scholarly journals Modeling and Prediction of Land Use Land Cover Change Dynamics Based on Land Change Modeler (LCM) in Nashe Watershed, Upper Blue Nile Basin, Ethiopia

2021 ◽  
Vol 13 (7) ◽  
pp. 3740
Author(s):  
Megersa Kebede Leta ◽  
Tamene Adugna Demissie ◽  
Jens Tränckner

Change of land use land cover (LULC) has been known globally as an essential driver of environmental change. Assessment of LULC change is the most precise method to comprehend the past land use, types of changes to be estimated, the forces and developments behind the changes. The aim of the study was to assess the temporal and spatial LULC dynamics of the past and to predict the future using Landsat images and LCM (Land Change Modeler) by considering the drivers of LULC dynamics. The research was conducted in Nashe watershed (Ethiopia) which is the main tributary of the Upper Blue Nile basin. The total watershed area is 94,578 ha. The Landsat imagery from 2019, 2005, and 1990 was used for evaluating and predicting the spatiotemporal distributions of LULC changes. The future LULC image prediction has been generated depending on the historical trends of LULC changes for the years 2035 and 2050. LCM integrated in TerrSet Geospatial Monitoring and Modeling System assimilated with MLP and CA-Markov chain have been used for monitoring, assessment of change, and future projections. Markov chain was used to generate transition probability matrices between LULC classes and cellular automata were used to predict the LULC map. Validation of the predicted LULC map of 2019 was conducted successfully with the actual LULC map. The validation accuracy was determined using the Kappa statistics and agreement/disagreement marks. The results of the historical LULC depicted that forest land, grass land, and range land are the most affected types of land use. The agricultural land in 1990 was 41,587.21 ha which increased to 57,868.95 ha in 2019 with an average growth rate of 39.15%. The forest land, range land, and grass land declined annually with rates of 48.38%, 19.58%, and 26.23%, respectively. The predicted LULC map shows that the forest cover will further degrade from 16.94% in 2019 to 8.07% in 2050, while agricultural land would be expanded to 69,021.20 ha and 69,264.44 ha in 2035 and 2050 from 57,868.95 ha in 2019. The findings of this investigation indicate an expected rapid change in LULC for the coming years. Converting the forest area, range land, and grass land into other land uses, especially to agricultural land, is the main LULC change in the future. Measures should be implemented to achieve rational use of agricultural land and the forest conversion needs to be well managed.

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Tatek Belay ◽  
Daniel Ayalew Mengistu

Abstract Background Soil erosion is one of the major threats in the Ethiopian highlands. In this study, soil erosion in the Muga watershed of the Upper Blue Nile Basin (Abay) under historical and future climate and land use/land cover (LULC) change was assessed. Future LULC was predicted based on LULC map of 1985, 2002, and 2017. LULC maps of the historical periods were delineated from Landsat images, and future LULC was predicted using the CA–Markov chain model. Precipitation for the future period was projected from six regional circulation models. The RUSLE model was used to estimate the current and future soil erosion rate in Muga watershed. Results The average annual rate of soil erosion in the study area was increased from about 15 t ha−1 year−1 in 1985 to 19 t ha−1 year−1 in 2002, and 19.7 t ha−1 year−1 in 2017. Expansion of crop cultivation and loss of vegetation caused an increase in soil erosion. Unless proper measure is taken against the LULC changes, the rate of soil loss is expected to increase and reach about 20.7 t ha−1 year−1 in 2033. In the 2050s, soil loss is projected to increase by 9.6% and 11.3% under RCP4.5 and RCP8.5, respectively, compared with the baseline period. Thus, the soil loss rate is expected to increase under both scenarios due to the higher erosive power of the future intense rainfall. When both LULC and climate changes act together, the mean annual soil loss rate shows a rise of 13.2% and 15.7% in the future under RCP4.5 and RCP8.5, respectively, which is due to synergistic effects. Conclusions The results of this study can be useful for formulating proper land use planning and investments to mitigate the adverse effect of LULC on soil loss. Furthermore, climate change will exacerbate the existing soil erosion problem and would need for vigorous proper conservation policies and investments to mitigate the negative impacts of climate change on soil loss.


2018 ◽  
Vol 10 (10) ◽  
pp. 3421 ◽  
Author(s):  
Rahel Hamad ◽  
Heiko Balzter ◽  
Kamal Kolo

Multi-temporal Landsat images from Landsat 5 Thematic Mapper (TM) acquired in 1993, 1998, 2003 and 2008 and Landsat 8 Operational Land Imager (OLI) from 2017, are used for analysing and predicting the spatio-temporal distributions of land use/land cover (LULC) categories in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq. The aim of this article was to explore the LULC dynamics in the HSCZ to assess where LULC changes are expected to occur under two different business-as-usual (BAU) assumptions. Two scenarios have been assumed in the present study. The first scenario, addresses the BAU assumption to show what would happen if the past trend in 1993–1998–2003 has continued until 2023 under continuing the United Nations (UN) sanctions against Iraq and particularly Kurdistan region, which extended from 1990 to 2003. Whereas, the second scenario represents the BAU assumption to show what would happen if the past trend in 2003–2008–2017 has to continue until 2023, viz. after the end of UN sanctions. Future land use changes are simulated to the year 2023 using a Cellular Automata (CA)-Markov chain model under two different scenarios (Iraq under siege and Iraq after siege). Four LULC classes were classified from Landsat using Random Forest (RF). Their accuracy was evaluated using κ and overall accuracy. The CA-Markov chain method in TerrSet is applied based on the past trends of the land use changes from 1993 to 1998 for the first scenario and from 2003 to 2008 for the second scenario. Based on this model, predicted land use maps for the 2023 are generated. Changes between two BAU scenarios under two different conditions have been quantitatively as well as spatially analysed. Overall, the results suggest a trend towards stable and homogeneous areas in the next 6 years as shown in the second scenario. This situation will have positive implication on the park.


BMC Ecology ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yeneayehu Fenetahun ◽  
Wang Yong-dong ◽  
Yuan You ◽  
Xu Xinwen

Abstract Background The gradual conversion of rangelands into other land use types is one of the main challenges affecting the sustainable management of rangelands in Teltele. This study aimed to examine the changes, drivers, trends in land use and land cover (LULC), to determine the link between the Normalized Difference Vegetation Index (NDVI) and forage biomass and the associated impacts of forage biomass production dynamics on the Teltele rangelands in Southern Ethiopia. A Combination of remote sensing data, field interviews, discussion and observations data were used to examine the dynamics of LULC between 1992 and 2019 and forage biomass production. Results The result indicate that there is a marked increase in farm land (35.3%), bare land (13.8%) and shrub land (4.8%), while the reduction found in grass land (54.5%), wet land (69.3%) and forest land (10.5%). The larger change in land observed in both grassland and wetland part was observed during the period from 1995–2000 and 2015–2019, this is due to climate change impact (El-Niño) happened in Teltele rangeland during the year 1999 and 2016 respectively. The quantity of forage in different land use/cover types, grass land had the highest average amount of forage biomass of 2092.3 kg/ha, followed by wetland with 1231 kg/ha, forest land with 1191.3 kg/ha, shrub land with 180 kg/ha, agricultural land with 139.5 kg/ha and bare land with 58.1 kg/ha. Conclusions The significant linkage observed between NDVI and LULC change types (when a high NDVI value, the LULC changes also shows positive value or an increasing trend). In addition, NDVI value directly related to the greenness status of vegetation occurred on each LULC change types and its value directly linkage forage biomass production pattern with grassland land use types. 64.8% (grass land), 43.3% (agricultural land), 75.1% (forest land), 50.6% (shrub land), 80.5% (bare land) and 75.5% (wet land) more or higher dry biomass production in the wet season compared to the dry season.


2020 ◽  
Vol 31 (15) ◽  
pp. 2168-2184
Author(s):  
Marye Belete ◽  
Jinsong Deng ◽  
Ghali A. Abubakar ◽  
Menberu Teshome ◽  
Ke Wang ◽  
...  

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