Sandy forest-steppe ecotone in Baiyinaobao Natural Reserve of Inner Mongolia Autonomous Region of China is one of the special landscape types in forest-steppe vegetation zone in China. Vegetation landscape types, land...Sandy forest-steppe ecotone in Baiyinaobao Natural Reserve of Inner Mongolia Autonomous Region of China is one of the special landscape types in forest-steppe vegetation zone in China. Vegetation landscape types, landscape patches, and patch size were measured by the field investigation, forest photograph, and airscape. The structure of landscape patches in sandy forest-steppe ecotone, including composition structure, and size structure, was studied and the dynamics and transformation of landscape patches were analyzed. The data obtained in this study could provide theoretical basis for the research on vegetation landscape in forest-steppe ecotones and other vegetation types.展开更多
水生植被分布情况、结构和演变趋势对湿地生态环境变具有重要的指示意义和科学研究价值。基于Sentinel-2遥感数据,综合应用光谱信息、水体植被指数、最佳指数法(Optimal Index Factory,OIF)计算的纹理特征,结合随机森林分类法,构建特征...水生植被分布情况、结构和演变趋势对湿地生态环境变具有重要的指示意义和科学研究价值。基于Sentinel-2遥感数据,综合应用光谱信息、水体植被指数、最佳指数法(Optimal Index Factory,OIF)计算的纹理特征,结合随机森林分类法,构建特征优化后的随机森林水生植被提取模型,对于桥水库进行水生植被提取。结果显示:该方法能有效的提取出水生植被,总体精度为93.22%,Kappa系数为0.91。进一步与最大似然和支持向量机(SVM)方法进行对比分析,结果表明本算法的总体精度分别提高了19.96%、8.53%,Kappa系数分别提高了0.25、0.11。基于水生植被全年提取结果,分析了于桥水库的水生植被年内变化,发现于桥水库水生植被在五月份最繁盛,随后逐渐消减,直至十月份基本消亡。实验表明:特征优化后的随机森林分类法在Sentinel-2影像水生植被提取中具有较好的适用性。展开更多
Quantitative attribution at the individual pixel level of the relative contributions of climate variability and human activities to vegetation productivity dynamics across Africa is generally lacking.This is because o...Quantitative attribution at the individual pixel level of the relative contributions of climate variability and human activities to vegetation productivity dynamics across Africa is generally lacking.This is because of the difficulty in establishing a baseline or potential vegetation against which the relative impacts of these factors can be assessed.This study addresses these gaps.First,annual potential net primary productivity(NPP_(P))for 2000–2014 was estimated for Africa using a model constructed from samples of NPP and environmental covariates from protected areas.Second,trends in NPP_(P),actual NPP(NPP_(A)),and human-appropriated NPP(NPP_(H)=NPP P−NPP_(A))were estimated and used in quantifying the relative contributions of climate and human activities to NPP dynamics.Over 2000–2014,NPP improvement was largely concentrated in equatorial and northern Africa,while subequatorial Africa exhibited the most NPP decline.Parts of Mali,Burkina Faso,and the central Africa region are associated with the greatest influence of climate-driven NPP improvement.Areas where humans dominated NPP decline include parts of Ethiopia and South Africa.Climate had a stronger role in driving NPP decline in subequatorial Africa.Nonetheless,further work is required to validate the results of this study with high-resolution imagery and field information.展开更多
基金The paper is supported by National Nature Science Foundation of China (grant numbers: 39900019, and 30070129).
文摘Sandy forest-steppe ecotone in Baiyinaobao Natural Reserve of Inner Mongolia Autonomous Region of China is one of the special landscape types in forest-steppe vegetation zone in China. Vegetation landscape types, landscape patches, and patch size were measured by the field investigation, forest photograph, and airscape. The structure of landscape patches in sandy forest-steppe ecotone, including composition structure, and size structure, was studied and the dynamics and transformation of landscape patches were analyzed. The data obtained in this study could provide theoretical basis for the research on vegetation landscape in forest-steppe ecotones and other vegetation types.
文摘水生植被分布情况、结构和演变趋势对湿地生态环境变具有重要的指示意义和科学研究价值。基于Sentinel-2遥感数据,综合应用光谱信息、水体植被指数、最佳指数法(Optimal Index Factory,OIF)计算的纹理特征,结合随机森林分类法,构建特征优化后的随机森林水生植被提取模型,对于桥水库进行水生植被提取。结果显示:该方法能有效的提取出水生植被,总体精度为93.22%,Kappa系数为0.91。进一步与最大似然和支持向量机(SVM)方法进行对比分析,结果表明本算法的总体精度分别提高了19.96%、8.53%,Kappa系数分别提高了0.25、0.11。基于水生植被全年提取结果,分析了于桥水库的水生植被年内变化,发现于桥水库水生植被在五月份最繁盛,随后逐渐消减,直至十月份基本消亡。实验表明:特征优化后的随机森林分类法在Sentinel-2影像水生植被提取中具有较好的适用性。
文摘Quantitative attribution at the individual pixel level of the relative contributions of climate variability and human activities to vegetation productivity dynamics across Africa is generally lacking.This is because of the difficulty in establishing a baseline or potential vegetation against which the relative impacts of these factors can be assessed.This study addresses these gaps.First,annual potential net primary productivity(NPP_(P))for 2000–2014 was estimated for Africa using a model constructed from samples of NPP and environmental covariates from protected areas.Second,trends in NPP_(P),actual NPP(NPP_(A)),and human-appropriated NPP(NPP_(H)=NPP P−NPP_(A))were estimated and used in quantifying the relative contributions of climate and human activities to NPP dynamics.Over 2000–2014,NPP improvement was largely concentrated in equatorial and northern Africa,while subequatorial Africa exhibited the most NPP decline.Parts of Mali,Burkina Faso,and the central Africa region are associated with the greatest influence of climate-driven NPP improvement.Areas where humans dominated NPP decline include parts of Ethiopia and South Africa.Climate had a stronger role in driving NPP decline in subequatorial Africa.Nonetheless,further work is required to validate the results of this study with high-resolution imagery and field information.
