Authors:
Jaskaran Singh Puri
and
Pedro Cabral
Affiliation:
NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312 Lisbon, Portugal
Keyword(s):
Suitability Analysis, Spatial Analysis, ArcGIS, GIS, Remote Sensing.
Abstract:
The metropolitan cities are facing a huge skewness of service distribution that is given in different parts of the same city. Given the rapid increase in immigration, the quality-of-life factors are often left out while performing housing searches. This paper explores the ideal sub-regions in Delhi, India, for living based on different lifestyle profiles. Using suitability analysis, it is possible to personalize a geographical area for housing. Five such factors, namely, rental budget, commute time, green landscape, pollution, and food accessibility were considered. Four different user profiles (18-65) and their importance to each of the factors were simulated. The range of each variable was standardized using transformations. Data was obtained from data-hubs like Kaggle, OSM, and GEE. The analysis was supported by ArcGIS Pro to get district-level features and suitability modelling. The commute variable is a derived variable from the cost surface raster and AQI values from the weathe
r stations were used. Four different suitability maps are generated using multi-criteria evaluation. This automated approach can be useful for customers and agents to find or consult housing for immigrants by making it personalized and providing insights to better explain consumer behaviour based on spatial attributes, hence making spatially intelligent tools.
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