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[{'author': None, 'author_email': None, 'creator_user_id': '64e47517-dce0-4a13-9ab7-ef1cfcd1d892', 'doi': '10.15493/SAEON.FYNBOS.10000001', 'featured': 'false', 'id': 'e66d4a36-8db1-4f93-9236-05523d2ad639', 'isopen': False, 'license_id': None, 'license_title': None, 'lineage_statement': 'A climate-aided Bayesian kriging approach is used to interpolate 20 years of daily meteorological observations (maximum and minimum temperature and precipitation) to a 1 arc-minute grid for the Cape Floristic Region of South Africa. Independent validation data revealed overall predictive performance of the interpolation to have R2 values of 0.90, 0.85, and 0.59 for maximum temperature, minimum temperature, and precipitation, respectively. A suite of ecologically-relevant climate metrics that include the uncertainty introduced by the interpolation were then generated. By providing the high resolution climate metric surfaces and uncertainties, this work facilitates richer and more robust predictive modeling in ecology and bio- geography. These data can be incorporated into ecological models to propagate the uncertainties through to the final predictions', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-10-16T11:32:14.831108', 'metadata_date': '2016-01-01T00:00', 'metadata_modified': '2025-10-17T09:38:59.712167', 'metadata_thumbnail': '', 'name': 'interpolated_observed_weather_data_for_the_cape_floristic_region', 'notes': 'Conservation of biodiversity demands comprehension of evolutionary and ecological patterns and processes that occur over vast spatial and temporal scales. A central goal of ecology is to understand the climatic factors that control ecological processes and this has become even more important in the face of climate change. Especially at global scales, there can be enormous uncertainty in underlying environmental data used to explain ecological processes, but that uncertainty is rarely quantified or incorporated into ecological models. In this study a climate-aided Bayesian kriging approach is used to interpolate 20 years of daily meteorological observations (maximum and minimum temperature and precipitation) to a 1 arc-minute grid for the Cape Floristic Region of South Africa. Independent validation data revealed overall predictive performance of the interpolation to have R2 values of 0.90, 0.85, and 0.59 for maximum temperature, minimum temperature, and precipitation, respectively. A suite of ecologically-relevant climate metrics that include the uncertainty introduced by the interpolation were then generated. By providing the high resolution climate metric surfaces and uncertainties, this work facilitates richer and more robust predictive modeling in ecology and bio- geography. These data can be incorporated into ecological models to propagate the uncertainties through to the final predictions.', 'num_resources': 1, 'num_tags': 6, 'organization': {'id': 'c4a18544-cded-4488-9f43-c02a1094ad39', 'name': 'saeon', 'title': 'NRF-SAEON', 'type': 'organization', 'description': 'The South African Environmental Observation Network (SAEON) is a long-term environmental observation and research facility of the National Research Foundation (NRF). SAEON’s three focus areas are environmental observation, data management and education outreach. The Department of Science, Technology and Innovation (DSTI) provides core funding for these activities. 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The mosaic was generated from using Sentinel-2 data from July -September 2024. The cloudless mosaic of South Africa consist of 4 spectral Sentinel-2 bands (Blue, Green, Red, and NIR) composite.. The entire country of South Africa and is presented in a georeferenced raster Geo-TIFF format and the spatial resolution is 10 meters. The Mosaic was downloaded by the South African National Agency(SANSA). SANSA combined separated 4 spectral bands into a single image. These data was packaged and organised into the country’s 4 UTMS zones. The Mosaic covers South Africa and presented in a map-corrected raster format, based on 10 x 10 m cells equivalent to the images resolution of the source sentinel multispectral imagery. 4 and pixel size is Pixel Size is 10,-10. 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The Mosaic covers South Africa and presented in a map-corrected raster format, based on 10 x 10 m cells equivalent to the images resolution of the source sentinel multispectral imagery. 4 and pixel size is Pixel Size is 10,-10. \r\n\r\nThe packaged datasets processed by SANSA are subject to strict distribution controls. Only SANSA is authorized to distribute these datasets directly to government departments or other approved requesters. \r\n', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': 'a959e782-51ce-4adc-b84d-f89961445cdb', 'name': 'sansa', 'title': 'SANSA', 'type': 'organization', 'description': 'SANSA was created to promote the use of space and strengthen cooperation in space-related activities while fostering research in space science, advancing scientific engineering through developing human capital, and supporting industrial development in space technologies. 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', 'num_resources': 1, 'num_tags': 1, 'organization': {'id': 'a959e782-51ce-4adc-b84d-f89961445cdb', 'name': 'sansa', 'title': 'SANSA', 'type': 'organization', 'description': 'SANSA was created to promote the use of space and strengthen cooperation in space-related activities while fostering research in space science, advancing scientific engineering through developing human capital, and supporting industrial development in space technologies. The research and work carried out at SANSA focuses on Earth observation, space science, space engineering and space operations. Much of this work involves monitoring the Earth for policy and decision making, resource and disaster management, food security and national security. 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SPOT 4 images with a spatial resolution of 20m (4 band multispectral(I)) and 10m panchromatic (M), processed to level 1A. The images were acquired between 22 September and 28 December 2010 covering some parts of South Africa and delivered in GeoTiff format', 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2025-08-25T10:37:59.621810', 'metadata_date': '2025-08-25T10:00', 'metadata_modified': '2025-08-25T10:39:31.888193', 'metadata_thumbnail': '', 'name': '2010-spot4-satellite-imagery', 'notes': 'SPOT 4 acquired and processed by the South African National Space Agency (then Satellite Application Centre) in South Africa. SPOT 4 images with a spatial resolution of 20m (4 band multispectral(I)) and 10m panchromatic (M), processed to level 1A. 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