Italian Ragweed Pollen Inventory

This study provides the first spatially detailed and complete inventory of Ambrosia pollen sources in Italy – the third largest centre of ragweed in Europe. The inventory relies on a well tested top-down approach that combines local knowledge, detailed land cover, pollen observations and a digital elevation model that assumes permanent ragweed populations mainly grow below 745m. The pollen data were obtained from 92 volumetric pollen traps located throughout Italy during 2004-2013. Land cover is derived from Corine Land cover information with 100m resolution. The digital elevation model is based on the NASA shuttle radar mission with 90m resolution. The inventory is produced using a combination of ArcGIS and Python for automation and validated using cross-correlation and has a final resolution of 5km x 5km. The method includes a harmonization of the inventory with other European inventories for the Pannonian Plain, France and Austria in order to provide a coherent picture of all major ragweed sources. The results show that the mean annual pollen index varies from 0 in South Italy to 6779 in the Po Valley. The results also show that very large pollen indexes are observed in the Milan region, but this region has smaller amounts of ragweed habitats compared to other parts of the Po Valley and known ragweed areas in France and the Pannonian Plain. A significant decrease in Ambrosia pollen concentrations was recorded in 2013 by pollen monitoring stations located in the Po Valley, particularly in the Northwest of Milan. This was the same year as the appearance of the Ophraella communa leaf beetle in Northern Italy. These results suggest that ragweed habitats near to the Milan region have very high densities of Ambrosia plants compared to other known ragweed habitats in Europe. The Milan region therefore appears to contain habitats with the largest ragweed infestation in Europe, but a smaller amount of habitats is a likely cause the pollen index to be lower compared to central parts of the Pannonian Plain. A low number of densely packed habitats may have increased the impact of the Ophraella beetle and might account for the documented decrease in airborne Ambrosia pollen levels, an event that cannot be explained by meteorology alone. Further investigations that model atmospheric pollen before and after the appearance of the beetle in this part of Northern Italy are needed to assess the influence of the beetle on airborne Ambrosia pollen concentrations. Future work will focus on short distance transport episodes for stations located in the Po Valley, and long distance transport events for stations in Central Italy that exhibit peaks in daily airborne Ambrosia pollen levels.

Quantifying Submerged Fluvial Topography Using Hyperspatial Resolution UAS Imagery and Structure From Motion Photogrammetry.

Quantifying the topography of rivers and their associated bedforms has been a fundamental concern of fluvial geomorphology for decades. Such data, acquired at high temporal and spatial resolutions, are increasingly in demand for process-oriented investigations of flow hydraulics, sediment dynamics and in-stream habitat. In these riverine environments, the most challenging region for topographic measurement is the wetted, submerged channel. Generally, dry bed topography and submerged bathymetry are measured using different methods and technology. This adds to the costs, logistical challenges and data processing requirements of comprehensive river surveys. However, some technologies are capable of measuring the submerged topography. Through-water photogrammetry and bathymetric LiDAR are capable of reasonably accurate measurements of channel beds in clear water. Whilst the cost of bathymetric LiDAR remains high and its resolution relatively coarse, the recent developments in photogrammetry using Structure from Motion (SfM) algorithms promise a fundamental shift in the accessibility of topographic data for a wide range of settings. Here we present results demonstrating the potential of so called SfM-photogrammetry for quantifying both exposed and submerged fluvial topography at the mesohabitat scale. We show that imagery acquired from a rotary-winged Unmanned Aerial System (UAS) can be processed in order to produce digital elevation models (DEMs) with hyperspatial resolutions (c. 0.02 m) for two different river systems over channel lengths of 50-100 m. Errors in submerged areas range from 0.016 m to 0.089 m, which can be reduced to between 0.008 m and 0.053 m with the application of a simple refraction correction. This work therefore demonstrates the potential of UAS platforms and SfM-photogrammetry as a single technique for surveying fluvial topography at the mesoscale (defined as lengths of channel from c.10 m to a few hundred metres). This article is protected by copyright. All rights reserved.