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Improved Algorithm for Monitoring Land Disturbances

Strategic Insights

— 1 min read

A new report from Hong Kong Polytechnic University proposes an improved method for detecting rapid ground changes using Harmonized Landsat and Sentinel (HLS) data. The research emphasizes the importance of accurate change detection in understanding land disturbances, particularly in rapidly urbanizing areas. By integrating land disturbances identified by the Continuous Monitoring of Land Disturbances (COLD) algorithm with publicly available land use/land cover (LULC) maps, researchers have developed a more accurate method for mapping and quantifying construction activities.

Key Takeaways:

  • The COLD algorithm is widely used for detecting rapid ground changes, but its accuracy is often limited by frequent ground alterations such as large-scale construction.
  • The improved COLD algorithm integrates land disturbances with LULC maps from Esri, covering the period from 2017 to 2024, to map and quantify construction activities.
  • The study focused on the new capital of Egypt as the study area, which is experiencing a surge in national infrastructure projects, tracking construction dynamics from 2016 to the present.
  • The spatiotemporal detection of land disturbances used the COLD algorithm with a dataset of 559 images from Harmonized Landsat and Sentinel missions.
  • The identified COLD breaks correspond to transition periods, capturing changes from July of one year to July of the next.
  • The improved method was validated by visually comparing detected construction activities over time and cross-referencing with historical satellite imagery from Google Earth.

Statistics:

  • 559 images from Harmonized Landsat and Sentinel missions were used in the spatiotemporal detection of land disturbances.
  • The improved COLD algorithm was applied to the new capital of Egypt, which is experiencing a surge in national infrastructure projects.
  • The study period spanned from 2016 to the present.
  • The LULC maps from Esri, covering the period from 2017 to 2024, were used in the improved algorithm.
  • The constructed area classified as undergoing construction using the improved method was found to be more extensive than using the LULC maps of the same year.

Sources:

  • An Improved COLD Approach for Monitoring Construction Dynamics Using HLS and LULC Data: A Case Study in the New Capital of Egypt. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2025,X-G-2025():3-10. (ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences - http://www.isprs.org/publications/annals.aspx).

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