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Riparian zones represent transitional areas occurring between land and freshwater ecosystems, characterised by distinctive hydrology, soil and biotic conditions and strongly influenced by the stream water. They provide a wide range of riparian functions (e.g. chemical filtration, flood control, bank stabilization, aquatic life and riparian wildlife support, etc.) and ecosystem services. The Riparian Zones products will support the objectives of several European legal acts and policy initiatives, such as the EU Biodiversity Strategy to 2020, the Habitats and Birds Directives and the Water Framework Directive. Land Cover/Land Use (LC/LU) classification is tailored to the needs of biodiversity monitoring in a tailored buffer zone along large and medium-sized European rivers (with Strahler levels 3-8 derived from EU-Hydro). LC/LU is extracted from VHR satellite data and other available data in a buffer zone of selected rivers. The classes follow the pre-defined nomenclature on the basis of MAES typology of ecosystems (Level 1 to Level 4) and Corine Land Cover, providing 80 distinct thematic classes with a Minimum Mapping Unit (MMU) of 0.5 ha and a Minimum Mapping Width (MMW) of 10 m. The production of the Riparian Zones products was coordinated by the European Environment Agency in the frame of the EU Copernicus programme.
Land cover information is necessary for a large range of environmental applications related to climate impacts and adaption, emergency response, wildlife habitat, etc. In Canada, a 2008 user survey indicated that the most practical land cover data is provided in a nationwide 30 m spatial resolution format, with an update frequency of five years. In response to this need, the Canada Centre for Remote Sensing (CCRS) has generated a 30 m land cover map of Canada for the base year 2010, as the first of a planned series of maps to be updated every five years, or more frequently. This land cover dataset is also the Canadian contribution to the 30 m spatial resolution 2010 Land Cover Map of North America, which is produced by Mexican, American and Canadian government institutions under a collaboration called the North American Land Change Monitoring System (NALCMS). This land cover dataset for Canada is produced using observation from Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) Landsat sensors. An accuracy assessment based on 2811 randomly distributed samples shows that land cover data produced with this new approach has achieved 76.60% accuracy with no marked spatial disparities. - [Land Cover of Canada - Cartographic Product Collection](https://open.canada.ca/data/en/dataset/11990a35-912e-4002-b197-d57dd88836d7)
Land cover information is necessary for a large range of environmental applications related to climate impacts and adaption, emergency response, wildlife habitat, etc. In Canada, a 2008 user survey indicated that the most practical land cover data is provided in a nationwide 30 m spatial resolution format, with an update frequency of five years. In response to this need, the Canada Centre for Remote Sensing (CCRS) has generated a 30 m land cover map of Canada for the base year 2010, as well as this 2015 land cover map. This land cover dataset is also the Canadian contribution to the 30 m spatial resolution 2015 Land Cover Map of North America, which is produced by Mexican, American and Canadian government institutions under a collaboration called the North American Land Change Monitoring System (NALCMS). This land cover dataset for Canada is produced using observation from Operational Land Imager (OLI) Landsat sensor. An accuracy assessment based on 806 randomly distributed samples shows that land cover data produced with this new approach has achieved 79.90% accuracy with no marked spatial disparities. - [Land Cover of Canada - Cartographic Product Collection](https://open.canada.ca/data/en/dataset/11990a35-912e-4002-b197-d57dd88836d7)
Collection of Land Cover products for Canada as produced by Natural Resources Canada using Landsat satellite imagery. This collection of cartographic products offers classified Land Cover of Canada at a 30 metre scale, updated on a 5 year basis. - [Landcover of Canada 2010](https://open.canada.ca/data/en/dataset/c688b87f-e85f-4842-b0e1-a8f79ebf1133) - [Landcover of Canada 2015](https://open.canada.ca/data/en/dataset/4e615eae-b90c-420b-adee-2ca35896caf6)
Skoðunarþjónustur fyrir INSPIRE tilskipunina
Nytjaland er verkefni sem miðaði að því að kortleggja yfirborð landsins, m.t.t. hversu grósku mikið það væri. Flokkunun var unnin með fjarkönnunaraðferðum á grunni Landsat 7 og SPOT 5 gervitunglamynda. Verkefnið var unnið á árunum 1999-2007. Var þá búið að gera yfirborðsflokkun á um 70% landsins í 12 flokka og 30% af yfirborðinu í 6 flokka. Nytjaland_N8 er einfölduð mynd af Nytjalandsgögnunum þar sem 12 flokka gögnin hafa verið aðlöguð að 6 flokka gögnunum. Flokkarnir graslendi, mólendi, rýrt mólendi og mosi (úr 12 flokka gögnunum) voru sameinaðir í einn flokk „Graslendi“. Inn í flokkuðu myndina Nytjaland_N8 hefur verið bætt gögnum Skógræktar ríkisins (2013) um "Náttúrulegt birkilendi“ og „Ræktaðan skóg". Flokkurinn ræktað land var hnitaður inn af gervitunglamyndum og var settur í rastagrunninn. Ár, vötn, jöklar og strandlína var samræmt vatnafarsgrunni LMÍ 2013. Viðmiðunarmælikvarði 1:30000
The Moderate Resolution Imaging Spectroradiometer (MODIS ) is one of the most sophisticated sensors that is used in a wide range of applications related to land, ocean and atmosphere. It has 36 spectral channels with spatial resolution varying between 250 m and 1 km at nadir. MODIS channels 1 (B1, visible) and 2 (B2, near infrared) are available at 250 m spatial resolution, an additional five channels for terrestrial applications (bands B3 to B7) are available at 500 m spatial resolution, the other twenty-nine channels not included in this data set capture images with a spatial resolution of 1 km. The MODIS record begins in March 2000 and extends to present with daily measurements over the globe. This level 3 product for Canada was created from the following original Level 1 (1B) MODIS data (collection 5): a) MOD02QKM - Level 1B 250 m swath data, 5 min granules; b ) MOD02HKM - level 1B , 500 m swath data, 5 min granules; c) MOD03 - level 1 geolocation information, 1 km swath data, 5 min granules. All these data are available from the DAAC Earth Observing System Data Gateway (NASA http://ladsweb.nascom.nasa.gov/data/search.html). The terrestrial channels MODIS (B3 to B7) at 500 m spatial resolution were reduced to 250 m with an adaptive regression system and normalization described in Trishchenko et al. (2006, 2009), and the data were mapped using a Lambert Conformal Conic (LCC ) projection (Khlopenkov et al., 2008). These data were combined to form pan-Canadian images using a technique for detection of clear sky, clouds and cloud shadows with a maximum interval of 10 days (Luo et al., 2008). Atmospheric and sun-sensor geometry corrections have not been applied. For each date, data include forward and backward scattering observations as separate files. This allows data to be optimized for a given application. For general use, data from either forward or backward scattering or both should be used. Future release of the MODIS time series will correct the forward and backward scattering geometry to provide a single best observation for each pixel.
Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) sensors were used to generate the circa 2010 Mosaic of Canada at 30 m spatial resolution. All scenes were processed to Standard Terrain Correction Level 1T by the United States Geological Survey (USGS). Further processing performed by the Canada Centre for Remote Sensing included conversion of sensor measurements to top of atmosphere reflectance, cloud and cloud shadow detection, re-projection, selection of best measurements, mosaic generation ,noise removal and quality control. To provide a clear sky measurement for each location in Canada, data from the years 2009, 2010, and 2011 were used, but 2010 was preferentially selected. Bands 3 (0.63-0.69 µm), 4 (0.76-0.90 µm), 5 (1.55-1.75 µm), and 7 (2.08-2.35 µm) are provided in this version as significant atmosphere effects strongly limit the quality of the blue (0.45-0.52 µm) and green (0.52-0.60 µm) bands. Multi-criteria compositing was used for the selection of the most representative pixel. For ETM+ onboard Landsat 7 a scan line malfunction caused missing lines of data in all scenes collected after May 2003. Atmosphere and target variability between scenes cause these lines to have significant radiometric differences in some cases. A Fourier transformation approach was applied to correct this occurrence. This mosaic was developed for land cover and biophysical mapping applications across Canada. Other applications of these data are also possible, but should consider the temporal and spectral limitations of the product. Research to enhance the spatial, spectral and temporal aspects are in development for future versions of moderate resolution products from historical Landsat sensors, Landsat 8, and Sentinel 2 data.
The MODIS surface albedo dataset was produced by the Canada Center for Remote Sensing (CCRS), Natural Resources Canada. The dataset represents the solar shortwave broadband surface albedo and it is at a 10-day interval covering the entire Canadian landmass as well as northern USA, Alaska, and the Greenland. The dataset was derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the TERRA satellite which provides a global coverage every 1-2 days in 36 spectral bands ranging from visible to infrared and to thermal wavelengths between 405 and 14,385 nm, and was available since 2000. For the estimation of surface albedo, the first seven spectral bands of B1 to B7 ranging from 459 nm to 2155 nm were used. B1 and B2 have a 250 meter resolution and B3 to B7 have a 500 meter resolution. A downscaling method using a regression and normalization scheme was employed to downscale the bands B3 to B7 to 250 meter resolution while preserving radiometric properties of the original data. To obtain clear-sky observations from MODIS, composite images for a 10 day period were generated by using a series of advanced algorithms (Luo et al., 2008). The 10-day composites of B1-B7 reflectance were then used to retrieve spatially continuous spectral albedo by using a combined land/snow BRDF (Bi-directional Reflectance Distribution Function) model. In that method, the modified RossThick-LiSparse BRDF model (Maignan et al., 2004) for land and Kokhanovsky and Zege’s model (2004) for snow are linearly combined for mixed surface conditions. They are weighted by snow fraction (0.0 ~ 1.0). The seven spectral albedo were then converted into the shortwave broadband surface albedo using the empirical MODIS polynomial conversion equation of Liang et al. (1999). The data product is in LCC (Lambert Conformal Conic) projection with a 250m pixel resolution. There are 36 albedo images per year. A dataset representing the pixel state (e.g. cloud/shadow, snow/ice, water, land, et al.) was also generated for each 10-day corresponding to the surface albedo product. References: Kokhanovsky, A. A. and Zege, E. P., 2004, Scattering Optics of Snow, Applied Optics, 43, 1589-1602, doi:10.1364/AO.43.001589, 20. Liang, S., Strahler, A.H., Walthall, C., 1999. Retrieval of land surface albedo from satellite observations: a simulation study. J. Appl. Meteorol. 38, 712–725. Luo, Y., Trishchenko, A.P., Khlopenkov, K.V., 2008. Developing clear-sky, cloud and cloud shadow mask for producing clear-sky composites at 250-meter spatial resolution for the seven MODIS land bands over Canada and North America. Remote Sens. Environ. 112, 4167–4185. Maignan, F., F.M. Bréon and R. Lacaze, 2004, Bidirectional reflectance of Earth targets : evaluation of analytical models using a large set of spaceborne measurements with emphasis with the hot spot, Remote Sens. Environ., 90, 210-220.