TY - JOUR
T1 - Urban Green Infrastructure Planning in Jaipur, India
T2 - A GIS-Based Suitability Model for Semi-Arid Cities
AU - Nathawat, Ritu
AU - Gupta, Saurabh Kumar
AU - Kanga, Shruti
AU - Singh, Suraj Kumar
AU - Chakraborty, Shamik
AU - Marazi, Asif
AU - Sajan, Bhartendu
AU - Abouleish, Mohamed Yehia
AU - Meraj, Gowhar
AU - Ali, Tarig
AU - Kumar, Pankaj
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/3
Y1 - 2025/3
N2 - Urbanization in Jaipur, India, has led to a 42% decline in green cover over the past two decades, exacerbating urban heat, air pollution, groundwater depletion, and reduced livability. Green Infrastructure (GI) offers a sustainable solution, but effective implementation requires robust, data-driven strategies. This study employs geospatial technologies—GIS, remote sensing, and Multi-Criteria Decision Analysis (MCDA)—to develop a suitability model for Urban Green Infrastructure (UGI) planning. Using an entropy-based weighting approach, the model integrates environmental factors, including the Normalized Difference Vegetation Index (NDVI), which fell by 18% between 2000 and 2020; Land Surface Temperature (LST), which increased by 1.8 °C; soil moisture; precipitation; slope; and land use/land cover (LULC). Proximity to water bodies was found to be a critical determinant of suitability, whereas land surface temperature and soil moisture played significant roles in determining UGI feasibility. The results were validated using NDVI trends and comparative analysis with prior studies so as to ensure accuracy and robustness. The suitability analysis reveals that 35% of Jaipur’s urban area, particularly peri-urban regions and river corridors, is highly suitable for UGI interventions, thereby presenting significant opportunities for urban cooling, flood mitigation, and enhanced ecosystem services. These findings align with India’s National Urban Policy Framework (2018) and the UN Sustainable Development Goal 11, supporting climate resilience and sustainable urban development. This geospatial approach provides a scalable methodology for integrating green spaces into urban planning frameworks across rapidly urbanizing cities.
AB - Urbanization in Jaipur, India, has led to a 42% decline in green cover over the past two decades, exacerbating urban heat, air pollution, groundwater depletion, and reduced livability. Green Infrastructure (GI) offers a sustainable solution, but effective implementation requires robust, data-driven strategies. This study employs geospatial technologies—GIS, remote sensing, and Multi-Criteria Decision Analysis (MCDA)—to develop a suitability model for Urban Green Infrastructure (UGI) planning. Using an entropy-based weighting approach, the model integrates environmental factors, including the Normalized Difference Vegetation Index (NDVI), which fell by 18% between 2000 and 2020; Land Surface Temperature (LST), which increased by 1.8 °C; soil moisture; precipitation; slope; and land use/land cover (LULC). Proximity to water bodies was found to be a critical determinant of suitability, whereas land surface temperature and soil moisture played significant roles in determining UGI feasibility. The results were validated using NDVI trends and comparative analysis with prior studies so as to ensure accuracy and robustness. The suitability analysis reveals that 35% of Jaipur’s urban area, particularly peri-urban regions and river corridors, is highly suitable for UGI interventions, thereby presenting significant opportunities for urban cooling, flood mitigation, and enhanced ecosystem services. These findings align with India’s National Urban Policy Framework (2018) and the UN Sustainable Development Goal 11, supporting climate resilience and sustainable urban development. This geospatial approach provides a scalable methodology for integrating green spaces into urban planning frameworks across rapidly urbanizing cities.
KW - geographic information systems (GIS)
KW - green infrastructure (GI)
KW - land surface temperature (LST)
KW - multi-criteria decision analysis (MCDA)
KW - normalized difference vegetation index (NDVI)
KW - remote sensing
UR - http://www.scopus.com/inward/record.url?scp=105001170966&partnerID=8YFLogxK
U2 - 10.3390/su17062420
DO - 10.3390/su17062420
M3 - 学術論文
AN - SCOPUS:105001170966
SN - 2071-1050
VL - 17
JO - Sustainability (Switzerland)
JF - Sustainability (Switzerland)
IS - 6
M1 - 2420
ER -