Identifying spatiotemporal patterns of land use and land cover changes (LULCC) and their impacts on the natural environment is essential in policy decisions for effective, sustainable natural resource management solut...Identifying spatiotemporal patterns of land use and land cover changes (LULCC) and their impacts on the natural environment is essential in policy decisions for effective, sustainable natural resource management solutions. This study employed supervised image classification in Google Earth Engine (GEE) cloud-based platform to assess the land cover land use changes for the past 30 years (1989-2020), as well as predict the land cover states and the risk of future forest loss in the next ten years, using TerrSet 20 software in Hurungwe district, Zimbabwe. The study findings revealed a net forest area and shrub loss of 32% and 10%, while croplands, water bodies, and bare lands have increased by about 171%, 7%, and 119% between 1989 and 2020, respectively. Croplands are the major contributor to the net change in forests, particularly tobacco farming. The predictive model estimated that by 2030 the district would lose approximately 7% of the current forest cover area, most likely converted into croplands, shrubs, and settlements. The results reinforce the importance of bridging the gap between socioeconomic activities and institutional policies to ensure proper natural resource management. Integrating institutional policy and socioeconomic goals is indispensable to ensure sustainable development.展开更多
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 c...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 efects.Conclusions:The results of this study can be useful for formulating proper land use planning and investments to mitigate the adverse efect 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.展开更多
城市的快速扩张不断改变着土地资源的转化,带来了诸多生态环境问题。分析和模拟城市扩张的机制,并对城市未来土地利用变化的风险进行预警,利于合理调控城市的发展。本文提出了一种基于地理分区和未来用地模拟(Future Land Use Simulatio...城市的快速扩张不断改变着土地资源的转化,带来了诸多生态环境问题。分析和模拟城市扩张的机制,并对城市未来土地利用变化的风险进行预警,利于合理调控城市的发展。本文提出了一种基于地理分区和未来用地模拟(Future Land Use Simulation,FLUS)模型的城市扩张模拟模型,用于模拟和预测复杂的土地利用变化。该模型利用多指标数据进行空间聚类,耦合地理分区结果进行城市扩张模拟。珠江三角洲2005-2015年的城市扩张模拟结果显示,分区下的模拟精度(FoM=0.2329,提高了9%)明显高于未分区,说明不同分区在土地利用转化上存在空间差异,该模型能更有效地模拟城市土地利用变化。另外,本文构建了一种城市扩张预警指标评价体系,用于评估城市扩张的警情。根据在2005-2015基础上预测的2025-2045年土地利用变化结果,对珠江三角洲城市扩张进行多尺度预警分析。综合预警结果显示该区域大部分城市至2045年城市扩张警情将达到中警和重警,其中东莞警情一直维持在重警。由此,未来需要加强对珠三角城市扩张的宏观调控,以此来缓解未来城市扩张的警情。展开更多
文摘Identifying spatiotemporal patterns of land use and land cover changes (LULCC) and their impacts on the natural environment is essential in policy decisions for effective, sustainable natural resource management solutions. This study employed supervised image classification in Google Earth Engine (GEE) cloud-based platform to assess the land cover land use changes for the past 30 years (1989-2020), as well as predict the land cover states and the risk of future forest loss in the next ten years, using TerrSet 20 software in Hurungwe district, Zimbabwe. The study findings revealed a net forest area and shrub loss of 32% and 10%, while croplands, water bodies, and bare lands have increased by about 171%, 7%, and 119% between 1989 and 2020, respectively. Croplands are the major contributor to the net change in forests, particularly tobacco farming. The predictive model estimated that by 2030 the district would lose approximately 7% of the current forest cover area, most likely converted into croplands, shrubs, and settlements. The results reinforce the importance of bridging the gap between socioeconomic activities and institutional policies to ensure proper natural resource management. Integrating institutional policy and socioeconomic goals is indispensable to ensure sustainable development.
基金The International Foundation for Science had funded this research(IFS)(Grant No.W_6250-1,January 2019)and Bahir Dar University。
文摘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 efects.Conclusions:The results of this study can be useful for formulating proper land use planning and investments to mitigate the adverse efect 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.
文摘城市的快速扩张不断改变着土地资源的转化,带来了诸多生态环境问题。分析和模拟城市扩张的机制,并对城市未来土地利用变化的风险进行预警,利于合理调控城市的发展。本文提出了一种基于地理分区和未来用地模拟(Future Land Use Simulation,FLUS)模型的城市扩张模拟模型,用于模拟和预测复杂的土地利用变化。该模型利用多指标数据进行空间聚类,耦合地理分区结果进行城市扩张模拟。珠江三角洲2005-2015年的城市扩张模拟结果显示,分区下的模拟精度(FoM=0.2329,提高了9%)明显高于未分区,说明不同分区在土地利用转化上存在空间差异,该模型能更有效地模拟城市土地利用变化。另外,本文构建了一种城市扩张预警指标评价体系,用于评估城市扩张的警情。根据在2005-2015基础上预测的2025-2045年土地利用变化结果,对珠江三角洲城市扩张进行多尺度预警分析。综合预警结果显示该区域大部分城市至2045年城市扩张警情将达到中警和重警,其中东莞警情一直维持在重警。由此,未来需要加强对珠三角城市扩张的宏观调控,以此来缓解未来城市扩张的警情。
