Modeling Land-use Land-cover Dynamics Using Remote Sensing And Gis Techniques The Case Of Ambo Town

Land use and land cover change are complex and tremendously dynamic. Many scholars have analyzed the pattern over some time. Few scholars have tried to integrate spatially and cellular automata (CA) as dynamic discrete space and time systems. The purpose of this study was to monitor the land use and land cover dynamics of Ambo town and to model its future development under different scenarios using GIS & RS techniques. This research used GIS and remote sensing in mapping land use and land cover dynamics in Ambo Town between 1990 and 2020 to detect and analyze the dynamics that have taken in the Town between these portions of time. The data sets used were Landsat TM of 1990, Landsat ETM 2000, 2010, and Landsat 8 OLI 2020. The modeling used in the present study comes under having particular shared characteristics of ‘scenario models’. The maximum likelihood algorism of supervised image classifications is used to generate land-use land-cover maps and assessment of their dynamics. The cellular Automata Markov (CA-Markov) modeling approach was used to forecast land-use change for 2030. Analysis of Landsat image data of Ambo Town from 1990 – 2020 showed there are significant land use and land cover changes in the town. In 1990 forest, agricultural land, and built-up area covered 21.8 %, 60.19 %, and 13.73 % of the total area, respectively. Bare land constituted less than 5% of the area. However, in 2000, after a decade, the agricultural land area was declined to–16.0 8% while built-up area, forest, and bare land were increased to 8.84 %, 3.69%, and 3.62% respectively. In 2010, after three decades, bare land and built-up area constituted 2.94 % and 22.55% of the area, respectively. On the other hand, agricultural and bare land areas were decreased by 14.71% and 10.83% from 33.33 % to 22.5 % and 26.47% to 11.7% respectively. With existing conditions, the simulated LULC map of the year 2030 indicates the same trends that forestland and built-up areas will increase by 2.99 %, and 4.04 %, respectively whereas agricultural land and bare land areas will be decreased by 3.76%, and 2.82. Therefore, the government has to provide different innovative policy reform strategies/scenarios to overcome the business as usual scenario. As urban land use expanding to agricultural land and forest, alternative land use is disproportionality affected, due to this it has an impact on productivity and environmental service. Thus, the town administration has to devise a mechanism that reduces urban expansion.

Get Full Work

Report copyright infringement or plagiarism