This study develops an integrated innovation for malaria early warning systems (MEWS), based on vulnerability monitoring, seasonal climate variability data, and epidemiologic surveillance. The main aim of the study is to examine the relationship between intra-annual climate variability and malaria transmission in Nigeria. For this study, climatic conditions considered suitable for the development of the malaria parasite and its transmission through the mosquito stage of its life cycle are temperatures within the range from 18°C to 32°C. Below 18°C the parasite development decreases significantly, while above 32°C the survival of the mosquito is compromised. Relative humidity greater than 60% is also considered a requirement for the mosquito to survive long enough for the parasite to develop sufficiently to be transmitted to its human host stage. The research findings show that seasonality of climate greatly influences the seasonality of malaria transmission. Specifically, rainfall plays an important role in the distribution and maintenance of breeding sites for the mosquito vector. Rainfall and surface water is required for the egg laying and larval stages of the mosquito life cycle and monthly rainfall above 80 mm is considered a requirement. Also, it is temperature that regulates the development rate of both the mosquito larvae and the malaria parasite (Plasmodium species) within the mosquito host. Relative humidity and temperature play an important role in the survival and longevity of the mosquito vector. This study is in conformity with the findings of the IPCC (2001) that malaria is caused by four distinct species of the Plasmodium parasite, transmitted by mosquitoes of the genus Anopheles, which are most abundant in tropical/subtropical regions, although they are also found in limited numbers in temperate climates.

Forest Reserves in Southwestern Nigeria have been threatened by urbanization and anthropogenic activities and the rate of deforestation is not known. This study examined the vegetation characteristics of Akure Forest Reserve using optical remote sensing data. It also assessed the changing pattern in the forest reserve between 1986 and 2017. Global Navigation Satellite System (GNSS) receiver was used to capture the location of the prominent settlements that surrounded the Forest Reserve in order to evaluate their effects on the forest. Landsat TM 1986, Landsat ETM+ 2002 and Landsat OLI_TIRS 2017 with 30m resolution were classified to assess the spatio-temporal changing pattern of the forest reserve. The results showed different composition of vegetation, which include undisturbed forest, secondary regrowth and farmlands. The study further revealed that in 1986, 2002 and 2017, undisturbed forest constituted 63.3%, 32.4% and 32.1% of the entire land area respectively, while secondary regrowth occupied 8.3% in 1986, 9.5% in 2002 and 15.6% in 2017. The farmlands had erratic growth between 1986 and 2017. It was 16.9% in 1986, 22.1% in 2002 and 17.5% in 2017. The bare ground exhibited inconsistency in the coverage. In 1986 the areal extent was 11.5%, when it increased to 36% in 2002 and decreased to 31.9% in 2017. In conclusion, the study revealed the extent of forest depletion at Akure Forest Reserve and it is therefore important that the residents, the government and the researchers show major concern about some of the critical factors to human beings that are responsible for forest depletion.

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Land use/land cover information is essential for a number of planning and management activities. The general patterns of land use/cover as they were recorded in remotely sensed data were discussed in this study. Multi-date satellite imageries (Landsat TM 1986, Landsat ETM+ 2001, Landsat ETM+ 2006 of 30m spatial resolution respectively and SPOT 5, 2007 of 10m spatial resolution) were obtained and used for the study. These images were enhanced, resampled, georeferenced and classified for the assessment of spatio-temporal pattern of land use/cover change in the study area. The study also utilized topographical map of the study area, derived from sheet number 247 of 1963, scale 1:50,000 to identify features, which were used as ground control point for image geo-referencing. ILWIS 3.2 Academic software was used to process the image data. The result of ground truthing was combined with visual image interpretation as training sites for supervised classification. Six different land uses/covers were identified and used to classify the image data. The results showed that the natural environments (vegetation, wetland resources, water bodies and mountainous terrain) were being threatened, as they reduced continually in the areal extent over time and space while the social environment (built up area) expanded tremendously. The study discovered that urbanization processes majorly responsible for land use/cover change in Lokoja. In conclusion, the study advanced our frontier of knowledge on land use/cover study by providing information on the status of natural and social environment in Lokoja, a confluence town, between 1986 and 2007 using remotely sensed images and Geographic Information Systems (GIS) technology.

Deforestation is driven by a variety of factors, and has resulted in land use changes that threaten biodiversity, water and energy resources. However, lack of reliable data and survey information in Nigeria has made the estimation of the effect of deforestation difficult to establish. Consequently, the extent and rate of deforestation are less well known. The study therefore, examined and analyzed the spatial and temporal patterns of deforestation over the period of 25 years ; measured the rates, trends and explained the factors that determined deforestation in Ijesa-Ekiti region of southwestern Nigeria. The major sources of data for the study were satellites images. These were Landsat MSS 1978, with spatial resolution of 80 m, SPOT XS 1986, SPOT XS 1994, with 20 m spatial resolution and NigeriaSat_1 2003, with 32 m spatial resolution. To make them comparable, they were georeferenced to the same coordinates system, filtered, resampled and enhanced for visualization in a GIS environment. Furthermore, Ilesa, Ijebu-Ijesa, Efon-Alaaye, Iloko-Ijesa, Erin-Oke and Erin-Ijesa were identified and selected for ground truthing to validate the tonal values recorded in the images with the features on the ground. The result of ground truthing was combined with visual image interpretation as training sites for supervised classification. Focus Group Discussions were held with people who had lived in the area for over 20 years as a means of eliciting factors of deforestation and the effects on forest biodiversity. The results indicated forest loss of 53,469.23 ha over the period of 25 years at an annual deforestation rate of 7.21, 2.47, and 5.40% per year for 1978-1986, 1986-1994 and 1994-2003, respectively. FGDs with various categories of people in the bigger towns confirmed deforestation in the area and were due to illegal lumbering, intensive agricultural practices and growth of settlements resulted from increase in human population. FGDs also revealed extinction of many forest species in their communities. In conclusion, the study advanced our understanding on techniques of analyzing deforestation using geo-spatial technology. It also generated a synthesis of information on the rates of deforestation and its driving forces, which are a complex mix of anthropogenic factors, the chief of which has been the conversion of forest resources to agricultural land use.