Maize products are very significant for domestic consumption as well as industrial uses both locally and globally. For there to truly appreciate the spread of maize production in Africa, the geospatial mapping and subsequent comparison of the value chain for Nigeria and Rwanda were necessitated hence the purpose of this study. Farm mapping geospatial techniques and remotely sensed data were used for both Nigeria and Rwanda in this study. GIMMS Global Agricultural Monitoring data from United States Department of Agriculture (USDA) were adopted for Nigeria and Rwanda. The crop calendars of both countries were examined which thereafter reviewed a marked distinction among them. The results of the agroecological zones for the two countries showed a significant variation in their distribution and types, which in turn affect both the planting and harvesting of maize; storage, marketing, processing, and policy framework for maize products value chain in Nigeria and Rwanda. Mapping of the two countries was carried out and the normalized differential vegetation index (NDVI) and the policy associated with maize value chains were checked and reported.

The main goal of this study is to evaluate the impacts of humaninduced activities on land surface temperature dynamics of Osogbo, in Osun State, Nigeria. Land surface temperature dynamics, land use land cover dynamics and the relationship between land surface temperature (LST) and land-use land-cover (LULC) were assessed using Landsat satellite data (ETM+ and OLI/TIRS) of Oshogbo, Osun State, Nigeria. The radiometrically corrected thermal infrared bands of the Landsat images of 2000 and 2018 were used to retrieve land surface temperature while the Maximum Likelihood algorithm in Erdas imagine 9.2 was used to generate a classified image for the two periods. Land surface temperature maps, land cover index maps and Normalized Differential Vegetation Index (NDVI)) were generated. Correlation analysis using Pearson's Product Moment Method was carried out between land surface temperature and normalized differential vegetation index (NDVI) data and the land cover index was digitized and overlaid on the LST map of 2018 to determine the association between them. The results revealed noticeable decrease in vegetated areas of Osogbo with an accompanying increase in land surface temperature from 28.045°C in 2000 to 29.200°C in 2018. Built-up increased within the same periods from 19 to 42%, which could be attributed to anthropogenic activities. The land surface temperature distribution maps showed a more pronounced intensity in areas of significant human activities than in areas covered by vegetation and waterbody. The

This study, aimed at evaluating the link between maize farmer lands and infrastructures. The main objective of the study was to find out the existing links between farmlands and infrastructures within the maize supply chain in the North Central States of Nigeria. The investigation was carried out using questioners to assess the constraints of farmers in supply chains, multi-stage sampling procedure was adopted to sample the respondents in Kuje Area Council and Mararaba. A total of 130 respondents were interviewed using a structured interview guide. Results indicated that the majority of the farmers have no access to adequate infrastructural facilities such as roads, processing facilities, storage facilities and markets. Proximity analysis was also carried out analyzing GRID3 data for farmlands, roads and market points using ArcGIS 10.8. The result also shows that the majority of the maize farmlands are not close to the markets and there are no major roads connecting the farms to the transportation of farm produce. Farmers are infrastructural constraints at the production, transportation and marketing stage. The study, therefore, suggests a more viable infrastructural facility for farmers to interconnect farmland, to enable farmers to have access to good roads, storage and processing facilities which will enhance the maize value chain.