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7 results for “diFUME”

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zenodo48/100

diFUME Digital Surface Model V0.2

<p>Description:</p> <p>Digital Surface Model (V0.2) of Basel for diFUME project. Terrain model (DTM) is calculated from the height model of the Basel-Stadt official survey (<a href="http://www.gva.bs.ch">http://www.gva.bs.ch</a>). The building digital surface model (DSM) combines the DTM product with the building heights derived from the 3D city model (<a href="http://www.gva.bs.ch">http://www.gva.bs.ch</a>). These products describe the height in meters above sea level. Tree crown heights (m above ground level) are derived by the airborne Lidar data (2018 campaign) made available by the civil engineering office of Basel-Stadt (<a href="https://www.tiefbauamt.bs.ch/">https://www.tiefbauamt.bs.ch/</a>).</p> <p>&nbsp;</p> <p>Data specifications:</p> <p>CRS: EPSG:32632 - WGS 84 / UTM zone 32N - Projected</p> <p>Spatial Extent: 392120.0,5266860.0 : 395160.0,5269840.0</p> <p>Temporal Extent: 2015 - 2019</p> <p>Units: meters</p> <p>Width: 3040</p> <p>Height: 2980</p> <p>Bands: 1</p> <p>Pixel Size: 1,-1</p> <p>Data type: Float32 - Thirty two bit floating point</p> <p>GDAL Driver Description: GTiff</p> <p>GDAL Driver Metadata: GeoTIFF</p>

opencc-by-4.0Oct 2022View details →
zenodo48/100

diFUME Land Cover V0.2

<p>Description:</p> <p>Land Cover map (V0.2) of Basel for diFUME project at three different levels of information. Level 1 information originates from the Official survey of Basel-Stadt (<a href="http://www.gva.bs.ch">http://www.gva.bs.ch</a>). Level 2 aggregates the information of Level 1 into 8 broad categories. Level 3 includes the information of tree canopies and crown, derived by airborne Lidar data (2018 campaign) made available by the civil engineering office of Basel-Stadt (<a href="https://www.tiefbauamt.bs.ch/">https://www.tiefbauamt.bs.ch/</a>) and classifies buildings to Commercial/Industrial according to building type information (<a href="http://www.geo.bs.ch">http://www.geo.bs.ch</a>). Additionally, road type classification is available according to a city map and the vehicle traffic zones (<a href="http://www.mobilitaet.bs.ch">http://www.mobilitaet.bs.ch</a>).</p> <p>&nbsp;</p> <p>Data specifications:</p> <p>CRS: EPSG:32632 - WGS 84 / UTM zone 32N - Projected</p> <p>Spatial Extent: 392120.0,5266860.0 : 395160.0,5269840.0</p> <p>Temporal Extent: 2019</p> <p>Units: meters</p> <p>Width: 3040</p> <p>Height: 2980</p> <p>Bands: 1</p> <p>Pixel Size: 1,-1</p> <p>Data type: Float32 - Thirty two bit floating point</p> <p>GDAL Driver Description: GTiff</p> <p>GDAL Driver Metadata: GeoTIFF</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>Legend:</p> <p>&nbsp;</p> <p>Level 1:</p> <p>0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Buildings</p> <p>1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tanks</p> <p>2&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Road</p> <p>3&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Pavement</p> <p>4&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Paved surfaces</p> <p>5&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Train lines</p> <p>6&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tram lines</p> <p>8&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Water</p> <p>9&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Port area</p> <p>10&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Industrial area</p> <p>11&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Paved surfaces</p> <p>12&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Sport facilities</p> <p>13&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Paved surfaces</p> <p>14&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Meadow</p> <p>17&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Gardens</p> <p>18&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Parks</p> <p>19&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Graveyard</p> <p>20&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Community gardens</p> <p>21&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Zoo</p> <p>22&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Sport facilities</p> <p>24&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Free lands</p> <p>25&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Agricultural lands</p> <p>27&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Water</p> <p>29&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Forest</p> <p>32&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Pervious surfaces</p> <p>&nbsp;</p> <p>Level 2:</p> <p>0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Buildings</p> <p>2&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Roads</p> <p>3&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Pavements</p> <p>4&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Paved surfaces</p> <p>5&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Train lines</p> <p>8&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Water</p> <p>29&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Forest</p> <p>33&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Soil/vegetation</p> <p>&nbsp;</p> <p>Level 3:</p> <p>0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Buildings</p> <p>2&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Roads</p> <p>3&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Pavements</p> <p>4&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Paved surfaces</p> <p>5&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Train lines</p> <p>8&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Water</p> <p>10&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Trees</p> <p>33&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Soil/low vegetation</p> <p>35&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Commercial/Industrial 50 %</p> <p>36&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Commercial/Industrial 100 %</p> <p>&nbsp;</p> <p>Road Classification:</p> <p>1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Settlement oriented roads</p> <p>2&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Main roads</p> <p>3&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Main collecting roads</p> <p>4&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Other roads/paths</p> <p>5&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Meeting areas (20 km/h)</p> <p>6&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tempo 30 (30 km/h)</p> <p>0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Nodata</p>

opencc-by-4.0Oct 2022View details →
zenodo48/100

diFUME In-situ meteorological dataset

<p>Description</p> <p>Air temperature and vapor pressure are measured on a micrometeorological tower located near the centre of Basel (BKLI). Vapor Pressure Deficit (VPD) is then calculated based on saturated vapor pressure estimation. Direct and diffuse incoming radiation are measured with a 2-axis sun tracker (INTRA, BRUSAG) at the roof-level in an unobscured location next to the micrometeorological tower. Measured shortwave radiant flux densities (W m-2) are converted to photon flux densities (&mu;mol m-2 s-1) within PAR (i.e. photosynthetic active radiation, solar shortwave radiation between 400 &ndash; 700 nm) using a standard conversion factor. Soil temperature (oC) and volumetric water content (m3 m-3) are continuously measured at three different locations of the study area at 10 cm below surface. The locations have different characteristics, BKLI is at a street canyon, BKFP is at a non-irrigated park location and BSMP is at an irrigated park location. Soil temperature is also continuously measured at a station outside the city center (BLER) and soil volumetric water content is estimated from lysimeter measurements from another station outside the city centre (BIN).</p> <p>Data format: comma separated values (csv)</p> <p>Time step: 60 min (aggregated)</p> <table> <tbody> <tr> <td> <p><strong>Station acronym</strong></p> </td> <td> <p><strong>Geographic location</strong></p> </td> <td> <p><strong>Variables</strong></p> </td> <td> <p><strong>Units</strong></p> </td> <td> <p><strong>Sensor type - model</strong></p> </td> <td> <p><strong>Sensor height (m a.g.l.)</strong></p> </td> </tr> <tr> <td> <p>BKLI</p> </td> <td> <p>47.56173 &deg;N, 7.58049 &deg;E</p> </td> <td> <p>Air temperature (Tair)</p> </td> <td> <p>Degrees Celsius</p> </td> <td> <p>Thermo-HYGrometer (Thygan)</p> </td> <td> <p>38</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Vapor pressure (WVP)</p> </td> <td> <p>kPa</p> </td> <td> <p>Thermo-HYGrometer (Thygan)</p> </td> <td> <p>38</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Saturation vapor pressure (es)</p> </td> <td> <p>kPa</p> </td> <td> <p>Estimated by Thygan measurements</p> </td> <td> <p>38</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Vapor pressure deficit (VPD)</p> </td> <td> <p>kPa</p> </td> <td> <p>Estimated by Thygan measurements</p> </td> <td> <p>38</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Direct radiation</p> </td> <td> <p>W / m2</p> </td> <td> <p>Pyrheliometer (CHP1, Kipp &amp; Zonen)</p> </td> <td> <p>21</p> <p>&nbsp;</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Diffuse radiation</p> </td> <td> <p>W / m2</p> </td> <td> <p>Pyranometer (CM21, Kipp &amp; Zonen)</p> <p>&nbsp;</p> </td> <td> <p>21</p> <p>&nbsp;</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>PAR direct</p> </td> <td> <p>&mu;mol / m2 / s</p> </td> <td> <p>Estimated by Pyrheliometer measurements</p> </td> <td> <p>21</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>PAR diffuse</p> </td> <td> <p>&mu;mol / m2 / s</p> </td> <td> <p>Estimated by Pyranometer measurements</p> </td> <td> <p>21</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>PAR global</p> </td> <td> <p>&mu;mol / m2 / s</p> </td> <td> <p>Estimated by Pyrheliometer and Pyranometer measurements</p> </td> <td> <p>21</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Soil temperature (Tsoil)</p> </td> <td> <p>Degrees Celsius</p> </td> <td> <p>Thermistor (CS655, Campbell Scientific Inc.)</p> </td> <td> <p>-0.1</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Soil moisture (theta)</p> </td> <td> <p>m3/m3</p> </td> <td> <p>Water content reflectometer (CS655, Campbell Scientific Inc.)</p> </td> <td> <p>-0.1</p> </td> </tr> <tr> <td> <p>BKFP</p> </td> <td> <p>47.56595 &deg;N,&nbsp;</p> <p>7.56921 &deg;E</p> </td> <td> <p>Soil temperature (Tsoil)</p> </td> <td> <p>Degrees Celsius</p> </td> <td> <p>Thermistor (CS655, Campbell Scientific Inc.)</p> </td> <td> <p>-0.1</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Soil moisture (theta)</p> </td> <td> <p>m3/m3</p> </td> <td> <p>Water content reflectometer (CS655, Campbell Scientific Inc.)</p> </td> <td> <p>-0.1</p> </td> </tr> <tr> <td> <p>BSMP</p> </td> <td> <p>47.5529 &deg;N,&nbsp;</p> <p>7.57456 &deg;E</p> </td> <td> <p>Soil temperature (Tsoil)</p> </td> <td> <p>Degrees Celsius</p> </td> <td> <p>Thermistor (CS655, Campbell Scientific Inc.)</p> </td> <td> <p>-0.1</p> </td> </tr> <tr> <td> <p>&nbsp;</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Soil moisture (theta)</p> </td> <td> <p>m3/m3</p> </td> <td> <p>Water content reflectometer (CS655, Campbell Scientific Inc.)</p> </td> <td> <p>-0.1</p> </td> </tr> <tr> <td> <p>BLER</p> </td> <td> <p>47.5923 &deg;N, 7.6493 &deg;E</p> </td> <td> <p>Soil temperature (Tsoil)</p> </td> <td> <p>Degrees Celsius</p> </td> <td> <p>Thermistor</p> </td> <td> <p>-0.1</p> </td> </tr> <tr> <td> <p>BIN</p> </td> <td> <p>47.5411 &deg;N, 7.5835 &deg;E</p> </td> <td> <p>Soil moisture (theta)</p> </td> <td> <p>m3/m3</p> </td> <td> <p>Estimated by weighable lysimeter measurements</p> </td> <td> <p>-2</p> </td> </tr> </tbody> </table>

opencc-by-4.0Oct 2022View details →
zenodo48/100

diFUME Population Density V0.1

<p>Description:</p> <p>Annual statistics per city block on residential population (by age group) and workplace employees (<a href="https://www.basleratlas.ch/">https://www.basleratlas.ch/</a> ) are used to derive maps of annual night-time and daytime building-scale population density (inhabitants per m2) for weekdays and weekends. The spatial resampling of the population is based on the assumption of proportionality between building inhabitants and building volume (estimated as mean building height&times;building plan area, derived by land cover and DSM products). Considering the building type, building volume is separated to residential volume and workplace volume, so that population is redistributed between night-time, daytime, workdays and weekends.</p> <p>&nbsp;</p> <p>Data specifications:</p> <p>CRS: EPSG:32632 - WGS 84 / UTM zone 32N - Projected</p> <p>Spatial Extent: 392120.0,5266860.0 : 395160.0,5269840.0</p> <p>Temporal Extent: 2018 - 2020</p> <p>Units: meters</p> <p>Width: 608</p> <p>Height: 596</p> <p>Bands: 1</p> <p>Pixel Size: 5,-5</p> <p>Data type: Float32 - Thirty two bit floating point</p> <p>GDAL Driver Description: GTiff</p> <p>GDAL Driver Metadata: GeoTIFF</p>

opencc-by-4.0Oct 2022View details →
zenodo48/100

diFUME eddy covariance dataset

<p>Net CO<sub>2</sub> flux (FC) time-series and the respective random error (RE) estimations at 30 min time step of the period 2018 - 2020 from two urban eddy covariance sites in the center of Basel. Data are produced using the EddyPro&reg; Software v7.0.6 (LI-COR Inc.). The main processing steps include axis rotation for tilt correction using the double rotation method, linear detrending to extract turbulent fluctuations, covariance maximization for time-lag compensation between the gas analyser and the sonic anemometer and density fluctuation compensation. Spectral corrections are also applied to flux estimates for low and high frequency losses. Quality flagging is performed according to steady state and integral turbulence characteristics tests &nbsp;based on the 3-point flagging system of Mauder and Foken. Flux random uncertainty estimation is performed according to the method of Finkelstein and Sims (2001). The time-series are filtered according to multiple criteria to avoid problematic values.</p> <p>&nbsp;</p> <p>Data format: comma separated values (csv)</p> <p>Time step: 30 min</p> <p>&nbsp;</p> <table> <tbody> <tr> <td> <p>Station acronym</p> </td> <td> <p>Geographic location</p> </td> <td> <p>Sensor height (m a.g.l.)</p> </td> <td> <p>Sensor models (sonic anemometer, gas analyser)</p> </td> <td> <p>Sonic azimuth (<sup>o</sup>)</p> </td> <td> <p>Acquisition frequency (Hz)</p> </td> </tr> <tr> <td> <p>BKLI</p> </td> <td> <p>47.56173 &deg;N, 7.58049 &deg;E</p> </td> <td> <p>39</p> </td> <td> <p>HS-100 (Gill Instruments Ltd.),</p> <p>LI-7500 (LI-COR Inc.)</p> </td> <td> <p>0</p> </td> <td> <p>20</p> </td> </tr> <tr> <td> <p>BAES</p> </td> <td> <p>47.55123 &deg;N, 7.59560 &deg;E</p> </td> <td> <p>41</p> </td> <td> <p>CSAT3 (Campbell Scientific Inc.), LI-7500 (LI-COR Inc.)</p> </td> <td> <p>340</p> </td> <td> <p>20</p> </td> </tr> </tbody> </table> <p>&nbsp;</p>

opencc-by-4.0Jan 2023View details →
zenodo44/100

diFUME Leaf Area Index V0.1

<p>Description:</p> <p>The Level 2A (L2A) product by the Theia Land Data Centre of CNES (Centre national d&#39;&eacute;tudes spatiales) is used, which provides georeferenced and orthorectified surface reflectance (SR), water vapor content (WVC), aerosol optical thickness (AOT), cloud and geophysical masks, processed by the MAJA atmospheric processing software. The 10 m SR bands in red (SRred : 665 nm) and near-infrared (SRNIR : 842 nm) are used to compute NDVI (Normalized Difference Vegetation Index) as (SRNIR &ndash; SRred)/(SRNIR + SRred) and the product is masked for clouds, cloud shadows and snow according to the L2A product flags. NDVI is converted to Leaf Area Index (LAI) values by applying an empirical exponential formula and is then resampled from 10 m to 5 m resolution, enhancing the initial LAI values, using the vegetation fraction derived by the 1 m Land Cover product.</p> <p>&nbsp;</p> <p>Data specifications:</p> <p>CRS: EPSG:32632 - WGS 84 / UTM zone 32N - Projected</p> <p>Spatial Extent: 392120.0,5266860.0 : 395160.0,5269840.0</p> <p>Temporal Extent: 2018 - 2020</p> <p>Units: meters</p> <p>Width: 608</p> <p>Height: 596</p> <p>Bands: 1</p> <p>Pixel Size: 5,-5</p> <p>Data type: Float32 - Thirty two bit floating point</p> <p>GDAL Driver Description: GTiff</p> <p>GDAL Driver Metadata: GeoTIFF</p>

opencc-by-4.0Oct 2022View details →
zenodo44/100

diFUME Modeled CO2 fluxes V03

<p>Description:</p> <p>Weekly mean CO<sub>2</sub> fluxes (FC, &mu;mol CO<sub>2</sub> m<sup>-2</sup> s<sup>-1</sup>) after the inversion method (posteriors) in weekly cycles developed in diFUME project. The variance (&sigma;<sup>2</sup>) of the posterior distributions is also provided. The inversion method is different from the posteriors of V02.</p> <p>&nbsp;</p> <p>Each flux component is provided separately:</p> <p>Building heating emissions: Eb</p> <p>Commercia/Industrial emissions: Ec</p> <p>Vehicle emissions: Ev</p> <p>Human respiration: Rh</p> <p>Biogenic flux: Bm (sum of soil respiration, plant respiration and plant photosynthesis)</p> <p>Total FC = Eb + Ec + Ev + Rh + Bm</p> <p>&nbsp;</p> <p>Filenames:</p> <p>**_postyyyyMMdd: Posterior model estimations for the week that starts at the day defined by yyyy: year, MM: month, dd: day</p> <p>**_post_varyyyyMMdd: Posterior model variances (&sigma;<sup>2</sup>) for the week that starts at the day defined by yyyy: year, MM: month, dd: day</p> <p>&nbsp;</p> <p>Data specifications:</p> <p>CRS: EPSG:32632 - WGS 84 / UTM zone 32N - Projected</p> <p>Spatial Extent: 392120.0,5266860.0 : 395160.0,5269840.0</p> <p>Temporal Extent: 2018</p> <p>Units: meters</p> <p>Width: 152</p> <p>Height: 149</p> <p>Bands: 1</p> <p>Pixel Size: 20,-20</p> <p>Data type: Float32 - Thirty two bit floating point</p> <p>GDAL Driver Description: GTiff</p> <p>GDAL Driver Metadata: GeoTIFF</p>

opencc-by-4.0Apr 2023View details →

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Last verified 2026-04-30Open record

International Brain Laboratory public data

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Last verified 2026-04-29Open record

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Last verified 2026-04-29Open record