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Smart city article details

Title	A Big Data Compatible Naive Measure For Estimating The Landscape Dynamics Using Open Geospatial Datasets
ID_Doc	451
Authors	Ghosh S.; Dey S.
Year	2020
Published	Proceedings of the 2020 International Conference on Smart Innovations in Design, Environment, Management, Planning and Computing, ICSIDEMPC 2020
DOI	http://dx.doi.org/10.1109/ICSIDEMPC49020.2020.9299576
Abstract	The process of urbanisation has been reported to be a driver of global climatic change. Rapid urbanisation is leading to a drastic change in the land use and land cover (LULC) pattern of any urban area. Urban LULC dynamics can be understood through the use of multi-Temporal geospatial datasets. The existence of multi-sensor and multi-Temporal remote sensing datasets enable the understanding of LULC dynamics. In this paper, we take Aurangabad as a pilot project for study. Aurangabad is a city located in the Marathwada region of the Maharashtra state in India, and is faced with the juxtaposition of the growing industry and the cultural heritage. The city has has been included in the list of 100 smart cities to be developed in India, by the Indian government. This paper proposes a new metric and area based method for the measurement of urban dynamics, and identification of hotspots. The superiority of the metric with respect to the Shannon's Entropy is also illustrated. The approach demostrated in this paper is extendable to the measurement of LULC dynamics and hotspot identification in a Big Data environment as well. © 2020 IEEE.
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