A Study On Big Data and Geo-Informatics: Shaping The Future of Spatial Analysis in Indian Context

References

[1] Aithal, B. H., & Ramachandra, T. V. (2016). Visualization of urban growth pattern in Chennai using geoinformatics and spatial metrics. Journal of the Indian Society of Remote Sensing, 44, 617-633.

[2] Augasta, M. G. (2017). Geo-Spatial Big Data Analysis: An Overview. International Journal of Trend in Research and Development, 4(3), 2394-9333.

[3] Barik, R. K., Dubey, H., Misra, C., Borthakur, D., Constant, N., Sasane, S. A., ... & Mankodiya, K. (2018). Fog assisted cloud computing in era of big data and internet-of-things: systems, architectures, and applications. Cloud computing for optimization: foundations, applications, and challenges, 367-394.

[4] Bhadra, T., Mukhopadhyay, A., & Hazra, S. (2017). Identification of river discontinuity using geo-informatics to improve freshwater flow and ecosystem services in Indian Sundarban Delta. Environment and earth observation: Case studies in India, 137-152.

[5] Chen, Y. Q. (2014). Geomatics Technologies for Hazards Mitigation. 14th World Conference on Earthquake Engineering. Retrieved from https://www.iitk.ac.in/nicee/wcee/article/14_11-0188.PDF

[6] Das, S. K., Pant, M., & Bebortta, S. (2019). Geospatial Data Analytics: A Machine Learning Perspective. SSRN Electronic Journal.

[7] Digital India. (2015). Government of India. Retrieved from https://www.digitalindia.gov.in/

[8] Eshrati, D., Mansourian, A., & Taleai, M. (2015). Multi-hazard risk assessment using GIS in urban areas: A case study of Tehran, Iran. Journal of Disaster Risk Science, 6(4), 296-306.

[9] Esri India. (2015). GIS for Smart Cities. ArcIndia News, 9(1). Retrieved from https://www.esri.in/content/dam/distributor-share/esri-in/pdf/vol9-issue1.pdf

[10] FG Assis, L. F., Ferreira, K. R., Vinhas, L., Maurano, L., Almeida, C., Carvalho, A., ... & Camargo, C. (2019). TerraBrasilis: a spatial data analytics infrastructure for large-scale thematic mapping. ISPRS International Journal of Geo-Information, 8(11), 513.

[11] Gupta, S., Karnatak, H., & Raju, P. L. N. (2016). Geo-informatics in India: Major milestones and present scenario. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 41, 111-121.

[12] ICARDA. (2019). Utilizing ‘Big Data’ and ICT innovations. Retrieved from https://www.icarda.org/impact/impact-stories/utilizing-big-data-and-ict-innovations

[13] India Law Journal. (2013). Big Data: A Challenge to Data Protection? Retrieved from https://www.indialawjournal.org/big_data_a_challenge_to_data_protection.php

[14] Joshi, P. K., & Priyanka, N. (2011). Geo-Informatics for Land Use and Biodiversity Studies. In Land Use, Climate Change and Biodiversity Modeling: Perspectives and Applications (pp. 52-77). IGI Global.

[15] Keesstra, S., Mol, G., de Leeuw, J., Okx, J., Molenaar, C., & de Cleen, M. (2018). Soil-related sustainable development goals: Four concepts to make land degradation neutrality and restoration work. Land, 7(4), 133.

[16] Korada, L., & Ahmed, S. (2019). Unlocking Urban Futures: The Role Of Big Data Analytics And AI In Urban Planning - A Systematic Literature Review And Bibliometric Insight. ResearchGate.

[17] Kumar, A., & Singh, M. (2018). A Survey on Flood Prediction and Classification using Machine Learning. Academia.edu. Retrieved from https://www.academia.edu/109031065/A_Survey_on_Flood_Predication_and_Classification_using_Machine_learning

[18] Kumar, P., Kumar, A., Panwar, S., Dash, S., Sinha, K., Chaudhary, V. K., & Ray, M. (2018). Role of big data in agriculture: A statistical prospective. ICAR-Indian Agricultural Statistics Research Institute. Retrieved from https://krishi.icar.gov.in/jspui/bitstream/123456789/20273/3/Bigdatapaper.pdf

[19] Li, Z., Tang, W., Huang, Q., Shook, E., & Guan, Q. (2020). Introduction to Big Data Computing for Geospatial Applications. ISPRS International Journal of Geo-Information, 9(8), 487.

[20] Mittal, H., Kumar, A., & Singh, S. K. (2019). Earthquake Genesis and Earthquake Early Warning Systems: Challenges and Opportunities. Springer. Retrieved from https://link.springer.com/article/10.1007/s10712-022-09710-7

[21] National Centre of Geo-Informatics (NCoG). (2019). Ministry of Electronics and Information Technology, Government of India. Retrieved from https://www.meity.gov.in/ncog

[22] National Geospatial Policy. (2016). Department of Science & Technology, Government of India. Retrieved from https://nsdiindia.gov.in/

[23] National Institute of Disaster Management. (2019). Climate Resilient Disaster Risk Management. Retrieved from https://nidm.gov.in/PDF/pubs/ACT-BestPracticesCompendium.pdf

[24] Paul, P., Aithal, P. S., Bhimali, A., & Kalishankar, T. (2019). Environmental informatics vis-à-vis big data analytics: The geo-spatial & sustainable solutions. International Journal of Applied Engineering and Management Letters (IJAEML), 4(2), 31-40.

[25] Pourghasemi, H. R., & Rossi, M. (2019). Landslide susceptibility modeling in a landslide prone area in Mazandaran Province, north of Iran: A comparison between GLM, GAM, MARS, and M-AHP methods. The Science of the Total Environment, 661, 620-632.

[26] Saini, V., & Tiwari, R. K. (2019). A systematic review of urban sprawl studies in India: a geospatial data perspective. Arabian Journal of Geosciences, 13, 1-21.

[27] Shah, S., Modi, P., & Shah, H. (2019). Big Data Analysis in Urban Planning. International Journal of Engineering Research & Technology, 8(10). Retrieved from https://www.ijert.org/big-data-analysis-in-urban-planning

[28] Sheregar, A. (2019). Data Analytics for the Agriculture Sector in India. International Journal of Computer Science and Mobile Computing, 8(11), 71-75. Retrieved from https://www.academia.edu/41214045/Data_Analytics_for_the_Agriculture_Sector_in_India_

[29] Singh, N. (2017). Digital India as an Innovation System. SSRN Electronic Journal. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3800604

[30] Thakuriah, P., Tilahun, N., & Zellner, M. (2016). Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery. In Seeing Cities Through Big Data (pp. 11-45). Springer. Retrieved from https://link.springer.com/chapter/10.1007/978-3-319-40902-3_2

[31] Thottolil, R., & Kumar, L. (2019). Cloud computing for big geospatial data analysis with Google Earth Engine: Urban research applications. ResearchGate. Retrieved from https://www.researchgate.net

[32] Upadhyay, R. K., Pandey, S., & Tripathi, G. (2019). Role of Geo‐Informatics in Natural Resource Management During Disasters: A Case Study of Gujarat Floods, 2017. Sustainable Development Practices Using Geoinformatics, 253-282.

@article{1702502,
      author = {Dr. Balakullayappa Madar},
      title = {A Study On Big Data and Geo-Informatics: Shaping The Future of Spatial Analysis in Indian Context},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {4},
      number = {4},
      pages = {181-193},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702502.pdf},
      abstract = {This conceptual study explores the transformative intersection of Big Data and Geo-Informatics within the Indian context, focusing on their theoretical underpinnings and potential impact on spatial analysis, wherein the proliferation of Big Data characterized by its high velocity, volume, and variety converges with Geo-Informatics, defined by its ability to collect, process, and analyze spatially-referenced data, to offer novel solutions for challenges in urban planning, environmental sustainability, resource management, and disaster resilience, while simultaneously addressing critical barriers such as data standardization, infrastructure inadequacies, privacy concerns, and the need for scalable analytical frameworks, thereby fostering innovative practices that integrate real-time analytics, machine learning, and geospatial modeling to develop dynamic, data-driven applications tailored to India's unique socio-economic and ecological landscapes, which are marked by rapid urbanization, population density, resource constraints, and vulnerability to natural disasters, with this integration demonstrating the potential to refine disaster early warning systems, optimize urban land use, enhance rural resource allocation, and facilitate sustainable development strategies, yet the challenges posed by fragmented governance frameworks, inadequate skill development, and the digital divide demand a cohesive, interdisciplinary policy approach that includes the establishment of national data standards, investment in resilient infrastructure, and capacity-building initiatives to bridge the gap between technical possibilities and practical implementation, ultimately contributing to the global discourse on harnessing data science and spatial technologies for public good, and this theoretical framework asserts the importance of fostering collaboration among academic institutions, industry stakeholders, and government agencies to drive innovation in spatial data applications and address India's complex socio-economic challenges in ways that are scalable, equitable, and environmentally sustainable, emphasizing the need for a robust ethical foundation and forward-looking regulatory mechanisms to ensure that technological advancements in Big Data and Geo-Informatics not only enhance analytical precision and decision-making capacity but also safeguard individual privacy and promote inclusive growth, with future research directions identified to include examining the scalability of Geo-Informatics applications in high-density urban centers, exploring the integration of indigenous knowledge with advanced spatial technologies, and analyzing the long-term impacts of spatially-driven policy interventions on India's economic and ecological resilience, thereby solidifying the role of Big Data and Geo-Informatics as central to the future of spatial sciences and sustainable development in India.},
      keywords = {Big Data, Geo-Informatics, Spatial Analysis, Urban Planning, Disaster Resilience, Sustainable Development},
      month = {October},
  }