Tools for advanced analysis

The initial analysis steps in Tovi are to help you complete and optimize the data. Now that they are finished, you are ready to perform more advanced analysis. In this section we describe how to use Tovi to accomplish some common advanced objectives, including the footprint analysis, flux gap filling, flux partitioning, and more.

  • Footprint analysis: Specify an area of interest, compute the probability of flux locations, set up quality flagging regions. See Footprint analysis.
  • Footprint flux allocation: Attribute fluxes to one of two classes. See Footprint allocation.
  • MDS gap filling: Estimate fluxes for gaps in the flux dataset using the Marginal Distribution Sampling (MDS). See Flux gap filling.
  • Nighttime flux partitioning: To parse fluxes into day and night. See Night-time method of Reichstein et al., 2005.