Modeling urban expension in Bangkok Metropolitan Region using demographic-economic data | |
| Author | Chudech Losiri |
| Call Number | AIT Diss. no.RS-17-03 |
| Subject(s) | Urban ecology--Thailand--Bangkok Demography--Economic aspects--Thailand--Bangkok |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Series Statement | Dissertation;no. RS-17-03 |
| Abstract | Urban growth and expansion are the important phenomena which many countries play attentions to monitor and try to understand such situations . Because, they have effects not only the development planning on political and economic but also the livelihoods of people in each country. Nowadays, the population who live in urban areas have increased dramatically. Those people demand the land for responding the basic of their everyday life such as living and working. Therefore, it will result in the expansion of urban areas globally. Thailand has also challenged with urban expansion situation which results in the spatial planning and environmental problem. Bangkok Metropolis (BM) has expanded rapidly in both size and population since the 1960s. Moreover, a flow of the globalization also brings the BM to confront with the new development. As a consequence of those developments, the BM has faced with the speedy expansion of the built - up area into its vicinity called Bangkok Metropolitan Region (BMR) . To understand the urban expansion phenomena and LULC in BMR , this study tries to address the complex phenomenon of the urban circumstance by studying the pattern of the urban expansion, integrating physical, demographic, and economic data into the LULC model to calibrate and simulate the future land use change. Urban expansion of the BMR has different patterns which affect land development and policy planning. Increasing in the number of the population puts forces to expand the built - up areas. The time series of remote sensing data from Landsat 5 and 8 images between 1988 and 2014 were extracted and used to detect the pattern of the expansion by using a set of spatial metrics. Their analysis can give more understanding about the urban spatial processes which related to urban patterns. The results from the study illustrated that the aggregation of the BMR had decreased. On the other hand, the urban areas of the adjacent provinces were an expansion from each city center where it did not settle next to Bangkok Metropolis. Moreover, the spatial landscape metric could illustrate that the urban expansion pattern of the BMR was compacted and have a complex form which the urban areas were expanded apart from each province via the main transportation network such as main road and other prospective mass transportation. For the dispersion pattern, the result from the analysis confirmed that the BMR had decreased dispersion. However, all of the urban areas of each province, presently, has expanded itself beyond the political boundary The population and economic of the BMR are the main importa nt information which can be used to illustrate the effect of the urban expansion. The results of the analysis can be found that the BMR had been increased in a number of population dramatically. Those increasing came from the rising number of population from the vicinity provinces of the BM. In contrast, the population of the BM was decreased because people migrated to those vicinities. The BMR was increased in population. Most of the increasing rate came from Pathum Thani and Nonthaburi provinces. Moreover , the density of BMR was increased continuously as a result from the vicinity provinces. Nowadays, the BMR h as situated in the high urbanization level already. In terms of economics, the income of the BMR came from the non - agricultural sectors. The manufac turing and wholesale and retail trade played as important sectors to rise the economic income of the region. For the economic base analysis, the other community, social and personal service activities of the BMR was a specialized sector when compared with the whole country. However, the manufacturing sector had declined in the specialization dramatically. For the driving forces analysis, it could comprehend that the demographic and economic data showed a few association between the conversions to urban LULC change. Urban expansion is considered as one of the most important problems in several developing countries. Bangkok Metropolitan Region (BMR) is the urbanized and agglomerated area of Bangkok Metropolis (BM) and its vicinity, which confronts the expans ion problem from the center of the city. Landsat images of 1988, 1993, 1998, 2003, 2008, and 2011 were used to detect the land use and land cover (LULC) changes. The demographic and economic data together with corresponding maps were used to determine the driving factors for land conversions. This study applied Cellular Automata - Markov Chain (CA - MC) and Multi - Layer Perceptron - Markov Chain (MLP - MC) to model LULC and urban expansions. The performance of the CA - MC and MLP - MC yielded more than 90% overall accuracy to predict the LULC, especially the MLP - MC method. Further, the annual population and economic growth rates were considered to produce the land demand for the LULC in 2014 and 2035 using the statistical extrapolation and system dynamics (SD). It was evident that the simulated map in 2014 resulting from the SD yielded the highest accuracy. Therefore, this study applied the SD method to generate the land demand for simulating LULC in 2035. The outcome showed that urban occupied the land around a half of the BMR |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Dissertation;no. RS-17-03 |
| Type | Dissertation |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Nagai, Masahiko |
| Examination Committee(s) | Shrestha, Rajendra Prasad ;Sarawut Ninsawat |
| Scholarship Donor(s) | Government of Japan |
| Degree | Thesis (Ph.D) - Asian Institute of Technology, 2017 |