Spatial identification and dynamic analysis of land use functions reveals distinct zones of multiple functions in eastern China

Land use function (LUF) is a valuable concept that allows for more integrated assessments of land system change. Identifying the changes and relationships of multiple LUFs is pertinent to land use planning and management. Selection and quantification of LUF indicators are critical for LUFs assessment. However, past studies have mostly assessed LUFs using socioeconomic data, which are not suitable for spatial variable quantification. In this study, we proposed a new LUFs classification system based on spatial planning goals, and we applied the system to assess 12 LUFs across 63 counties in Jiangsu Province of eastern China based on multi-source data using geospatial modeling tools combined with statistical analysis of socioeconomic data. We also analyzed the change in LUFs between 2000 and 2015, as well as the interactions among multiple functions. Finally, we identified distinct function zones based on the LUFs assessment in 2000 and 2015 using k-means clustering. The result showed that 12 LUFs displayed significant changes and interactions between 2000 and 2015, which can be explained by differing topography and social-ecological characteristics among counties. Additionally, we found four distinct LUF zones that are spatially agglomerated in similar landscapes and characterize specific LUF relationships in each cluster. In the future, local LUFs and their changes over time should be taken into consideration for land use planning and management, which provide a reference for policy-makers to make decisions that better match local development realities. (C) 2018 Elsevier B.V. All rights reserved.