Buckthorns(Glossy buckthorn,Frangula alnus and common buckthorn,Rhamnus cathartica)represent a threat to biodiversity.Their high competitivity lead to the replacement of native species and the inhibition of forest reg...Buckthorns(Glossy buckthorn,Frangula alnus and common buckthorn,Rhamnus cathartica)represent a threat to biodiversity.Their high competitivity lead to the replacement of native species and the inhibition of forest regeneration.Early detection strategies are therefore necessary to limit invasive alien plant species’impacts,and remote sensing is one of the techniques for early invasion detection.Few studies have used phenological remote sensing approaches to map buckthorn distribution from medium spatial resolution images.Those studies highlighted the difficulty of detecting buckthorns in low densities and in understory using this category of images.The main objective of this study was to develop an approach using multi-date very high spatial resolution satellite imagery to map buckthorns in low densities and in the understory in the Québec city area.Three machine learning classifiers(Support Vector Machines,Random Forest and Extreme Gradient Boosting)were applied to WorldView-3,GeoEye-1 and SPOT-7 satellite imagery.The Random Forest classifier performed well(Kappa=0.72).The SVM and XGBoost’s coefficient Kappa were 0.69 and 0.66,respectively.However,buckthorn distribution in understory was identified as the main limit to this approach,and LiDAR data could be used to improve buckthorn mapping in similar environments.展开更多
本文以黄土高原临夏盆地巴谢河流域的上正滑坡为例,采用14C同位素年代学方法,结合文献查阅和实地走访,建立了该滑坡的多期次滑动的年代学框架。研究显示,上正滑坡至少经历了3个期次的活动:约33 ka B.P.,5~7 ka B.P.和距今约160年。这一...本文以黄土高原临夏盆地巴谢河流域的上正滑坡为例,采用14C同位素年代学方法,结合文献查阅和实地走访,建立了该滑坡的多期次滑动的年代学框架。研究显示,上正滑坡至少经历了3个期次的活动:约33 ka B.P.,5~7 ka B.P.和距今约160年。这一年龄框架与此滑坡的变形破坏特征和成因机理相结合,对认识滑坡的发展演化规律有着重要的意义。这一地区普遍存在的滑坡多期次的活动,能够对这一区域的地质构造和气候演化提供科学数据,对黄土-泥岩滑坡的成因机理和演化规律加深科学认识,并能对现今的地质灾害防治措施提供借鉴。展开更多
文摘Buckthorns(Glossy buckthorn,Frangula alnus and common buckthorn,Rhamnus cathartica)represent a threat to biodiversity.Their high competitivity lead to the replacement of native species and the inhibition of forest regeneration.Early detection strategies are therefore necessary to limit invasive alien plant species’impacts,and remote sensing is one of the techniques for early invasion detection.Few studies have used phenological remote sensing approaches to map buckthorn distribution from medium spatial resolution images.Those studies highlighted the difficulty of detecting buckthorns in low densities and in understory using this category of images.The main objective of this study was to develop an approach using multi-date very high spatial resolution satellite imagery to map buckthorns in low densities and in the understory in the Québec city area.Three machine learning classifiers(Support Vector Machines,Random Forest and Extreme Gradient Boosting)were applied to WorldView-3,GeoEye-1 and SPOT-7 satellite imagery.The Random Forest classifier performed well(Kappa=0.72).The SVM and XGBoost’s coefficient Kappa were 0.69 and 0.66,respectively.However,buckthorn distribution in understory was identified as the main limit to this approach,and LiDAR data could be used to improve buckthorn mapping in similar environments.
文摘本文以黄土高原临夏盆地巴谢河流域的上正滑坡为例,采用14C同位素年代学方法,结合文献查阅和实地走访,建立了该滑坡的多期次滑动的年代学框架。研究显示,上正滑坡至少经历了3个期次的活动:约33 ka B.P.,5~7 ka B.P.和距今约160年。这一年龄框架与此滑坡的变形破坏特征和成因机理相结合,对认识滑坡的发展演化规律有着重要的意义。这一地区普遍存在的滑坡多期次的活动,能够对这一区域的地质构造和气候演化提供科学数据,对黄土-泥岩滑坡的成因机理和演化规律加深科学认识,并能对现今的地质灾害防治措施提供借鉴。
