A spatially explicit database of wind disturbances in European forests over the period 2000-2018

Strong winds may uproot and break trees and represent a major natural disturbance for European forests. Wind disturbances have intensified over the last decades globally and are expected to further rise in view of the effects of climate change. Despite the importance of such natural disturbances, there are currently no spatially explicit databases of wind-related impact at a pan-European scale. Here, we present a new database of wind disturbances in European forests (FORWIND). FORWIND is comprised of more than 80 000 spatially delineated areas in Europe that were disturbed by wind in the period 2000-2018 and describes them in a harmonized and consistent geographical vector format. The database includes all major windstorms that occurred over the observational period (e.g. Gudrun, Kyrill, Klaus, Xynthia and Vaia) and represents approximately 30% of the reported damaging wind events in Europe. Correlation analyses between the areas in FORWIND and land cover changes retrieved from the Landsat-based Global Forest Change dataset and the MODIS Global Disturbance Index corroborate the robustness of FORWIND. Spearman rank coefficients range between 0.27 and 0.48 (p value < 0.05). When recorded forest areas are rescaled based on their damage degree, correlation increases to 0.54. Wind-damaged growing stock volumes reported in national inventories (FORESTORM dataset) are generally higher than analogous metrics provided by FORWIND in combination with satellite-based biomass and country-scale statistics of growing stock volume. The potential of FORWIND is explored for a range of challenging topics and scientific fields, including scaling relations of wind damage, forest vulnerability modelling, remote sensing monitoring of forest disturbance, representation of uprooting and breakage of trees in large-scale land surface models, and hydrogeological risks following wind damage. Overall, FORWIND represents an essential and open-access spatial source that can be used to improve the understanding, detection and prediction of wind disturbances and the consequent impacts on forest ecosystems and the land-atmosphere system. Data sharing is encouraged in order to continuously update and improve FORWIND

A Spectral Database for the Recognition of Urban Objects in Kaunas City: Performance and Morphometric Issues

International audienceThe possibilities of use of urban objects spectral library as an important component of city’s knowledge database are extensive. They are used for the recognition, characterisation and identification of the urban objects and spaces in different towns. But their geographic accuracy is dependent on the study’s area, and possibilities of using in another city are often restricted. Use of urban objects spectral libraries is limited because of the sensors, the geographic and temporal variabilities of the object’s spectral signatures, the environmental conditions, or the remote sensing data. The difficulty of standardisation of the existing spectral databases and sensors fostered us to create a specific urban object spectral database for Kaunas. Despite the fact that spectral databases of urban objects have a low level of transposability to another urban territory, the specificity of the urban environment of Kaunas constitutes another main interest: the diversity of urban materials, contemporary and historical urban structures, urban planning peculiarities and spatial complexity of post-Soviet Baltic cities permitted the development of a "broad spectrum" object-oriented spectral database. The created spectral database was tested applying conventional artificial intelligence algorithms used in remote sensing and image processing. The results obtained on the recognition and characterization of urban materials and buildings are substantial. The performance of the recognition of built-up areas is improved with the use of the morphometric urban object database. The performance of the detection of urban vegetation is poor or average according to the species. This is due to the differences in the scalar level of the spectral measurements between the spectral library created and the spatial resolution of the airborne hyperspectral images

A spatially explicit database of wind disturbances in European forests over the period 2000-2018

Strong winds may uproot and break trees and represent a major natural disturbance for European forests. Wind disturbances have ntensified over the last decades globally and are expected to further rise in view of the effects of climate change. Despite the importance of such natural disturbances, there are currently no spatially explicit databases of wind-related impact at a pan-European scale. Here, we present a new database of wind disturbances in European forests (FORWIND). FORWIND is comprised of more than 80 000 spatially delineated areas in Europe that were disturbed by wind in the period 2000–2018 and describes them in a harmonized and consistent geographical vector format. The database includes all major windstorms that occurred over the observational period (e.g. Gudrun, Kyrill, Klaus, Xynthia and Vaia) and represents approximately 30 % of the reported damaging wind events in Europe. Correlation analyses between the areas in FORWIND and land cover changes retrieved from the Landsat-based Global Forest Change dataset and the MODIS Global Disturbance Index corroborate the robustness of FORWIND. Spearman rank coefficients range between 0.27 and 0.48 (p value < 0.05). When recorded forest areas are rescaled based on their damage degree, correlation increases to 0.54. Wind-damaged growing stock volumes reported in national inventories (FORESTORM dataset) are generally higher than analogous metrics provided by FORWIND in combination with satellite-based biomass and country-scale statistics of growing stock volume. The potential of FORWIND is explored for a range of challenging topics and scientific fields, including scaling relations of wind damage, forest vulnerability modelling, remote sensing monitoring of forest disturbance, representation of uprooting and breakage of trees in largescale land surface models, and hydrogeological risks following wind damage. Overall, FORWIND represents an essential and open-access spatial source that can be used to improve the understanding, detection and prediction of wind disturbances and the consequent impacts on forest ecosystems and the land–atmosphere system. Data sharing is encouraged in order to continuously update and improve FORWIND. The dataset is available at https://doi.org/10.6084/m9.figshare.9555008 (Forzieri et al., 2019)JRC.D.1-Bio-econom