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<p>Accurate estimation of built-up areas provides valuable information on urbanization trends and infrastructure development, which enables policymakers to formulate decisions in the planning and management of urban infrastructure, resource allocation, and environmental management. Although many remote sensing-based indices are widely used to map built-up areas and monitor the impact of urbanization on climate change, the close resemblances in the spectral features of built-up areas with bare soil areas pose a great challenge in the precise delineation of built-up areas, which may result in their overestimation. Moreover, most of the existing built-up indices use thresholding techniques to discriminate built-up areas from bare soil, but their effectiveness is limited due to the spatio-temporal variability that affects mapping accuracy. The present research introduces a novel constraint-based built-up indexing (AMCBI) method that improves the distinction between target and background features with similar spectral signatures, eliminating the need for thresholding, and demonstrates its potential over existing spectral indices for precise mapping applications. The qualitative and quantitative analysis of AMCBI revealed overall agreement values of above 97% and an F1 score above 0.95 across all study sites. Further, the weak correlation between AMCBI and existing indices indicates reduced spectral confusion and eliminates the need for thresholding or masking techniques. The superiority of the AMCBI can be mainly attributed to the ability of the constraint-based indexing technique to de-correlate built-up areas from bare soil. The findings of the study suggest that AMCBI is a viable alternative in mapping built-up areas, especially in heterogeneous urban landscapes. Clinical trial number: not applicable.</p>

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Built-up area mapping for sustainable urban planning: a novel satellite imagery based approach for detection of urbanization and landscape changes

  • 期刊论文

  • 发表日期：

    2026年6月19日

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  • Prema Somanathan Smitha,
  • Kesavan Maya,
  • Kulamulla Parambath Sudheer,
  • Vijayalekshmi Muraleedharan Bindhu,
  • Krishnan Sreelash,
  • Damodharan Padmalal

摘要

Accurate estimation of built-up areas provides valuable information on urbanization trends and infrastructure development, which enables policymakers to formulate decisions in the planning and management of urban infrastructure, resource allocation, and environmental management. Although many remote sensing-based indices are widely used to map built-up areas and monitor the impact of urbanization on climate change, the close resemblances in the spectral features of built-up areas with bare soil areas pose a great challenge in the precise delineation of built-up areas, which may result in their overestimation. Moreover, most of the existing built-up indices use thresholding techniques to discriminate built-up areas from bare soil, but their effectiveness is limited due to the spatio-temporal variability that affects mapping accuracy. The present research introduces a novel constraint-based built-up indexing (AMCBI) method that improves the distinction between target and background features with similar spectral signatures, eliminating the need for thresholding, and demonstrates its potential over existing spectral indices for precise mapping applications. The qualitative and quantitative analysis of AMCBI revealed overall agreement values of above 97% and an F1 score above 0.95 across all study sites. Further, the weak correlation between AMCBI and existing indices indicates reduced spectral confusion and eliminates the need for thresholding or masking techniques. The superiority of the AMCBI can be mainly attributed to the ability of the constraint-based indexing technique to de-correlate built-up areas from bare soil. The findings of the study suggest that AMCBI is a viable alternative in mapping built-up areas, especially in heterogeneous urban landscapes. Clinical trial number: not applicable.