[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2528":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"view_count":31,"doi":32,"paper":33,"created_at":45},2528,"Assessment of Deforestation in Mbaav 1 Forest Reserve in Gwer East Local Government Area of Benue State, Nigeria","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fijaes.vol.11.no5.2025.pg28.42","The study investigates the ongoing issue of deforestation in Mbaav1 Forest Reserve, located in Gwer East Local Government Area (LGA), Benue State, Nigeria. Deforestation in the reserve is exacerbated by socio-economic factors such as agricultural expansion, population growth, logging, and development projects. Understanding these drivers is crucial for effective policy formulation and sustainable forest management. The primary aim of this study is to assess changes in forest cover in Mbaav1 Forest Reserve between 1989 and 2019, with particular emphasis on the socio-economic factors driving deforestation. The study specifically examines the socio-economic characteristics of local communities, land use changes, the extent of deforestation, and the key drivers of these changes. Data were collected using both primary and secondary methods. Primary data were gathered through semi-structured questionnaires and interviews with 387 community members, while secondary data were obtained from Landsat satellite imagery (1989, 2009, and 2019), For socio-economic analysis, simple descriptive statistics were used to present data on respondents' characteristics, including income, age, education, occupation, and household size. To examine the influence of socioeconomic factors on deforestation, a binary logistic regression model was adopted. Landsat satellite imageries were analyzed using Geographic Information Systems (GIS) and remote sensing tools. The supervised and unsupervised classification methods were used to detect and classify land cover changes. The Normalized Difference Vegetation Index (NDVI) was also used to map vegetation changes. The results of analysis revealed significant relationships between deforestation and factors such as income, population growth, developmental projects, and land-use activities. Notably, income had the highest influence on deforestation, with a unit increase in income leading to a 1.35 increase in deforestation (β = 1.35, p\u003C0.05). Population growth (β = 1.02, p\u003C0.05) and development projects (β = 0.77, p\u003C0.05) also significantly contributed to forest loss. Logging (β = 0.10, p\u003C0.05) and farming (β = 0.39, p\u003C0.05) further exacerbated deforestation, although to a lesser degree. The percentage of land cover change between 1989, 2009, and 2019 revealed a consistent decline in forest area. In 1989, the forest area covered 75.56% of the total land, but by 2019, this had dropped to 36.25%. Meanwhile, farmland increased from 5.86% in 1989 to 29.83% in 2019, reflecting the expansion of agricultural activities. The study concludes that the rapid deforestation in Mbaav1 Forest Reserve is driven by human activities, particularly agricultural expansion and logging, compounded by socio-economic pressures such as income and population growth. The study recommends that addressing these drivers through sustainable practices like agroforestry, improving forest management, and implementing policies that integrate forest conservation with agricultural development are essential. Furthermore, public awareness campaigns on the environmental and socio-economic consequences of deforestation are crucial for fostering community participation in conservation efforts.","本研究探讨了尼日利亚贝努埃州格韦尔东地方政府区（LGA）内Mbaav1森林保护区持续存在的毁林问题。农业扩张、人口增长、伐木和开发项目等社会经济因素加剧了该保护区的毁林。理解这些驱动因素对于有效制定政策和可持续森林管理至关重要。本研究的主要目的是评估1989年至2019年间Mbaav1森林保护区森林覆盖的变化，特别关注驱动毁林的社会经济因素。研究具体考察了当地社区的社会经济特征、土地利用变化、毁林程度以及这些变化的主要驱动因素。数据采用一手和二手方法收集。一手数据通过半结构化问卷和对387名社区成员的访谈获取，二手数据来自Landsat卫星影像（1989年、2009年和2019年）。在社会经济分析方面，采用简单描述性统计来呈现受访者特征数据，包括收入、年龄、教育程度、职业和家庭规模。为考察社会经济因素对毁林的影响，采用了二元逻辑回归模型。Landsat卫星影像使用地理信息系统（GIS）和遥感工具进行分析。采用监督分类和非监督分类方法检测和分类土地覆盖变化。归一化植被指数（NDVI）也被用于绘制植被变化图。分析结果显示，毁林与收入、人口增长、开发项目和土地利用活动等因素之间存在显著关系。值得注意的是，收入对毁林的影响最大，收入每增加一个单位，毁林增加1.35（β = 1.35，p\u003C0.05）。人口增长（β = 1.02，p\u003C0.05）和开发项目（β = 0.77，p\u003C0.05）也显著导致森林丧失。伐木（β = 0.10，p\u003C0.05）和耕作（β = 0.39，p\u003C0.05）进一步加剧了毁林，但程度较低。1989年、2009年和2019年间的土地覆盖变化百分比显示森林面积持续下降。1989年，森林面积占总土地的75.56%，但到2019年，这一比例降至36.25%。与此同时，农田从1989年的5.86%增加至",null,"INTERNATIONAL JOURNAL OF AGRICULTURE AND EARTH SCIENCE","2026-09-14T00:00:00Z","论文",10,false,61,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":17,"relevant":21,"comment":22},8,18,15,12,1,"基于Landsat与NDVI的30年森林覆盖变化实证研究，数据扎实但属尼日利亚地方案例，对国内三农信息化仅有方法借鉴价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"遥感监测","土地利用","农业扩张","森林保护","毁林治理",0,"10.56201\u002Fijaes.vol.11.no5.2025.pg28.42",{"doi":32,"openalex_id":34,"authors":35,"venue":10,"cited_by_count":31,"oa_url":9,"card":38,"direction":42,"ingested_from":44},"W7212586088",[36],{"name":37,"orcid":9},"I. Verinumbe",{"tldr":39,"method":40,"finding":41,"direction":42,"opportunity":43},"评估尼日利亚Mbaav1森林保护区1989-2019年森林砍伐，并分析其社会经济驱动因素。","Landsat影像、GIS与遥感分类、NDVI，结合387份问卷和二元逻辑回归。","森林覆盖率从75.56%降至36.25%，收入、人口增长和开发项目是主要驱动因素。","农业遥感与作物表型","可结合多源遥感与农户调查，在热带森林区构建社会经济-遥感耦合的砍伐预警模型。","openalex","2026-09-15T23:30:20.501919Z"]