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  • These data are high-resolution datasets related to in-land water for limnology (study of in-land waters) and remote sensing applications. This includes: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates on a high-resolution (1/360x1/360 degree) grid, produced by the Department of Meteorology at the University of Reading. Data was derived using the ESA CCI Land Cover Map (see linked documentation). Datasets containing information to locate and identify water bodies have been generated from high-resolution (1/360x1/360 degree, about 300mx300m) data locating static-water-bodies recently released by the Land Cover Climate Change Initiative (LC CCI) of the European Space Agency. The new datasets provide: distance to land, distance to water, water body identifiers and lake centre locations. The lake identifiers (IDs) are from the Global Lakes and Wetlands Database (GLWD), and lake centres are defined for in-land waters for which GLWD IDs were determined. The new datasets therefore link recent lake/reservoir/wetlands extent to the GLWD, together with a set of coordinates which locates unambiguously the water bodies in the database. The LC CCI water bodies dataset has been obtained from multi-temporal metrics based on time series of the backscattered intensity recorded by ASAR (Advanced Synthetic Aperture Radar) on Envisat between 2005 and 2010. Temporal change in water body extent is common. Future versions of the LC CCI dataset are planned to represent temporal variation, and this will permit these derived datasets to be updated. The paper associated with this dataset is: L.Carrea O. Embury C.J. Merchant "High-resolution datasets related to in-land water for limnology and remote sensing applications: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates" Geoscience Data Journal, vol. 2 issue 2, pp. 83-97, November 2015. DOI: 10.1002/gdj3.32

  • This dataset collection holds high-resolution datasets related to in-land water for limnology (study of in-land waters) and remote sensing applications. These were produced by the Department of Meteorology at the University of Reading. Information on distance-to-land for each water cell and the distance-to-water for each land cell has many potential applications in remote sensing, where the applicability of geophysical retrieval algorithms may be affected by the presence of water or land within a satellite field of view (image pixel). The data was recorded over a 5 year period from 2005-2010 on a global scale. It is expected that new and updated datasets will be added in the future.

  • A geographic database of lakes on the Antarctic Peninsula compiled over the past five years from a number of information sources: satellite images, aerial photography, old maps and reports. The database fields include: Lake unique id; Name; location; imager reference/how identified; locality; size (longest axis); area; type (as per Hutchinson''s lake classification); reference - any existing scientific work on the lake; salinity; depth; x co-ordinate; y co-ordinate. Many of the lakes are previously unknown, and very few have been studied before. The list represents the first attempt to collate all the lakes in the area into one usable dataset. The data is available as a down-loadable text file with point co-ordinates, or as a polygon coverage downloadable from the Antarctic Digital database.

  • In-lake temperature data for a peatland headwater lake of the Conwy catchment, North Wales are presented from November 2006 until December 2008. The Lake for which the data represents is Llyn Conwy situated on the Migneint blanket bog within Snowdonia National Park. The data is from a temperature string suspended from a buoy anchored above the deepest part of the lake. Temperature is recorded at 2m intervals throughout the lake profile from 1 to 19m. The purpose of this data is to investigate water column stability and to determine when, and to what degree stratification/mixing occurs and to make inferences about the effect of this on productivity, nutrient and chemical cycling. Note: there are gaps in this data set due to equipment/battery failures and/or freezing of the lake surface which meant it was not accessible. Full details about this dataset can be found at https://doi.org/10.5285/7bb6c7df-7630-4621-a0d4-eacc3ec2202b