ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume X-5/W2-2025
https://doi.org/10.5194/isprs-annals-X-5-W2-2025-365-2025
https://doi.org/10.5194/isprs-annals-X-5-W2-2025-365-2025
19 Dec 2025
 | 19 Dec 2025

Quantifying and simulating urban growth through Multi-Temporal Land Use and Spatial Perspectives

Sanjana Kumbhare, Anita Gautam, and Bharath Haridas Aithal

Keywords: Land Use, Spatial Metrics, Cellular Automata, Patch analysis, Land Use Simulation

Abstract. Urbanisation is an irreversible phenomenon associated with the transition from rural areas and, coupled with unplanned and dispersed growth, has resulted in vast and uncontrolled changes to the natural landscape in impervious built-up regions. Such transformations result in severe and often irreversible ecological destruction, socio-economic inequity, and spatial disintegration, particularly around rapidly urbanising cities. Given these challenges, analyzing urban development that has undergone severe landscape transformations is necessary. This study aims to systematically quantify and analyse the spatiotemporal changes in the urban landscape of Bangalore city by utilizing very high-resolution satellite imagery from different periods to understand land-use changes. The study also aims to quantify urban areas and characterise landscape structure by integrating spatial metrics, which will evaluate the growth of landscape changes from various land uses to urban land use, identify spatial cohesiveness, and understand the complexity of these arrangements. Then, we utilized the knowledge of spatial configuration to visualize future land use transitions through the theory of cellular automata- based patch-generating land use simulation (CA-PLUS) model. The result indicates a noticeable upward trend in urban growth, from 42.81% (2012) to 63.40% (2023). Additionally, the analysis reveals that the layout of land is changing rapidly, with urban areas becoming more connected, while other types of land are becoming insufficient and broken up; however, the model predictable a future expansion of urban area land from 71.77% in 2036 to 73.26% in 2042, potentially leading to the development of a significant continuous growth. Such insights can assist decision-makers and urban planners in creating data-driven approaches to sustainable development, infrastructure optimisation, and planned growth.

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