An approach to scenario based multi-scale modeling of urban growth and future implications of urbanization on quality of life | |
| Author | Bhatti, Saad Saleem |
| Call Number | AIT Diss. no.RS-15-02 |
| Subject(s) | Cities and towns--Growth Urbanization--Social aspects--Pakistan--Lahore Quality of life--Pakistan--Lahore |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of PhilosophyinRemote Sensing & Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Series Statement | Dissertation ; no. RS-15-02 |
| Abstract | This study explores the potential of geospatial techniques for evaluation andanalyses of urbanization, land use/land cover (LULC) and urban quality of life (QOL) in city district Lahore in the Punjab province of Pakistan.The differences in growth characteristics of urban and peri-urban areas were examined through LULC maps of 1999 and 2011. The LULC of urban areas of Lahore was mapped by applying spectral indices to Landsat operational land imager data of 2013, whereas the QOL was assessed in five urban towns of Lahore through questionnaire survey.A multilayer perceptron neural network was employed for modeling the built-up growthat city district, urban and peri-urban scales, and it was found that the accuracies of the sub-models developed for urban (77%) and peri-urban (81%) subsets were better compared to those produced at thecity district scale (71%). The prediction maps of 2013 were generated at three spatial scales considering four different growth scenarios for land transitions. The model output was tested by comparing all predicted maps with the actual LULC map of 2013; the results indicated that the subset approach was better for modeling urban sprawl in a metropolitan region. The prediction maps of 2021 and 2035 were produced and the results showed that the rate of land change to built-up was higher than the persistent growth rate.Moreover, anew approach, built-up area extraction method (BAEM), was developed for mapping the built-up areas. Through integration of temperature data, normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI), the BAEM was able to improve the overall accuracy of built-up area extraction by 11.84% compared to the customary normalized difference built-up index approach. The BAEM, NDVI and MNDWI were further analyzed to generate the LULC map of urban areas of Lahore. Furthermore, data related to six QOL domains, physical health, psychological, social relationships, environment (natural and built), economic condition and development, and access to facilities and services, were collected. The weights/relative importance of each QOL domain was determined through experts’ survey; the “access to facilities and services” domain was ranked the highest. The urban QOL, population density and LULC were mapped to examine their spatial distribution.The highest population density was observed towards the north of the study area, in old parts of the city, whereas the highest values of QOL were observed in a few areas of Gulberg, Data Gunj Baksh and Samanabad towns. The lowest QOL values were observed in the old city areas. The analyses revealed that the QOL exhibited an inverse relationship with the built-up density and population density, which was quite significant in the Shalimar town indicating the deficiency of access to the required QOL facilities in this town compared to the others.The LULC prediction maps of 2021 and 2035 were used to assess the impacts of future urban growth on the QOL, and it was found that the implementation of appropriate land conservation scenarios can result in significant control in the growth of built-up areas in Ravi and Data Gunj Baksh towns. This study would not only support the mapping and modeling of LULC and QOL in the metropolitan regions, but also assist in devising appropriate land management and QOL improvement strategies and policies in the city district Lahore |
| Year | 2015 |
| Corresponding Series Added Entry | Asian Institute of Technology. Dissertation ; no. RS-15-02 |
| 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) | Tripathi, Nitin Kumar |
| Examination Committee(s) | Nagai, Masahiko ;Vilas Nitivattananon ;Taravudh Tipdecho |
| Scholarship Donor(s) | Government of Japan |
| Degree | Thesis (Ph. D.) - Asian Institute of Technology, 2015 |