Local Knowledge Coupled with GIS and Remote Sensing in Landscape Analysis for Re-Greening and Rehabilitation of Degraded Lands in South Eastern Zone of Tigray, Northern Ethiopia.

The objective of this study is to analyze and evaluate the landscape pattern for re-greening and rehabilitating the degraded landscapes of Hidmo-myhaydi Village, south eastern zone of Tigray. For this study, a combination of remotely sensed data, field observations and information from local people were analyzed and used. Landsat imageries (1984-2009) of the study area were classified into five land use/cover (LULC) types using supervised image classification method with Maximum Likelihood classifier algorithm. Analysis of LULC change was done through a post classification change detection method. A rapid reduction in forest land cover was observed during the first (1984–2000) and second (1984–2009) transition periods by 4, and 2.5% respectively. Forest land increased in third transition period (2000–2009) by 1.6 %. Similarly, settlement land cover increased by 2.2%, 11.5% and 9.3% during the first, second and third periods respectively. Bare land declined by10.7, 14.5%, and 3.8 during the three periods, respectively. With the help of poly-scape, it becomes imperative to identify which trees to plant and where based on the capacity of a location to support plant growth. The analysis of local knowledge and prevailing biophysical conditions helps draw implications that would assist policy makers to decrease the vulnerability of rural farming communities to adverse impacts of LU/LC change and enabled to develop polyscape trade-off map.

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