Search

This paper assesses evidence-based applications of Remote Sensing for Sustainable and Precision Agriculture in the Northern Savanna Regions of Ghana for three decades (1990–2023). During this period, there have been several government policy intervention schemes and pragmatic support actions from development agencies towards improving agriculture in this area with differing level of success. Over the same period, there have been dramatic advances in remote sensing (RS) technologies with tailored applications to sustainable agriculture globally. However, the extent to which intervention schemes have harnessed the incipient potential of RS for achieving sustainable agriculture in the study area is unknown. To the best of our knowledge, no previous study has investigated the synergy between agriculture policy interventions and applications of RS towards optimizing results. Thus, this study used systematic literature review and desk analysis to identify previous and current projects and studies that have applied RS tools and techniques to all aspects of agriculture in the study area. Databases searched include Web of Science, Google Scholar, Scopus, AoJ, and PubMed. To consolidate the gaps identified in the literature, ground-truthing was carried out. From the 26 focused publications found on the subject, only 13 (54%) were found employing RS in various aspects of agriculture observations in the study area. Out of the 13, 5 studies focused on mapping the extents of irrigation areas; 2 mapped the size of crop and pasturelands; 1 focused on soil water and nutrient retention; 1 study focused on crop health monitoring; and another focused on weeds/pest infestations and yield estimation in the study area. On the type of data, only 1 (7%) study used MODIS, 2 (15%) used ASTER image, 1 used Sentinel-2 data, 1 used Planetscope, 1 used IKONOS, 5 used Landsat images, 1 used Unmanned Aerial Vehicles (UAVs) and another 1 used RADAR for mapping and monitoring agriculture activities in the study area. There is no evidence of the use of LiDAR data in the area. These results validate the hypothesis that failing agriculture in the study area is due to a paucity of high-quality spatial data and monitoring to support informed farm decision-making. [ABSTRACT FROM AUTHOR]

The use of mercury in small-scale gold mining is globally the largest anthropogenic source of mercury in the environment. In countries like Ghana, where small-scale gold mining is a highly important economic sector, the activity is also expected to cause local pollution. This study is based on a hypothesis that the mining activity in Ghana is causing more widespread soil pollution also outside active mining sites, and that the main part of regional differences in soil concentrations of mercury might come from pollution. Little systematic and dependable data has been collected to assess the extent of mercury contamination of soils in areas outside active mining areas. The regional aspect of mercury pollution from mining has not been studied in Ghana or other countries with a large small-scale gold mining sector. Systematic collection of soil samples on a 25 × 25 km2 net covering the entire country was carried out to ensure the representativeness of data and to allow calculation of spatial trends. The soil concentrations found in one-third of the country, where most intensive mining takes place, are three times higher than concentrations in the rest of the country. This difference cannot be explained by sources of natural variation in mercury concentrations but can be explained by decades of atmospheric deposition. It is therefore likely that the mining activity has caused a more widespread increase in soil concentrations, also outside active mining sites. The mercury concentrations found are on average 0.024 mg kg−1, which is low compared to published studies from other countries and regions and estimated world averages. All measured concentrations are well below soil quality criteria for human health. The build-up of soil concentrations in the mining area is still problematic because mercury is a hazardous substance in the environment. [Display omitted] • The use of mercury in small-scale gold mining causes local and widespread regional and global pollution. • A systematic 25 × 25 km2 net soil collection across the country was used to calculate spatial trends. • Background soil mercury concentrations in Ghana are low, but with large regional variation. • High regional concentrations can have been significantly increased by pollution from mining. [ABSTRACT FROM AUTHOR]

Background: Anthropogenic activities such as artisanal mining pose a major environmental health concern due to the potential for discharge of toxic metals into the environment., Objectives: To determine the distribution and pollution patterns of arsenic (As), iron (Fe), nickel (Ni), cobalt (Co), chromium (Cr), manganese (Mn), copper (Cu) and zinc (Zn) in the topsoil of a mining community in Ghana, along with potential human health risks and in vitro bioaccessibility., Methods: Concentrations of metals were determined using X-ray fluorescence techniques and validated using inductively coupled plasma-mass spectrometry., Results: Concentrations of the metals in topsoil were in the order of magnitude of Cu (31.38 mg/kg) < Ni (45.39 mg/kg) < As (59.66 mg/kg) < Cr (92.87 mg/kg) < Zn (106.98 mg/kg) < Mn (1195.49 mg/kg) < Fe (30061.02 mg/kg). Geo-statistical and multivariate analyses based on hazard indices including contamination, ecological risks, geo-accumulation, and pollution load suggest that the topsoils are contaminated in the study area. The potential ecological risk index (PERI) showed high ecological risk effects (PERI=269.09), whereas the hazard index (1×10 -7 ) and carcinogenic risk index (1×10 -5 ) indicated low human health risks. Elevated levels of As, Cr, Ni, and Zn were found to emanate from anthropogenic origins, whereas Fe, Mn, and Cu levels were attributed mainly to geological and atmospheric depositions. Physicochemical parameters (pH, electrical conductivity and total organic carbon) showed weak positive correlations to the metal concentrations. Elemental bioaccessibility was variable, decreasing in the order of Mn (35± 2.9%) > Cu (29± 2.6%) > Ni (22± 1.3%) > As (9± 0.5%) > Cr (4± 0.6%) > Fe (2± 0.4%)., Conclusions: Incorporation of in-vitro bioaccessibility into the risk characterization models resulted in a hazard index of less than 1, implying low human health risks. However, due to accumulation effects of the metals, regular monitoring is required., Competing Interests: The authors declare no competing financial interests.