##plugins.themes.bootstrap3.article.main##

Remote sensing and Geographic Information System (GIS) over the years play great role when integrated in the right way to study changes taken place on the planet. Most times, these changes are natural and beyond human interaction but often times too, the changes are occasioned by human factor in the search for development and daily survival. In achieving this, the forest is made to suffer unnecessarily thereby reducing its health status through excessive forest resources depletion. This study focusses on the monitoring of forest resource health in Akure forest reserve between 1972 and 2013 using Landsat MSS of 11/11/1972, Landsat TM of 17/12/1986, Landsat ETM+ of 03/01/2002, and Landsat ETM+ of 02/02/2013 downloaded from USGS website. Minimum Mahalanobis distance supervised classification was used to categorize land use pattern in the study area while ILWIS 3.2 Academic GIS was deployed to perform NDVI image classification analysis with a precision of 0.01m to determine the health status of the forest reserve. The analysis revealed that the total annual rate of depletion for 41 years stood at 2.46% while forest health status diminished during the study period as NDVI value ranged between -0.04to +0.44 (1972) to -1.0to +1.0 in 2013. The study recommends that open areas which are not homogeneous forest (shrub/grass land) detected in this study should be re-planted with varieties of tree species without delay to allow carbon sequestration for overall human benefits.

References

  1. V.A.J. Adekunle, J.O. Okunola, and D.O. Oke, “Management of forest ecosystem for food security and rural livelihood in South West Nigeria”, Final project Report for 2011 START Grants for Global Change Research in Africa. 2011, pp 143.
     Google Scholar
  2. J. R. Anderson, A land use and land cover classification system for use with remote sensor data Washington: US Government Printing Office, 1984, Vol. 964.
     Google Scholar
  3. O. Eludoyin, and O. O. Iyanda, (2018). Land cover change and forest management strategies in Ife nature reserve, Nigeria. GeoJournal. [Online]Available:https://www.researchgate.net/publication/327943944.
     Google Scholar
  4. G. O. Enaruvbe, and O. P. Atafo, “Analysis of deforestation pattern in the Niger Delta region of Nigeria” Journal of Land Use Science, vol 11(1), pp 113-130, 2016.
     Google Scholar
  5. Food and Agriculture Organization (FAO) (1990). Forest resources assessment, 1990: Tropical Countries. FAO Forestry paper 112, Rome, Italy.
     Google Scholar
  6. Forestry Association of Nigeria (FAN) (2014). Nigerian Forestry Information System. Available: at http://www.nfis.gov.ng/index.php/state-information/ondo-state290.
     Google Scholar
  7. I.A. Gbiri, and N.O. Adsoye, “Analysis of pattern of deforestation in Akure forest reserve, Ondo State”, Nigeria. Journal of Environmental Geography, vol 12(1-2), pp 1-11, 2019.
     Google Scholar
  8. B. Gorte, “Spatial Statistics for Remote Sensing: Description of data used in this book” In Stein, A.; Van der Meer, F.; and Gorte, B. (eds.). London: Kluwer Academic Publishers, 1999, pp. 3-8.
     Google Scholar
  9. I. A, Ikhuoria, I.I. Ero, and E. A. Ikhuoria, “Imperatives of space for sustainable forest management “Satellite detection and GIS analysis of lowland rainforest reserve reduction in Edo State, Nigeria”, In Salami, A.T (ed.). Abuja: Space Application and Environmental Science Laboratory, OAU, Ile- Ife, 2006, Pp. 72-93.
     Google Scholar
  10. T.M. Lillesand and R.W. Kiefer, “Remote Sensing and Image Interpretation” 3rd Edition. John Wiley & Sons, Inc., New York. 1994, pp. 750.
     Google Scholar
  11. National bureau of statistics (2017). Demographic Statistics Bulletin, 3rdediton [Online] Available: http://nigerianstat.gov.ng.
     Google Scholar
  12. O. O. I. Orimoogunje, “The impact of land use dynamics on Oluwa Forest Reserve in Southwestern, Nigeria”, Journal of Landscape Ecology, vol. 7(2), pp. 25–44, 2014.
     Google Scholar
  13. O. O. I. Orimoogunje, O. Ekanade, and F.A Adesina, “Land use changes and forest reserve management in a changing environment: South-western Nigeria Experience”, Journal of Geography and Regional Planning, vol. vol. 2(11), pp. 283-290, 2009.
     Google Scholar
  14. O.J. Pelemo, C. Adeosun, C.S, Osudiala, and A.C. Adetogun, (2011) “Assessment of growth Dynamics of tree species in SRN2, Akure forest reserves”, Nigeria Journal of research in forestry, wildlife, and environment vol. 3(2), pp. 6.
     Google Scholar
  15. A. T. Salami, “Vegetation dynamics on the fringes of lowland tropical rainforest of Southwestern Nigeria—An assessment of environmental change with Air Photos and Landsat TM”, International Journal of Remote Sensing, vol. 20(6), pp. 1169–1182, 1999.
     Google Scholar
  16. A. T. Salami, Monitoring Nigerian forest with Nigeriasat-1 and other satellite. In Ayobami T. Salami (eds)Imperatives of space technology for sustainable forest management in Nigeria. Ile-Ife: Space Applications & Environmental Science Laboratory, Obafemi Awolowo University, 2006.
     Google Scholar
  17. A. T. Salami, O. Ekaanade, and R. O. Oyinloye, (1999), “Detection of forest reserve incursion in south-western Nigeria from a combination of multi-date aerial photographs and high-resolution satellite”, imagery. International Journal of Remote Sensing, vol. 20(8), pp. 1487–1497, 1999.
     Google Scholar
  18. J. Weier and D. Herring, (2000). Measuring Vegetation (NDVI AND EVI): Feature Article, NASA Goddard Space Flight Center [Online] Available: http://m.earthobservatory.nasa.gov/Features/MeasuringVegetation/.
     Google Scholar
  19. World Bank (1991). Forest Sector Policy Paper. The World Bank. Washington. DC.
     Google Scholar