Land change models (LCMs) describe, project, and explain changes in and the dynamics of land use and land-cover. LCMs are a means of understanding ways that humans are changing the Earth's surface in the past, present, in forecasting land change into the future.

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Physical and Socioeconomic Driving Forces of Land-Use and Land-Cover Changes: A Case Study of Wuhan City, China

¹School of Environment, Resources and International Trade, Hubei University of Economics, Wuhan 430205, China
²Center of Hubei Cooperative Innovation for Emissions Trading System, Wuhan 430205, China
³School of Public Administration, China University of Geosciences, Wuhan 430074, China
⁴School of Economics and Management, China University of Geosciences, Wuhan 430074, China

Received 3 December 2015; Revised 17 February 2016; Accepted 14 March 2016

Academic Editor: Elmetwally Elabbasy

Bootstrap installation procedure for laminate countertops. Copyright © 2016 Xiangmei Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract

To investigate precise nexus between land-use and land-cover changes (LUCC) and driving factors for rational urban management, we used remotely sensed images to map land use and land cover (LULC) from 1990 to 2010 for four time periods using Wuhan city, China, as a case study. Partial least squares (PLS) method was applied to analyze the relationships between LUCC and the driving factors, mainly focusing on three types of LULC, that is, arable land, built-up area, and water area. The results were as follows: during the past two decades, the land-use pattern in Wuhan city showed dramatic change. Arable land is made up of the largest part of the total area. The increased built-up land came mainly from the conversion of arable land for the purpose of economic development. Based on the Variable Importance in Projection (VIP), the joint effects of socioeconomic and physical factors on LUCC were dominant, though annual temperature, especially annual precipitation, proved to be less significant to LUCC. Population, tertiary industry proportion, and gross output value of agriculture were the most significant factors for three major types of LULC. This study could help us better understand the driving mechanism of urban LUCC and important implications for urban management.

1. Introduction

Land-use and land-cover changes (LUCC) increasingly have been regarded as a primary source of global environmental change such as emission of greenhouse gases, global climate change, loss of biodiversity, and loss of soil resources [1–3]. However, the causes of LUCC are complex and change over time and from region to region [4]. In the early 1990s, keeping in view the diverse reasons and causes of land-use change emphasizes the importance of interdisciplinary research to address the issue of land-use change with a particular focus on the human dimensions [5]. LUCC have been led by a set of socioeconomic driving forces and conditioned by different natural endowments [6] that determine the trajectories of landscape development [7]. Understanding the driving mechanisms of LUCC caused by a variety of driving forces is one of the major goals of global change research in recent decades [8–10].

To understand the human and biophysical processes of LUCC, many researchers focus on the various forces driving LUCC, including socioeconomic [11], demographic [12], political [13], technological [14], biophysical [15], and industrial structure [16], to provide effective support for developing urban land planning and management regulations. To comprehensively analyze the driving factor’s effects and mitigate the negative impacts of land-use change, Shu et al. (2014) [17] investigated the effects of various factors, including natural ecoenvironment factors, land control policies, accessibility factors, and neighborhood factors, on urban land expansion during various periods in different regions. Chen et al. (2014) [18] selected industrial structure, GDP, transportation, and policy as the driving factors to study the impacts on urban land expansion and sustainable urban development in Shenzhen and Dongguan. In addition, an integration of biophysical and human factors was applied in the explanation of LUCC dynamics of Mediterranean Europe due to its particular climatic and physical conditions [15]. Obviously, the outstanding characteristics of the studied cases, such as economy, culture, climate, and policy, often were considered as the important driving forces in the explanation of LUCC dynamics. However, though many researches on land-use change have been conducted, climate factors were seldom available on driving analysis of LUCC.

Various research methods were employed to explore the nexus between LUCC and their driving forces. Multivariate regression was used to model how the major forces drive the physical expansion of urban land cover at the global level [19]. Li et al. (2013) [20] applied binary logistic regression to investigate the effects of the selected driving variables on the probability of urban expansion. Analytic hierarchy process (AHP), as a subjective method, provided rigorous quantitative measures to understand the interactive process of urban growth and factors [21]. System dynamics (SD) was combined with CLUE-S model to reflect the complexity of the land-use system [22], regarded as a macrolevel, “top-down” implementation process. However, few attempts have been made to investigate precise nexus between LUCC and driving factors. Partial least squares (PLS) method, as a major regression technique for multivariate data, may handle highly correlated noise-corrupted data sets by explicitly assuming the dependency between variables and estimating the underlying structures [23]. It could effectively reflect the significant PLS components using the cross validation technique [24]. In the paper, PLS was used to accurately reflect the nexus between LUCC and driving factors, meanwhile determining the significant components of the selected driving factors.

In the paper, our main objectives were to address the processes of land-use dynamics in Wuhan city and its integrated driving forces through combining satellite-based efforts at mapping land use and land cover (LULC) and physical, socioeconomic data. Based on RS images in 1990, 1995, 2000, 2005, and 2010, we analyzed the variant change of each LULC type during 4 periods (1990–1995, 1995–2000, 2000–2005, and 2005–2010). Thirteen variables of physical and socioeconomic factors were selected as the potential driving factors of LUCC. Partial least squares (PLS) method is applied to select the important driving factors and analyze the relationships between LUCC and the factors triggering each land-use change type, mainly focusing on three major types of LUCC, that is, arable land, built-up land, and water area. Finally, we suggested some possible management measures that are crucial for future sustainable utilization and management of its existing land resources, for example, managing urban growth and protecting cultivated land.

2. Study Area

Wuhan city, as a central hinterland megalopolis of China, is situated in the east of Jianghan plain and covers over 8494.41 km² (113°41′–115°05′ E, 29°58′–31°22′ N). Terrain is dominated by flat areas with a surface elevation ranging from 0 to 100 m, and the slope is less than 10°, making up 95.78% of the total. The low hills, which have an elevation between 200 and 400 m and a slope varying from 10 to 25°, constitute 3.89% of its total area, while the mountainous area (elevation 400~800 m; slope >25°) accounts for only 0.33% (Figure 1). The Yangtze River and its largest tributary Han River meet here, which divides Wuhan into three parts, Hankou, Hanyang, and Wuchang, commonly known as “the three towns of Wuhan.’’ The area has the subtropical humid monsoon climate. Its climate feature is obvious, characterized by abundant rainfall, summer heat, and winter cold, with an annual temperature of approximately 15.8–17.5°C and mean annual precipitation of 1150–1450 mm. A huge water network was formed with the Yangtze River as the backbone and supplemented by quantities of lakes or ponds. Therefore, Wuhan city has a reputation of “city of hundred lakes.’’ The water area accounts for 25.6% of the city area.

Acknowledgments

We gratefully acknowledge the generous financial support by the German Academic Exchange Service (DAAD) for the first author to conduct the study. We also express our acknowledgment to the RapidEye Science Archive (RESA) of German Aerospace Center (DLR) for providing RapidEye image and the TUM Graduate School/Faculty Graduate Center Weihenstephan at Technische Universität München for covering local field expenses during data collection. Special thanks also go to the Forestry Research Center of the Ethiopian Institute of Agricultural Research for providing a field car, Mr. Temesgen Yohannes for assisting during data collection, and all the farmers who took part during the survey.