A method of correlating satellite position data with terrestrial features , the terrestrial features including a plurality of trails , the satellite position data including data collected over time as a vehicle traverses at least one trail, the locations of the terrestrial features being given by terrestrial survey data , comprising: using a geometric snapping algorithm to correlate the satellite position data and terrestrial survey data and snap the satellite position data to the terrestrial features ; determining whether the satellite position data can be snapped to unique terrestrial features by said using the geometric snapping algorithm ; and if the satellite position data cannot be snapped to the unique terrestrial features by said using the geometric snapping algorithm , then using a hybrid space-time snapping algorithm to correlate the satellite position data and the terrestrial survey data and snap the satellite position data to the unique terrestrial features, characterized by the hybrid space-time snapping algorithm using a spatial traversing component to reduce a possible number of trails available for snapping and using a temporal component to snap the satellite position data based on a spatial-temporal score, wherein said using the hybrid space-time snapping algorithm comprises using the spatial-temporal score to snap the satellite position data to the trail actually traversed by the vehicle , and wherein said using the spatial-temporal score comprises determining each of a spatial-proximity value, a spatial-evenness value, and a temporal-evenness value, and determining a third root of the product of the spatial-proximity value, the spatial-evenness value, and the temporal evenness value, wherein the spatial-evenness value is the ratio of an effective number of snapping error distances and a number of snapping error distances, wherein the effective number of snapping error distances is determined from an Inverse Herfindahl Index of the number of snapping error distances, wherein the temporal-evenness value is determined from a distribution of time differences between consecutive snapped trail points. using a geometric snapping algorithm to correlate the satellite position data and terrestrial survey data and snap the satellite position data to the terrestrial features ; determining whether the satellite position data can be snapped to unique terrestrial features by said using the geometric snapping algorithm ; and if the satellite position data cannot be snapped to the unique terrestrial features by said using the geometric snapping algorithm , then using a hybrid space-time snapping algorithm to correlate the satellite position data and the terrestrial survey data and snap the satellite position data to the unique terrestrial features, characterized by the hybrid space-time snapping algorithm using a spatial traversing component to reduce a possible number of trails available for snapping and using a temporal component to snap the satellite position data based on a spatial-temporal score, wherein said using the hybrid space-time snapping algorithm comprises using the spatial-temporal score to snap the satellite position data to the trail actually traversed by the vehicle , and wherein said using the spatial-temporal score comprises determining each of a spatial-proximity value, a spatial-evenness value, and a temporal-evenness value, and determining a third root of the product of the spatial-proximity value, the spatial-evenness value, and the temporal evenness value, wherein the spatial-evenness value is the ratio of an effective number of snapping error distances and a number of snapping error distances, wherein the effective number of snapping error distances is determined from an Inverse Herfindahl Index of the number of snapping error distances, wherein the temporal-evenness value is determined from a distribution of time differences between consecutive snapped trail points. <EOS>