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UK Environmental Change Network - Water temperature data for selected lake, river & stream sites
No full textWater temperature data from selected UK Environmental Change Network (ECN) freshwater sites (lakes, rivers, streams). These data are collected at ECN's freshwater sites in accordance with the ECN Surface Water Chemistry & Quality protocol: http://www.ecn.ac.uk/measurements/freshwater/fwc-fwa. Surface water temperatures are recorded by hand-held thermometers at the freshwater chemistry sampling point when water samples are collected. The temporal range varies from site-to-site (earliest record from 1975, latest from 2012). ECN (www.ecn.ac.uk) is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. A full list of the organisations supporting ECN is available at http://www.ecn.ac.uk/what-we-do/about. The organisations providing the data included in the file are: Centre for Ecology & Hydrology, Environment Agency, James Hutton Institute, ENSIS Ltd (University College London) and Scottish Environment Protection Agency
LTER Kopaonik National Park, Serbia, Vegetation data 2010-2013
No full textVegetation survey data of study area Kopaonik National Park, Serbia (LTER_EU_RS_008) between the years 2010 and 2013. The percentage ground cover of every vascular plant was determined on permanently marked subplots (100 m²)
Plynlimon (Wales, UK) air temperatures
No full textWater temperature data for 6 locations in the Plynlimon site (eLTER site, DEIMS code EXPEER-UK-02), Mid Wales. Recorded with handheld thermometer during routine water sampling for chemical analysis. Plynlimon is at the headwaters of the Rivers Severn and Wye (Hafren and Gwy in Welsh) and currently comprises 9 instrumented catchments. Other Plynlimon hydrochemistry and spatial datasets are available at https://catalogue.ceh.ac.uk/documents/91961a0f-3158-4d00-984d-91eb1e03e8bd. Monitoring is funded by the Centre for Ecology & Hydrology, and is ongoing since 1968
ECHAM-HAMMOZ reference simulation 2003-2012: stratospheric diagnostics (2008)
No full textThese datasets represent a selection of daily stratospheric diagnostics from the reference simulation of the ECHAM-HAMMOZ chemistry climate model (CCM), which is described in the journal paper "The Chemistry Climate Model ECHAM6.3-HAM2.3-MOZ1.0" by M. G. Schultz et al. (Geosci. Model Dev., 2018). The data are daily mean fields of global atmospheric composition (from the surface to ~80 km altitude) and they include some meteorological fields as well as specific diagnostics for the evaluation of stratospheric chemical processes. The file format is netCDF.double hyai(nhyi) ;
double hyam(nhym) ;
double hybi(nhyi) ;
double hybm(nhym) ;
double lat(lat) ;
double lev(lev) ;
double lon(lon) ;
double time(time) ;
float ps(time, lat, lon) ;
float orography(time, lat, lon) ;
float hno3_cond(time, lev, lat, lon) ;
float sad_strat_NAT(time, lev, lat, lon) ;
float sad_strat_ice(time, lev, lat, lon) ;
float sad_strat_sulfate(time, lev, lat, lon) ;
float temperature(time, lev, lat, lon) ;
float u(time, lev, lat, lon) ;
float v(time, lev, lat, lon) ;
float Bry(time, lev, lat, lon) ;
float CLO(time, lev, lat, lon) ;
float CLONO2(time, lev, lat, lon) ;
float CO(time, lev, lat, lon) ;
float Cly(time, lev, lat, lon) ;
float HBR(time, lev, lat, lon) ;
float HCL(time, lev, lat, lon) ;
float HNO3(time, lev, lat, lon) ;
float NO2(time, lev, lat, lon) ;
float NOy(time, lev, lat, lon) ;
float O3(time, lev, lat, lon)
LTER Val Masino, Italy, Vegetation data 1999-2012
No full textVegetation survey data of the LTER study site Val Masino LOM1 (LTER_EU_IT_028). The percentage cover of every vascular plant and moss species was determined on 12 permanently marked subplots (10 x 10 m) on a 0.25 ha study area, by vertical layers between the years 1999 and 2012
Vaihingen benchmark dataset
No full textSubset of the dataset provided by the International Society for Photogrammetry and Remote Sensing (ISPRS), working group II/4, in the framework of a ''2D semantic labeling contest'' - benchmark 1. The original dataset [1] is composed of 33 orthorectified image tiles acquired by a near infrared (NIR) - green (G) - red (R) aerial camera, over the town of Vaihingen (Germany). The average size of the tiles is 20494 x 20064 pixels with a spatial resolution of 9 cm. Images are accompanied by a digital surface model (DSM) representing absolute height of pixels. 16 out of the 33 tiles are fully annotated at pixel level and are upload here in HDF5 format.
E.g. Vaihingen_xx.hdf5
x_1 = near infrared, red, green, nDSM, NDVI
y_1 = Groundtruth
m_1 = Boundaries
nDSM: normalized DSM , it represents the pixels height relative to the elevation of the nearest ground surface [2].
NDVI: Normalized Difference Vegetation Index
Groundtruth: annotated pixels
Boundaries: binary mask
The semantic segmentation task involves the discrimination of 6 land-cover / landuse classification classes: ''impervious surfaces'' (IS) (roads, concrete surfaces), ''buildings'' (BU), ''low vegetation'' (LV), ''trees'' (TR), ''cars'' (CA) and a class of ''clutter'' (CL) representing uncategorizable land covers. Classes are highly imbalanced: classes ''buildings'' and ''impervious surfaces'' cover 50% of the data, while ''car'' and ''clutter''only for 2% of the total labels. The 16 tiles are fully annotated at pixel level (i.e., Groundtruth ). Since there is uncertainty associated with the boundary of objects in the Groundtruth, these boundaries can be ignored for the evaluation (i.e., pixels with value 1 in the mask Boundaries)
[1] http://www2.isprs.org/commissions/comm3/wg4/semantic-labeling.html
[2] Gerke, M. (Author). (2014). Use of the stair vision library within the ISPRS 2D semantic labeling benchmark (Vaihingen). Web publication/site, ResearcheGate. DOI: 10.13140/2.1.5015.968
Nitrogen deposition 2017 - Brenna (Poland)
No full textDeposition (monthly and annual) of nitrogen compounds was calculated on the basis of analisys of throughfall samples. Collectors were installed in the spruce stand at the high of 750m asl
LTER Monte Rufeno, Italy, Vegetation data 1999-2016
No full textVegetation survey data of the study site Monte Rufeno LAZ1 (LTER_EU_IT_034). The percentage cover of every vascular plant and moss species was determined on 12 permanently marked subplots (10 x 10 m) on a 0.25 ha study area, by vertical layers between the years 1999 and 2016
eLTER VA Data Postojna Planina CS microclimate data
No full textCave microclimate is prone to important changes in certain passages due to intensive tourism. Monitoring the climatic parameters (air temperature, CO2) in Postojna-Planina Cave System helps to have a proper picture of the impact of tourism for the cave. It is very useful to compare if additional increase of temperature is associated with the changes at the surface climate. The dataset comprises two types of daily mean air temperature data: 1) the daily mean air temperature data (°C) measured in “Lepe jame” cave passage from Postojna Cave, counting constantly a very high number of tourists; the measurements were made in the same point, by three sensors placed at three different height points (in the wall cracks [T1], at ceiling level [T3], and at 2 m height [T2]). Values are recorded at 10 min intervals and then averaged for daily data (the dataset for Lepe jame cave passage is provided by MEIS Environmental consulting d.o.o. (http://www.meis.si/) while the data are part of the project "Assesment of natural and antropogenic processes in micro-meteorology of Postojna cave system by numerical models and modern methods of data aquisition and transfer" [https://izrk.zrc-sazu.si/en/programi-in-projekti/assesment-of-natural-and-antropogenic-processes-in-micrometeorology-of-postojna#v]; 2) the surface daily mean air temperature measured at 2 m height (°C) at the Postojna meteorological station, as part of the national network of meteorological stations within the Environmental Agency of the Republic of Slovenia (ARSO; http://meteo.arso.gov.si/)