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9 results for “2003-2015”
Water quality and watershed attributes of 41 Pampean streams in Argentina, 12 years later (2003-2015).
This database consists of water chemistry (pH, conductivity, dissolved oxygen, nutrients, and carbonates) and catchment attributes for 41 streams of Buenos Aires province, Argentina. Water quality was measured in 2003/4 and 12 years later (2015/16). Sampling were made in May (autumn), November (spring), and February (summer) at baseflow condition. Some physico-chemical parameters were measured in situ. Parameters determined at laboratory were nutrients and salts. And catchment attributes were determined (physiographic parameters, land use, soil type and geology).
Spring and Fall Leaf Phenology from Coweeta LTER Soil Moisture Sites SM2 & SM4, Coweeta Hydrologic Laboratory, Otto, NC, 2003-2015
Spring vegetative bud break, leaf elongation, fall leaf color, and leaf senescence are monitored at the two scaffold towers located at Project 1040 soil moisture microclimate sites 2 and 4. We have identified a variety of species at the elevation extremes within the Coweeta basin for this yearly monitoring project.
Canary Islands La Palma: pinar canario change map (2003-2015)
<p>A change map for the land cover class "PINAR CANARIO" in "La Palma" PA, obtained by the Cross Correlation Analysis algorithm (CCA) [1,2] considering at time T1 the layer "PINAR CANARIO" from an existing land cover map dated 2003 and at time T2 a Landsat 8 image dated July 8th, 2015.</p> <p>The map was produced at 30 meters spatial resolution and projected in WGS84/UTM28N.</p> <p>The map has binary values where value 1 indicates pixels changed from PINAR CANARIO to other whereas value 0 indicates No changed/Not considered pixels.</p> <p>[1] Koeln, G., & Bissonnette, J. (2000). Cross-correlation analysis: Mapping landcover changes with a historic landcover database and a recent, single-date, multispectral image. Proc. 2000 ASPRS Annual Convention, Washington, D.C. (8 pp.).</p> <p>[2] C. Tarantino, M. Adamo, R. Lucas, P. Blonda. (2016). “Detection of changes in semi-natural grasslands by cross correlation analysis with Worldview-2 images and new Landsat 8 data”, Remote Sensing of Environment, Vol. 175C, pp. 65-72, doi: 10.1016/j.rse.2015.12.031, ISSN 0034-4257</p>
Canary Islands La Palma: pinar disperso change map (2003-2015)
<p>A change map for the land cover class "PINAR DISPERSO" in "La Palma" PA, obtained by the Cross Correlation Analysis algorithm (CCA) [1,2] considering at time T1 the layer "PINAR DISPERSO" from an existing land cover map dated 2003 and at time T2 a Landsat 8 image dated July 8th, 2015.</p> <p>The map was produced at 30 meters spatial resolution and projected in WGS84/UTM28N.</p> <p>The map has binary values where value 1 indicates pixels changed from PINAR DISPERSO to other whereas value 0 indicates No changed/Not considered pixels.</p> <p>[1] Koeln, G., & Bissonnette, J. (2000). Cross-correlation analysis: Mapping landcover changes with a historic landcover database and a recent, single-date, multispectral image. Proc. 2000 ASPRS Annual Convention, Washington, D.C. (8 pp.).</p> <p>[2] C. Tarantino, M. Adamo, R. Lucas, P. Blonda. (2016). “Detection of changes in semi-natural grasslands by cross correlation analysis with Worldview-2 images and new Landsat 8 data”, Remote Sensing of Environment, Vol. 175C, pp. 65-72, doi: 10.1016/j.rse.2015.12.031, ISSN 0034-4257</p>
Canary Islands La Palma: improductivo change map (2003-2015)
<p>A change map for the land cover class "IMPRODUCTIVO" in "La Palma" PA, obtained by the Cross Correlation Analysis algorithm (CCA) [1,2] considering at time T1 the layer "IMPRODUCTIVO" from an existing land cover map dated 2003 and at time T2 a Landsat 8 image dated July 8th, 2015.</p> <p>The map was produced at 30 meters spatial resolution and projected in WGS84/UTM28N.</p> <p>The map has binary values where value 1 indicates pixels changed from IMPRODUCTIVO to other whereas value 0 indicates No changed/Not considered pixels.</p> <p>[1] Koeln, G., & Bissonnette, J. (2000). Cross-correlation analysis: Mapping landcover changes with a historic landcover database and a recent, single-date, multispectral image. Proc. 2000 ASPRS Annual Convention, Washington, D.C. (8 pp.).</p> <p>[2] C. Tarantino, M. Adamo, R. Lucas, P. Blonda. (2016). “Detection of changes in semi-natural grasslands by cross correlation analysis with Worldview-2 images and new Landsat 8 data”, Remote Sensing of Environment, Vol. 175C, pp. 65-72, doi: 10.1016/j.rse.2015.12.031, ISSN 0034-4257</p>
Canary Islands La Palma: cultivo change map (2003-2015)
<p>A change map for the land cover class "CULTIVO" in "La Palma" PA, obtained by the Cross Correlation Analysis algorithm (CCA) [1,2] considering at time T1 the layer "CULTIVO" from an existing land cover map dated 2003 and at time T2 a Landsat 8 image dated July 8th, 2015.</p> <p>The map was produced at 30 meters spatial resolution and projected in WGS84/UTM28N.</p> <p>The map has binary values where value 1 indicates pixels changed from CULTIVO to other whereas value 0 indicates No changed/Not considered pixels.</p> <p>[1] Koeln, G., & Bissonnette, J. (2000). Cross-correlation analysis: Mapping landcover changes with a historic landcover database and a recent, single-date, multispectral image. Proc. 2000 ASPRS Annual Convention, Washington, D.C. (8 pp.).</p> <p>[2] C. Tarantino, M. Adamo, R. Lucas, P. Blonda. (2016). “Detection of changes in semi-natural grasslands by cross correlation analysis with Worldview-2 images and new Landsat 8 data”, <em>Remote Sensing of Environment</em>, Vol. 175C, pp. 65-72, doi: 10.1016/j.rse.2015.12.031, ISSN 0034-4257</p>
Antarctic BHM mass trends for the period 2003-2015
<p>This Antarcitc_BHM_mass_trends_README.txt file was generated on 2019-05-10 by Stephen J. Chuter</p> <p>-------------------<br> GENERAL INFORMATION<br> -------------------</p> <p>Title of Dataset: Antarctic BHM mass trends for the period 2003-2015</p> <p>Author Information (Name, Institution, Address, Email)<br> Name: Stephen J Chuter</p> <p>Institution: University of Bristol, School of Geographical Sciences<br> Email: s.chuter@bristol.ac.uk</p> <p>Geographic location of data collection: Antarctica - Region and basin spatial scales</p>
Global-Gridded Daily Methane Emissions Climatology from Lake Systems, 2003-2015
This dataset provides global gridded information on lake surface area and open water CH4 emissions at a resolution of 0.25-degree x 0.25-degree for an annual climatology representative of the average conditions from 2003 to 2015. A compilation of flux data from 575 individual lake systems and 893 aggregated flux values were used, and each flux measurement was classified into one of seven ecoclimatic types. Ice-cover-regulated emission seasonality was derived from satellite microwave observations of ice cover phenology and freeze-thaw dynamics. Global lake area was determined from the merger of HydroLAKES and Climate Change Initiative Inland-Water (CCI-IW) remote-sensing data, and lakes were classified into ecoclimatic regions to facilitate linking these types with ecosystem-specific CH4 measurements in the flux compilation. Exploratory estimates of fluxes associated with ice melt and with spring and fall water-column turnover are also included. The data are provided in NetCDF format.
Gridded CO2 and CH4 Flux Estimates for pan-Arctic and Boreal Regions, 2003-2015
This dataset provides gridded estimates of gross primary productivity (GPP), ecosystem respiration (Reco), net ecosystem CO2 exchange (NEE = Reco - GPP), and methane (CH4) emissions from tundra and boreal wetland soils, across the pan-Arctic and Boreal zone (>49 degrees north) at 1-km spatial resolution. The data were produced through simulations of the Arctic Terrestrial Carbon Flux Model (TCFM-Arctic) and are provided at the daily time step for the years 2003-2015. TCFM-Arctic uses a light-use efficiency approach driven by satellite estimates of FPAR (fraction of absorbed photosynthetically active radiation) to estimate GPP, and autotrophic respiration (Rauto) is estimated as a fraction of GPP. Heterotrophic respiration (Rhetero) is estimated using decomposition rates with environmental constraints applied to three near-surface soil organic carbon (SOC) pools, and Reco is determined as the sum of Ra and Rh. Methane production is estimated using optimal CH4 production rates with environmental constraints applied to the labile carbon pool, and transfer of CH4 from the soil to the atmosphere is modeled through vegetation, soil diffusion, and water ebullition pathways. The model estimates were calibrated and evaluated using >60 tower eddy covariance (EC) sites. Baseline carbon pools were initialized by continuously cycling (spinning-up) the model for 1,000 model years using recent climatology from 1985 to 2002 to reach a dynamic steady-state between estimated net primary productivity (NPP = GPP - Rauto) and near-surface SOC pools. The TCFM-Arctic simulations were extended to the full Arctic-boreal domain at a 1-km spatial resolution using land cover maps representing high latitude vegetation communities. The data are provided in NetCDF and comma-separated values (CSV) formats.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.