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All Journal Indonesian Journal of Earth Sciences Priviet Social Sciences Journal Applied Environmental Science
Sani, Inuwa Sani
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Spatio-Temporal Land Use Change Analysis at Dutse International Airport Using Google Earth Imagery Sani, Inuwa Sani; Wibowo, Adi; Imam, Mahmoud Zubair
Indonesian Journal of Earth Sciences Vol. 5 No. 1 (2025): January-June
Publisher : MO.RI Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52562/injoes.2025.1435

Abstract

This study discusses spatial-temporal land use change around Dutse International Airport, Nigeria, using high-resolution Google Earth imagery of 2012, 2018, and 2023. Change was triggered by the development of an airport in 2014 and has brought about phenomenal changes, including urbanization and agricultural and vegetated land cover loss. With supervised classification in ArcGIS, aided by geometric correction and accuracy measurements (confusion matrix, user and producer accuracy, kappa coefficient), quantitative estimation of land use change over time is ascertained in the study. Findings reveal the steep decline of agricultural land from 452.41 ha in 2012 to 116.01 ha in 2023, and loss in vegetation from 278.33 ha to 104.42 ha. In contrast, cover of settlement expanded from 97.21 ha to 346.42 ha and road infrastructure expanded from 172.54 ha to 296.54 ha. The result indicates natural and agricultural landscape pressure induced by infrastructure-based development. The research suggests land use planning through zoning policy, ecological buffer zones, and remote monitoring to harmonize development and conservation of peri-urban ecosystems.
Dynamics of surface water resource management towards fulfilling agricultural irrigation Sani, Inuwa Sani; Taqyuddin; Naabba, Aliyu Hassan
Applied Environmental Science Vol. 3 No. 2: (January) 2026
Publisher : Institute for Advanced Science, Social, and Sustainable Future

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61511/aes.v3i2.2026.2036

Abstract

Background: The dynamics of surface water resources and their influence on agriculture irrigation in Kano State, Nigeria, 2015-2025, are displayed in this research. This study aims to examine the influence of surface water availability changes on irrigation potential in semi-arid catchment. With looming uncertainty concerning water scarcity, particularly in Northern Nigeria, spatial-temporal dynamics of the surface water are critical to sustainable agriculture planning. Current studies have used satellite-based indices to monitor changes in water bodies and emphasized that such changes must be associated with climatic factors and land use patterns for irrigation development decision-making. Methods: Remote sensing data, including Normalized Difference Water Index (NDWI) from Landsat and Sentinel data, and rainfall data from the CHIRPS dataset, were used for the study. Spatiotemporal modeling methodology was used that included NDWI trend analysis, NDWI–rainfall relation, overlay with cover of cultivated land, and zonal statistics at the Local Government Area (LGA) level. Findings: Findings show that there is general surface wetness expansion in the southern and central regions of Kano State owing to enhanced irrigation activities, heightened water holding capacity, and possible aquifer recharge. Conclusion: The study concludes that water resource management in Kano must be specially crafted to overcome localized climatic stress conditions and spatial hydrological imbalance to facilitate sustainable irrigation under semi-arid conditions.Ground-truth verification is however absent, which limits the accuracy of surface wetness estimates, and future incorporation of field-based hydrological observations is recommended. The findings present actionable advice for policymakers on improving irrigation strategy formulation and adaptive water management in semi-arid climates. Novelty/Originality of this article: This research integrates satellite-based NDWI for the first time with rain anomaly and land use overlays to determine water body dynamics and their agricultural implications at sub-regional scales.
Harnessing artificial intelligence for census in Nigeria: Advancing accuracy, efficiency, and governance outcomes Sani, Inuwa Sani; Dimyati, Muhammad; Umar, Aliyu Aminu
Priviet Social Sciences Journal Vol. 5 No. 11 (2025): November 2025
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/pssj.v5i11.662

Abstract

Successful administration of national censuses in Nigeria has been a protracted agony plagued by inherent problems, including logistic, political, and methodological issues, which cumulatively have caused delays in enumeration, undercounting, and inconsistency of data. These defects diminish the credibility of demographic data needed for evidence-based governance, economic planning, and equitable resource allocation._. In this study, we explored opportunities for harnessing Artificial Intelligence (AI) to transform census activities in Nigeria through the injection of state-of-the-art computational approaches into the national enumeration exercise. We showcased a multimodal AI pipeline comprising Convolutional Neural Networks (CNNs) for population density estimation from satellite images, Natural Language Processing (NLP) pipelines for address standardization and matching in various languages, and unsupervised anomaly detection algorithms for real-time data quality verification. AI-based enumeration methods were simulated at both national and sub-national levels. CNN-generated heatmaps revealed population concentration trends in Lagos and other states and enabled the precise delineation of high-density urban agglomerations and underserved rural enclaves. The NLP tool generalized well to the linguistically diverse environments in Nigeria, with F1-scores greater than 0.90 for all but a few states for broken address reconciliation. Anomaly detection models built using Isolation Forest algorithms detected anomalous enumeration patterns as flags for potential undercounts or data manipulation. Population pyramid analysis for Lagos revealed an extremely young population structure, consistent with country-wide age trends. These findings provide empirical evidence that AI integration can promote census accuracy, operational efficiency and government effectiveness in Nigeria.
Co-Authors Adi Wibowo Imam, Mahmoud Zubair Muhammad Dimyati Naabba, Aliyu Hassan Taqyuddin Umar, Aliyu Aminu