This study investigates the trend in monthly and annual rainfall, and minimum and maximum temperature (Tmin and Tmax) in the Savannah region of Togo. The historical data of Mango and Dapaong weather stations from 1981 to 2019 were used. A serial correlation test was applied to all time series to identify serially independent series. A Non-parametric Mann–Kendall (MK) test was applied to serially independent series. The magnitude of the trend was calculated using the Sen’s slope (SS) method. For the data influenced by serial correlation, a modified version of the Mann–Kendall test was applied. An open-source library package was developed in the R language, namely, “mkmodified”. For annual rainfall, results showed a significant increasing trend at Dapaong (p < 0.05) and a non-significant decreasing trend at Mango (p > 0.05) at 95%. There was an increasing trend in the Tmin both at Mango and Dapaong. No statistically significant trend was found at Mango (p > 0.05), while at Dapaong (p < 0.05), a significant trend was found at 95%. Simlarly, there was a statistically increasing trend in the Tmax both at Mango and Dapaong. Rainfall in Dapaong has increased (5.50 mm/year) whereas in Mango, it has decreased (−0.93 mm/year). Tmn increased by 0.04 and 0.008 °C per year in Mango and Dapaong, respectively. Tmax increased by 0.03 and 0.02 °C per year in Mango and Dapaong, respectively. A Rainfall Anomaly Index (RAI) was also used to present a temporal variation in rainfall; the historical series presented drier years. Many studies have analysed the trend of climate parameters in northern Togo, but none of them has specifically targeted the Savannah region that is considered the poorest region of the country.

Unplanned urban expansion poses significant challenges to environmental sustainability and urban planning. This study analyzes the spatiotemporal dynamics of Zinder’s urban landscape using Landsat satellite imagery from 1988, 2000, 2011, and 2022. The study applied remote sensing (RS), geographic information system (GIS) techniques, and urban growth models. The random forest classifier, a machine learning algorithm, was used to classify three land use/land cover categories: “vegetation”, “built-up”, and “others”. Zinder’s arid environment is characterized by sparse vegetation, which constitutes a limited but vital component of its landscape. Despite the already sparse vegetation in the area, the findings reveal a 3.5% reduction in vegetation cover between 1988 and 2022, alongside an 11.5% increase in “built-up” areas and an 8% decrease in the “others” category. This loss of already minimal vegetation raises significant concerns about environmental degradation and the exacerbation of desertification risks. Interestingly, urban expansion showed no significant correlation with population growth (r = 0.29, p > 0.5), suggesting that other factors, such as economic activities, infrastructure development, and land use policies, drive land conversion. Edge expansion emerged as the dominant growth type, with a significant directional preference (Chi-Square = 2334.41, p < 0.001) toward major roads and areas with higher accessibility to public services. These findings emphasize the need for strategic urban planning and land management policies to address the drivers of unplanned expansion. Prioritizing sustainable infrastructure development, enforcing land use regulations, and conserving natural landscapes are critical to balancing urban growth with environmental preservation, ensuring resilience and sustainability in Zinder.

Senegalese cities have experienced rapid urbanisation, leading to profound landscape changes. Dakar, one of Senegalese’s fastest-growing cities, is experiencing rapid urban expansion, significantly reducing green spaces. These green spaces, essential for urban sustainability and resilience, have become increasingly scarce, affecting the city’s environment and the quality of life for its residents. This study aims to assess the spatiotemporal changes in Dakar’s green spaces from 1990 to 2022. Using satellite imagery, this study produces land use maps to quantify green space coverage over the years. The results show a gradual decline in green spaces in Dakar between 1990 and 2022. In 1990, green spaces covered an estimated 13.36% of Dakar’s area, which decreased significantly to 9.54% by 2022. In contrast, other land uses, such as built-up areas, increased significantly over this period, rising from 19.23% in 1990 to 39.34% in 2022. Moreover, built-up areas are not the sole contributor to the reduction of green spaces in Dakar. The study revealed that, between 1990 and 2022, 5.49% of green spaces were converted into bare soil due to excessive tree cutting. This pattern highlights the growing challenge of green space availability as built-up areas expand rapidly, particularly when growth is unplanned. This study underscores the importance of sustainable urban planning that integrates the protection and conservation of Dakar’s vegetation to preserve vital ecosystem services.

Senegalese cities have experienced rapid urbanisation, leading to profound landscape changes. Dakar, one of the cities with the fastest urban expansion, has seen major negative impacts on the availability and quality of its green spaces. This study examines the spatio-temporal evolution of Dakar’s green spaces over recent decades. Using satellite imagery, this study produces land use maps to quantify green space coverage. The results show a gradual decline in green spaces in Dakar between 1990 and 2022. 1990 green spaces covered an estimated 13.36 % of Dakar’s area, which decreased significantly to 9.54 % by 2022. Meanwhile, other land uses, such as built-up areas, increased significantly during this period, from 19.23 % in 1990 to 39.34 % in 2022. This pattern highlights the growing challenge of green space availability as built-up areas expand rapidly, particularly when growth is unplanned. This study underscores the importance of sustainable urban planning that integrates the protection and conservation of Dakar’s vegetation to preserve vital ecosystem services.