Global NDVI Records and Environmental Predictors

sf data frame with POINT geometry representing 9,265 global locations with 5 response variables encoding the Normalized Difference Vegetation Index (NDVI) and 58 environmental predictors (47 numeric, 11 categorical). Use vi_extra() to download an extended version with 30,000 rows.

NDVI values are derived from the Copernicus Global Land Service Long Term Statistics product (1999-2019) at 1 km resolution. Locations were spatially thinned to reduce spatial autocorrelation.

Response variable encodings:

vi_numeric: continuous NDVI values in the range 0-1.
vi_counts: simulated integer counts created by multiplying vi_numeric by 1000 and coercing to integer.
vi_binomial: simulated binary variable created by thresholding vi_numeric at 0.5.
vi_categorical: character variable with categories "very_low", "low", "medium", "high", and "very_high", with thresholds at quantiles of vi_numeric.
vi_factor: vi_categorical converted to factor.

Environmental predictors were extracted as pixel values from rasters at 1 km resolution.

Usage

data(vi)

Format

An sf data frame with 9265 rows (locations) and 64 columns:

Response variables (5):

vi_numeric: Continuous NDVI value (0-1).
vi_counts: Integer count encoding of NDVI (vi_numeric * 1000).
vi_binomial: Binary encoding of NDVI (1 if vi_numeric > 0.5, else 0).
vi_categorical: Categorical encoding of NDVI ("very_low", "low", "medium", "high", "very_high").
vi_factor: Factor encoding of NDVI (vi_categorical as factor).

Predictor variables - Climate classification (3):

koppen_zone: Koppen climate zone code (Beck et al. 2018).
koppen_group: Koppen climate group name.
koppen_description: Koppen climate description.

Predictor variables - Soil type (1):

soil_type: Soil classification type.

Predictor variables - Topography (3):

topo_slope: Topographic slope in degrees.
topo_diversity: Number of combinations of different elevations, slopes, and aspects in a 5 km radius around each 1 km cell.
topo_elevation: Elevation in meters.

Predictor variables - Soil water index (4):

swi_mean: Mean annual soil water index (unitless, 0-100 cm depth).
swi_max: Maximum annual soil water index (unitless, 0-100 cm depth).
swi_min: Minimum annual soil water index (unitless, 0-100 cm depth).
swi_range: Annual soil water index range (unitless, 0-100 cm depth).

Predictor variables - Soil temperature (4):

soil_temperature_mean: Mean annual land surface temperature (degrees C).
soil_temperature_max: Maximum annual land surface temperature (degrees C).
soil_temperature_min: Minimum annual land surface temperature (degrees C).
soil_temperature_range: Annual land surface temperature range (degrees C).

Predictor variables - Soil properties (6):

soil_sand: Soil sand content (%).
soil_clay: Soil clay content (%).
soil_silt: Soil silt content (%).
soil_ph: Soil pH.
soil_soc: Soil organic carbon content (%).
soil_nitrogen: Soil nitrogen content (%).

Predictor variables - Solar radiation (4):

solar_rad_mean: Mean annual solar radiation (kJ m-2).
solar_rad_max: Maximum annual solar radiation (kJ m-2).
solar_rad_min: Minimum annual solar radiation (kJ m-2).
solar_rad_range: Annual solar radiation range (kJ m-2).

Predictor variables - Growing season (4):

growing_season_length: Length of the growing season (days).
growing_season_temperature: Mean temperature of the growing season (degrees C).
growing_season_rainfall: Accumulated precipitation of the growing season (kg m-2).
growing_degree_days: Growing degree days above 0 degrees C accumulated over one year (degree-days).

Predictor variables - Temperature (5):

temperature_mean: Mean annual air temperature (degrees C; CHELSA bio1).
temperature_max: Maximum temperature of warmest month (degrees C; CHELSA bio5).
temperature_min: Minimum temperature of coldest month (degrees C; CHELSA bio6).
temperature_range: Annual air temperature range (degrees C; CHELSA bio7).
temperature_seasonality: Temperature seasonality as standard deviation of monthly means (degrees C; CHELSA bio4).

Predictor variables - Rainfall (4):

rainfall_mean: Mean annual rainfall (kg m-2).
rainfall_min: Minimum monthly rainfall (kg m-2).
rainfall_max: Maximum monthly rainfall (kg m-2).
rainfall_range: Annual rainfall range (kg m-2).

Predictor variables - Evapotranspiration (4):

evapotranspiration_mean: Mean annual potential evapotranspiration (kg m-2 month-1; Penman-Monteith).
evapotranspiration_max: Maximum monthly potential evapotranspiration (kg m-2 month-1; Penman-Monteith).
evapotranspiration_min: Minimum monthly potential evapotranspiration (kg m-2 month-1; Penman-Monteith).
evapotranspiration_range: Annual potential evapotranspiration range (kg m-2 month-1; Penman-Monteith).

Predictor variables - Cloud cover (4):

cloud_cover_mean: Mean annual total cloud cover (%).
cloud_cover_max: Maximum monthly total cloud cover (%).
cloud_cover_min: Minimum monthly total cloud cover (%).
cloud_cover_range: Annual total cloud cover range (%).

Predictor variables - Aridity (1):

aridity_index: Mean aridity index (unitless ratio; higher values indicate wetter conditions).

Predictor variables - Humidity (4):

humidity_mean: Mean annual near-surface relative humidity (%).
humidity_max: Maximum monthly near-surface relative humidity (%).
humidity_min: Minimum monthly near-surface relative humidity (%).
humidity_range: Annual near-surface relative humidity range (%).

Predictor variables - Biogeography (3):

biogeo_ecoregion: Ecoregion name.
biogeo_biome: Biome name.
biogeo_realm: Ecological realm name.

Predictor variables - Administrative (4):

country_name: Country name.
continent: Continent name.
region: UN region name.
subregion: UN sub-region name.

Geometry:

geometry: Point geometry (WGS84, EPSG:4326).

Source

Response variables (NDVI):

Copernicus Land Monitoring Service. (2019). Normalised Difference Vegetation Index Statistics (Long Term 1999-2019), raster 1 km, global, version 3. European Commission, Joint Research Centre. https://doi.org/10.2909/290e81fb-4c84-42ad-ae12-f663312b0eda

Climate classification:

Beck, H.E., et al. (2018). Present and future Koppen-Geiger climate classification maps at 1-km resolution. Scientific Data, 5, 180214. https://doi.org/10.1038/sdata.2018.214

Soil water index:

Copernicus Land Monitoring Service: Soil Water Index. https://doi.org/10.2909/290e81fb-4c84-42ad-ae12-f663312b0eda

Climate predictors (temperature, rainfall, solar radiation, growing season, evapotranspiration, cloud cover, humidity):

Brun, P., Zimmermann, N.E., Hari, C., Pellissier, L., & Karger, D.N. (2022). CHELSA-BIOCLIM+ A novel set of global climate-related predictors at kilometre-resolution. EnviDat. https://doi.org/10.16904/envidat.332

Soil type and properties:

Hengl, T., et al. (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLOS ONE, 12(2), e0169748. https://doi.org/10.1371/journal.pone.0169748

Soil temperature:

Wan, Z., Hook, S., & Hulley, G. (2015). MOD11A2 MODIS/Terra Land Surface Temperature/Emissivity 8-Day L3 Global 1km SIN Grid V006. NASA EOSDIS LP DAAC. https://doi.org/10.5067/MODIS/MOD11A2.006

Ecoregions and biogeography:

Dinerstein, E., et al. (2017). An Ecoregion-Based Approach to Protecting Half the Terrestrial Realm. BioScience, 67(6), 534-545. https://doi.org/10.1093/biosci/bix014

Elevation and topography:

Jarvis, A., Guevara, E., Reuter, H. I., & Nelson, A. D. (2008). Hole-filled SRTM for the globe: version 4, data grid. Web publication/site, CGIAR Consortium for Spatial Information. https://srtm.csi.cgiar.org

Aridity index:

Zomer, R.J., Xu, J., & Trabucco, A. (2022). Version 3 of the Global Aridity Index and Potential Evapotranspiration Database. Scientific Data, 9, 409. https://doi.org/10.1038/s41597-022-01493-1

Country, continent, region, and subregion:

Natural Earth. Free vector and raster map data. https://www.naturalearthdata.com/

Global NDVI Records and Environmental Predictors

Usage

Format

Source

See also