Spatio-Temporal Analysis of Land Use/Land Cover Change and the Implications on Sustainable Development Goals in the Vea Catchment of Ghana

Rangeland Ecology & Management, Год журнала: 2024, Номер 94, С. 83 - 94

Опубликована: Март 20, 2024

Язык: Английский

Implications of land use and land cover change in Mampong municipality, Ghana

Sustainable Environment, Год журнала: 2024, Номер 10(1)

Опубликована: Апрель 25, 2024

Understanding and managing land use cover (LULC) changes are crucial for addressing environmental challenges, promoting efficient utilization of natural resources, sustainability ecological systems the well-being both present future generations. This study was conducted to map geo-physical features Mampong municipality assess extent LULC dynamism using Landsat 7 TOA (top-of-atmosphere) image 2006 8 images 2013 2020. Supervised random forest machine learning classification algorithm applied classify examine dynamics in area. Markov chain simulation adopted magnitude transition changes. The results revealed a substantial change uses area over period (2006–2020). trend analysis percentage indicated that deciduous had reduced drastically mainly purpose agriculture production build-ups human settlement as by negative or reduction typical biodiversity hotspot reservations: (−22.71%), (−26.74%) water bodies (−32.11%) with positive components such built-up (29.11%), barren (4.96) (37.91) study, however, serious extinction within dynamic results, suggesting 7.86 km2 originally under pathways have been converted 0.76 lands exposed erosion (barren land). A prediction year 2032 probability increasing rate urban surface build-up at 2.33% 1.69%, respectively, substantive resources given scenario. Given changes, we recommend major stakeholders including protection agency, guides, Ghana company municipal assembly authorities should develop feasibility holistic preventive measures seek ensure effective promote livelihood individuals who depend on these survival.

Язык: Английский

Integrated use of the CA-Markov model and the Trends.Earth module to enhance the assessment of land cover degradation: Application in the Upper Zambezi Basin, southern Africa

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Май 9, 2024

This study aims to demonstrate the potential of assessing future land cover degradation status by combining forecasting capabilities Cellular-Automata-Markov chain (CA-Markov) models in Idris Selva with (LCD) model Trends.Earth module. The focuses on upper Zambezi Basin (UZB) southern Africa, which is one regions high rates globally. Landsat satellite imagery utilised generate historical (1993–2023) and use (LCLU) maps for UZB, while European Space Agency Climate Change Initiative (ESA CCI) global LCLU are obtained from CA-Markov employed predict changes between 2023 2043. LCD module QGIS 3.34 then used assess forecasted status. findings reveal that produced local classifications provide more detailed information compared those ESA CCI product. Between 2043, UZB predicted experience a net reduction approximately 3.2 million hectares forest cover, an average annual rate -0.13%. In terms degradation, remain generally stable, 87% 96% total area expected be stable during periods 2023–2033 2033–2043, respectively, relative base years 2033. Reduction due expansion grassland, human settlements, cropland projected drive improvements anticipated through conversion grassland into forested areas. By leveraging predictive power model, as evidenced this study, valuable can effectively monitoring degradation. implement targeted interventions align objective realising United Nations' neutral world target 2030.

Язык: Английский