ACCURACY ASSESSMENT OF IMAGE CLASSIFICATION ALGORITHMS

Iso-cluster unsupervised classification was performed using the multivariate toolset of ArcMap 10.1 to identified the spectral clusters or natural statistical groupings present in Kwali Area Council of the Federal Capital Territory Abuja using 2011 Landsat-7 ETM+ and adopting supervised classification that involves ground truthing, the previous knowledge of the study area and creating training site. The maximum likelihood classification (supervised classification), default colour was changed to multiple colour that can easily be interpreted. The new colour assignment was based on information obtained from prior knowledge of the study area. The supervised classified image was further processed to remove all the noises - unwanted or non-relevant information that made it appeared speckled. Using the generalization toolset of ArcMap 10.1 spatial analyst tool, the classified output was filtered to remove the noise; this was done using eight nearest neighbours kernel majority filter. Also, the ragged boundaries of the classified output were smooth as well as clumping the classes together using boundary clean toolset

ACCURACY ASSESSMENT OF PIXEL-BASED IMAGE CLASSIFICATION OF KWALI COUNCIL AREA, ABUJA, NIGERIA

In this study, Kwali Council Area located on the western part of the Federal Capital Territory, Abuja was selected as a study area covering approximately 1,206 km² for comparing the two major pixel-based image classification algorithms (Supervised and Unsupervised classification). For this purpose, land use and land cover classification of the study area was conducted by supervised classification particularly maximum likelihood classification (MLC) and Iso-cluster unsupervised classification procedures and the results were compared with one another using 2011 Landsat-7 ETM+ satellite. However, the result of classification accuracy illustrates that light vegetation shrubs records dominance value of 27.54%, savannah grasses 23.04%, cultivated areas 20.12%, wetland flood plain 13.78%, sand open surfaces 11.01% and water body 4.52%. Overall, supervised pixel-based classification methods are found to be more reliable, accurate and outperformed unsupervised pixel-based classification methods in this study. The higher accuracy was attributed to the fact that supervised classification took advantage of spectral information of land cover, based on the spectral signature defined in the training set and digital image classification software that determines each class on what it resembles most in the training set in the remotely sensed imagery. This study is a good example of some of the limitations of unsupervised pixel-based image classification techniques, whereby the unsupervised image classification technique is commonly used when no sample sites exist. These improvements are likely to have significant benefits for land-cover mapping and change detection applications. It is recommended that, the two approach can be used together to provide a standard, accurate and finest result for specific applications by users in different parts of the world.   Keywords: Accuracy, assessment, pixel-based image classification algorithms, iso-cluster unsupervised, ML

Analysis of Change Detection of Birnin-Kudu Land Cover Using Image Classification And Vegetation Indices

The study utilizes Landsat-7 ETM+ based Normalized Differences Vegetation Index (NDVI) and Normalized Differences Water Index (NDWI) from 1972 to 2012 at the study area situated in Birnin Kudu, Jigawa state, in North-western Nigeria. The classified satellite data based NDVI of 1972, 1986, 2003 and 2012, including NDWI of 1986, 2003 and 2012 were used to determine land-cover change; vegetation and water body that have occurred in the study areas. This study attempts to use a comparative change detection analysis to produce the best way to quantify changes that has occurred in the study area with a lag time of 40 years (1972-2012) for NDVI and 26 years (1986-2012) for NDWI. The results of the classifications of NDVI and NDWI were displayed on satellite imagery, of which the percentage differences of change detected from variations of land cover/vegetation using NDVI of 1972-1986 is 15%, 1986-2003 is 40% and 2003-2012 is 11.6%. In the same vein, the result of percentage differences of change detected from variations of water bodies using NDWI of 1986-2003 is 0.03% and 2003-2012 is 1.5%. In the final analysis the change detected using NDVI for the period of 40 years (1972-2012) is 43.4%, while using NDWI for the periods of 26 years (1986-2012) is 1.47%. The study recommends periodic examination of land-use changes for determining various ecological and developmental consequences over time. The study area is of great environmental and economic importance having land cover rich in agricultural production and livestock grazing. Keywords: Analysis, change detection, land-cover, image classification algorithms, NDVI, NDW

Assessment of a Vulnerable Rural Community to Typhoid Fever using Geospatial-Temporal Analysis: Case Study of Ejule, Kogi State of Nigeria

The rural community of Ejule in Kogi state has suffered for decades to access quality water. Therefore, the high prevalence cases of typhoid fever are largely due to unavailability of safe and clean water in the study area. This study adopts spatial-temporal techniques and Statistical Package for Social Science (SPSS) to analyze the data collected and investigates the spatial variation of typhoid fever in the study area. The results showed that the total reported cases of typhoid fever for a lag period of three years are 12,733, of which the year 2011 recorded 3986 (31.30%), 2012 record 4233 (33.24%) and 2013 also record 4514 (35.45%). This implies that a total of 77.17% of the entire population of the study area were affected in the preceding year of 2011, 2012 and 2013. The results also identify that the high cases of typhoid fever recorded in the dry/cool season is as a result of supply of untreated contaminated stream/river water and the decrease in rainfall amounts, while lower transmission is recorded in the wet/rainy season when partial clean rain water were highly available. The study further indicates that a total of 97,060,000 litres of contaminated river water was supplied to 13,481 people, which are 81.70% of the entire population in the study area. The results of the classification of Land-use (LU) and Land-cover (LC) from satellite imagery confirmed that the study area is without water body. However, the availability of contaminated and polluted river/stream water positively correlates to typhoid fever of which the determination coefficient are 81.03% with high level of confidence and strong strength in their relationship. In the final analysis the spatial spread of contaminated water increase the vulnerability of typhoid fever and health risk to the community, particularly people in the area. It is evident that the only source of water to the community is from river Umomi and Ochadamu, these water points are highly susceptible to contamination, thus the high concentration of water borne diseases (typhoid fever) in the area. The study recommends improved environmental sanitation and enhanced water management strategies. Keywords: assessment, vulnerable, ejule rural community, typhoid fever, geospatial, temporal, contaminatio

Assessment of Human African Trypanosomiasis Foci using Change Detection Algorithms

Environ-climatic change influences the occurrence and propagation of Human African Trypanosomiasis (HAT), focusing on two foci; Delta State and Jigawa State Nigeria where HAT has been reported. Geospatial and temporal based ground truthing exercise carried out to harvest HAT vector in Jigawa state did not yield any results; this indicates that the disease might have been phased out in the state.  In the same vein, resurging of HAT disease in the Delta State has been reported of recent. Thus, a change detection analysis was conducted in a geographic information systems (GIS) environment, to investigate the foci landscape. Using normalised difference vegetation index (NDVI), normalised difference water index (NDWI) and tasseled cap transformation (TCT), changes with a lag time of two decades was assessed for the two foci.  The analysis suggested that the landscape has changed considerably over the years that show Delta State as the potential active HAT foci as explained from the regression analysis of 0.9868 (99%) ahead of Jigawa state 0.0000 (0%) that can be regarded as non-active foci.  However, on-going programs, such as afforestation, forestation, irrigation farming and water reservoir projects may result in re-introduction of favourable landscape, thus, re-invasion of the area by the HAT vector. Therefore strategies that will maintain the present HAT-free status of the non-active foci, without adverse effect on the environment should be a government priority. To effectively reduce or control HAT propagation, integrated prevention schemes should be developed and executed.  The two HAT foci are of great economic importance; Delta State landscape is rich in hydrocarbons while Jigawa State is known for its extensive grazing and arable landscape. Keywords: Trypanosomiasis, Afforestation, Foci, HAT, Landscape, Environ-climatic, Spatial, Irrigatio

Analysis of Sensor Imaging and Field-Validation for Monitoring, Evaluation and Control Future Flood Prone Areas along River Niger and Benue Confluence Ecology, Lokoja, Nigeria

The study area often suffered from flood for the last two year resulting to ecological damages including farmlands, infrastructures, property damage, loss of life and degradation of land-cover. Flood prone areas assessment is conducted using sensor data from space-borne optical sensors with cross-validation by ground-truthing the study area along the two major rivers that converge at Lokoja, otherwise called river-confluence. Maximum likelihood classification (MLC) and ISO-clustering unsupervised classification method of Arcmap-10.1 using NigeriaSat-1 data is applied to the regimes of up-stream and down-stream of River Niger and River Benue respectively. Based on ground truthing of the study areas, classification of inundated areas closely connected with actual flood prone area was developed. The results of the classifications of flood prone areas were displayed on satellite imagery, of which the percentage differences of change detected from variations of 16 class of land-use (LU) and land-cover (LC) using optical sensor shows that wetland flood plain comprising of runoffs-routes and lowland areas recorded the highest of 14.42% using MLC and 16.02% using ISO-DATA. In the final analysis, the classification accuracy conducted shows that the ecology of flood prone areas can be adequately classified using MLC (54.89%) and ISO-clustering unsupervised classification (45.11%). In the same vein, the result of regression function shows high correlation coefficient of 0.6242 (62%) and high strength in their relationship of which the potential flood runoff-route did correlate with the state of the location of the study area. It is anticipated that remote-sensing data integrated from optical sensors could be used to supplement up-stream, down-stream and runoffs-route to monitor, evaluate and detect floods prone areas. It is therefore significant that government and relevant agencies adopts these findings to help in the monitoring, evaluating and control of future ecological disasters. Keywords:Analysis, lokoja,river niger, river benue, confluence, monitor, evaluate, control, ecology, flood, spatial, tempora

Rainfall Variations as the Determinant of Malaria in the Federal Capital Territory Abuja, Nigeria

This study highlights the increasing interest in identifying the parameters adequate to measure rainfall and wet day’s variations as the determinant of malaria occurrences and distribution for a period of twelve months (2012) in the Federal Capital Territory. Satellite data were developed to identify malaria risk area and to evaluate amounts of rainfall and the durations of wet or rainy days conducive to malaria outbreaks at appropriate scales. Secondly, the studies examine the correlation of monthly and annual malaria cases, and rainfall amounts, including wet days with a lag time of one year. The result of correlation analysis shows that relationship exists between the observed weather variables and malaria. The coefficients of determination R2 of rainfall influencing malaria is 0.3109 (31.1%) and wet days influencing malaria is 0.3920 (39.2%). These results indicate that the rainfall amounts positively correlate with malaria cases with prediction estimate by 78.47% and 88.68% respectively when the peak was August (rainfall) and June (malaria). The study further shows that a significant rainfall variation was identified, and further revealed that certain necessary measures have to be adequately taken to ensure that the existing malaria problems are dealt with and further occurrence is minimized, if not forestalled all together. It is recommended that more attention should be given to weather and climate mechanism that determines the occurrence and distribution of malaria. Keywords: rainfall, amount, wet day, duration, variation, determinant, malaria, occurrence, distribution, risk map

An Assessment of Alternative Water Source for Domestic Used in Minna Metropolis, Niger State, Nigeria

Making freshwater available in urban centre are major challenge to be faced in 21st century globally. Population growth and industrialisation have put a lot of pressure on water resources the world over. Minna, the capital city of Niger State Nigeria, has witnessed population growth due to the influx of people from the various regions to seek greener pastures. The population growths have resulted in an inadequate water supply to the populace by conventional means. These problems result in an individual effort to meet their daily water demand. To explore this problem, structured questionnaire were distributed to two hundred households purposively selected from six areas in the town and semi-structured interviews were administered on five water analyst. Statistical Package for Social Science (SPSS) was used to analyze the data collected. The study reveals that inadequate budgetary allocation to ministry of water resources is the major problem hindering water availability in Minna. The three alternative sources of water supply for domestic use identified were well water, water from vendors and boreholes. Consequently increase in resource allocation to the ministry of water resources in a way of policy framework that guaranty private investment in water sector, among others to improve water availability in the study area. Key words: alternative, water, sources, domestics, borehole, well, vendor

Assessment of Housing Conditions for a Developing Urban Slum using Geospatial Analysis: A Case Study of Durumi, Garki-2, Gishiri and Jabi of the City of Abuja, Federal Capital Territory of Nigeria

The parameters used for urban slum classification are water source, accessibility types, wall materials, conditions and types of waste disposal, roof and roof trusses types, and cluster nature of the study areas as detected by NigeriaSAT-1 imagery data. Applications of remote sensing are best and better appropriate way to identify slums through the presence of the following features; housing density, structure, and roof composition. However, it was observed that the study areas had been in a condition of virtual slum before 2005. The results of housing conditions classification shows that slums are often associated and characterized by substandard housing structures, poor living conditions, narrow access that do not allow vehicles, experience a high rate of disease, poor water quality, window and door made from substandard material, and  unhealthy disposal of waste. In addition, the geo-statistical analysis also show positive relationship with the slum index; water 0.0536 (5%), solid and liquid waste 0.3707 (37%), wall to the building 0.7594 (76%), roof 0.3253 (33%), toilet wall 0.5313 (53%), kitchen wall 0.6020 (60%), door 0.3191 (32%), window 0.4255 (43%) and accessibility 0.3167 (32%). In the final analysis, it was observed that the methods agree largely with the areas classified as slum or squatter settlement. This conclusion was made based on the results of the housing conditions classifications, statistical analysis and cluster nature of the study areas displayed in palette of Arcmap-10.1 supervised classification. It is recommended that, this classification approach be used for assessing the state of housing conditions in urban slums. Keywords: assessment, housing conditions, urban/city slum, geospatial algorithm

Meningococcus serogroup C clonal complex ST-10217 outbreak in Zamfara State, Northern Nigeria.

After the successful roll out of MenAfriVac, Nigeria has experienced sequential meningitis outbreaks attributed to meningococcus serogroup C (NmC). Zamfara State in North-western Nigeria recently was at the epicentre of the largest NmC outbreak in the 21st Century with 7,140 suspected meningitis cases and 553 deaths reported between December 2016 and May 2017. The overall attack rate was 155 per 100,000 population and children 5-14 years accounted for 47% (3,369/7,140) of suspected cases. The case fatality rate (CFR) among children 5-9 years was 10%, double that reported among adults ≥ 30 years (5%). NmC and pneumococcus accounted for 94% (172/184) and 5% (9/184) of the laboratory-confirmed cases, respectively. The sequenced NmC belonged to the ST-10217 clonal complex (CC). All serotyped pneumococci were PCV10 serotypes. The emergence of NmC ST-10217 CC outbreaks threatens the public health gains made by MenAfriVac, which calls for an urgent strategic action against meningitis outbreaks