SummaryThis dataset provides georeferenced occurrence records of Cortaderia selloana (pampas grass; hereafter C. selloana) across mainland Portugal, obtained from high-resolution imagery acquired by Uncrewed Aerial Vehicles (UAVs, or drones) during two campaigns in 2019 and 2020. This data was produced within the framework of the project LIFE17 NAT/ES/000495 – LIFE STOP CORTADERIA: Urgent measures for controlling the spread of Pampa Grass (Cortaderia selloana) in the Atlantic area. The dataset was generated under the contract “Acquisition of services for the elaboration of the cartography of the priority distribution areas of Cortaderia selloana in the study area and respective distribution analysis, prediction and trends” commissioned by the Municipality of Vila Nova de Gaia (Portugal) to ICETA/CIBIO-InBIO, Universidade do Porto.A total of 7,756 of aerial photographs were collected at 63 surveyed sites from Valença to Oeiras municipalities. 47,661 individual plants were georeferenced and plant diameter was annotated/estimated based on a circle encompassing the basal area at nadir projection. The number of plants per site ranged from 7 to 6,172 individuals. Plant densities ranged from 1 to 1,682 individuals per hectare. The average plant diameter was 1.5 m ± 0.8 m, with quantiles (25%, 50%, and 75%) at 0.9 m, 1.4 m, and 2.0 m, respectively.Dataset descriptionEach record corresponds to an individual C. selloana plant with a circle roughly encompassing its basal area observed at nadir in aerial images (i.e., orthomosaics), accompanied by its geographic coordinates (x/y of the centroid) and morphometric attributes (e.g., area, perimeter, estimated plant diameter). According to UAV-based surveys the presence of C. selloana was found in a wide range of disturbed and semi-natural environments, corresponding to the following general land-use and habitat types:Peri-urban industrial or post-industrial areas, including both active and abandoned sites with sparse or degraded vegetation cover;(Semi-)abandoned urban lots (“vacant” or “expectant” spaces) characterized by strong anthropogenic disturbance and colonization by ruderal vegetation;Road verges and adjacent areas, most frequently along embankments and highway access ramps;Other linear features, both artificial (e.g., railways) and natural (e.g., riverbanks and streams);Open semi-natural habitats such as shrublands or grasslands with low and discontinuous vegetation cover, often with exposed soil;Estuarine margins and sandbanks, notably in systems such as the Lima River and the Ria de Aveiro;Abandoned quarries, spoil heaps, and dumping sites showing clear evidence of anthropogenic disturbance;Gardens and landscaped areas, both public and private, where the species often occurs as an ornamental planting.The dataset provides a highly detailed spatial baseline for mapping, monitoring, and modelling the current extent of C. selloana invasion in coastal, peri-urban, industrial (or post-industrial) and urbanized areas of Portugal. It constitutes one of the most comprehensive fine-scale geospatial datasets of this invasive species to date and supports the development of predictive ecological models and management strategies aimed at invasive plant control.Use and applicationsThis dataset can be used to:Quantify the spatial extent and density of C. selloana invaded sites/populations;Validate and/or train species distribution or habitat suitability models;Support environmental management and restoration planning;Monitoring the invasion extent and abundance of C. selloana;Assess the environmental drivers of C. selloana abundance and distribution;Develop automated detection workflows for invasive species assessment and monitoring using satellite imagery and machine learning algorithms;Data availabilityThe dataset is publicly available via the Zenodo repository under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Users are required to cite the dataset, the authors of the data mentioned in this page and the LIFE STOP Cortaderia project in any derived work or publication.

SummaryThis dataset provides georeferenced occurrence records of Cortaderia selloana (pampas grass; hereafter C. selloana) across mainland Portugal, obtained from high-resolution imagery acquired by Uncrewed Aerial Vehicles (UAVs, or drones) during two campaigns in 2019 and 2020. This data was produced within the framework of the project LIFE17 NAT/ES/000495 – LIFE STOP CORTADERIA: Urgent measures for controlling the spread of Pampa Grass (Cortaderia selloana) in the Atlantic area. The dataset was generated under the contract “Acquisition of services for the elaboration of the cartography of the priority distribution areas of Cortaderia selloana in the study area and respective distribution analysis, prediction and trends” commissioned by the Municipality of Vila Nova de Gaia (Portugal) to ICETA/CIBIO-InBIO, Universidade do Porto.A total of 7,756 of aerial photographs were collected at 63 surveyed sites from Valença to Oeiras municipalities. 47,661 individual plants were georeferenced and plant diameter was annotated/estimated based on a circle encompassing the basal area at nadir projection. The number of plants per site ranged from 7 to 6,172 individuals. Plant densities ranged from 1 to 1,682 individuals per hectare. The average plant diameter was 1.5 m ± 0.8 m, with quantiles (25%, 50%, and 75%) at 0.9 m, 1.4 m, and 2.0 m, respectively.Dataset descriptionEach record corresponds to an individual C. selloana plant with a circle roughly encompassing its basal area observed at nadir in aerial images (i.e., orthomosaics), accompanied by its geographic coordinates (x/y of the centroid) and morphometric attributes (e.g., area, perimeter, estimated plant diameter). According to UAV-based surveys the presence of C. selloana was found in a wide range of disturbed and semi-natural environments, corresponding to the following general land-use and habitat types:Peri-urban industrial or post-industrial areas, including both active and abandoned sites with sparse or degraded vegetation cover;(Semi-)abandoned urban lots (“vacant” or “expectant” spaces) characterized by strong anthropogenic disturbance and colonization by ruderal vegetation;Road verges and adjacent areas, most frequently along embankments and highway access ramps;Other linear features, both artificial (e.g., railways) and natural (e.g., riverbanks and streams);Open semi-natural habitats such as shrublands or grasslands with low and discontinuous vegetation cover, often with exposed soil;Estuarine margins and sandbanks, notably in systems such as the Lima River and the Ria de Aveiro;Abandoned quarries, spoil heaps, and dumping sites showing clear evidence of anthropogenic disturbance;Gardens and landscaped areas, both public and private, where the species often occurs as an ornamental planting.The dataset provides a highly detailed spatial baseline for mapping, monitoring, and modelling the current extent of C. selloana invasion in coastal, peri-urban, industrial (or post-industrial) and urbanized areas of Portugal. It constitutes one of the most comprehensive fine-scale geospatial datasets of this invasive species to date and supports the development of predictive ecological models and management strategies aimed at invasive plant control.Use and applicationsThis dataset can be used to:Quantify the spatial extent and density of C. selloana invaded sites/populations;Validate and/or train species distribution or habitat suitability models;Support environmental management and restoration planning;Monitoring the invasion extent and abundance of C. selloana;Assess the environmental drivers of C. selloana abundance and distribution;Develop automated detection workflows for invasive species assessment and monitoring using satellite imagery and machine learning algorithms;Data availabilityThe dataset is publicly available via the Zenodo repository under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Users are required to cite the dataset, the authors of the data mentioned in this page and the LIFE STOP Cortaderia project in any derived work or publication.