It is evident that forests have been managed for several years in the world, but in most cases especially in the developing world, various regimes have tried to come up with an institutional framework to guide forest management with no much success due to lack of forest monitoring systems. The study entailed detecting forest degradation and modeling forest future scenarios. Analysis of Satellite imagery provided spatial temporal data with ground truthing exercise using Global positioning system was used for data validation. Population census data showing trends of population change over the study period was used to study relationship between population growth and forest trends. The study gave detailed data for the Embobut forest cover, data on trends of forest cover the relationship between forest and population change. The resultant data was used to project future forest scenarios for Embobut forest. The major forest cover types in the study area are; Cupressus lusitanica, Mixed Podocarpus latifolius, Juniperus-Nuxia-Podocarpus factus, Tree ferns Cyathea manniana and Bamboo and Acacia abyssinica and Scrabby grassland, there is also Bare land and rocky and Water Bodies. Cupressus lusitanica, Bare land and rocky and Water Bodies recorded positive changes while all other forest classes decreased in size. The study found a loss of 7,172.31 hectares or 28% forest loss over the study period study period-1986-2011. The study found that deforestation increased as population grew. Cohen’s coefficient showed that the predominant forest class in 2020 will be Tree ferns Cyathea manniana and Bamboo, the land cover that will have the highest increase will be Cupressus lusitanica with additional about 4 000 hectares. In the years 2050 and 2100 Podocarpus latifolius, JuniperusNuxia-Podocarpus factus, Acacia abyssica and Scrabby will reduce in size though they remain to be the highest land cover types by 65%, most of the reduction will be due to increase in Cupressus lusitanica, which will cover additional about 5 977 hectares by the year 2050 with a decline to 1 507 hectares by the year 2100. The land cover classes bare land and Rocky will also increase by 2% by the year 2100. The study therefore recommends that reforestation of the areas that were previously forested and to avoid the dominance few land cover types, efforts for reforestation to consider the use of native tree species on their respective ecosystems to retain the indigenous forest types in the study area. For further studies, the researcher recommends inclusion of socio-economical surveys which will capture the demand for forest and forestry products like fuel wood, timber, poles and animal feed.
ISAAC, K (2021). Spatio-Temporal Degradation Detection And Modeling Future Scenarios Of Embobut Forest In Elgeyo Marakwet County, Kenya. Afribary. Retrieved from https://afribary.com/works/spatio-temporal-degradation-detection-and-modeling-future-scenarios-of-embobut-forest-in-elgeyo-marakwet-county-kenya
ISAAC, KIPKEMOI "Spatio-Temporal Degradation Detection And Modeling Future Scenarios Of Embobut Forest In Elgeyo Marakwet County, Kenya" Afribary. Afribary, 28 May. 2021, https://afribary.com/works/spatio-temporal-degradation-detection-and-modeling-future-scenarios-of-embobut-forest-in-elgeyo-marakwet-county-kenya. Accessed 22 Feb. 2024.
ISAAC, KIPKEMOI . "Spatio-Temporal Degradation Detection And Modeling Future Scenarios Of Embobut Forest In Elgeyo Marakwet County, Kenya". Afribary, Afribary, 28 May. 2021. Web. 22 Feb. 2024. < https://afribary.com/works/spatio-temporal-degradation-detection-and-modeling-future-scenarios-of-embobut-forest-in-elgeyo-marakwet-county-kenya >.
ISAAC, KIPKEMOI . "Spatio-Temporal Degradation Detection And Modeling Future Scenarios Of Embobut Forest In Elgeyo Marakwet County, Kenya" Afribary (2021). Accessed February 22, 2024. https://afribary.com/works/spatio-temporal-degradation-detection-and-modeling-future-scenarios-of-embobut-forest-in-elgeyo-marakwet-county-kenya