Geo-spatial analysis on Socioeconomic mapping between Demographic data and Economic growth: A case study of Mumbai
Abstract
Background: The Industrial Revolution and globalization spurred global economic growth, creating financial hubs like New York and London. Indias post-independence focus on industrialization and 1991 liberalization fueled rapid growth in IT, manufacturing, and finance, with Mumbai emerging as a trade and investment hub. Maharashtra's robust industrial base and Mumbais strategic coastal location, migration, and key institutions like the RBI and BSE cemented its status as Indias financial capital.
Aim: [3][4]To understand and evaluate GIS Mapping of Mumbai concerning economic growth and sustainability.
Objectives: To identify the financial zones in Mumbai using GIS Mapping, to analyze the literature and case studies in Mumbai using GIS, and to develop Maps for demographic data and economic growth of Mumbai.
Research question: RQ 1) What are the demographic characteristics of Mumbai? RQ 2) Why is Mumbai considered the financial capital of India in terms of economic growth?
Methods and results: With the use of ArcGIS Pro and census data (2011) in shape files and table data, we developed a suite of symbology maps to visually represent and analyze data patterns and growth trends.
Conclusion: Through ten literature reviews, the identified research gaps in Mumbai provided valuable insights into the city's financial growth. I utilized GIS tools to create maps that integrate demographic, GDP, and population data. These GIS maps reveal patterns that impact the planning and implementation of economic strategies in Mumbai. This research provides essential insights into spatial planning and financial management within the city, emphasizing how Mumbai's economic growth plays a crucial role in India's overall economic progress, effectively illustrated through the GIS visuals.
Limitations: This study focuses on demographic and economic spatial data due to limitations in data availability and time constraints. Future research on Mumbai could expand to include sustainable indicators such as environmental factors, technological advancements, and governance practices.
Keywords: GIS, geospatial data, mapping, spatial patterns, sustainability, socio-economy, demography, Mumbai, growth
References
- 1) Khatri, S., Kokane, P., Kumar, V., & Pawar, S. (2022). Prediction of waterlogged zones under heavy rainfall conditions using machine learning and GIS tools: A case study of Mumbai. GeoJournal, 87(4), 1–15.
- 2) Vinayak, B., Lee, H. S., & Gedem, S. (2021). Prediction of land use and land cover changes in Mumbai City, India using remote sensing data and a multilayer perceptron neural network-based Markov chain model. Sustainability, 13(2), 471.
- 3) Raskar-Phule, R., & Choudhury, D. (2015). Vulnerability mapping for disaster assessment using ArcGIS tools and techniques for Mumbai City, India. International Journal of Earth Sciences and Engineering, 8(4), 1695–1700.
- 4) Kumar, A., Gupta, I., Brandt, J., Kumar, R., Dikshit, A. K., & Patil, R. S. (2016). Air quality mapping using GIS and economic evaluation of health impact for Mumbai City, India. Journal of the Air & Waste Management Association, 66(5), 470–481.
- 5) Mann, R., & Gupta, A. (2023). Mapping flood vulnerability using an analytical hierarchy process (AHP) in the metropolis of Mumbai. Environmental Monitoring and Assessment, 195, 1534.
- 6) Chinnasamy, P., & Parikh, A. (2021). Remote sensing-based assessment of coastal regulation zones in India: A case study of Mumbai, India. Environment, Development and Sustainability, 23, 7931–7950.
- 7) Bodhankar, S., Gupta, K., Kumar, P., et al. (2022). GIS-based multi-objective urban land allocation approach for optimal allocation of urban land uses. Journal of the Indian Society of Remote Sensing, 50, 763–774.
- 8) Bherwani, H., Kumar, S., Kumar, N., Singh, A., & Kumar, R. (2021). Geospatial analysis to understand the linkage between urban sprawl and temperature of a region: Micro- and meso-scale study of Mumbai City. In Sustainable Climate Action and Water Management, Advances in Geographical and Environmental Sciences, 1–15.
- 9) Sansare, D. A., & Mhaske, S. Y. (2020). Land use change mapping and its impact on storm water runoff using remote sensing and GIS: A case study of Mumbai, India. IOP Conference Series: Earth and Environmental Science, 573(1), 012001.
- 10) Ramakrishna, B., & Ramesh, S. (2023). Contentions of affordability in the habitat planning of a new town: A case of Navi Mumbai, India. CIDADES, Comunidades e Territórios, 47.
- 11) Sathyakumar, V., Ramsankaran, R. A. A. J., & Bardhan, R. (2018). Linking remotely sensed urban green space distribution patterns and socio-economic status: A multi-scale probabilistic analysis in Mumbai, India. GIScience & Remote Sensing, 56, 1–20.
- 12) Gupta, J. (2022). Statistical assessment of spatial autocorrelation on air quality in Bengaluru, India. In International Conference on Intelligent Vision and Computing, 254–265. Springer Nature.
- 13) Gupta, J., & Kumar, R. (2001). Urban growth modelling based on CA–Markov approach in Bengaluru, India. Assessment, 91(21), 21.
- 14) Gupta, J., & Kumar, R. (2022). Evaluating the sustainable indicators of cities of India: ESG framework review.
- 15) Sao, A., & Gupta, J. (2023). Sustainability indicators and ten smart cities review. In IEEE International Conference on Contemporary Computing and Communications (InC4), 1–6.
- 16) Kunnath, A. R. E., & Gupta, J. (2024). A review of biophilic design at Kuttikattoor School for children. E3S Web of Conferences, 546, 01002.
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