Other language confidence: 0.6603347524050658
Conductivity-temperature-depth profiles were measured using a ADM-CTD SN MOCNET during RV ALKOR cruise AL592. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. The oxygen sensor (galvanic oxygen micro-sensor (AMT)) was exchanged in the beginning of the year. The sensors are used throughout the year and no post-cruise calibration is applied. All other sensors of the CTD are calibrated irregularly. Data were connected to the station book of the specific cruise as available in the DSHIP database. This dataset presents conductivity–temperature–depth (CTD) profiles collected during the research cruise. The data were processed using a custom Python workflow designed to summarize, standardize, and prepare CTD measurements for publication. Raw sensor output files (.TOB format) were parsed using a dedicated reader that extracts header metadata and harmonizes variable naming conventions across all profiles. Quality control procedures included the removal of non-physical values, treatment of missing or malformed entries, and consistency checks across key variables such as pressure, temperature, conductivity, and derived parameters (e.g., salinity and oxygen). Oxygen values were scaled, and salinity values were corrected according to the respective CTD calibration. Sensor channels were standardized and renamed to ensure compatibility with common data standards. Geographic coordinates were converted from degrees and minutes to decimal degrees to improve geospatial usability. Pressure was linearly interpolated to a uniform 1 dbar grid, and all depth-dependent parameters were interpolated accordingly. Maximum recorded pressure was cross-checked against local bathymetry (elevation); in cases of mismatch, profiles were truncated at the maximum depth of the corresponding location. The workflow further includes visual quality control of oxygen saturation, station locations, and vertical profiles of temperature
Conductivity-temperature-depth profiles were measured using a ADM-CTD SN MOCNET during RV ALKOR cruise AL601. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. The oxygen sensor (galvanic oxygen micro-sensor (AMT)) was exchanged in the beginning of the year. The sensors are used throughout the year and no post-cruise calibration is applied. All other sensors of the CTD are calibrated irregularly. This dataset presents conductivity–temperature–depth (CTD) profiles collected during the research cruise. The data were processed using a custom Python workflow designed to summarize, standardize, and prepare CTD measurements for publication. Raw sensor output files (.TOB format) were parsed using a dedicated reader that extracts header metadata and harmonizes variable naming conventions across all profiles. Quality control procedures included the removal of non-physical values, treatment of missing or malformed entries, and consistency checks across key variables such as pressure, temperature, conductivity, and derived parameters (e.g., salinity and oxygen). Oxygen values were scaled, and salinity values were corrected according to the respective CTD calibration. Sensor channels were standardized and renamed to ensure compatibility with common data standards. Geographic coordinates were converted from degrees and minutes to decimal degrees to improve geospatial usability. Pressure was linearly interpolated to a uniform 1 dbar grid, and all depth-dependent parameters were interpolated accordingly. Maximum recorded pressure was cross-checked against local bathymetry (elevation); in cases of mismatch, profiles were truncated at the maximum depth of the corresponding location. The workflow further includes visual quality control of oxygen saturation, station locations, and vertical profiles of temperature, salinity, and oxygen.
The Tree Species Germany product provides a map of dominant tree species across Germany for the year 2016 at a spatial resolution of 10 meters. The map depicts the distribution of ten tree species groups derived from multi-temporal optical Sentinel-2 data. The input features explicitly incorporate phenological information to capture seasonal vegetation dynamics relevant for species discrimination. A total of over 100,000 training and test samples were compiled from publicly accessible sources, including urban tree inventories, Google Earth Pro, Google Street View, and field observations. The final product was created by majority-voting on annual XGBoost Sentinel-2 tree species classifications (2016–2024) and filtering with forest structure data. If no clear majority vote was achieved, the class uncertain was assigned. The Tree Species Germany 2016 product achieves an overall F1-score of 0.95. For the dominant species pine, spruce, beech, and oak, class-wise F1-scores range from 0.92 to 0.99, while F1-scores for other widespread species such as birch, alder, larch, Douglas fir, fir, and other deciduous species range from 0.85 to 0.96. The product provides a consistent, high-resolution, and up-to-date representation of tree species distribution across Germany. Its transferable, cost-efficient, and repeatable methodology enables reliable large-scale forest monitoring and offers a valuable basis for assessing spatial patterns and temporal changes in forest composition in the context of ongoing climatic and environmental dynamics.
Conductivity-temperature-depth profiles were measured using a Sea&Sun CTM2049 CTD during RV ALKOR cruise AL639. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. The oxygen sensor (galvanic oxygen micro-sensor (AMT)) was exchanged in the beginning of the year. All other sensors were calibrated in March 2024. The sensors are used throughout the year and no post-cruise calibration is applied. Data were connected to the station book of the specific cruise as available in the DSHIP database. This dataset presents conductivity–temperature–depth (CTD) profiles collected during the research cruise. The data were processed using a custom Python workflow designed to summarize, standardize, and prepare CTD measurements for publication. Raw sensor output files (.TOB format) were parsed using a dedicated reader that extracts header metadata and harmonizes variable naming conventions across all profiles. Quality control procedures included the removal of non-physical values, treatment of missing or malformed entries, and consistency checks across key variables such as pressure, temperature, conductivity, and derived parameters (e.g., salinity and oxygen). Oxygen values were scaled, and salinity values were corrected according to the respective CTD calibration. Sensor channels were standardized and renamed to ensure compatibility with common data standards. Pressure was linearly interpolated to a uniform 1 dbar grid, and all depth-dependent parameters were interpolated accordingly. Maximum recorded pressure was cross-checked against local bathymetry (elevation); in cases of mismatch, profiles were truncated at the maximum depth of the corresponding location. The workflow further includes visual quality control of oxygen saturation, station locations, and vertical profiles of temperature, salinity, and oxygen.
Conductivity-temperature-depth profiles were measured using a Sea&Sun CTM2049 CTD during RV ALKOR cruise AL630. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. The oxygen sensor (galvanic oxygen micro-sensor (AMT)) was exchanged in the beginning of the year. All other sensors were calibrated in March 2024. The sensors are used throughout the year and no post-cruise calibration is applied. Data were connected to the station book of the specific cruise as available in the DSHIP database. This dataset presents conductivity–temperature–depth (CTD) profiles collected during the research cruise. The data were processed using a custom Python workflow designed to summarize, standardize, and prepare CTD measurements for publication. Raw sensor output files (.TOB format) were parsed using a dedicated reader that extracts header metadata and harmonizes variable naming conventions across all profiles. Quality control procedures included the removal of non-physical values, treatment of missing or malformed entries, and consistency checks across key variables such as pressure, temperature, conductivity, and derived parameters (e.g., salinity and oxygen). Oxygen values were scaled, and salinity values were corrected according to the respective CTD calibration. Sensor channels were standardized and renamed to ensure compatibility with common data standards. Geographic coordinates were converted from degrees and minutes to decimal degrees to improve geospatial usability. Pressure was linearly interpolated to a uniform 1 dbar grid, and all depth-dependent parameters were interpolated accordingly. Maximum recorded pressure was cross-checked against local bathymetry (elevation); in cases of mismatch, profiles were truncated at the maximum depth of the corresponding location. The workflow further includes visual quality control of oxygen saturation, station locations, and vertical profiles of temperature, salinity, and oxygen.
Conductivity-temperature-depth profiles were measured using a ADM-CTD SN MOCNET during RV ALKOR cruise AL563. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. The oxygen sensor (galvanic oxygen micro-sensor (AMT)) was exchanged in the beginning of the year. The sensors are used throughout the year and no post-cruise calibration is applied. All other sensors of the CTD are calibrated irregularly. This dataset presents conductivity–temperature–depth (CTD) profiles collected during the research cruise. The data were processed using a custom Python workflow designed to summarize, standardize, and prepare CTD measurements for publication. Raw sensor output files (.TOB format) were parsed using a dedicated reader that extracts header metadata and harmonizes variable naming conventions across all profiles. Quality control procedures included the removal of non-physical values, treatment of missing or malformed entries, and consistency checks across key variables such as pressure, temperature, conductivity, and derived parameters (e.g., salinity and oxygen). Oxygen values were scaled, and salinity values were corrected according to the respective CTD calibration. Sensor channels were standardized and renamed to ensure compatibility with common data standards. Geographic coordinates were converted from degrees and minutes to decimal degrees to improve geospatial usability. Pressure was linearly interpolated to a uniform 1 dbar grid, and all depth-dependent parameters were interpolated accordingly. Maximum recorded pressure was cross-checked against local bathymetry (elevation); in cases of mismatch, profiles were truncated at the maximum depth of the corresponding location. The workflow further includes visual quality control of oxygen saturation, station locations, and vertical profiles of temperature, salinity, and oxygen.
Conductivity-temperature-depth profiles were measured using a CTD during RV ALKOR cruise AL435. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. All sensors are calibrated irregularly. Data were connected to the station book of the specific cruise as available in the DSHIP database.
Conductivity-temperature-depth profiles were measured using a ADM-CTD SN MOCNET during RV ALKOR cruise AL594. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. The oxygen sensor (galvanic oxygen micro-sensor (AMT)) was exchanged in the beginning of the year. The sensors are used throughout the year and no post-cruise calibration is applied. All other sensors of the CTD are calibrated irregularly. Data were connected to the station book of the specific cruise as available in the DSHIP database. This dataset presents conductivity–temperature–depth (CTD) profiles collected during the research cruise. The data were processed using a custom Python workflow designed to summarize, standardize, and prepare CTD measurements for publication. Raw sensor output files (.TOB format) were parsed using a dedicated reader that extracts header metadata and harmonizes variable naming conventions across all profiles. Quality control procedures included the removal of non-physical values, treatment of missing or malformed entries, and consistency checks across key variables such as pressure, temperature, conductivity, and derived parameters (e.g., salinity and oxygen). Oxygen values were scaled, and salinity values were corrected according to the respective CTD calibration. Sensor channels were standardized and renamed to ensure compatibility with common data standards. Geographic coordinates were converted from degrees and minutes to decimal degrees to improve geospatial usability. Pressure was linearly interpolated to a uniform 1 dbar grid, and all depth-dependent parameters were interpolated accordingly. Maximum recorded pressure was cross-checked against local bathymetry (elevation); in cases of mismatch, profiles were truncated at the maximum depth of the corresponding location. The workflow further includes visual quality control of oxygen saturation, station locations, and vertical profiles of temperature, salinity, and oxygen.
Conductivity-temperature-depth profiles were measured using a Sea&Sun CTM2049 CTD during RV ALKOR cruise AL632. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. The oxygen sensor (galvanic oxygen micro-sensor (AMT)) was exchanged in the beginning of the year. All other sensors were calibrated in March 2024. The sensors are used throughout the year and no post-cruise calibration is applied. Data were connected to the station book of the specific cruise as available in the DSHIP database. This dataset presents conductivity–temperature–depth (CTD) profiles collected during the research cruise. The data were processed using a custom Python workflow designed to summarize, standardize, and prepare CTD measurements for publication. Raw sensor output files (.TOB format) were parsed using a dedicated reader that extracts header metadata and harmonizes variable naming conventions across all profiles. Quality control procedures included the removal of non-physical values, treatment of missing or malformed entries, and consistency checks across key variables such as pressure, temperature, conductivity, and derived parameters (e.g., salinity and oxygen). Oxygen values were scaled, and salinity values were corrected according to the respective CTD calibration. Sensor channels were standardized and renamed to ensure compatibility with common data standards. Pressure was linearly interpolated to a uniform 1 dbar grid, and all depth-dependent parameters were interpolated accordingly. Maximum recorded pressure was cross-checked against local bathymetry (elevation); in cases of mismatch, profiles were truncated at the maximum depth of the corresponding location. The workflow further includes visual quality control of oxygen saturation, station locations, and vertical profiles of temperature, salinity, and oxygen.
Conductivity-temperature-depth profiles were measured using a Sea&Sun CTM2049 CTD during RV ALKOR cruise AL610. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. The oxygen sensor (galvanic oxygen micro-sensor (AMT)) was exchanged in the beginning of the year. All other sensors were calibrated in March 2024. The sensors are used throughout the year and no post-cruise calibration is applied. Data were connected to the station book of the specific cruise as available in the DSHIP database. This dataset presents conductivity–temperature–depth (CTD) profiles collected during the research cruise. The data were processed using a custom Python workflow designed to summarize, standardize, and prepare CTD measurements for publication. Raw sensor output files (.TOB format) were parsed using a dedicated reader that extracts header metadata and harmonizes variable naming conventions across all profiles. Quality control procedures included the removal of non-physical values, treatment of missing or malformed entries, and consistency checks across key variables such as pressure, temperature, conductivity, and derived parameters (e.g., salinity and oxygen). Oxygen values were scaled, and salinity values were corrected according to the respective CTD calibration. Sensor channels were standardized and renamed to ensure compatibility with common data standards. Geographic coordinates were converted from degrees and minutes to decimal degrees to improve geospatial usability. Pressure was linearly interpolated to a uniform 1 dbar grid, and all depth-dependent parameters were interpolated accordingly. Maximum recorded pressure was cross-checked against local bathymetry (elevation); in cases of mismatch, profiles were truncated at the maximum depth of the corresponding location. The workflow further includes visual quality control of oxygen saturation, station locations, and vertical profiles of temperature, salinity, and oxygen.
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