| Author: | Hasan, Sarah |
| Title: | Long-term land use land cover change and its impact on ecosystem services : a comprehensive study in Guangdong, Hong Kong, and Macau (GHKM) region |
| Advisors: | Shi, Wen-zong John (LSGI) Zhu, Xiaolin (LSGI) |
| Degree: | Ph.D. |
| Year: | 2022 |
| Subject: | Land use -- China, Southeast Land cover -- China, Southeast Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Land Surveying and Geo-Informatics |
| Pages: | xiv, 157 pages : color illustrations |
| Language: | English |
| Abstract: | Land use and land cover (LULC) changes is a major global problem cause by intense human activities and socioeconomic development. These are especially more pronounced in fast developing regions such as Guangdong, Hong Kong, and Macau (GHKM), in South China. GHKM has undergone rapid economic development and urbanization over the past three decades (1986–2017) significantly influenced the LULC changes and ecosystem service value (ESV) and expected to continue in future. The alteration in ESV leads to the requirement of a significant tailored analysis of ecosystem services regarding incisive and relevant planning to ensure sustainability at regional level. To understand and assess the outcomes of these changes in the long term, the availability of reliable and adequate information about LULC change over the years is becoming increasingly necessary. It is essential to monitor, manage, and utilize ecosystems accurately to halt the ongoing loss of ecosystem services and maintain or balance the supply of different ecosystem services in the landscape. To date, studies in their quantitative analysis and the spatiotemporal variability at the regional level (in GHKM) are very limited. Therefore, this study aims to investigates the changes in LULC of GHKM based on multi-year Landsat (TM, ETM+ and OLI) and nighttime light (NTL) data, simulate future scenario using Land Change modeler (LCM), and their impact on ecosystem services value (ESV). 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. The demographic activities are studied by calculating the light index, using nighttime light data. Several socioeconomic factors, derived from statistical yearbooks, are used to determine the impact on the LULC changes 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 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. Using Land Change Modeler (LCM) predict the future scenario of the years 2024 and 2031 based on the past trend 2005—2017. 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 the rate of 4.72% during 2005—2017 and will continue to rise from 10.31% in 2017 to 16.30% in 2031 at a rate of 3.27%. This increase in urban area will encroach further into farmland and fishponds. However, forest cover will continue to increase from 45.02% in 2017 to 46.88% in 2031. This implies a decrease in the mean Euclidian Nearest Neighbor Distance (ENN) of forest patches (from 217.57m to 206.46m) and urban clusters (from 285.55m to 245.06m) during 2017—2031, indicating an accelerated landscape transformation, if the current patterns of change continue over the next decade. 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. Thus, the speed of development suggests that opportunistic development has taken place, which requires a pressing need for smart LULC planning and to improve land use policies and regulations for more sustainable urban development, to guarantee ecosystem service sustainability, and protection of natural resources. |
| Rights: | All rights reserved |
| Access: | open access |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/11750