scholarly journals Analysis of the Current and Future Prediction of Land Use/Land Cover Change Using Remote Sensing and the CA-Markov Model in Majang Forest Biosphere Reserves of Gambella, Southwestern Ethiopia

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Semegnew Tadese ◽  
Teshome Soromessa ◽  
Tesefaye Bekele
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Markov Model ◽  
Fire Risk ◽  
Land Use Land Cover ◽  
Fuel Wood ◽  
Biosphere Reserves ◽  
Southwestern Ethiopia ◽  
Wood Extraction ◽  
Land Use Plan

This study aimed to evaluate land use/land cover changes (1987–2017), prediction (2032–2047), and identify the drivers of Majang Forest Biosphere Reserves. Landsat image (TM, ETM+, and OLI-TIRS) and socioeconomy data were used for the LU/LC analysis and its drivers of change. The supervised classification was also employed to classify LU/LC. The CA-Markov model was used to predict future LU/LC change using IDRISI software. Data were collected from 240 households from eight kebeles in two districts to identify LU/LC change drivers. Five LU/LC classes were identified: forestland, farmland, grassland, settlement, and waterbody. Farmland and settlement increased by 17.4% and 3.4%, respectively; while, forestland and grassland were reduced by 77.8% and 1.4%, respectively, from 1987 to 2017. The predicted results indicated that farmland and settlement increased by 26.3% and 6.4%, respectively, while forestland and grassland increased by 66.5% and 0.8%, respectively, from 2032 to 2047. Eventually, agricultural expansion, population growth, shifting cultivation, fuel wood extraction, and fire risk were identified as the main drivers of LU/LC change. Generally, substantial LU/LC changes were observed and will continue in the future. Hence, land use plan should be proposed to sustain resource of Majang Forest Biosphere Reserves, and local communities’ livelihood improvement strategies are required to halt land conversion.

scholarly journals Simulation of changes in land-use/land cover on wetlands through CA-Markov model

2018 ◽  
Vol 11 (6) ◽  
pp. 2057-2066
Author(s):  
João Paulo Delapasse Simioni ◽  
Laurindo Antonio Guasselli
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Markov Model ◽  
Land Use Land Cover

Land Use Land Cover Dynamics in Ribb Watershed and Its Implication to the Sustainability of Ribb Dam

2019 ◽  
pp. 146-159
Author(s):  
Yidnekachew Jember
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Population Pressure ◽  
Land Use Land Cover ◽  
Fuel Wood ◽  
Grazing Land ◽  
Land Cover Dynamics ◽  
Widespread Phenomenon ◽  
Land Water

Land use land cover dynamics is a widespread phenomenon in many parts of Ethiopia and in Ribb watershed. The main objective of the research was assessing land use land cover dynamics and its implication to the sustainability of Ribb Dam in 1973, 1986, 2001, and 2016 by using Landsat image and household questioner. During the last 44 years, cultivated and settlement land and forest cover showed an increment from 26.29% to 54.89% and 9.45% to 12.86%, respectively. The bush land, grazing land, water body, and wetland, however, showed a relative decrement from 29.48% to 17.09%, 21.45% to 12.70%, 4.64% to 2.39%, and 8.70% to 0.08%, respectively. Population pressure, poverty, weak policy and institutional enforcement, and tenure insecurity revealed as a major cause of the change in land use land cover. Soil erosion, lack of fuel wood, and impact on livelihood are major consequences of land use land cover change.

scholarly journals Analysis and Projection of Land-Use/Land-Cover Dynamics through Scenario-Based Simulations Using the CA-Markov Model: A Case Study in Guanting Reservoir Basin, China

2020 ◽  
Vol 12 (9) ◽  
pp. 3747 ◽  
Author(s):  
Gebdang B. Ruben ◽  
Ke Zhang ◽  
Zengchuan Dong ◽  
Jun Xia
Keyword(s):  
Land Use ◽  
Sustainable Development ◽  
Land Cover ◽  
Markov Model ◽  
Water Body ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Guanting Reservoir ◽  
Reservoir Basin ◽  
Business As Usual

Understanding the rate and process of land-use/land-cover (LULC) change in a watershed is essential for managing natural resources and achieving sustainable development. Therefore, this study aims to analyze historical LULC change from 1980 to 2010 and project future changes in 2030, 2060, and 2090 in the Guanting Reservoir Basin (GRB), China, a critical water-supplying watershed for China’s capital Beijing, through scenario-based simulations. Two LULC scenarios, ‘business-as-usual’ and ‘governance’ (Gov), were projected using the Cellular Automata-Markov (CA–Markov) model. Historical LULC trend analysis shows that built-up land increased from 2.6% in 1980 to 5.26% in 2010, while cropland, grassland, and water body decreased. LULC conversion analysis indicates that, in general, grassland, cropland, and woodland were converted to built-up area from 1980 to 2010. The BAU scenario projects a dramatic increase in built-up area, rising from 2296.98 km2 (5.26%) in 2010 to 11,757.35 km2 (26.93%) in 2090 at the expense of cropland and grassland areas. Conversely, the Gov scenario predicts an increase in water body, woodland, and grassland, encouraging sustainable development. Overall, these results provide useful inputs to the LULC planners and water resources managers to elaborate on eco-friendly policies and regulations for GRB.

scholarly journals Landscape variables influencing forest fires in central Spain

2011 ◽  
Vol 20 (5) ◽  
pp. 678 ◽  
Author(s):  
José M. Moreno ◽  
Olga Viedma ◽  
Gonzalo Zavala ◽  
Belén Luna
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Resource Selection ◽  
Selection Index ◽  
Fire Risk ◽  
Land Cover Type ◽  
Land Use Land Cover ◽  
Central Spain ◽  
Landscape Variables ◽  
Cover Type

In assessing fire risk, it is important to determine whether all areas in a landscape burn at similar rates. This goal is complicated by the limitations of burned-area data and the temporally dynamic nature of landscapes. We assessed the differential degree of forest-fire burning for six landscape variables (land-use–land-cover type, distances to roads and towns, topography (slope, aspect, elevation)), each comprising several categories. The study area (95 × 55 km) was located in central Spain, and the study period covered 16 years. Landsat multispectral scanner images were used to annually map fire perimeters and to classify the landscape. We calculated an annual resource selection index for each category within a variable. The sizes and shapes of all fires occurring within a year were randomly distributed into the landscape 1000 times, and the corresponding resource selection index was calculated. This provided a null random-burning model against which we tested the actual resource selection index of the fires in each year. Pine woodlands showed consistent and significant positive fire selectivity, whereas deciduous woodlands showed consistent and significant negative selectivity. No differences in the resource selection indices of land-use–land-cover types were found between large (>100 ha) and small fires (<100 ha). Fires positively selected (resource selection index >1) areas at small or intermediate distances to towns and intermediate distances to roads. Selectivity for topographic variables was less marked. Our study demonstrates that landscape variables defining composition (land-use–land-cover type) or proximity to human influence are important factors for fire risk.

scholarly journals Analysis of the Future Land Use Land Cover Changes in the Gaborone Dam Catchment Using CA-Markov Model: Implications on Water Resources

2021 ◽  
Vol 13 (13) ◽  
pp. 2427
Author(s):  
Botlhe Matlhodi ◽  
Piet K. Kenabatho ◽  
Bhagabat P. Parida ◽  
Joyce G. Maphanyane
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Markov Model ◽  
Water Resource ◽  
Water Body ◽  
Environmental Changes ◽  
Resource Planning ◽  
Catchment Management ◽  
Land Use Land Cover ◽  
Lulc Changes

Land use/land cover (LULC) changes have been observed in the Gaborone dam catchment since the 1980s. A comprehensive analysis of future LULC changes is therefore necessary for the purposes of future land use and water resource planning and management. Recent advances in geospatial modelling techniques and the availability of remotely sensed data have become central to the monitoring and assessment of both past and future environmental changes. This study employed the cellular automata and Markov chain (CA-Markov) model combinations to simulate future LULC changes in the Gaborone dam catchment. Classified Landsat images from 1984, 1995, 2005 and 2015 were used to simulate the likely LULCs in 2015 and 2035. Model validation compared the simulated and observed LULCs of 2015 and showed a high level of agreement with Kappa variation estimates of Kno (0.82), Kloc (0.82) and Kstandard (0.76). Simulation results indicated a projected increase of 26.09%, 65.65% and 55.78% in cropland, built-up and bare land categories between 2015 and 2035, respectively. Reductions of 16.03%, 28.76% and 21.89% in areal coverage are expected for shrubland, tree savanna and water body categories, respectively. An increase in built-up and cropland areas is anticipated in order to meet the population’s demand for residential, industry and food production, which should be taken into consideration in future plans for the sustainability of the catchment. In addition, this may lead to water quality and quantity (both surface and groundwater) deterioration in the catchment. Moreover, water body reductions may contribute to water shortages and exacerbate droughts in an already water-stressed catchment. The loss of vegetal cover and an increase in built-up areas may result in increased runoff incidents, leading to flash floods. The output of the study provides useful information for land use planners and water resource managers to make better decisions in improving future land use policies and formulating catchment management strategies within the framework of sustainable land use planning and water resource management.

Sign in / Sign up

Export Citation Format

Share Document