Geospatial assessment of land surface temperature in Owo Forest Reserve Area, Ondo State Nigeria

V. A. Ijaware
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Abstract

Nigeria forest reserves acts as the last succour for the entire citizenry and also have significant contributions to her economy. This study was intended at assessing the Land Surface Temperature (LST) in Owo Forest Reserve Area (FRA) with a view for sustainable forest management. The objectives set for the research includes: (i.) assessing the vegetation changes in Owo FRA, (ii.) evaluate the LST and (iii.) relate changes in vegetation cover to LST to ascertain whether the observed difference in vegetation cover have noticeable effect and contribution to LST values obtained in Owo FRA. Recorded spatial coordinates of selected points constitute the primary data while the secondary data includes: Operational Landsat Imager, Enhanced Thematic Mapper, and Thematic Mapper of different years (1991, 2002, 2014 and 2020). Specifically, thermal bands of Landsat image and Normalized Difference Vegetation Index were utilized for mapping the LST. Various data acquired was processed and predicted to 2030 using Markov chain model. The results obtained showed that dense and moderate vegetation has been decreasing while non vegetation and sparse vegetation also increased for the period of studies. Again, the results garnered from 1991 to 2020 revealed that areas with vegetation (Dense, moderate and sparse) had low LST values as the forecast LST for the year 2030 are in the purview of 31.33°C(minimum) and 38.29°C (maximum). The research recommends significant increase in the rate of tree planting and preserving green areas to mitigate upsurge of LST while upholding the tenacity of laws guiding illegal logging.
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尼日利亚翁多州奥沃森林保护区地表温度的地理空间评估
尼日利亚的森林保护区是全体国民的最后依靠,也对其经济做出了重大贡献。本研究旨在评估奥沃森林保护区(FRA)的地表温度(LST),以促进可持续森林管理。研究目标包括(i.) 评估奥沃森林保护区的植被变化;(ii.) 评估地表温度;(iii.) 将植被变化与地表温度联系起来,以确定观察到的植被差异是否对奥沃森林保护区的地表温度值有明显影响和贡献。选定点的空间坐标记录构成主要数据,次要数据包括不同年份(1991 年、2002 年、2014 年和 2020 年)的陆地卫星业务成像仪、增强型专题成像仪和专题成像仪。具体而言,大地遥感卫星图像的热波段和归一化植被指数被用于绘制 LST 图。利用马尔科夫链模型对获取的各种数据进行处理并预测到 2030 年。研究结果表明,在研究期间,密集植被和中等植被在减少,而非植被和稀疏植被在增加。同样,从 1991 年到 2020 年收集的结果显示,有植被的地区(茂密、中等和稀疏)的低温层值较低,2030 年的预测低温层最低温度为 31.33°C,最高温度为 38.29°C。研究建议大幅提高植树率,保护绿地,以缓解 LST 的急剧升高,同时维护法律对非法采伐的顽强管控。
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