cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10884482
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-09-01/2022-10-31): Spectral indices

description: Data information
        
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).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.5281/zenodo.10884483
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-09-01/2022-10-31): Spectral indices

description: Data information
        
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).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.5281/zenodo.10884447
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-07-01/2022-08-31): Spectral indices

description: Data information
        
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).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.5281/zenodo.10884448
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-07-01/2022-08-31): Spectral indices

description: Data information
        
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).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.5281/zenodo.10884419
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-05-01/2022-06-30): Spectral indices

description: Data information
        
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).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.5281/zenodo.10884420
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-05-01/2022-06-30): Spectral indices

description: Data information
        
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).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.5281/zenodo.10884406
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-03-01/2022-04-30): Spectral indices

description: Data information
        
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).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.5281/zenodo.10884407
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-03-01/2022-04-30): Spectral indices

description: Data information
        
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).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.5281/zenodo.10884387
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-01-01/2022-02-28): Spectral indices

description: Data information
        
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).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.5281/zenodo.10884388
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-01-01/2022-02-28): Spectral indices

description: Data information
        
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).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.6084/m9.figshare.25567335
title: In silico mutagenesis predictions

description: See <b>doi:</b> https://doi.org/10.1101/2024.03.29.587323 for more information.Model in silico perturbation results.
DOI: 10.6084/m9.figshare.25567335.v1
title: In silico mutagenesis predictions

description: See <b>doi:</b> https://doi.org/10.1101/2024.03.29.587323 for more information.Model in silico perturbation results.
DOI: 10.15468/dl.r24xqz
title: Occurrence Download

description: A dataset containing 49 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Python anchietae Bocage, 1887"
 ]
}

 The dataset includes 49 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035620-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.