I’m happy to announce that the {skytrackr} package is on its way to CRAN. The {skytrackr} R package provides a convenient template fitting methodology and a Bayesian based optimization approach to estimate locations from light profiles. In my research together with Lyndon Kearsley we’ve used geolocation by light extensively to track swifts (an example light profile, as recorded during a year by a micro-logger on the back of a swift, is shown below).
The CHELSA dataset provides access to climatologies at high resolution for the earth’s land surface areas. Among those are the global climate-related predictors at kilometer resolution for the past and future (Brun et al. 2022) - generally known as bio-climatic variables. This dataset is provided through the main CHELSA website and links to a file download option which focuses on bulk file downloads.
However, it seems that the geotiffs provided are cloud optimized geotiffs (COG files).
Today we received the news from Dr. Michele Thornton at the Oak Ridge National Laboratory (ORNL) that the DAYMET API they host will be decommissioned. This change will be effective within weeks and affect first and foremost the spatial (gridded) data products, before most likely covering the whole THREDDS data server setup including point based data.
In short, it is unlikely that the DAYMET API at ORNL will be maintained for much longer (past the end of the year).