But for each row the selleck screening library transition probability values still sum to unity. Such a CTPM was used to express the cross-correlations between sample data and the legacy map. The sample data set has five soil types while the legacy soil map has seven soil types; thus, they have five types in common. These five soil types show strong cross-field autocorrelations, and two of them have no changes (i.e., cross-field transition probabilities are 1.0).Figure 4Two subsets of transiogram models interpolated from experimental transiograms estimated from the sample data. The numbers in transiogram labels (1 to 5) refer to the five updated soil series (i.e., SU2, SU3, SU4, SU6, and SU7), respectively.Table 1Cross-field transition probability matrix from sample data (5 soil series) to colocated data in the legacy soil map (7 soil series).

The search radius chosen is 30 pixels (i.e., 600m). One hundred realizations were generated for the cosimulation conditioned on both the sample data and the legacy soil map using Co-MCSS, and occurrence probability maps were estimated from those realizations. The optimal prediction map was obtained from maximum occurrence probabilities. For the purpose of comparison, the same was done without conditioning on the legacy soil map using MCSS. The PCC (percentage of correctly classified locations) values were estimated for the optimal prediction map and realization maps against the reference soil map (sample data being excluded) to verify the simulation accuracies. 3.2. Results of CosimulationThe updated categorical soil maps include the optimal prediction map, a series of simulated realization maps, and occurrence probability maps.

But the most important should be the optimal prediction map generated from maximum occurrence probabilities that reflect the best predictions for a chosen method and available data. The optimal prediction map of the soil series and the corresponding maximum occurrence probability map (Figure 5) were estimated from simulated realizations generated by Co-MCSS, conditioned on both the sample data and the legacy soil map. The maximum occurrence probability map reflects the uncertainty of the optimal prediction map against the conditioning data. Comparing with the legacy soil map and the reference map (Figure 3) shows that the unchanged S2 and S4 were e
Recent decades have witnessed the prosperity and maturity of space technology, and the problem of spacecraft rendezvous has received detailed attention, GSK-3 as this is a key aspect for future missions which rely on the paradigms of spacecraft on-orbit service and space interception and capture [1�C3]. Many control algorithms have been developed to perform rendezvous with a target spacecraft.