Browsing by Author "Areola, O."

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Inland habitat environmental sensitivity index mapping and modeling using geographic information systems and remote sensing technology
(2007) Taiwo, O.; Areola, O.
This study applies the Inland ESI mapping model developed by ERML and ESRI for the Niger Delta to the southeastern coastal region of Nigeria. Traditionally ESI mapping had been applied to shoreline areas and the maps typically contain three types of information: shoreline classification in terms of sensitivity to oiling, human-use resources, and biological resources. The ESI shoreline classification scheme is a numeric characterization of the sensitivity of coastal environments and wildlife to spilled oil. ESI was developed to reduce the environmental consequences of a spill and help prioritize the placement and allocation of resources during cleanup efforts. An improvement to the traditional ESI atlas has further been added through the development of ESI for inland/interior areas. This is particularly significant in the Nigeria context where many oil and gas facilities are located in the inland/interior habitats. This study shows that the model developed for the Niger delta is equally applicable to southeast coastal environment. The modeling is done using satellite imagery followed by rigorous field data collection and modeling within Arcview GIS environment. The GIS approach is quite ideal for ESI modeling because of its capability to sequentially overlay different data layers for various kinds of spatial statistical analysis and spatial modeling. The most critical element is the construction of the database: the relational database structure adopted greatly facilitates data search and analytical operations.
A spatial temporal analysis of wetland losses in the Lagos coastal region, Southwestern Nigeria, using multi-date satellite imagery
(2009) Taiwo, O. J.; Areola, O.
This paper assesses the temporal trend and the spatial patterns of wetland forest loss in the Lagos coastal region of southwestern Nigeria between 1978 and 2006 based on the comparative analysis of multi-date satellite imageries for 1978, 1987, 1995, 2000 and 2006. The initial number of wetland habitats was derived using an unsupervised classification algorithm. Freshwater and mangrove swamp forests dominated the area. Generally, the wetlands declined by 19% between 1978 and 2006 at 0.6% annual rate of loss. The freshwater and mangrove swamp forests declined by 20.9% and 13.0% with an annual rate of loss of 0.7% and 0.43% respectively. Using the Markov Chain technique, the trend in wetland loss would likely continue if the current economic, social and political systems are maintained. The lower rate of decline of mangrove forests compared with freshwater swamp forests is a reflection of the more waterlogged and difficult terrain.