Find research datasets worth reusing

Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-09-01/2022-10-31): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2022-09-01/2022-10-31. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2022-07-01/2022-08-31): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2022-07-01/2022-08-31. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2022-03-01/2022-04-30): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2022-03-01/2022-04-30. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2022-01-01/2022-02-28): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2022-01-01/2022-02-28. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2000-11-01/2000-12-31): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2000-11-01/2000-12-31. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2000-09-01/2000-10-31): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2000-09-01/2000-10-31. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2022-11-01/2022-12-31): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2022-11-01/2022-12-31. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2000-07-01/2000-08-31): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2000-07-01/2000-08-31. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2000-05-01/2000-06-30): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2000-05-01/2000-06-30. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2000-03-01/2000-04-30): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2000-03-01/2000-04-30. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2022-05-01/2022-06-30): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2022-05-01/2022-06-30. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2000-01-01/2000-02-28): Spectral indices

<h2><strong>Data information</strong></h2> <p>This dataset includes widely used indices for 2000-01-01/2000-02-28. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).</p> <ul> <li><strong>Normalized Difference Vegetation Index (NDVI)</strong> is used to evaluate vegetation health and biomass. It is calculated as <code>(nir - red) / (nir + red)</code> (<a href="https://www.sciencedirect.com/science/article/pii/0034425779900130?via%3Dihub">Tucker, 1979</a>).</li> <li><strong>Normalized Difference Tillage Index (NDTI)</strong>, also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as <code>(swir1 - swir2) / (swir1 + swir2)</code> (<a href="https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf">Van Deventer et al., 1997</a>).</li> <li><strong>Soil Adjusted Vegetation Index (SAVI)</strong> is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as <code>((nir - red) / (nir + red + 0.5)) * 1.5</code> (<a href="https://www.sciencedirect.com/science/article/pii/003442578890106X">Huete, 1988</a>).</li> <li><strong>Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</strong> provides a more direct measurement of plant productivity. It is calculated as <code>((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001</code> (<a href="https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.74">Robinson et al., 2018</a>).</li> <li><strong>Normalized Difference Water Index (NDWI)</strong> provides insights into water dynamics and climatic characteristics. It is calculated as <code>(nir - swir1) / (nir + swir1)</code> (<a href="https://www.sciencedirect.com/science/article/pii/S0034425796000673">Gao, 1996</a>).</li> <li><strong>Normalized Difference Snow Index (NDSI)</strong> helps identify snowy areas. It is calculated as <code>(green - swir1) / (green + swir1)</code> (<a href="https://ieeexplore.ieee.org/abstract/document/1645275/">Salomonson and Appel, 2006</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 - Bimonthly predictor (2000-05-01/2000-06-30): Reflectance bands

<h2><strong>Data Information</strong></h2> <p>This dataset includes seven reflectance bands: blue, green, red, nir, swir1, swir2, and thermal, for the period 2000-05-01/2000-06-30.</p> <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 - Bimonthly predictor (2022-03-01/2022-04-30): Reflectance bands

<h2><strong>Data Information</strong></h2> <p>This dataset includes seven reflectance bands: blue, green, red, nir, swir1, swir2, and thermal, for the period 2022-03-01/2022-04-30.</p> <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 - Bimonthly predictor (2000-07-01/2000-08-31): Reflectance bands

<h2><strong>Data Information</strong></h2> <p>This dataset includes seven reflectance bands: blue, green, red, nir, swir1, swir2, and thermal, for the period 2000-07-01/2000-08-31.</p> <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 - Bimonthly predictor (2022-11-01/2022-12-31): Reflectance bands

<h2><strong>Data Information</strong></h2> <p>This dataset includes seven reflectance bands: blue, green, red, nir, swir1, swir2, and thermal, for the period 2022-11-01/2022-12-31.</p> <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 - Bimonthly predictor (2000-11-01/2000-12-31): Reflectance bands

<h2><strong>Data Information</strong></h2> <p>This dataset includes seven reflectance bands: blue, green, red, nir, swir1, swir2, and thermal, for the period 2000-11-01/2000-12-31.</p> <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 - Bimonthly predictor (2000-01-01/2000-02-28): Reflectance bands

<h2><strong>Data Information</strong></h2> <p>This dataset includes seven reflectance bands: blue, green, red, nir, swir1, swir2, and thermal, for the period 2000-01-01/2000-02-28.</p> <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 - Bimonthly predictor (2022-01-01/2022-02-28): Reflectance bands

<h2><strong>Data Information</strong></h2> <p>This dataset includes seven reflectance bands: blue, green, red, nir, swir1, swir2, and thermal, for the period 2022-01-01/2022-02-28.</p> <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 - Bimonthly predictor (2022-07-01/2022-08-31): Reflectance bands

<h2><strong>Data Information</strong></h2> <p>This dataset includes seven reflectance bands: blue, green, red, nir, swir1, swir2, and thermal, for the period 2022-07-01/2022-08-31.</p> <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>