Landscape transformations in rapidly urbanizing Guangdong, Hong Kong, and Macao (GHKM) regions of South China represent the most complex and dynamic processes altering the local ecology and environment. In this study, Land Change Modeler (LCM) is applied to land use land cover (LULC) maps for the years 2005, 2010, and 2017, derived from Landsat images, with the aim of understanding land use land cover change patterns during 2005–2017 and, further, to predict the future scenario of the years 2024 and 2031. Furthermore, the changes in spatial structural patterns are quantified and analyzed using selected landscape morphological metrics. The results show that the urban area has increased at an annual rate of 4.72% during 2005–2017 and will continue to rise from 10.31% (20,228.95 km2) in 2017 to 16.30% (31,994.55 km2) in 2031. This increase in urban area will encroach further into farmland and fishponds. However, forest cover will continue to increase from 45.02% (88,391.98 km2) in 2017 to 46.88% (92,049.62 km2) in 2031. This implies a decrease in the mean Euclidian nearest neighbor distance (ENN_MN) of forest patches (from 217.57 m to 206.46 m) and urban clusters (from 285.55 m to 245.06 m) during 2017–2031, indicating an accelerated landscape transformation if the current patterns of the change continues over the next decade. Thus, knowledge of the current and predicted LULC changes will help policy and decision makers to reconsider and develop new policies for the sustainable development and protection of natural resources.
Land use and land cover changes (LULCC) are prime variables that reflect changes in ecological systems. The Guangdong, Hong Kong, and Macau (GHKM) region located in South China has undergone rapid economic development and urbanization over the past three decades (1986–2017). Therefore, this study investigates the changes in LULC of GHKM based on multi-year Landsat and nighttime light (NTL) data. First, a supervised classification technique, i.e., support vector machine (SVM), is used to classify the Landsat images into seven thematic classes: forest, grassland, water, fishponds, built-up, bareland, and farmland. Second, the demographic activities are studied by calculating the light index, using nighttime light data. Third, several socioeconomic factors, derived from statistical yearbooks, are used to determine the impact on the LULCC in the study area. The post-classification change detection shows that the increase in the urban area, from 0.76% (1488.35 km2) in 1986 to 10.31% (20,643.28 km2) in 2017, caused GHKM to become the largest economic segment in South China. This unprecedented urbanization and industrialization resulted in a substantial reduction in both farmland (from 53.54% (105,123.93 km2) to 33.07% (64,932.19 km2)) and fishponds (from 1.25% (2463.35 km2) to 0.85% (1674.61 km2)) during 1986–2017. The most dominant conversion, however, was of farmland to built-up area. The subsequent urban growth is also reflected in the increasing light index trends revealed by NTL data. Of further interest is that the overall forest cover increased from 33.24% (65,257.55 km2) to 45.02% (88,384.19 km2) during the study period, with a significant proportion of farmland transformed into forest as a result of different afforestation programs. An analysis of the socioeconomic indicators shows that the increase in gross domestic product, total investment in real estate, and total sales of consumer goods, combined with the overall industrialization, have led to (1) urbanization on a large scale, (2) an increased light index, and (3) the reduction of farmland. The speed of development suggests that opportunistic development has taken place, which requires a pressing need to improve land policies and regulations for more sustainable urban development and protection of farmland.
The rapid increase in anthropogenic activities, socioeconomic development, and land use land cover (LULC) changes since the opening of economic reforms (1978), have changed the ecosystem service value (ESV) in Guangdong, Hong Kong, and Macao (GKHM) region located in South China. This leads to the requirement of a significant tailored analysis of ecosystem services regarding incisive and relevant planning to ensure sustainability at regional level. This study focuses on the use of Landsat satellite imagery to quantify the precise impact of LULC changes on the ecosystem services in GHKM over the past three decades . The most renowned established unit value transfer method has been employed to calculate the ESV. The results show that the total ecosystem service value in GHKM has decreased from 680.23 billion CNY in 1986 to 668.45 billion CNY in 2017, mainly due to the decrease in farmland and fishponds. This overall decrease concealed the more dynamic and complex nature of the individual ESV. The most significant decrease took place in the values of water supply (-22.20 billion CNY, -14.72%), waste treatment (-20.77 billion CNY, −14.63%), and food production (-7.96 billion CNY, −33.18%). On the other hand, the value of fertile soil formation and retention (6.28 billion CNY, +7.26%) and recreation and culture (5.09 billion CNY, +12.91%) increased. Furthermore, total ESV and ESV per capita decreased significantly with the continuous increase in total gross domestic product (GDP) and GDP per capita. A substantial negative correlation exists between farmland ESV and GDP indicating human encroachment into a natural and semi natural ecosystems. The results suggest that in the rapidly urbanizing region, the protection of farmland and to control the intrusion of urban areas has marked an important societal demand and a challenge to the local government. This required a pressing need for smart LULC planning and to improve policies and regulation to guarantee ecosystem service sustainability for acceptable life quality in the study area and other fast expanding urban areas in China.
Abstract. Land use land cover (LULC) of Guangdong, Hong Kong, and Macao (GHKM), south china, has undergone significant changes in the last few decades. This study analyze the spatio-temporal LULC changes and urban expansion during 2010–2017 using Landsat TM, ETM+, and OLI. The Landsat images were classified using support vector machine (SVM) into seven classes as forest, grassland, water, fishponds, built-up, bareland, and farmland. Several socioeconomic factors were also obtained to determine their impact on LULC. The result shows that during the studied period, massive economic development and urbanization has increased the built-up area from 8.26% (16,209.61 km2) to 10.31% (20241.77 km2) and substantial reduction in both farmland from 37.64% (73,897.77 km2) to 33.05% (64932.19 km2) and fishponds from 1.25% (2451.12 km2) 0.85% (1674.71 km2). The most dominant conversion were from farmland to built-up and to forest. Furthermore, forest cover increased to 45.02 % (88384.97 km2) in 2017 from 42.38% (83215.59 km2) in 2010 as a result of different afforestation scheme and policies in order to make Greener study area. The analysis of socioeconomic factors shows that increase in gross domestic product (GDP), total investment in fixed assets, and industrialization has led to urbanization growth on a large scale and reduction of farmland. Therefore, there is pressing need for sustainable development and protection of farmlands.
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