As part of the ESA Land Cover Climate Change Initiative (CCI) project a static map of open water bodies at 150 m spatial resolution at the equator has been produced. The CCI WB v4.0 is composed of two layers: 1. A static map of open water bodies at 150 m spatial resolution resulting from a compilation and editions of land/water classifications: the Envisat ASAR water bodies indicator, a sub-dataset from the Global Forest Change 2000 - 2012 and the Global Inland Water product. This product is delivered at 150 m as a stand-alone product but it is consistent with class "Water Bodies" of the annual MRLC (Medium Resolution Land Cover) Maps. The product was resampled to 300 m using an average algorithm. Legend : 1-Land, 2-Water 2. A static map with the distinction between ocean and inland water is now available at 150 m spatial resolution. It is fully consistent with the CCI WB-Map v4.0. Legend: 0-Ocean, 1-Land. To cite the CCI WB-Map v4.0, please refer to : Lamarche, C.; Santoro, M.; Bontemps, S.; D’Andrimont, R.; Radoux, J.; Giustarini, L.; Brockmann, C.; Wevers, J.; Defourny, P.; Arino, O. Compilation and Validation of SAR and Optical Data Products for a Complete and Global Map of Inland/Ocean Water Tailored to the Climate Modeling Community. Remote Sens. 2017, 9, 36. https://doi.org/10.3390/rs9010036

As part of the ESA Land Cover Climate Change Initiative (CCI) project a set of Global Land Cover Maps have been produced. These are available at 300m spatial resolution for three epochs centred on the year 2010 (2008-2012), 2005 (2003-2007) and 2000 (1998-2002), where each epoch covers a 5-year period. Each pixel value corresponds to the label of a land cover class defined using UN-LCCS classifiers. For each epoch, the land cover map is delivered along with 4 quality flags which document the reliability of the classification. These are described further in the Product User Guides. Further Land Cover CCI products, user tools and a product viewer are available at: http://maps.elie.ucl.ac.be/CCI/viewer/index.php

As part of the ESA Land Cover Climate Change Initiative (CCI) project a new set of Global Land Cover Maps have been produced. These maps are available at 300m spatial resolution for each year between 1992 and 2015. Each pixel value corresponds to the classification of a land cover class defined based on the UN Land Cover Classification System (LCCS). The reliability of the classifications made are documented by the four quality flags (decribed further in the Product User Guide) that accompany these maps. Data are provided in both NetCDF and GeoTiff format. Further Land Cover CCI products, user tools and a product viewer are available at: http://maps.elie.ucl.ac.be/CCI/viewer/index.php . Maps for the 2016-2020 time period have been produced in the context of the Copernicus Climate Change service, and can be downloaded from the Copernicus Climate Data Store (CDS).

Land cover of Signy Island, consisting of rock outcrop, moraine, lakes, permanent ice and streams. All data were manually digitised from a VHR (very high resolution) satellite image acquired on the 10th February 2020. WorldView-2 satellite image (c) 2020 Maxar Technologies. The datasets are available as polygon and point shapefiles and GeoPackages. The data were created to support the updated release of the British Antarctic Survey (BAS) Signy Island map (BAS, 2024)

Bird4pop is a process-based model, written in R, that simulates the foraging, dispersal and population processes of nidicolous passerines. It accounts for both amount and configuration of habitat resources to predict spatially-explicit relative abundance and foraging rates, for a given input landscape. The input landcover information must be in raster format. The model can ingest a base landcover raster as well as edgecover rasters, which represent the locations of small habitat features that occupy only a fraction of a pixel. Model outputs are raster stacks with the same spatial extent and resolution as the input landcover raster. The bird4pop model was co-developed by the UK Centre for Ecology & Hydrology and the British Trust for Ornithology. It has been parameterised for seven UK birds/bird groups (woodland specialists, woodland generalists, edge-nesting farmland birds, skylark (Alauda arvensis) – an open-nesting farmland bird, nuthatch (Sitta europaea) – a woodland specialist, robin (Erithacus rubecula) – a woodland generalist, yellowhammer (Emberiza citrinella) – an edge-nesting farmland bird). These parameter files (bird_guild_params.csv and bird_habitat_params.csv) are included. The model’s predictions have been validated against observations of these birds/bird groups collected across Great Britain through the BTO/RSPB/JNCC Breeding Bird Survey. Data in bird_guild_params.csv includes movement ranges (breeding season foraging range, juvenile dispersal range in meters), population growth parameters (nest density per ha, mean number of chicks produced per year, growth parameters in arbitrary units) and survival parameters (yearly adult survival probability, yearly juvenile survival probability) for seven birds/bird groups (woodland specialists, woodland generalists, edge-nesting farmland birds, skylark – an open-nesting farmland bird, nuthatch – a woodland specialist, robin – a woodland generalist, yellowhammer – an edge-nesting farmland bird), used in bird4pop model. Data in bird_habitat_params consists of scores representing the relative availability of suitable nest sites (on a scale from 0-1, where 0 = none and 1 = very high) and the relative availability of foraging resources during the breeding season (on a scale from 0-5, where 0 = none and 5 = very high) for four bird groups (woodland specialists, woodland generalists, edge-nesting farmland birds, skylark – an open-nesting farmland bird) and the 78 landcover classes, used in bird4pop model. Given scores are the mean values across n contributing experts. The data also include the number of contributing experts, the standard error on the mean score, and the alpha and beta values that describe a beta distribution consistent with the measured mean and variance for each score. This model is intended to help support understanding of how birds might be using landscapes. No decisions should ever be made solely on the basis of this model’s predictions – on-the-ground ecological surveys and integration of local knowledge are always required before any landscape-level or site-level decisions are made, due to real-life bird activity levels potentially differing from predicted levels. Users are recommended to get in touch with the model developers to ensure they have the most up-to-date version of the code and to receive support on model use and interpretation. Full details about this application can be found at https://doi.org/10.5285/985691ce-e66b-416a-bb85-fc9ad0eca6ed