| Autor: |
ADAMU, I. S., AIGBOKHAN, O. J., AGBOR, C. F., ORUNKOYI, A. R., OGOLIEGBUNE, O. M. |
| Zdroj: |
Journal of Applied Sciences & Environmental Management; 2021, Vol. 25 Issue 6, p917-925, 9p |
| Abstrakt: |
Forest stress or health has become a topic of serious interest to researchers in recent times. It reached a crescendo consequent upon the renewed interest in climate change's effects, resilience and mitigation. Forest stress is majorly a climate-related occurrence that can only be managed but not totally eradicated. Therefore, this study is aimed at assessing thermal induced stress in Akure forest reserve in Ondo State, Nigeria, using the instrumentality of Remote Sensing and Geographic Information System (GIS). The temperature data used for this study was extracted from Landsat 8 (OLI) imagery obtained from United States Geological Survey (USGS) database between the years 2016 and 2020. A land use land cover change detection analysis of the study area revealed that between 2016 and 2020, forest and water body decreased from 4344.59 to 2971.71 ha and 187.28 to 178.23 ha respectively while shrubs and bare land increased from 1472.13 to 2533.05 ha and 578.16 to 899.34 ha respectively. Forest stress and health of the study area was assessed using vegetation indices and land surface temperature LST). The result reveals changes in mean LST across the four lands cover types during the study period. It ranges between 22.28 °C (water body) in 2016 to 28.99 °C (bare land) in 2018. The spatial trend of Vegetation Health Index (VHI) was used to delineate the health of the forest. The study reveals that the spectral changes in the biophysical characteristics of the forest could not be solely attributed to temperature variability. Other climatic parameters and soil related variables must have contributed to notice stress in the forest reserve. However, this study has brought to the fore the robustness of geospatial technologies on the study of forest stress, health and drought. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
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