Identifying suitable watersheds is a prerequisite to operationalizing planning interventions for agricultural development. With the help of geospatial tools, this paper identified suitable watersheds across Nigeria using biophysical parameters to aid agricultural planning. Our study included various critical thematic layers such as precipitation, temperature, slope, land-use/land-cover (LULC), soil texture, soil depth, and length of growing period, prepared and modeled on the Google Earth Engine (GEE) platform. Using expert knowledge, scores were assigned to these thematic layers, and a priority map was prepared based on the combined weighted average score. We also validated priority watersheds. For this, the study area was classified into three priority zones ranging from ‘high’ to ‘low’. Of the 277 watersheds identified, 57 fell in the high priority category, implying that they are highly favorable for interventions. This would be useful for regional-scale water resource planning for agricultural landscape development.

Noise remains an important challenge, particularly in informal settings where planning and regulation are relatively weak. This study aims at developing a model to predict noise in a largely informal urban Kano, the second most populated city in Nigeria. Sound level meter (SLM) 200 TL was used to measure noise at locations covering different land use: residential, industrial, commercial, educational, and administrative areas. Data were collected for seven days, and each day measurements were taken for six hours: 8–10 a.m., 12–2 p.m. and 4–6 p.m. Land use, population density, residential division, traffic volume, and land cover were used to generate a noise model using weighted geographic regression. The findings revealed that noise in the area is higher than the permissible limits set by the WHO and Nigeria’s regulatory agency. The model identified population density as the most influencing factor, followed by land cover, traffic volume and distance to the road, then land use. Seventy three percent of the model’s residual are below five, indicating a significant association between noise and the variables used. The R² ranges between 18% and 26% depending on the time of the day. Noise in the area can be effectively control by paying serious attention to city planning and enforcing traffic regulation measures.