The number of active landmines is uncertain, however, estimated 5,554 people were killed or injured by mines in 2019. Understanding the land-cover before mine clearance process provides valuable information on the scale of the problem, the resources to clear the field and ensures all hazardous areas prioritized. In this paper, we present a new framework for land clearness prioritization using land-cover analysis. We use remote sensing images from sentinel-2 to estimate the changes in the land cover. Specifically, we estimate the changes in vegetation and non-vegetation areas. Further, we use the amount and number of land changes during a period to provide recommendations on the clearance priority for different areas. A case study for different areas in the Kingdom of Cambodia is presented with several observations of satellite images for the years 2019 and 2020. Several suspected hazardous areas (or polygons) are defined by landmine surveying expert for analysis. A change matrix for each polygon is obtained from consecutive observations. Then, a series of qualitative and quantitative 2- dimensional characteristics are extracted such as class change mask from-to, percentage loss and gain per class. The 2D characteristics, together with expert-defined scores of class-change importance are used to compute the amount and number of changes in each polygon and a recommendation on the clearance priorities. Our study demonstrates that analysing the changes in land-cover is a promising direction to help in the non-technical survey process and increasing the productivity of the land release.
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