https://journals.bilpubgroup.com/index.php/jbr <p>ISSN: 2630-5054(Online)</p> <p>Email: jbr@bilpublishing.com</p> en-US jbr@bilpublishing.com (Managing Editor ： Amy) ojs@bilpublishing.com (Amie) Fri, 28 Nov 2025 00:00:00 +0800 OJS 3.3.0.13 http://blogs.law.harvard.edu/tech/rss 60 https://journals.bilpubgroup.com/index.php/jbr/article/view/12523 <p>Vegetation health plays a critical role in sustaining ecosystem functions, particularly in regions experiencing climatic and environmental pressures. This study examined the effects of environmental factors on vegetation health across three ecologically diverse states in Nigeria, Kaduna, Benue, and Bayelsa, between 2014 and 2024. Using Normalized Difference Vegetation Index (NDVI) derived from satellite data, alongside soil temperature, soil moisture, and nitrogen dioxide (NO₂) concentrations, the study employed descriptive statistics, trend analysis, and multiple linear regression to assess spatial and temporal vegetation patterns and their determinants. Results revealed clear spatial variations in NDVI, with Bayelsa exhibiting the highest mean NDVI (0.528), followed by Benue (0.443), and Kaduna (0.391), reflecting ecological gradients from rainforest to savanna. Bayelsa maintained stable vegetation over time, Kaduna showed low and highly variable NDVI, while Benue displayed moderate seasonal fluctuations. Soil temperature emerged as the most significant predictor of NDVI in Kaduna (<em>p</em> = 0.026) and nearly significant in Bayelsa (<em>p</em> = 0.056), indicating its strong influence across ecological zones. Soil moisture and NO₂ showed no significant effects in any state, likely due to annual averaging and scale limitations. Regression models explained vegetation variability best in Kaduna (R² = 0.531), moderately in Bayelsa (R² = 0.458), and least in Benue (R² = 0.237). The study concludes that environmental variables, particularly temperature, strongly influence vegetation health in savanna regions, while human land-use practices may dominate in transitional zones. It recommends region-specific management strategies, seasonal monitoring of moisture, improved pollution data resolution, and integration of satellite data into vegetation management frameworks.</p> Favour Bright Iyalla, Miracle Uzoma, Keayiabarido Jude, Sobomate Chuku, Emmanuel Bakpo, Aroloye Numbere Copyright © 2025 Favour Bright Iyalla, Miracle Uzoma, Keayiabarido Jude, Sobomate Chuku, Emmanuel Bakpo, Aroloye Numbere https://creativecommons.org/licenses/by-nc/4.0 https://journals.bilpubgroup.com/index.php/jbr/article/view/12523 Fri, 28 Nov 2025 00:00:00 +0800