Analyses of Traits and Driving Forces on Urban Land Expansion in a Typical Coal-Resource-Based City in a Loess Area

Environ Earth Sci (2016) 75:1191 DOI 10.1007/s12665-016-5926-5 THEMATIC ISSUE Analyses of traits and driving forces on urban land expansion in a typical coal-resource-based city in a loess area 1,2 1,2 1,2 1 Yingui Cao • Zhongke Bai • Wei Zhou • Xiaoran Zhang Received: 28 December 2015 / Accepted: 21 July 2016 / Published online: 18 August 2016 Ó Springer-Verlag Berlin Heidelberg 2016 Abstract The development of coal-resource-based cities is serve as a reference for resource-based cities regarding cyclical and presents different traits affected by different urban land use and sustainable development. socio-economic driving forces in each stage. In this paper, we study urban land expansion in the Pinglu District in Keywords Resource-based cities Á Urban land expansion Á Shuozhou City, Shanxi Province, China, by interpreting Driving forces Á Urbanization Á Development and transition six-phase remote sensing images to reveal the traits and driving forces of urban land expansion during different stages. Overall, the following results were observed. (1) Introduction Urban land expansion was obvious from 1986 to 2013, with an increase of 992.80 ha, mainly due to the occupa- Urban land expansion is an important aspect of global land tion of cultivated land. Urban land expansion mainly use/cover change (Foley et al. 2005) and profoundly occurred along the periphery of the city, which was 1–2 km impacts regional ecological systems (Grimm et al. 2008). from the urban centre. (2) The influence of the coal In developing countries, the urban land area has grown five industry on urban land expansion can be divided into two times faster than in developed countries (Bhagyanagar stages, the establishment stage of the coal industry system et al. 2012). The urbanization rate was 2.14 % greater in and the development stage of coal industry promotion and China than that of the world average. In addition, urban urbanization. (3) The traits of urban land expansion mat- land expansion has become out of control (Fang 2009; ched economic models and traits. The non-agricultural Gibson et al. 2014). China is currently undergoing an population and industrial electricity consumption can unprecedented urbanization process in which massive reflect how economic development can impact urban land amounts of rural land, especially the cultivated land, have expansion. The periodic traits of urban land expansion and been converted to urban land (Forman 2008; Chen et al. the coal industry life cycle have shown a high degree of 2014; Cao 2015; Huang et al. 2015). consistency. Furthermore, the results of this study could Consequently, the land use structure has been changed (Weber and Puissant 2003; Jiang et al. 2013), the agricultural land use intensity has been decreased (Cao et al. 2010a, b;Jiangetal.2013), and the pressure on This article is part of a Topical Collection in Environmental Earth Sciences on ‘‘Environment and Health in China II’’, guest edited by remaining fertile agricultural soils has been increased Tian-Xiang Yue, Cui Chen, Bing Xu and Olaf Kolditz. (Doygun et al. 2008). Urban land expansion corresponds with administrative hierarchy, and cities with higher & Wei Zhou administrative levels (ranked by central government) [email protected] generally expand more rapidly when controlling for 1 School of Land Science and Technology, China University of other economic and demographic drivers of urban Geosciences, Beijing 100083, China expansion (Li et al. 2015). 2 Key Lab of Land Consolidation, Ministry of Land and Developing monitoring technologies advance revealing Resources of the PRC, Beijing 100035, China the traits and processes of urban land expansion, especially 123 1191 Page 2 of 13 Environ Earth Sci (2016) 75:1191 the GIS and RS technologies (Doygun et al. 2008; Hutyra black triangle of the Loess Plateau at the border of Shaanxi, et al. 2011; Haregeweyn et al. 2012; Yan and Huang 2013). Shanxi, and Inner Mongolia (Fig. 1). The Pinglu District is Studies of the driving mechanisms of urban land expansion a typical coal-resource-based urban district surrounded by have mainly focused on socio-economic driving factors three open-cast coal mines and three underground mines in and used qualitative and quantitative methods (Hu and Lo the Pingshuo mining area, as well as many other local 2007; Shu et al. 2014; Huang et al. 2015). underground mines (Fig. 1). This district is a typical eco- The major driving forces for urban land expansion logically fragile area on the Loess Plateau and includes an include the enhanced economic activity due to the port and original landscape of loess mountain hills with serious soil industrialization (Bhagyanagar et al. 2012), the local eco- erosion, a dry surface, and windy weather during the winter nomic development and population growth (Han 2010), and spring. Currently, more than 40 types of mineral and the increasing value of urban land and budgetary resources have been found, including coal, kaolin, graphite, government revenues, and the decreasing value of agri- and limestone. The socioeconomic information in Pinglu cultural land (Lichtenberg and Ding 2009). Overall, it is District is followed in Table 1. important to formulate different policies to guide reasonable urban land expansion (Shu et al. 2014; Li et al. 2014). Coal-based city is one of the important kinds of resource- Data sources and processing based city, and it is the indispensable energy supply base for economic growth in China. There are 76 coal-based cities Data sources distributing in Shanxi Province, Shaanxi Province Nei- menggu Province, etc. in China (Yu 2014). Most coal-based We used six remote sense images in 1986, 1996, 2000, cities have faced a series of social and economic contra- 2004, 2009, and 2013. The parameters of images including dictions and environmental problems, such as the industry date, sensor, wavelength, and spatial resolution are shown economic benefit going down, unemployment rising, and in Table 2. There are three TM images of Landsat 5, two eco-environment damaging (Rivas et al. 2006;Zhao2006; HRG images of SPOT 5 and one Reference 3D image of Cao et al. 2014). There are lots of land use problems in coal- SPOT 6. The SPOT images are from Shibao Satellite based cities such as extensive land use, unreasonable space Imagery Corporation in Beijing, China. The TM images layout of urban land, abuse of cultivated land, and serious are from US Landsat resource sharing platform. land damage (Du et al. 2009;Franksetal.2010). Consequently, their transition is of concern. Firstly, the Data processing government should make different countermeasures accord- ing to the different development directions and tasks in coal- Using geographic maps (scale is 1: 10,000) of the mining based cities, and make different land use policies (Yuan et al. area, we used the ENVI 5.0 Software to rectify the six- 2015). Secondly, urban land structure optimization and phase remote sensing images. During the high-precision intensive urban land use should be persisted, and spatial rectification process, ground control points were selected evolution progress of urban land in different stages should be evenly and quadratic, polynomial, and neighbouring re- analysed (Cao et al. 2010a, b;Yangetal.2015). Thirdly, sampling were used (Zhang et al. 2012; Fan et al. 2012). suitable urban land use and reasonable layout and location Following this process, the rectified data included the UTM should be assessed from the ecological carrying capacity in projection and the WGS-84 ellipsoid. coal-based cities (David et al. 2012;Guetal.2014). Based on the ‘‘Current Land Use Classification’’ (SAC In this study, we considered urban land expansion in the 2007), land use types were classified into cultivated land, Pinglu District of Shuozhou City. We interpreted six-phase woodland, grassland, urban land, rural settlement, and remote sensing images, analysed the changing spatial–tem- transportation land. The texture features of each land use poral traits of urban land during 1986–2013, and revealed type on the images were used to establish the interpretation the driving mechanisms from the economic development of signs (Yu 2014). Next, we used the tool of Neural Network coal. These results can provide a reference for urban land for Classification in ENVI 5.0 Software to supervise and use and sustainable development in resource-based cities. classify the remote sensing images and adopted the stan- dard method employing the overall accuracy and Kappa coefficient to detect the accuracy of the classification Research area (Zheng et al. 2006). The total accuracy and Kappa coeffi- cients of land use classification during each year are fol- The research area is located in the Pinglu District of lowed in Table 3. Next, we sampled thirty points in the Shuozhou City in Shanxi Province, China, near the Ping- research area and compared the land use types between the shuo mining area of the China Coal Group Co. Ltd. in the fields and maps. The accuracy rates reached up to 90 %. 123 Environ Earth Sci (2016) 75:1191 Page 3 of 13 1191 Fig. 1 Location of research area Furthermore, we revised the land use types of the maps 1986, an increase of 36.77 ha each year, and an annual when they were inconsistent within the field. growth rate of 21.41 %. When considering the changes in the urban land area during each stage, the area of urban land obviously increased by 548.55 ha in 1986–2004, Results and analysis representing an increase of nearly 30.47 ha each year and an annual growth rate of 17.74 %. In 2004–2013, the urban Spatial–temporal traits of urban land changes land area slowly increased by 444.25 ha at a rate of nearly 49.36 ha each year and at an annual growth rate of 6.85 %.

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