DMP Section Type:
Data Input - Existing Collection
Description:
Low-resolution environmental data that was used allows for analyzing regional-scale processes, and consisted of a set of climate variables from the WorldClim database and satellite remotely sensed variables at 30 arcsec resolution. After removing cross-correlated variables (Pearson cross-correlation > 0.9), we included the following climate variables: Annual Mean Temperature (BIO01), Mean Diurnal Temperature Range (Mean of monthly maximum temp minus minimum temperature; (BIO02)), Temperature Seasonality (standard deviation * 100; (BIO04)), Maximum Temperature of warmest Month (BIO05), Minimum Temperature of Coldest Month (BIO06), Annual Precipitation (BIO12), Precipitation Seasonality (Coefficient of Variation; (BIO15), Precipitation of Warmest Quarter (BIO18), and Precipitation of Coldest Quarter (BIO19).
Second a set of remotely-sensed data variables was used. These included Moderate Resolution Imaging Spectroradiometer (MODIS), we included the Normalized Difference Vegetation Index (NDVI) (calculated from the red and near infrared reflection of the earth’s surface) and its standard deviation (NDVIstd) as a measure of greenness and seasonality, as well as percent tree cover, computed from the Vegetation Continuous Field (VCF) for the year 2001. We used radar data from the Quick Scatterometer (QuickSCAT), delivering information about near-surface moisture content, and a Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM) at 30 arc second resolution.
In addition to this lower-resolution data, we also included high-resolution (30 m) remotely sensed data, derived from the ASTER mission. The red (RED; band 2) and far infrared (FIR; band 3n) bands served as basis to compute NDVI as follows:
NDVI = (RED – NIR) / (RED + NIR)
Band 11 was also used, which contains temperature data that does not need further processing. In addition to these data sets from the ASTER layers, high-resolution elevation data and a tree cover data set in 30 m resolution were used as environmental predictors.
