Abstract

Identifying patterns and drivers of regional land use changes is crucial for supporting land management and planning. Doing so for mountain ecosystems in East Asia, such as the So-yang River Basin in South Korea, has until now been a challenge because of extreme social and ecological complexities. Applying the techniques of geographic information systems (GIS) and statistical modeling via multinomial logistic regression (MNL), we attempted to examine various hypothesized drivers of land use changes, over the period 1980 to 2000. The hypothesized drivers included variables of topography, accessibility, spatial zoning policies and neighboring land use. Before the inferential statistic analyses, we identified the optimal neighborhood extents for each land use type. The two archetypical sub-periods, i.e., 1980–1990 with agricultural expansions and 1990–2000 with reforestation, have similar causal drivers, such as topographic factors, which are related to characteristics of mountainous areas, neighborhood land use, and spatial zoning policies, of land use changes. Since the statistical models robustly capture the mutual effects of biophysical heterogeneity, neighborhood characteristics and spatial zoning regulation on long-term land use changes, they are valuable for developing coupled models of social-ecological systems to simulate land use and dependent ecosystem services, and to support sustainable land management.

Highlights

  • Land use and land cover change (LUCC) is regarded as one of the prime determining factors of global environmental change, with significant impacts on ecosystems, climate and human vulnerability [1,2].Human impacts on ecosystems mainly occur via land-cover conversion, land degradation or land-use intensification [3]

  • We aimed to find land-use change patterns and factors using logistic regression methods to develop statistical models of land-use changes

  • We extracted neighborhood variables as an index of enrichment factors and various environmental data used as independent variables in multinomial logistic models

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Summary

Introduction

Land use and land cover change (LUCC) is regarded as one of the prime determining factors of global environmental change, with significant impacts on ecosystems, climate and human vulnerability [1,2]. Human impacts on ecosystems mainly occur via land-cover conversion, land degradation or land-use intensification [3]. Despite the fact that mountain ecosystems are changing rapidly in response to diverse natural and anthropogenic drivers and are characterized by high social-ecological heterogeneity, so far LUCC studies have not been as focused on mountain regions when compared to other areas for LUCC process [4]. Many LUCC researches for mountain regions focused on the land abandonment in upland areas, though other phenomena are important LUCC processes in mountainous areas [5]. Drivers of land use change are defined as proximate and underlying factors [7]

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