What question did this study set out to answer?

This research aims to evaluate the changes in land cover within an open-pit mining area over selected years using satellite imagery and image analysis techniques.

June 5, 2026Open Access

Assessment of Land Cover Changes in an Open Pit Mine Using Object-Based Image Analysis: Case of Hahotoe-Kpogame Phosphate Mining at Togo

Key Points

This research aims to evaluate the changes in land cover within an open-pit mining area over selected years using satellite imagery and image analysis techniques.
Utilized Landsat satellite imagery from 1986, 2015, and 2024 for analysis.
Employed Object-Based Image Analysis (OBIA) methodology to classify land cover types.
Applied Random Forest model for classification and assessed performance with Kappa coefficients.
Identified six land cover classes: active mining area, bare ground, water, persistent vegetation, agricultural land, and settlements.
Active mining area decreased by 19.6% since 1986; agricultural land increased by 37.3% by 2024.
Settlements grew by 100.5%, indicating rapid urbanization; persistent vegetation declined by 21.3%.

Abstract

This study assesses land cover changes in an open-pit mining area: the Hahotoe-Kpogame phosphate mining site in southern Togo. The analysis utilizes Landsat satellite imagery across three specific years: 1986, 2015, and 2024. The adopted methodology is Object-Based Image Analysis (OBIA), which groups pixels into homogeneous objects called segments prior to classification. The Random Forest model was employed for this purpose. In total, six land cover classes were identified: active mining area, bare ground, water, persistent vegetation, agricultural land, and settlements. The results demonstrate a satisfactory performance of the classification model, with Kappa coefficients of 0.72, 0.8, and 0.85 for 1986, 2015, and 2024, respectively. Landscape dynamics reveal a 19.6% decrease in the active mining area compared to 1986, indicating a relative decline in mining activity. Agricultural land was already the dominant class in 1986 and had increased by 37.3% by 2024. The settlements class showed the most significant growth, with an increase of 100.5%, reflecting rapid urbanization trends. Persistent vegetation corresponding to patches of wooded and shrub savannah located between agricultural lands and vegetation encroaching on waterways experienced a decline of 21.3%. Finally, the water and bare ground classes are highly dynamic and influenced by river behaviour. Indeed, the flooding and receding of the study areas main waterways intermittently leave behind marshy bare soils and temporary water bodies, making it difficult to determine a precise evolutionary trend for these specific classes.

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