{"title":"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","authors":"V. A. Ijaware","doi":"10.5897/ajest2023.3236","DOIUrl":null,"url":null,"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.","PeriodicalId":7483,"journal":{"name":"African Journal of Environmental Science and Technology","volume":"63 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Geospatial assessment of land surface temperature in Owo Forest Reserve Area, Ondo State Nigeria\",\"authors\":\"V. A. Ijaware\",\"doi\":\"10.5897/ajest2023.3236\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":7483,\"journal\":{\"name\":\"African Journal of Environmental Science and Technology\",\"volume\":\"63 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"African Journal of Environmental Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5897/ajest2023.3236\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"African Journal of Environmental Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5897/ajest2023.3236","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Geospatial assessment of land surface temperature in Owo Forest Reserve Area, Ondo State Nigeria
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.