high-value areas expanded to mining areas and urban-rural integration areas related to urban construction and development. 3. The random forest algorithm based on GEE shows a high degree of accuracy for land use classification. The overall classification accuracy in three years exceeds 90% and the kappa coefficient exceeds 0.85. The study results can be used as an essential reference for optimizing the urban ecological environment and provide technical backing for the urbanization process and green space construction of Anshan City.