Mapping Real Estate-induced Urban Expansion in Delhi NCR: A Synergy of Artificial Intelligence and Geospatial Models

Publication type: Journal Article
Publication date: 2025-02-21
Springer Nature
scimago Q1
wos Q1
SJR: 1.391
CiteScore: 11.7
Impact factor: 4.7
ISSN: 25099426, 25099434
Abstract
Urban expansion induced by real estate development is a significant phenomenon in metropolitan cities, especially in developing countries. Real estate development plays an important role in shaping urban landscapes, influencing spatial pattern, and socio-economic dynamics. Delhi National Capital Region (NCR), one of the fastest-growing metropolitan regions of India, provides a compelling case for understanding the drivers of real estate-induced urban expansion. This study aims to analyse the drivers of real estate induced urban expansion in Delhi NCR using Multilayer Perceptron Neural Network (MLP NN) and Geographically Weighted Regression (GWR) model. A comprehensive dataset comprising of physical, economic, demographic and spatial factors from 1990 to 2021 have been used for the analysis. The MLP NN model has been applied to assess the relative importance of drivers of real estate induced urban expansion in Delhi NCR. The results of MLP NN show that real estate expansion in Delhi NCR is primarily influenced by proximity factors, with the highest importance value of 0.21, observed for distance to regional centres (RC), followed by the distance to major centres (MC) at 0.16, and distance to utility services (US) at 0.14. Population density (0.12) and investment (0.08) also emerged as the main drivers. In contrast, physical factors like slope and elevation had the lowest significance values, 0.003 and 0.004, respectively are less important. The GWR model showed spatial heterogeneity in the influence of these drivers across the districts of Delhi NCR. The model exhibited high explanatory power, with an R2 value of 0.97 alongside an Akaike Information Criterion (AIC) of 416.49, which shows robustness of the model. This study highlights the significance of considering spatial heterogeneity in urban planning and policy formulation to address the dynamic nature of real estate-induced urban expansion for sustainable urban development.
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Naikoo M. W. et al. Mapping Real Estate-induced Urban Expansion in Delhi NCR: A Synergy of Artificial Intelligence and Geospatial Models // Earth Systems and Environment. 2025.
GOST all authors (up to 50) Copy
Naikoo M. W., Shahfahad, Talukdar S., Rihan M., Ishtiaq M., Roy S. S., Rahman A. Mapping Real Estate-induced Urban Expansion in Delhi NCR: A Synergy of Artificial Intelligence and Geospatial Models // Earth Systems and Environment. 2025.
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TY - JOUR
DO - 10.1007/s41748-025-00588-0
UR - https://link.springer.com/10.1007/s41748-025-00588-0
TI - Mapping Real Estate-induced Urban Expansion in Delhi NCR: A Synergy of Artificial Intelligence and Geospatial Models
T2 - Earth Systems and Environment
AU - Naikoo, Mohd Waseem
AU - Shahfahad
AU - Talukdar, Swapan
AU - Rihan, Mohd
AU - Ishtiaq, M
AU - Roy, Shouraseni Sen
AU - Rahman, A
PY - 2025
DA - 2025/02/21
PB - Springer Nature
SN - 2509-9426
SN - 2509-9434
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2025_Naikoo,
author = {Mohd Waseem Naikoo and Shahfahad and Swapan Talukdar and Mohd Rihan and M Ishtiaq and Shouraseni Sen Roy and A Rahman},
title = {Mapping Real Estate-induced Urban Expansion in Delhi NCR: A Synergy of Artificial Intelligence and Geospatial Models},
journal = {Earth Systems and Environment},
year = {2025},
publisher = {Springer Nature},
month = {feb},
url = {https://link.springer.com/10.1007/s41748-025-00588-0},
doi = {10.1007/s41748-025-00588-0}
}