Overpopulation growth and urban center crowd became a global phenomenon which mainly cause urban growth in both developed and developing countries cities including Nigeria. Understanding the extent and pattern of such growth required spatial information as well as earth observation data that will be analyse on a temporal dimension. Remote sensing data and geospatial approach together with other auxiliary’s data were used to detect and monitor the spatio-temporal growth pattern and extent in the three decades of Hadejia town. The aim of this research is to understand how Hadejia town are spatial expand in terms of size and population between the years 1984-2019. Nevertheless, the spatio-temporal analysis over the three decades of 1984, 1999 and 2019 have been made. The research was carried out via remote sensing and geospatial method, satellite data were acquired across the region; atmospheric corrected using QUAC in Envi software; and also produced landuse landcover map. However, the research utilized object based image analysis (OBIA) for image classification and then built-up area were extracted in order to evaluate the urban expansion. The results indicate that the overall urban expansion occurred in between 1999 – 2019 with expansion of 566 hectares. Most of the changes happens along town major highway especial along interstate routes. The city has experienced an extreme growth geographically at East- Northern part due to plain terrain than Southern part because of present of river Hadejia.

Malaria is a significant public health issue in Nigeria where it accounts for more infections and deaths than any other nation in the world. Malaria is a concern for 97 percent of Nigeria’s population. The remaining 3 percent of the people reside in the malaria free highlands. There are an estimated 100 million malaria cases with over 300,000 deaths per year in Nigeria. It contrasts with 215,000 deaths a year in Nigeria from HIV / AIDS. Malaria contributes to an estimated 11 percent of maternal mortality. The study employed interpolated approach for the assessment and mapping of malaria cases from 2014 to 2018 in Hadejia metropolis and compares five year data of malaria prevalence within the political wards in the study area, using geo-spatial tools. The results showed that certain wards in the city have malaria cases danger which have a direct impact on human safety, social welfare which economy. The prevalence of the malaria parasites primarily exists in north and east of the sample country. Consequently the district is divided into eleven strata (political wards) which demonstrate that the higher incidence of Malaria for both years around Kasuwar Kofa, Kasuwar Kuda, Dubantu, Yayari and some portion of Matsaro and Gagulmari.

Fisheries and aquaculture plays a significant role in the Nigerian economy by providing employment, diversifying livelihoods, providing animal nutrition, and earning returns on foreign exchange. Fish is an important economic factor for many nations, as serves as a staple diet in many countries. As evident, in many developed nations, fishing is a crucial source of livelihood, particularly for low-income families in rural areas, where it offer local jobs in many communities and is a key source of food for millions. Over the past few decades, fish populations have deteriorated dramatically, and species at risk have experienced growing environmental challenges. Dams, overfishing, pollution, erosion, soil loss and other human activities are main threats to fisheries ecology. The presents study aimed to analyze the decline in diversity of the fish, adaptive management of artisanal fishermen in the wetlands of Hadejia-Nguru, Guri local government area of Jigawa State and to explore the correlation of environmental factors for the decline in fish diversity. In this study the data were collected through questionnaire interview (QI), focus group conversation (FGD), and field data collection (FDC), and the test objectives were accomplished via the analysis workflow. Geostatistical software was used to analyze the information obtained from QI, FGD and other sources while other auxiliary data and field data were collected using GPS receiver. The research findings can be considered as a tools for decision-making, policy-making, management plan development, fish conservation strategies plan and ultimately help to achieve the UN's Sustainable Development Goals (SDGs) 1, 2, 8, 14 and 15 of the 2030 agenda.

Despite recent advances in reducing poverty across the world, millions of people remain on the verge of or already living in severe multidimensional poverty especially in third world nations. The poor in Nigeria suffer from a feeling of voicelessness, helplessness, mistreatment, a complete lack of capacity to influence important choices that impact their life, and a lack of social networking inside state and societal organisations. The goal of this research is to conduct a geospatial analysis of Nigeria’s multidimensional poverty and to identify the geospatial distribution pattern of poverty in Jigawa State as a case study. As a result, comprehend the causes of Jigawa’s complicated poverty condition and to create the state’s first ever poverty map. Also, to look at the country’s poverty trends, with a particular emphasis on Jigawa. The National Bureau of Statistics provided the headcount poverty statistics for Nigerian states, which were downloaded and analysed using simple geospatial approach. The findings revealed a dynamic pattern in Nigerian state poverty from 1996 to 2019. The distribution of poverty in Jigawa state, as a case study, revealed that physical and natural environment resources play a critical role in the state’s high poverty rate. Natural drainage, fertile soil, flat topography, and vegetation pattern all aid other people’s poverty levels in different parts of the state. Future study will examine the linking between environmental, social, religious, and political factors and multidimensional poverty using a geospatial method to map the state’s poverty, which has consistently ranked at the bottom of the Nigeria States Poverty Index.