Monitoring of bark beetle "green" attack of Norway spruce using Planet Multispectral Imagery скачать в хорошем качестве

Monitoring of bark beetle "green" attack of Norway spruce using Planet Multispectral Imagery

Instagram: @resdinet Facebook:   / resdinet   ********************************************************** Norway spruce predisposition to bark beetle and monitoring of green attack phases using Planet Multispectral Imagery. Presentation by Aleksei Trubin at RESDiNET project workshop “Advances in new sensors and data processing development related to forest disturbance ecology” held at the Institute of Forest Ecology of the Slovak Academy of Sciences (IFE SAS) in Zvolen, Slovakia, on 22-23 February, 2023. Aleksei Trubin is a PhD student at the Faculty of Forestry and Wood Sciences of the Czech University of Life Sciences Prague, Czech Republic. *********************************************************** RESDiNET is an international research project funded by the European Research Executive Agency, Horizon Europe. The project enhances networking activities between research institution in Widening country (IFE SAS) and top-class counterparts at the EU level (Finnish Geospatial Research Institute, The University of Eastern Finland and Swedish University of Agricultural Sciences). The project builds on networking for excellence through knowledge transfer and exchange of best practices between involved institutions. The project establishes initial network and development of a new joint research project in novel RST applications in FDE. Rigorous analyses of severe insect-induced disturbances using novel RST is carried out in test areas representing different forest and climate types: mountain forests in Slovakia and boreal forests in Finland and Sweden. The project integrates in situ UAV and drone acquired remotely sensed data, existing multitemporal geospatial information and field data, particularly data on bark beetle population density, visible infestation symptoms linked to outbreak phases, and tree physiology parameters measured using electronic dendrometers or sapflow meters. The combined dataset are used to develop new tools for landscale-level early bark beetle attack identification and for designing bark beetle infestation risk assessment model. We draw on the latest advances in drone technologies and image analytical tools, including deep Convolutional Neural Networks based machine learning techniques and Artificial Intelligence algorithms. #remotesensing #forestdisturbance #forestdisturbanceecology #multispectralimagery #barkbeetle #barkbeetleoutbreak #remotesensors #remotelandmonitoring #earlydetection #barkbeetleinfestation #norwayspruce #barkbeetledisturbance #climatechange #drought #ipstypographus #piceaabies #tr eemortality #researchproject #horizoneurope #horizonwidera #euresearch #europeanresearch #forestecology #forestmanagement #urbanforest #finland #uef #coniferousforests