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Research data keyboard_double_arrow_right Dataset 2019Publisher:Smithsonian Tropical Research Institute Authors: Paton, Steven;doi: 10.25573/data.10059455.v28 , 10.25573/data.10059455.v6 , 10.25573/data.10059455.v30 , 10.25573/data.10059455.v34 , 10.25573/data.10059455.v45 , 10.25573/data.10059455.v33 , 10.25573/data.10059455 , 10.25573/data.10059455.v13 , 10.25573/data.10059455.v9 , 10.25573/data.10059455.v31 , 10.25573/data.10059455.v22 , 10.25573/data.10059455.v14 , 10.25573/data.10059455.v27 , 10.25573/data.10059455.v11 , 10.25573/data.10059455.v44 , 10.25573/data.10059455.v15 , 10.25573/data.10059455.v38 , 10.25573/data.10059455.v17 , 10.25573/data.10059455.v16 , 10.25573/data.10059455.v2 , 10.25573/data.10059455.v29 , 10.25573/data.10059455.v12 , 10.25573/data.10059455.v32 , 10.25573/data.10059455.v39 , 10.25573/data.10059455.v26 , 10.25573/data.10059455.v19 , 10.25573/data.10059455.v41 , 10.25573/data.10059455.v25 , 10.25573/data.10059455.v23 , 10.25573/data.10059455.v10 , 10.25573/data.10059455.v20 , 10.25573/data.10059455.v21 , 10.25573/data.10059455.v24 , 10.25573/data.10059455.v1 , 10.25573/data.10059455.v8 , 10.25573/data.10059455.v3 , 10.25573/data.10059455.v5 , 10.25573/data.10059455.v46 , 10.25573/data.10059455.v4 , 10.25573/data.10059455.v42 , 10.25573/data.10059455.v18 , 10.25573/data.10059455.v43 , 10.25573/data.10059455.v40 , 10.25573/data.10059455.v7
doi: 10.25573/data.10059455.v28 , 10.25573/data.10059455.v6 , 10.25573/data.10059455.v30 , 10.25573/data.10059455.v34 , 10.25573/data.10059455.v45 , 10.25573/data.10059455.v33 , 10.25573/data.10059455 , 10.25573/data.10059455.v13 , 10.25573/data.10059455.v9 , 10.25573/data.10059455.v31 , 10.25573/data.10059455.v22 , 10.25573/data.10059455.v14 , 10.25573/data.10059455.v27 , 10.25573/data.10059455.v11 , 10.25573/data.10059455.v44 , 10.25573/data.10059455.v15 , 10.25573/data.10059455.v38 , 10.25573/data.10059455.v17 , 10.25573/data.10059455.v16 , 10.25573/data.10059455.v2 , 10.25573/data.10059455.v29 , 10.25573/data.10059455.v12 , 10.25573/data.10059455.v32 , 10.25573/data.10059455.v39 , 10.25573/data.10059455.v26 , 10.25573/data.10059455.v19 , 10.25573/data.10059455.v41 , 10.25573/data.10059455.v25 , 10.25573/data.10059455.v23 , 10.25573/data.10059455.v10 , 10.25573/data.10059455.v20 , 10.25573/data.10059455.v21 , 10.25573/data.10059455.v24 , 10.25573/data.10059455.v1 , 10.25573/data.10059455.v8 , 10.25573/data.10059455.v3 , 10.25573/data.10059455.v5 , 10.25573/data.10059455.v46 , 10.25573/data.10059455.v4 , 10.25573/data.10059455.v42 , 10.25573/data.10059455.v18 , 10.25573/data.10059455.v43 , 10.25573/data.10059455.v40 , 10.25573/data.10059455.v7
Monthly and daily summary from Barro Colorado Island (BCI). Data organized in horizontal format for seasonal and inter-year comparisonsLocation 9°9'42.36"N, 79°50'15.67"WParameters: air temperature, relative humidity, wind speed and direction, precipitation, sea surface temperature, solar radiation (pyranometer), air pressure, soil moisture, runoff, potential evapotranspiration, wet/dry season starting datesLutz catchment is a 9.73ha protected watershed on BCIThe Lutz tower was built in 1972 and was originally 42m. In 2002 it was increased to 48mThe data from 48m should be considered a separate data series from the data at 42m. Wind speed is significantly higher at 48m due to the distance to the top of the canopy.The Clearing is a small, open area surrounded by forest and some buildings. Station established in 1972. Consists of a Stevenson screen with max/min thermometers and air pressure sensor. Temperature/humidity sensor, rain gauge and evaporation sensors are located at various locations around the screen.
https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:DOE Open Energy Data Initiative (OEDI); National Renewable Energy Laboratory (NREL) Authors: Mooney, Meghan; Waechter, Katy;doi: 10.25984/1804725
The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded at the AWS S3 explorer page. The GitHub documentation page provides a description of the dataset with methods and assumptions. The Puerto Rico Solar-For-All dataset provides Census Tract level estimates of residential low-to-moderate income (LMI) PV rooftop technical potential as well as solar electric bill savings potential for LMI communities at the municipality level.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Publisher:PANGAEA Fischer, Andrea; Fickert, Thomas; Schwaizer, Gabriele; Patzelt, Gernot; Groß, Günther;Monitoring of plant succession in glacier forelands so far has been restricted to field sampling. In this study, in situ vegetation sampling along a chronosequence between Little Ice Age (LIA) maximum extent and the recent glacier terminus at Jamtalferner/Silvretta (ferner is a Tyrolian toponym for glacier) is compared to time series of the Normalized Difference Vegetation Index (NDVI) calculated from 13 Landsat scenes (1985-2016). The glacier terminus positions at 16 dates between the LIA maximum and 2015 were analysed from historical maps, orthophotos and LiDAR images and used for site age determination. We sampled plots of different time since deglaciation, from very recent to approx. 150 years: after 100 years, roughly 80% of the ground is covered by plants and ground cover did not increase essentially thereafter. Species number increases from 10-20 species on young sites to 40-50 species after 100 years. The NDVI increases for all plots between 1985 and 2016, from a mean of 0.11 for 1985-1991 to 0.2 in 2009 and 0.27 in 2016. For the plots deglaciated between 1 and about 150 years, the NDVI increases with the time of exposure. As the increase in ground cover is clearly reproduced by the NDVI (R² ground cover/NDVI 0.84) - even for sparsely vegetated areas -, we see a high potential of satellite-borne NDVI to perform regional characterizations of glacier forelands for hydrological, ecological and hazard management related applications. This data collection comprises the galcier outlines, NDVIs and chronosequencing locations with diversity and ground cover data.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2019License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2019License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Publisher:Mendeley Authors: Lan, K;The upload research data are including the fishery data of area coordinate, fishing effort (number of hooks), fishing date, number of catches and CPUE of immature and mature cohorts, and marien environmental date of SST, Chl-a, SSHD and MIL for 5° spatial grid from 2003 to 2012.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:Mendeley Authors: Oberschelp, Christopher;This dataset contains global raster maps to calculate particulate matter life cycle impacts from primary fine particulate matter (PM2.5), sulfur dioxide (SO2), nitrogen oxides (NOx) and ammonia (NH3) emissions. It also includes the R source code to reproduce these maps, a case study on the particulate matter health impacts of global coal power generation, and aggregated characterization factor tables for several spatial resolutions that are commonly used in life cycle assessment (LCA) (for example in the ecoinvent life cycle inventory (LCI) database).
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For further information contact us at helpdesk@openaire.eu2 citations 2 popularity Average influence Average impulse Average Powered by BIP!
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:The University of Hong Kong Authors: Lishan Ran (9057026);This is the dataset for our research on assessing CO2 emissions from Chinese inland waters, including streams, rivers, lakes and reservoirs. The dataset includes three parts, including Part 1: Lakes and Reservoirs_1980s, Part 2: CO2 Dataset_2010s, and Part 3: Water chemistry records. Detailed information on these data can be found from the 'README' text file.
https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY NCData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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visibility 33visibility views 33 download downloads 21 Powered bymore_vert https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY NCData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 11 Nov 2022Publisher:Dryad Authors: Eslamdoust, Jamshid;Plot design and harvesting Twelve sampling plots (16 m × 16 m) in three P. deltoides plantations were established based on systematic random design. To minimize edge effects, surrounding rows were not considered during sampling. The age of the stands was 18-20 years old. In each sampling plot, the DBH (diameter at breast height 1.3 m above the ground) of the individual trees was measured with a caliper in two perpendicular directions and the mean DBH determined. Tree height was measured by Haglöf-Vertex IV hypsometer. Based on the DBH and height measurements, 10 DBH classes from 15 to 42 cm (3 cm intervals) were established. The value of each DBH class represented the central value (i.e., class 15 included all DBH from 12.5 to 17.5 cm). In each DBH class, one representative tree was selected and harvested for a total of 10 P. deltoides trees. Measurements of bark percentagesThe stems of harvested trees were marked and cut into 2 m-segments. The mid-length diameter of each segment was measured outside the bark in two perpendicular directions with a caliper to determine the mean diameter. A 5 cm-thick disc was cut from the middle of each segment. A total of 123 discs were obtained and brought to the laboratory. All the discs were arranged into 2-cm wide diameter classes. The value of each disc class represents the central value (i.e., class 20 included all discs whose diameters ranged from 19.5 to 20.5 cm). Bark was separated from the wood using a peeler knife for each disc. Fresh bark and wood were weighted separately, oven-dried at 80 °C until constant weight, and the oven-dry weight measured. The bark percentage of each disc was considered as bark percentage of a 2 m-segment for fresh and dry weight. Finally, the bark percentage of the whole stem in each DBH class was calculated by adding the 2 m-segments. Bark biomass as an energy source has a high economic value. Bark content variations and production helps recognize the potential of this bioenergy source spatially before harvesting. The percentage of fresh and dry bark in Populus deltoides grown under a monoculture system was examined in the temperate region of northern Iran. Diameter at breast height (DBH) and total height data were analyzed based on an initial inventory. Ten sample trees were felled, separated into 2 m-segments, and weighted in the field. A 5-cm-thick disc from each segment was extracted for determining fresh and dry bark percentages. These were statistically significantly different in disc diameter classes and decreased with increasing disc diameters. Bark percentage of the disc classes ranged from 21.8 to 24.4% in small-sized diameters to 8.1‒9.3% in large-sized diameters. The differences between fresh and dry bark percentages depended on water content variations. Allometric power equations were fitted to data of fresh and dry bark percentages and disc diameters as well as DBH. The values of R2 ranged from 0.89 to 0.90. In addition, allometric power equations provided the best fits for relationships between total stem dry biomass, dry bark biomass, and DBH, R2 = 0.986 and 0.979 for the total stem dry biomass and stem dry bark biomass, respectively. The allometric models can be used to estimate bark percentage and bark production of P. deltoides in segments and for the whole stem for a wide range of segment diameters (8‒44 cm) and DBH (15‒45 cm).
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visibility 6visibility views 6 download downloads 5 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:4TU.ResearchData Authors: Reijnders, Victor; Gerards, Marco; Hurink, Johann;The data in this dataset was collected during the GridFlex Heeten project, as part of Victor Reijnders' PhD project.The data was collected between August 2018 and August 2020 in 77 households all situated in Heeten (The Netherlands) and consists of electricity consumption and gas usage per minute per household. All participating households specified their anonymous data could be used in further research. The data of this project was collected in accordance with a privacy-by-design approach.
Smithsonian figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY ND SAData sources: Bielefeld Academic Search Engine (BASE)4TU.ResearchData | science.engineering.designDataset . 2021License: CC BY NC SAData sources: Datacite4TU.ResearchData | science.engineering.designDataset . 2021License: CC BY NC SAData sources: DataciteDANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert Smithsonian figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY ND SAData sources: Bielefeld Academic Search Engine (BASE)4TU.ResearchData | science.engineering.designDataset . 2021License: CC BY NC SAData sources: Datacite4TU.ResearchData | science.engineering.designDataset . 2021License: CC BY NC SAData sources: DataciteDANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2015Publisher:International Institute of Refrigeration (IIR) Authors: HAGLUND STIGNOR, C.; MARTIN SANTANA, S.; LARSSON, O.;In this study, a completely new type of air-to-liquid heat exchanger, adapted for obtaining good heat transfer performance even at a laminar flow regime on the liquid side has been evaluated in a display cabinet application. The heat exchanger consists of parallel plates, with liquid in every second passage and air in the other passages. Tests were performed with a traditional open vertical display cabinet, first with a traditional finned-tube coil and thereafter with the new type of heat exchanger placed in the bottom of the display cabinet. The results showed that the same cooling capacity and mean temperature of the “food packages” could be obtained with around 6 K higher inlet temperature of the liquid, -7°C with the traditional coil and -1°C with the new type of heat exchanger, which can lead to considerable energy savings.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:U.S. EPA Office of Research and Development (ORD) doi: 10.23719/1519294
These are the soil quality data for each county (listed by fips code) for each scenario
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Research data keyboard_double_arrow_right Dataset 2019Publisher:Smithsonian Tropical Research Institute Authors: Paton, Steven;doi: 10.25573/data.10059455.v28 , 10.25573/data.10059455.v6 , 10.25573/data.10059455.v30 , 10.25573/data.10059455.v34 , 10.25573/data.10059455.v45 , 10.25573/data.10059455.v33 , 10.25573/data.10059455 , 10.25573/data.10059455.v13 , 10.25573/data.10059455.v9 , 10.25573/data.10059455.v31 , 10.25573/data.10059455.v22 , 10.25573/data.10059455.v14 , 10.25573/data.10059455.v27 , 10.25573/data.10059455.v11 , 10.25573/data.10059455.v44 , 10.25573/data.10059455.v15 , 10.25573/data.10059455.v38 , 10.25573/data.10059455.v17 , 10.25573/data.10059455.v16 , 10.25573/data.10059455.v2 , 10.25573/data.10059455.v29 , 10.25573/data.10059455.v12 , 10.25573/data.10059455.v32 , 10.25573/data.10059455.v39 , 10.25573/data.10059455.v26 , 10.25573/data.10059455.v19 , 10.25573/data.10059455.v41 , 10.25573/data.10059455.v25 , 10.25573/data.10059455.v23 , 10.25573/data.10059455.v10 , 10.25573/data.10059455.v20 , 10.25573/data.10059455.v21 , 10.25573/data.10059455.v24 , 10.25573/data.10059455.v1 , 10.25573/data.10059455.v8 , 10.25573/data.10059455.v3 , 10.25573/data.10059455.v5 , 10.25573/data.10059455.v46 , 10.25573/data.10059455.v4 , 10.25573/data.10059455.v42 , 10.25573/data.10059455.v18 , 10.25573/data.10059455.v43 , 10.25573/data.10059455.v40 , 10.25573/data.10059455.v7
doi: 10.25573/data.10059455.v28 , 10.25573/data.10059455.v6 , 10.25573/data.10059455.v30 , 10.25573/data.10059455.v34 , 10.25573/data.10059455.v45 , 10.25573/data.10059455.v33 , 10.25573/data.10059455 , 10.25573/data.10059455.v13 , 10.25573/data.10059455.v9 , 10.25573/data.10059455.v31 , 10.25573/data.10059455.v22 , 10.25573/data.10059455.v14 , 10.25573/data.10059455.v27 , 10.25573/data.10059455.v11 , 10.25573/data.10059455.v44 , 10.25573/data.10059455.v15 , 10.25573/data.10059455.v38 , 10.25573/data.10059455.v17 , 10.25573/data.10059455.v16 , 10.25573/data.10059455.v2 , 10.25573/data.10059455.v29 , 10.25573/data.10059455.v12 , 10.25573/data.10059455.v32 , 10.25573/data.10059455.v39 , 10.25573/data.10059455.v26 , 10.25573/data.10059455.v19 , 10.25573/data.10059455.v41 , 10.25573/data.10059455.v25 , 10.25573/data.10059455.v23 , 10.25573/data.10059455.v10 , 10.25573/data.10059455.v20 , 10.25573/data.10059455.v21 , 10.25573/data.10059455.v24 , 10.25573/data.10059455.v1 , 10.25573/data.10059455.v8 , 10.25573/data.10059455.v3 , 10.25573/data.10059455.v5 , 10.25573/data.10059455.v46 , 10.25573/data.10059455.v4 , 10.25573/data.10059455.v42 , 10.25573/data.10059455.v18 , 10.25573/data.10059455.v43 , 10.25573/data.10059455.v40 , 10.25573/data.10059455.v7
Monthly and daily summary from Barro Colorado Island (BCI). Data organized in horizontal format for seasonal and inter-year comparisonsLocation 9°9'42.36"N, 79°50'15.67"WParameters: air temperature, relative humidity, wind speed and direction, precipitation, sea surface temperature, solar radiation (pyranometer), air pressure, soil moisture, runoff, potential evapotranspiration, wet/dry season starting datesLutz catchment is a 9.73ha protected watershed on BCIThe Lutz tower was built in 1972 and was originally 42m. In 2002 it was increased to 48mThe data from 48m should be considered a separate data series from the data at 42m. Wind speed is significantly higher at 48m due to the distance to the top of the canopy.The Clearing is a small, open area surrounded by forest and some buildings. Station established in 1972. Consists of a Stevenson screen with max/min thermometers and air pressure sensor. Temperature/humidity sensor, rain gauge and evaporation sensors are located at various locations around the screen.
https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:DOE Open Energy Data Initiative (OEDI); National Renewable Energy Laboratory (NREL) Authors: Mooney, Meghan; Waechter, Katy;doi: 10.25984/1804725
The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded at the AWS S3 explorer page. The GitHub documentation page provides a description of the dataset with methods and assumptions. The Puerto Rico Solar-For-All dataset provides Census Tract level estimates of residential low-to-moderate income (LMI) PV rooftop technical potential as well as solar electric bill savings potential for LMI communities at the municipality level.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Publisher:PANGAEA Fischer, Andrea; Fickert, Thomas; Schwaizer, Gabriele; Patzelt, Gernot; Groß, Günther;Monitoring of plant succession in glacier forelands so far has been restricted to field sampling. In this study, in situ vegetation sampling along a chronosequence between Little Ice Age (LIA) maximum extent and the recent glacier terminus at Jamtalferner/Silvretta (ferner is a Tyrolian toponym for glacier) is compared to time series of the Normalized Difference Vegetation Index (NDVI) calculated from 13 Landsat scenes (1985-2016). The glacier terminus positions at 16 dates between the LIA maximum and 2015 were analysed from historical maps, orthophotos and LiDAR images and used for site age determination. We sampled plots of different time since deglaciation, from very recent to approx. 150 years: after 100 years, roughly 80% of the ground is covered by plants and ground cover did not increase essentially thereafter. Species number increases from 10-20 species on young sites to 40-50 species after 100 years. The NDVI increases for all plots between 1985 and 2016, from a mean of 0.11 for 1985-1991 to 0.2 in 2009 and 0.27 in 2016. For the plots deglaciated between 1 and about 150 years, the NDVI increases with the time of exposure. As the increase in ground cover is clearly reproduced by the NDVI (R² ground cover/NDVI 0.84) - even for sparsely vegetated areas -, we see a high potential of satellite-borne NDVI to perform regional characterizations of glacier forelands for hydrological, ecological and hazard management related applications. This data collection comprises the galcier outlines, NDVIs and chronosequencing locations with diversity and ground cover data.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2019License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2019License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Publisher:Mendeley Authors: Lan, K;The upload research data are including the fishery data of area coordinate, fishing effort (number of hooks), fishing date, number of catches and CPUE of immature and mature cohorts, and marien environmental date of SST, Chl-a, SSHD and MIL for 5° spatial grid from 2003 to 2012.
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.17632/p46tx55872&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:Mendeley Authors: Oberschelp, Christopher;This dataset contains global raster maps to calculate particulate matter life cycle impacts from primary fine particulate matter (PM2.5), sulfur dioxide (SO2), nitrogen oxides (NOx) and ammonia (NH3) emissions. It also includes the R source code to reproduce these maps, a case study on the particulate matter health impacts of global coal power generation, and aggregated characterization factor tables for several spatial resolutions that are commonly used in life cycle assessment (LCA) (for example in the ecoinvent life cycle inventory (LCI) database).
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.17632/8jnj4vzbh6.1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu2 citations 2 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.17632/8jnj4vzbh6.1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:The University of Hong Kong Authors: Lishan Ran (9057026);This is the dataset for our research on assessing CO2 emissions from Chinese inland waters, including streams, rivers, lakes and reservoirs. The dataset includes three parts, including Part 1: Lakes and Reservoirs_1980s, Part 2: CO2 Dataset_2010s, and Part 3: Water chemistry records. Detailed information on these data can be found from the 'README' text file.
https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY NCData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.25442/hku.13560452.v1&type=result"></script>'); --> </script>
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visibility 33visibility views 33 download downloads 21 Powered bymore_vert https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY NCData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 11 Nov 2022Publisher:Dryad Authors: Eslamdoust, Jamshid;Plot design and harvesting Twelve sampling plots (16 m × 16 m) in three P. deltoides plantations were established based on systematic random design. To minimize edge effects, surrounding rows were not considered during sampling. The age of the stands was 18-20 years old. In each sampling plot, the DBH (diameter at breast height 1.3 m above the ground) of the individual trees was measured with a caliper in two perpendicular directions and the mean DBH determined. Tree height was measured by Haglöf-Vertex IV hypsometer. Based on the DBH and height measurements, 10 DBH classes from 15 to 42 cm (3 cm intervals) were established. The value of each DBH class represented the central value (i.e., class 15 included all DBH from 12.5 to 17.5 cm). In each DBH class, one representative tree was selected and harvested for a total of 10 P. deltoides trees. Measurements of bark percentagesThe stems of harvested trees were marked and cut into 2 m-segments. The mid-length diameter of each segment was measured outside the bark in two perpendicular directions with a caliper to determine the mean diameter. A 5 cm-thick disc was cut from the middle of each segment. A total of 123 discs were obtained and brought to the laboratory. All the discs were arranged into 2-cm wide diameter classes. The value of each disc class represents the central value (i.e., class 20 included all discs whose diameters ranged from 19.5 to 20.5 cm). Bark was separated from the wood using a peeler knife for each disc. Fresh bark and wood were weighted separately, oven-dried at 80 °C until constant weight, and the oven-dry weight measured. The bark percentage of each disc was considered as bark percentage of a 2 m-segment for fresh and dry weight. Finally, the bark percentage of the whole stem in each DBH class was calculated by adding the 2 m-segments. Bark biomass as an energy source has a high economic value. Bark content variations and production helps recognize the potential of this bioenergy source spatially before harvesting. The percentage of fresh and dry bark in Populus deltoides grown under a monoculture system was examined in the temperate region of northern Iran. Diameter at breast height (DBH) and total height data were analyzed based on an initial inventory. Ten sample trees were felled, separated into 2 m-segments, and weighted in the field. A 5-cm-thick disc from each segment was extracted for determining fresh and dry bark percentages. These were statistically significantly different in disc diameter classes and decreased with increasing disc diameters. Bark percentage of the disc classes ranged from 21.8 to 24.4% in small-sized diameters to 8.1‒9.3% in large-sized diameters. The differences between fresh and dry bark percentages depended on water content variations. Allometric power equations were fitted to data of fresh and dry bark percentages and disc diameters as well as DBH. The values of R2 ranged from 0.89 to 0.90. In addition, allometric power equations provided the best fits for relationships between total stem dry biomass, dry bark biomass, and DBH, R2 = 0.986 and 0.979 for the total stem dry biomass and stem dry bark biomass, respectively. The allometric models can be used to estimate bark percentage and bark production of P. deltoides in segments and for the whole stem for a wide range of segment diameters (8‒44 cm) and DBH (15‒45 cm).
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visibility 6visibility views 6 download downloads 5 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:4TU.ResearchData Authors: Reijnders, Victor; Gerards, Marco; Hurink, Johann;The data in this dataset was collected during the GridFlex Heeten project, as part of Victor Reijnders' PhD project.The data was collected between August 2018 and August 2020 in 77 households all situated in Heeten (The Netherlands) and consists of electricity consumption and gas usage per minute per household. All participating households specified their anonymous data could be used in further research. The data of this project was collected in accordance with a privacy-by-design approach.
Smithsonian figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY ND SAData sources: Bielefeld Academic Search Engine (BASE)4TU.ResearchData | science.engineering.designDataset . 2021License: CC BY NC SAData sources: Datacite4TU.ResearchData | science.engineering.designDataset . 2021License: CC BY NC SAData sources: DataciteDANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert Smithsonian figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY ND SAData sources: Bielefeld Academic Search Engine (BASE)4TU.ResearchData | science.engineering.designDataset . 2021License: CC BY NC SAData sources: Datacite4TU.ResearchData | science.engineering.designDataset . 2021License: CC BY NC SAData sources: DataciteDANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2015Publisher:International Institute of Refrigeration (IIR) Authors: HAGLUND STIGNOR, C.; MARTIN SANTANA, S.; LARSSON, O.;In this study, a completely new type of air-to-liquid heat exchanger, adapted for obtaining good heat transfer performance even at a laminar flow regime on the liquid side has been evaluated in a display cabinet application. The heat exchanger consists of parallel plates, with liquid in every second passage and air in the other passages. Tests were performed with a traditional open vertical display cabinet, first with a traditional finned-tube coil and thereafter with the new type of heat exchanger placed in the bottom of the display cabinet. The results showed that the same cooling capacity and mean temperature of the “food packages” could be obtained with around 6 K higher inlet temperature of the liquid, -7°C with the traditional coil and -1°C with the new type of heat exchanger, which can lead to considerable energy savings.
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18462/iir.icr.2015.0790&type=result"></script>'); --> </script>
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18462/iir.icr.2015.0790&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:U.S. EPA Office of Research and Development (ORD) doi: 10.23719/1519294
These are the soil quality data for each county (listed by fips code) for each scenario
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.23719/1519294&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.23719/1519294&type=result"></script>'); --> </script>
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