Forest Degradation Monitoring and Assessment of Biomass in Harenna Buluk Woreda, Bale Zone, Ethiopia, Using Remote Sensing and GIS Techniques
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Date
2017-06
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Addis Ababa Universty
Abstract
Forest is one of major natural resources, which play vital role in maintaining the ecological balance of nature. Detection of forest degradation with remote sensing remains a challenging field of study. Over utilization of forest resources has resulted in the depletion of forests resources. The present study was undertaken to monitor deforestation, forest degradation, and biomass estimation using remote sensing and GIS technology in Harenna Buluk Woreda in Ethiopia. Supervised classification technique was applied to Landsat images of 1995, 2005 and 2016. Satellite images were classified into different land-use/land-cover classes using maximum likelihood algorithm with the aid of field observations and Google Earth. Forest degradation was assessed using Object Based Image Analysis (OBIA) from Sentinel-2A satellite image. Results of this study has revealed that during, 1995–2016, forest and shrubland areas were decreased by 119.2 km2 (6.19%) and 12.1 km2 (0.62%), respectively. Farmland, bareland, grassland, settlement and water body were increased by 99.94 km2 (5.19%), 43.11 km2 (2.24%), 75.78 km2 (3.94%), 20.54 km2 (1.06%) and 6.93 km2 (0.36%), respectively. As a result, the biomass dramatically decreased. The Normalized Difference Vegetation Index (NDVI) value between years 1995 and 2016 was significantly decreased indicating that vegetation cover in the study area was highly disturbed. Results derived from the Sentinel-2A satellite image showed that there was significant decrease of forest area. The estimated degradation from the result of Sentinel-2A image classification during the year 2016 was 145.91 km2 (7.58%), while deforestation accounted for 171.39 km2 (8.91%) of the total study area. Thus, advanced satellite images are more useful to monitor forest cover and degradation process of natural habitats in the context of human related impacts.
Key words: Forest, Biomass, OBIA, Remote Sensing, GIS, Sentinel-2A, Forest Degradation
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Keywords
Forest, Biomass, OBIA, Remote Sensing, GIS, Sentinel-2A, Forest Degradation