Urban growth pattern modelling and future projection using time series satellite data: a case study for Nagpur, India | |
| Author | Kumar, Pedhabudhi Kranthi |
| Call Number | AIT Thesis no.RS-17-24 |
| Subject(s) | Time-series analysis--India--Nagpur Remote-sensing images--India--Nagpur |
| Note | A thesis report submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. RS-17-24 |
| Abstract | Cities are experiencing rapid urban expansions which deteriorates the quality of life of city dwellers and ecological sustainability of the region. The concentration of people in urban areas, especially in developing countries, calls for the use of monitoring systems like remote sensing. Such systems along with spatial analysis techniques like digital image processing and geographic information system (GIS) can be used for the monitoring and planning purposes as these enable the reporting of overall sprawl at a detailed level. Quantifying urban growth patterns and development processes of the past trends can help better understandings on the dynamics of built up area and guide sustainable urban development planning of the future urban growth. The combined approach using remote sensing, spatial metrics and urban modeling may prove a productive new direction for the improved understanding, representation and modeling of the urban spatiotemporal patterns. Although the integrated approach is powerful, the forecasting of urban form remains problematic and could benefit from further research on spatial metrics and urban model. In this work Nagpur, India a rapidly growing city is considered as a case study, and urban expansion has been studied over a period of 15 years to predict future urban expansion in the year 2025 and 2030.For spatio-temporal analysis of Nagpur city, four Landsat images of year 2000,2005, 2010 and 2015 were used. After processing the imagery, land use land cover images are developed in ERDAS Imagine. The starting point of any management programmed will be based on the modeling of the future growth and in this paper, Cellular Automata Markov(CA-Markov)model is used for projections.CA-Markov model was calibrated using the multitemporal datasets for the entire study region and the urban growth was projected for 2025 and 2030. Further modelling based on these changes would help in understandings on future changes. It is done with the combination of multi criteria decision making (MCDM) to produce urban suitability expansion by considering urban affecting factors. The results show that built up of Nagpur city has been increased from 80.75 km2in 2000 to 119.06 km2in 2015 and finally to 131.34 km2in 2030. The percentage increase in built up area from 2000 to 2015is 32.17% and that from 2015to 2030 is 13.27%. An accuracy of more than 80% was obtained in all stages. By this study we come to know that existing urban is the one of the most affecting factor for urban expansion. The output images and analysis are also presented for understanding the extent of urban growth. Spatial metrics were used specifically to assess the impact of urban development in four periods (2000,2005,2010 and 2015), and generally to analyze the spatial and temporal dynamics of urban form. Landscape pattern indicators provide simple measures of landscape structure that can be easily calculated with readily available data and software. Landscape metrics is applied to the predicted land cover and land use (LULC)for detecting cities pattern. The results illustrate the utility of modeling in explaining the amount and spatial change of urban form. The result suggested that aggregation of urban patch is going on increasing, after 2010 urban patches were elongating and whereas isolation process may increase at the time 2025 and 2030 |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. RS-17-24 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Miyazaki, Hiroyuki |
| Examination Committee(s) | Tripathi, Nitin Kumar;Kim, Sohee Minsun |
| Scholarship Donor(s) | AIT Fellowship |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2017 |