Integrated geospatial database design for land use pattern analysis and its impact on local governance: A case study of Manesar Urban Complex, Gurugram, India
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Abstract
The absence of an integrated geospatial database hinders effective decision-making among various stakeholders in national projects and programs. The study aimed to create an integrated geospatial database for the Manesar tehsil, District Gurugram, Haryana. Another objective was to create a land use map to analyze the temporal change in land use patterns and its socioeconomic impact along the surrounding areas. The first stage of the study involved creating an integrated database after interviewing different stakeholders. In the second stage, the satellite imagery was georeferenced using Ground Control Points, and the land use patterns were digitized using Landsat imagery for 1987, 2011, 2014, and 2022. The study suggested that the construction area has grown up to 6% while cultivation has dropped significantly from 76% in 1987 to 50% in 2022. Likewise, the industrial area has grown up to 2% and natural vegetation dropped in coverage from 11% to 4%. The area witnessed a population growth rate of 3.2% per year and a decadal growth rate of 39.7%. Less than 50% of the land in the tehsil is used for agricultural purposes. It estimates that 4% of the tehsil's entire surface was covered by natural vegetation in 2019, down from 11% in 1987. The study recommends the creation of an integrated geospatial database that will help reduce duplication and speed up decision-making in government. This will pave the way for improving e-governance in local bodies. The framework created for developing the database system is universally applicable and can be used appropriately by other states, regions, and the entire country.
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Keywords
E-governance, Geographical information system, Geospatial database, Land use, Remote sensing, Temporal analysis, Urban planning
References
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Dalla Valle, L. & Kenett, K. (2018). Social media big data integration: a new approach based on calibration. Expert Systems with Applications, 111, 76–90.
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Hazra, Sukla & Khan, Atanu & Saradar Jhantu. (2013). Asset Mapping of Gram Panchayat and Web based Interface for Development. Indian Cartographer, 23, 123-127
Hor, A.-H., Jadidi, A. & Sohn, G. Bim(2016). GIS Integrated Geospatial Information Model Using Semantic Web and RDF Graphs. ISPRS Annual Photogrammetry Remote Sensing Spatial Information Science, 3, 73–79, doi:10.5194/isprs-annals-III-4-73-2016
Hor, A.-H., Sohn, G., Claudio, P., Jadidi, M. & Afnan, A. (2018). A Semantic Graph Database for Bim-Gis Integrated Information Model for an Intelligent Urban Mobility Web Application. ISPRS Annual Photogrammetry Remote Sensing Spatial Information Science, 4, 89–96, doi:10.5194/isprs-annals-IV-4-89-2018
Hu, F., Xu, M.; Yang, J., Liang, Y., Cui, K., Little, M.M., Lynnes, C.S., Duffy, D.Q. & Yang, C. (2018). Evaluating the Open-Source Data Containers for Handling Big Geospatial Raster Data. ISPRS International Journal Geo Information, 7, 144, doi:10.3390/ijgi7040144.
Irizarry, J., Karan, E.P. & Jalaei, F. (2013). Integrating BIM and GIS to improve the visual monitoring of construction. Supply chain management, Automation, Construction, 31, 241–254, doi:10.1016/j.autcon.2012.12.005
Jain, M., Dawa, D., Mehta, R., Dimri, A. P. & Pandit, M. K. (2016). Monitoring land use change and its drivers in Delhi, India using multi-temporal satellite data. Modeling Earth Systems and Environment, 2(1). doi:10.1007/s40808-016-0075-0
Jain, R.K., Kamal Jain & Rehan Ali, S. (2017). Remote Sensing Enabled Urban Growth Analysis for Gurgaon from 1995 To 2015. Advances in Computational Sciences and Technology, ISSN 0973-6107, 10(6), 1745-1757.
Jyothi. S, Saritha, K. & Manjula. K. R. (2013). Classification of Deforestation Factors using Data Mining Techniques. International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR), 3 (4), 159-172.
Kaushik, Saurabh & Kandpal, Kishor & Pandey, Arvind. (2017). Application of GIS in Panchayati raj System in India: A Case Study of Naugaon Village, Uttarakhand, India (An Initiative of G- governance). International Journal of Advanced Remote Sensing and GIS, 6. 2367-2376. doi:10.23953/cloud.ijarsg.301
Khovrichev, M., Elkhovskaya, L. Fonin, V. & Balakhontceva, M. (2019). Intelligent approach for heterogeneous data integration: information processes analysis engine in clinical remote monitoring systems. Procedia Computer Science, 156, 134–141, doi:10.1016/j.procs.2019.08.188
Kumar M. & Duffy C. (2010). An Object-Oriented Shared Data Model for GIS and Distributed Hydrologic Models. International Journal of Geographical Information Science, 24 (7), 1061-79, 2010. doi:10.1080/ 13658810903289460
Li, Daqian. (2022). Data Integration Method Design of Decision Spatial Information System. Security and Communication Networks, 1-12. Doi:10.1155/2022/8114454
Lienhardt, P. (1994). N-Dimensional Generalized Combinatorial Maps and Cellular Quasi-Manifolds. International Journal of Computational Geometry and Applications, 4, 275–324, doi:10.1142/S0218195994000173
Le, H.H., Gabriel, P., Gietzel, J. & Schaeben, H. (2013). An object-relational spatio-temporal geoscience data model. Computer Geoscience, 57, 104–115.
Manjula K. R. & Jyothi, S. (2012). Mining Multilevel Spatiotemporal Association Rules for Analyzing the Factors of Deforestation. First International Conference on Intelligent Infrastructure and 47th Annual National Convention, CSI, 256 – 260.
Manoj Panwar, Ar. & Er. Pardeep Sindhu. (2016). Critical Analysis of Land Use Planning along Kundli Manesar Palwal Expressway. International Journal of Latest Trends in Engineering and Technology (IJLTET), 6(3), ISSN:2278-621X
Mekala, A. (2020). An ontology approach to data integration using mapping method. International Journal for Modern Trends in Science and Technology, 6(12), 28–32, doi: 10.46501/IJMTST061206
M. Masmoudi, S. B. A. B. Lamine, H. B. Zghal, B. Archimede & M. H. Karray. (2021). Knowledge hypergraph-based approach for data integration and querying: application to Earth Observation. Future Generation Computer Systems, 115(1),720–740, doi:10.1016/j.future.2020.09.029
M. Wiedau, L. Von Wedel, H. Temmen * R. N. Welke. (2019). ENPRO data integration: extending DEXPI towards the asset lifecycle. Chemie Ingenieur Technik, 91(3), 240–255, doi:10.1002/cite.201800112
M. Lenzerini. (2002). Data integration: A theoretical perspective. 21st ACM SIGMOD-SIGACT-SIGART. Symposium on Principles of Database Systems (PODS), 233–246, doi:10.1145/543613.543644
Michael, F. Worboys, Hilary M. Hearnshaw, and David J. Maguire. (1990). Object-Oriented Data modeling for Spatial databases. International Journal of Geographical Information Systems, 4, 369–383, doi:10.1080/0269 3799008941553
Mohan, Manju & Kandya, Anurag & Battiprolu, Arunachalam. (2011). Urban Heat Island Effect over National Capital Region of India: A Study using the Temperature Trends. Journal of Environmental Protection, 2, 465-472, doi:10.4236/jep.2011.24054
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How to Cite
Integrated geospatial database design for land use pattern analysis and its impact on local governance: A case study of Manesar Urban Complex, Gurugram, India. (2023). Journal of Applied and Natural Science, 15(4), 1541-1556. https://doi.org/10.31018/jans.v15i4.5084
