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1,254 results for “pan”
Level A Pan Europe Modelled river discharge, E-HYPE 2.5
Simulated river discharge at each subbasin from E-HYPEv2.5 in m3/s. Daily data for 1961 to 2001 as time-series. Original data source: See information about the E-HYPE setup. Tools for repurposing: HYPE. Temporal resolution: Daily. Spatial resolution: 215 km2. Unit: m3/s. Data format: Zipped text file. On the first row there is a brief description and the rest of the file contains one row per time step, with the sub basin id as each column header on the second row. The first item on each line is the time step using the format YYYY-MM-DD, so 1961-01-01 for the first of January 1961. The dataset, Subbasin(EHYPE2pt5).zip (shapefile with subbasin polygons) can be linked with the data.
Level A Pan Europe Temperature, E-HYPE 2.5
Time series for 1961 to 2001 describing corrected air temperature for each E-HYPE subbasin. The data describes daily values for each subbasin. Unit of measurement: degrees Celsius. The temperature is derived from the WFD gridded data set which consists of the ERA-40 reanalysis data set daily temperature (Weedon et al. 2011). For each subbasin (mean area 215km2), the grid point nearest the subbasin centroid is used. Temperature at the grid elevation is corrected in the HYPE model to temperature at the subbasin elevation using a factor in the parameter file. Original data source was WFD Forcing data and HYDE was used for repurposing. The data formate is a zipped text file. On the first row there is a brief description and the rest of the file contains one row per time step, with the sub basin id as each column header on the second row. The first item on each line is the time step using the format YYYY-MM-DD, so 1961-01-01 for the first of January 1961.
C2D2: An Open-Source, Pan-European, Harmonised Crop Development Database for Use in Regulatory Pesticide Exposure Modelling and Risk Assessment.
<p>There is a regulatory need for crop development dates to assess current default values used within chemical exposure assessments as well as to justify refinements within risk assessments. However, a readily available pan-European crop phenology database covering key FOCUS (FOrum for the Co-ordination of pesticide fate models and their USe) crops and scenarios to meet this need is not currently available. Therefore, we describe the development of a harmonised, pan-European, CropLife Europe Crop Development Database, C2D2, that is fully aligned with this regulatory requirement utilising efficacy trials data generated for regulatory submissions when registering plant protection products under Regulation (EU) 1107/2009. Evaluation of C2D2 against an independent dataset showed good agreement for equivalent time periods, crop growth stages and geographical regions. We illustrate how this database can be used to evaluate existing default crop development dates mandated by regulatory agencies for use within exposure assessments. Despite the large dataset compiled and the geographical coverage of C2D2, not all FOCUSsw/gw scenarios have sufficient data to facilitate comparison, with less significant scenarios, like FOCUSgw Porto, being under-represented. For those scenarios with sufficient data, clear differences between C2D2 and crop development dates assumed in the FOCUS modelling framework (using the AppDate tool) are often indicated over some/many growth stages suggesting that amendment of the existing representation of crop development within the risk assessment process may be required. C2D2 is freely available under a Creative Commons licence to facilitate innovation in exposure science to allow for more accurate and realistic risk assessment leading to enhanced crop and environmental protection.</p>
Implications of Socio-Economic Conditions on Common Mental Disorders: A Case-study of Salt Pan Workers in Marakkanam Block of Tamil Nadu
<p>Socio-economic indicators of Saltpan workers in Marakaanam, Tamil Nadu, India and their SRQ-20 scoring.</p><p>Data regarding; Consumption, Wages, Debt, Social Group, Gender, Age, Ration Card, Education, Distance from work(saltpan), ownership of house and the SRQ-20 Questionanaire used for Screening of CMDs and Distress levels </p>
Landsat-based Spectral Indices for pan-EU 2000-2022
<h2><strong>Description</strong></h2> <h3><strong>General description</strong></h3> <p>Here, we present the ARCO (analysis-ready and cloud-optimized) Landsat-based Spectral Indices data cube. Available at 30m resolution from 2000 to 2022, it includes multiple spectral indices and multi-tier predictors (bimonthly, annual, and long-term) for continental Europe, including Ukraine, the UK, and Turkey (excluding Svalbar). This data cube has a broad coverage of indices, each providing unique insights into different aspects, including: surface reflectance, vegetation, water, soil and crop. All data layers are cloud-masked and then gap-filled, ready for analysis, modeling, and mapping applications. Technical details:</p> <ul> <li><strong>Coordinate reference system:</strong> EPSG:3035</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (900,000, 899,000, 7,401,000, 5,501,000)</li> <li><strong>Spatial resolution:</strong> 30m</li> <li><strong>Image size:</strong> 216,700P x 153,400L</li> <li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li> </ul> <p>Considering the data volume, only bimonthly data layers for the years 2000 and 2022 are uploaded. However, all annual and long-term layers are available. For the full data cube, please visit this <a href="https://docs.google.com/spreadsheets/d/1QTA6OkkYlZljfHst_inCrkC7DJcMAyHnM9k0iHulwpg/edit?usp=sharing">catalog</a>. Due to Zenodo's storage limits, the data layers are stored in different buckets. Use the identifier-navigation list below to access the bucket of your interest and download the corresponding layers.</p> <h3><strong>Identifier navigation list</strong></h3> <p>This data cube includes 4 tiers of data, depending on the processing extend in the temporal scale:</p> <ul> <li><strong>Tier-1: Bimonthly Landsat reflectance bands</strong><br>2000 (<a href="../records/12805260">Jan</a> <a href="../records/12806079">Mar</a> <a href="../records/12803844">May</a> <a href="../records/12805020">Jul</a> <a href="../records/12915187">Sep</a> <a href="../records/12804826">Nov</a>) 2022 (<a href="../records/12805807">Jan</a> <a href="../records/12804063">Mar</a> <a href="../records/12911628">May</a> <a href="../records/12805508">Jul</a> <a href="../records/12805649">Sep</a> <a href="../records/12804421">Nov</a>)</li> <li><strong>Tier-2: Bimonthly spectral indices</strong><br>2000 (<a href="../records/10884234">Jan</a> <a href="../records/10884272">Mar</a> <a href="../records/10884296">May</a> <a href="../records/10884311">Jul</a> <a href="../records/10884340">Sep</a> <a href="../records/10884358">Nov</a>) 2022 (<a href="../records/10884387">Jan</a> <a href="../records/10884406">Mar</a> <a href="../records/10884419">May</a> <a href="../records/10884447">Jul</a> <a href="../records/10884482">Sep</a> <a href="../records/10884503">Nov</a>)</li> <li><strong>Tier-3: Annual predictors<br></strong> <ul> <li>Reflectance bands, NDVI and NDWI P25<br><a href="../records/10777969">2000</a> <a href="../records/10777971">2001</a> <a href="../records/10777973">2002</a> <a href="../records/10777975">2003</a> <a href="../records/10777977">2004</a> <a href="../records/10777979">2005</a> <a href="../records/10777981">2006</a> <a href="../records/10777983">2007</a> <a href="../records/10777985">2008</a> <a href="../records/10777987">2009</a> <a href="../records/10777989">2010</a> <a href="../records/10777991">2011</a> <a href="../records/10777993">2012</a> <a href="../records/10777995">2013</a> <a href="../records/10777997">2014</a> <a href="../records/10777999">2015</a> <a href="../records/10778001">2016</a> <a href="../records/10778003">2017</a> <a href="../records/10778005">2018</a> <a href="../records/10778007">2019</a> <a href="../records/10778009">2020</a> <a href="../records/10778011">2021</a> <a href="../records/10778013">2022</a></li> <li>Reflectance bands, NDVI and NDWI P50<br><a href="../records/10851076">2000</a> <a href="../records/10864828">2001</a> <a href="../records/10864838">2002</a> <a href="../records/10864852">2003</a> <a href="../records/10864874">2004</a> <a href="../records/10864896">2005</a> <a href="../records/10864952">2006</a> <a href="../records/10865027">2007</a> <a href="../records/10865253">2008</a> <a href="../records/10865315">2009</a> <a href="../records/10865398">2010</a> <a href="../records/10865486">2011</a> <a href="../records/10865536">2012</a> <a href="../records/10865630">2013</a> <a href="../records/10865721">2014</a> <a href="../records/10865803">2015</a> <a href="../records/10865857">2016</a> <a href="../records/10865905">2017</a> <a href="../records/10865920">2018</a> <a href="../records/10865948">2019</a> <a href="../records/10865973">2020</a> <a href="../records/10865992">2021</a> <a href="../records/10851078">2022</a></li> <li>Reflectance bands, NDVI and NDWI P75<br><a href="../records/10851080">2000</a> <a href="../records/10866025">2001</a> <a href="../records/10866071">2002</a> <a href="../records/10866095">2003</a> <a href="../records/10866108">2004</a> <a href="../records/10866121">2005</a> <a href="../records/10866153">2006</a> <a href="../records/10866194">2007</a> <a href="../records/10866224">2008</a> <a href="../records/10866256">2009</a> <a href="../records/10866294">2010</a> <a href="../records/10866319">2011</a> <a href="../records/10866337">2012</a> <a href="../records/10866367">2013</a> <a href="../records/10866410">2014</a> <a href="../records/10866436">2015</a> <a href="../records/10866474">2016</a> <a href="../records/10866496">2017</a> <a href="../records/10866514">2018</a> <a href="../records/10866533">2019</a> <a href="../records/10866572">2020</a> <a href="../records/10866603">2021</a> <a href="../records/10851082">2022</a></li> <li>Aggregated spectral indices<br><a href="../records/10777868">2000</a> <a href="../records/10777870">2001</a> <a href="../records/10777872">2002</a> <a href="../records/10777874">2003</a> <a href="../records/10777876">2004</a> <a href="../records/10777878">2005</a> <a href="../records/10777880">2006</a> <a href="../records/10777882">2007</a> <a href="../records/10777884">2008</a> <a href="../records/10777886">2009</a> <a href="../records/10777888">2010</a> <a href="../records/10777890">2011</a> <a href="../records/10777892">2012</a> <a href="../records/10777894">2013</a> <a href="../records/10777896">2014</a> <a href="../records/10777898">2015</a> <a href="../records/10777900">2016</a> <a href="../records/10777902">2017</a> <a href="../records/10777904">2018</a> <a href="../records/10777906">2019</a> <a href="../records/10777908">2020</a> <a href="../records/10777910">2021</a> <a href="../records/10777912">2022</a></li> <li>Cumulative spectral indices<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022</li> </ul> </li> <li><strong>Tier-4: Long-term predictors 2000-2022</strong><br><a href="../records/10776891">trend</a> <a href="../records/12805999">P25</a> <a href="../records/12804351">P50</a> <a href="../records/12805181">P75</a></li> </ul> <h3><strong>Name convention</strong></h3> <p>To ensure consistency and ease of use across the data layers, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p> <ol> <li><strong>generic variable name:</strong> ndti.min.slopes = the long term slope of minNDTI</li> <li><strong>variable procedure combination:</strong> glad.landsat.ard2.seasconv.yearly.min.theilslopes - theil slopes calculated from yearly minimum values of NDTI</li> <li><strong>Position in the probability distribution/variable type:</strong> m = mean | sd = standard deviation | n = number of observations | qa = quality assessment</li> <li><strong>Spatial support:</strong> 30m</li> <li><strong>Depth reference:</strong> s = surface</li> <li><strong>Time reference begin time:</strong> 20000101 = 2000-01-01</li> <li><strong>Time reference end time:</strong> 20221231 = 2022-12-31</li> <li><strong>Bounding box:</strong> eu = europe (without Svalbar)</li> <li><strong>EPSG code:</strong> epsg.3035</li> <li><strong>Version code:</strong> v20231218 = 2023-12-18 (creation date)</li> </ol> <h3><strong>Citation</strong></h3> <p>Please cite this dataset using the DOI: [<a href="https://doi.org/10.5281/zenodo.10776891">10.5281/zenodo.10776891</a>], which represents all versions of this dataset. This ensures your citation remains up to date with the latest version.</p> <h3><strong>Support</strong></h3> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">GitHub issue</a>!</p> <h2><strong>Long-term spectral indices trend</strong></h2> <p>On this landing page of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>, four long-term spectral indices trend data are stored, as Zenodo doesn't allow empty buckets. Therefore, this page serves not only as the landing page for the entire dataset but also as the bucket for the long-term trend of spectral indices.</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2019): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2019. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2020): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2020. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2015): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2015. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2011): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2011. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2005): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2005. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2000): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2000. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2018): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2018. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2010): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2010. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2004): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2004. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2014): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2014. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2006): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2006. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2017): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2017. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2009): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2009. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2016): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2016. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
Landsat-based Spectral Indices for pan-EU 2000-2022 - Annual predictor (2013): BSF, minNDTI, and NOS
<h2><strong>Data information</strong></h2> <p>This dataset provides annual aggregated predictors BSF, minNDTI, and NOS for the year 2013. They are calculated as follows:</p> <ul> <li><strong>minNDTI (minimum NDTI)</strong> is determined as the minimum value of the six NDTI values over a year (<a href="https://www.sciencedirect.com/science/article/pii/S0034425711003439?casa_token=5P1XeaRMuT4AAAAA:8VyzOkBJb_gbpap0uzjuT6YoYhylvqc_vY2-AOX2KCsZGrwQw1jySGd4Ox9JFz55TPQmF231IQ">Zheng et al., 2012</a>).</li> <li><strong>BSF (bare soil fraction)</strong> is calculated by dividing the number of pixels classified as bare surface within a year's time series (identified by the criterion of NDVI values below 0.35) by the total number of pixels analyzed in that year (<a href="https://www.mdpi.com/2072-4292/11/18/2121">Castaldi et al., 2019</a>).</li> <li><strong>NOS (number of seasons)</strong> indicates the frequency of cropping cycles within a year, calculated by counting NDVI peaks throughout the year (<a href="https://www.mdpi.com/2072-4292/6/3/2473">Li et al., 2014</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0034425720304685?casa_token=u4YFBsBotd4AAAAA:TgMiw5E7HNA9-oSF-oszmaRLzLPQJJmV-I13lvdkog1ibfEIZoPxJ3jA4F8Jcu5eXpzVBOyjew">Liu et al., 2020</a>). </li> </ul> <h2><strong>As a part of a Data Cube</strong></h2> <p>This data represents a subset of the <a href="../records/10776892">Time-series of Landsat-based Spectral Indices (EU, 30m) data cube</a>. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.</p> <ul> <li>To cite this dataset, refer to the DOI available on the landing page.</li> <li>To access other data layers in the data cube, use the navigation catalog on the landing page as well.</li> </ul> <h2><strong>Support</strong></h2> <p>If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a <a href="https://github.com/AI4SoilHealth/SoilHealthDataCube/issues">Github Issue</a>!</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.