The dataset provides raster gridded estimates of open water and inundated vegetation for the Barotseland Region in Western Zambia. There are a total of 55 images covering the period 2016-2019 at a spatial resolution of 10m. The images were generated using an automatic classification routine applied to Sentinel-1 radar imagery, with classification refinements made using ancillary datasets such as the Global Urban Footprint, and the Height Above Nearest Drainage terrain derivative generated using SRTM digital elevation data. These data are valuable for a range of applications including public health and water resources. Full details about this dataset can be found at https://doi.org/10.5285/4ef558d2-05d4-4ae2-988e-a5c2450b95dd

The dataset contains abundance data of airborne pollen (including Anthoxanthum odoratum (sweet vernal-grass), Arrhenatherum elatius (false oat-grass), Cynosurus cristatus (crested dog's-tail), Dactylis glomerata (cock's-foot), Lolium perenne (perennial ryegrass), Phleum pratense (Timothy), Poa pratensis (smooth meadow-grass), grass species within the genera Alopecurus/Agrostis, and one probe that was found to be degenerate and unable to discriminate grass species. Here we used qPCR to track the seasonal progression of airborne grass pollen, in time and space. To do this we collected aerial samples from thirteen sites across the UK during the pollen seasons (May to September) of 2016 and 2017. Full details about this dataset can be found at https://doi.org/10.5285/28208be4-0163-45e6-912c-2db205126925