Time series of fractional vegetation cover (fCover) information for West Africa. The regionally adapted, continuous, and gap free time series has been created by data fusion methods based on fCover products of LSA-SAF (http://landsaf.meteo.pt/) and geoland 2 (BioPar, http://www.gmes-geoland.info/service-portfolio/biophysical-parameter-products.html). Additional information on the data: - 10-day timesteps (3 datasets per month) - spatial resolution: ~1km (Lat/Lon WGS-84, 0.00892857 deg) - coverage: 2007-2012 - data scaling: FCOVER[%]= pixelvalue/250 - valid data range: 0-250 (=0-100%), 255=no data - number of samples: 2130, number of lines: 1345

These datasets show the leaf area index (LAI), the one-sided area of green leaves per unit ground area for West Africa from 2007 to 2012. The regionally adapted, continuous, and gap free time series has been created by data fusion methods based on LAI products of LSA-SAF (http://landsaf.meteo.pt/) and geoland 2 (BioPar, http://www.gmes-geoland.info/service-portfolio/biophysical-parameter-products.html). Additional information: - 10-day timesteps (3 datasets per month) - spatial resolution: ~1km (Lat/Lon WGS-84, 0.00892857 deg) - coverage: 2007-2012 - data scaling: LAI[%]= pixelvalue/30 - valid data range: 0-210 (=LAI of 0-7), 255=no data - number of samples: 2130, number of lines: 1345

The database contains point data from several sites within the study area, comprising a steep south-north gradient of climatic aridity reaching from northern Ghana to central Burkina Faso between 9.0°N and 13.5°N latitude and 0.1°W and 2.0°W longitude. It is located in the southern and northern Sudanian zone of West Africa’s savanna belt, capturing a precipitation range of 600 mm to 1200 mm corresponding to UNEP aridity indices of 0.31 (semi-arid) to 0.69 (humid). Data collection took place at 44 sites during the rainy seasons in 2012 (June-September) and 2013 (July-October) and the end of the rainy season 2014 (October). Our sampling design intended to cover diverse vegetation types and a wide range of land-use intensities (including protected and degraded areas). We stratified sampling at sites by topographic position (upslope, footslope and lowland). At each slope position per site, 3-5 plots (10x10 m) were placed, containing three random circular subplots. The point data collected at each (sub)plot contains modelled data on forage quality (metabolisable energy) and quantity (green & total biomass) from spectrometric measurements, vegetation relevées (i.e. species data, vegetation clusters, phenology, photosynthetic pathway, height, cover, life span...), interview data on livestock keeping, grazing pressure and soil attributes (N, C, P, soil depth, soil structure...). Based on climate data, aridity indices were calculated. Based on fire occurrences detected by satellite images, fire frequency around sites was calculated. Based on soil moisture values detected by (radar) satellite images, soil moisture was extracted and modelled for the time of data collection. Further information: Ferner, J., Linstädter, A., Südekum, K. H., & Schmidtlein, S. (2015). Spectral indicators of forage quality in West Africa’s tropical savannas. International Journal of Applied Earth Observation and Geoinformation, 41, 99-106.

The time series of maps is showing three differnt forage parameters (green biomass, metabolisable energy, metabolisable energy yield) from 04.12.2015 to 29.09.2016. The covered area matches the Vea catchment at the border region of Ghana and Burkina Faso. For model calibration, data was collected during the rainy season 2012 at 21 sites spread along a north-south climate gradient reaching from northern Ghana to central Burkina Faso. Spectral reflectance measurements of vegetation plots were performed using a FieldSpec 3 Hi-Res Portable Spectroradiometer (ASD Inc., Boulder, CO, USA). Partial least squares regression was used to calibrate spectral models between reflectance data and forage characteristics (green biomass & metabolisable energy). Metabolisable enrgy yield was calculated based on the other two forage parameters. For more details regarding sampling design and model calibration, see Ferner, Linstädter et al. (2015). Sentinel-2 images were acquired for twelve dates. Imagery was atmospherically corrected using the plugin ‘sen2cor’ within the SNAP toolbox, provided by the European Space Agency (ESA). To assure that forage models were only applied on vegetated areas, a vegetation mask was build based on MESMA (multiple endmember spectral mixture analysis) and only pixels with a fractional cover of green vegetation of more than 30% were used. Finally, forage provision models resampled to Sentinel-2 spectral resolution were applied to obtain maps of estimated forage provision. Further information: Ferner, J., Linstädter, A., Südekum, K. H., & Schmidtlein, S. (2015). Spectral indicators of forage quality in West Africa’s tropical savannas. International Journal of Applied Earth Observation and Geoinformation, 41, 99-106.

The time series of maps is showing three differnt forage parameters (green biomass, metabolisable energy, metabolisable energy yield) from 04.12.2015 to 29.09.2016. The covered area matches the Vea catchment at the border region of Ghana and Burkina Faso. For model calibration, data was collected during the rainy season 2012 at 21 sites spread along a north-south climate gradient reaching from northern Ghana to central Burkina Faso. Spectral reflectance measurements of vegetation plots were performed using a FieldSpec 3 Hi-Res Portable Spectroradiometer (ASD Inc., Boulder, CO, USA). Partial least squares regression was used to calibrate spectral models between reflectance data and forage characteristics (green biomass & metabolisable energy). Metabolisable enrgy yield was calculated based on the other two forage parameters. For more details regarding sampling design and model calibration, see Ferner, Linstädter et al. (2015). Sentinel-2 images were acquired for twelve dates. Imagery was atmospherically corrected using the plugin ‘sen2cor’ within the SNAP toolbox, provided by the European Space Agency (ESA). To assure that forage models were only applied on vegetated areas, a vegetation mask was build based on MESMA (multiple endmember spectral mixture analysis) and only pixels with a fractional cover of green vegetation of more than 30% were used. Finally, forage provision models resampled to Sentinel-2 spectral resolution were applied to obtain maps of estimated forage provision. Further information: Ferner, J., Linstädter, A., Südekum, K. H., & Schmidtlein, S. (2015). Spectral indicators of forage quality in West Africa’s tropical savannas. International Journal of Applied Earth Observation and Geoinformation, 41, 99-106.

The time series of maps is showing three differnt forage parameters (green biomass, metabolisable energy, metabolisable energy yield) from 04.12.2015 to 29.09.2016. The covered area matches the Vea catchment at the border region of Ghana and Burkina Faso. For model calibration, data was collected during the rainy season 2012 at 21 sites spread along a north-south climate gradient reaching from northern Ghana to central Burkina Faso. Spectral reflectance measurements of vegetation plots were performed using a FieldSpec 3 Hi-Res Portable Spectroradiometer (ASD Inc., Boulder, CO, USA). Partial least squares regression was used to calibrate spectral models between reflectance data and forage characteristics (green biomass & metabolisable energy). Metabolisable enrgy yield was calculated based on the other two forage parameters. For more details regarding sampling design and model calibration, see Ferner, Linstädter et al. (2015). Sentinel-2 images were acquired for twelve dates. Imagery was atmospherically corrected using the plugin ‘sen2cor’ within the SNAP toolbox, provided by the European Space Agency (ESA). To assure that forage models were only applied on vegetated areas, a vegetation mask was build based on MESMA (multiple endmember spectral mixture analysis) and only pixels with a fractional cover of green vegetation of more than 30% were used. Finally, forage provision models resampled to Sentinel-2 spectral resolution were applied to obtain maps of estimated forage provision. Further information: Ferner, J., Linstädter, A., Südekum, K. H., & Schmidtlein, S. (2015). Spectral indicators of forage quality in West Africa’s tropical savannas. International Journal of Applied Earth Observation and Geoinformation, 41, 99-106.