Urban Expansion and Its Impact on the Land Use Pattern in Xishuangbanna since the Reform and Opening up of China

Abstract

Abstract:Since the Chinese government carried out the reform and opening up policy, Xishuangbanna Dai Autonomous Prefecture has experienced rapid urbanization and dramatic land use change. This research aims at analyzing urban expansion in Xishuangbanna and its impact on the land use pattern using combined methods, including radar graph, the gradient-direction method and landscape metrics. Seven land use maps from 1976 to 2015 were generated and analyzed, respectively. The results showed that urban and rubber expanded rapidly, while forest decreased during the last 40 years. The city proper, the county town of Menghai and the county town of Mengla showed the most significant and fastest urban expansion rates. In response to rapid urban expansion, land use types outside urban areas changed dramatically. In Jinghong and Mengla, urban areas were usually surrounded by paddy, shrub, rubber and forest in 1976, while most areas were dominated by rubber by 2015. With the development of Xishuangbanna, landscape diversity increased along urban-rural gradients, but decreased in some key urban areas. Urban expansion slightly reduced the connectivity of forest and increased agglomeration of rubber at the same time. Based on the analyses above, we moved forward to discuss the consequences of urban expansion, rubber plantations and land fragmentation.

Effects of Urban Expansion on Forest Loss and Fragmentation in Six Megaregions, China

“…This result is consistent with previous studies that found urban expansion led to forest fragmentation [18,29,30]. However, at the megaregion scale, the increase in mean patch size of forested land indicated the decrease in the level of forest fragmentation in most megaregions (Table 5).…”

“…The second type of studies focuses on the spatiotemporal pattern of urban expansion along an urban-rural gradient and how such patterns affect the changes (both gain and loss) in forested land, e.g., [10,[26][27][28]. The third type of studies explicitly addresses the spatial patterns of forested land and its change associated with urbanization, [17,18,29,30]. In addition to change in the area of forested land, these studies focus on the spatial distribution of forests, with particular emphasis on forest fragmentation caused by urban expansion.…”

Urban Sprawl and Adverse Impacts on Agricultural Land: A Case Study on Hyderabad, India

“…Alqurashi [11] used object-based image analysis (OBIA) segmentation and classification for mapping LULC in five cities in Saudi Arabia and, depending on the size of patches of LULC, created two levels of image segmentation and classification by adjusting the thresholds in the rules applied. Similarly Cao [12] used an OBIA-based decision tree process to map 13 land-use types, with visual modification employed to improve the classification. Lui et al [13] used various kinds of automatic classification methods to efficiently map urban areas, and also employed the visual interpretation method combined with professional knowledge to obtain urban boundaries.…”

Analysis of the Spatial Structure of Urban Antropogenic Areas

“…The data potential in this type of research has been used repeatedly (Dietzel et al 2005a, Herold et al 2002, Deng et al 2009, Triantakonstantis and Stathakis 2015. The size, shape, location, and relations between particular categories of land cover may be subject to research (Kistowski 2003, Cao et al 2017. Such analyses make it possible, among other things, to determine the correlation between different areas, to understand the prevailing trends, and to measure the pace of changes, which are taking place.…”

“…Detailed analyses of changes in land use and land cover are enabled and significantly accelerated by the remote sensing techniques (Fan and Myint 2014) and GIS -Geographic Information Systems (Pawlak 1999, López et al 2001, Foody 2007. Integration of GIS with correctly maintained databases on land cover makes it possible to characterize space in terms of structures that occur in it (Sudhira 2004) and, what is important, it enables quantitative determination of the intensity of phenomena as well as monitoring of spatial-temporal dynamics of the changes (Cao et al 2017), and modelling of future transformations (Jat et al 2008). Due to the ability to facilitate performing such versatile and comprehensive spatial analyses (Johanson 1990, Longley et al 2008, Gajos and Sierka 2011, Urbański 2012, there is a dynamic growth in the use of GIS tools also in urban transformation research (Cheng andMasser 2003, Jat et al 2008), including studies of areas at risk of anthropofenic pressure (Salata et al 2016, Cegielska et al 2017a, Cegielska et al 2017b).…”