A computer-implemented method comprising: receiving a plurality of instances of probe data, each instance being from a probe apparatus of a plurality of probe apparatuses, the probe apparatus comprising a plurality of sensors and being onboard a vehicle, wherein an instance of the plurality of instances of probe data comprises location information indicating a location of the corresponding probe apparatus; for each of one or more instances of the plurality of instances of probe data, determining a distance parameter based on the location information and a road segment corresponding to the location; defining a set of distance parameters based on the distance parameter determined for each of the one or more instances of the plurality of instances of probe data; analyzing the set of distance parameters to identify clusters of probe data, wherein the analyzing the set of distance parameters to identify clusters of probe data comprises: segmenting the distance parameters into a set of buckets based on the values of the distance parameters; determining if pairs of adjacent buckets of the set of buckets are spatially distinct; responsive to determining that a pair of adjacent buckets are not spatially distinct, combining the pair of adjacent buckets into one bucket; and responsive to determining that a pair of adjacent buckets are spatially distinct, defining a cluster based on at least one of the buckets of the pair of adjacent buckets; determining the number of clusters identified; comparing the number of clusters identified to a historical number of clusters; and responsive to determining that the number of clusters identified satisfies a threshold based upon the historical number of clusters, determining that there is a lane closure corresponding to the road segment. receiving a plurality of instances of probe data, each instance being from a probe apparatus of a plurality of probe apparatuses, the probe apparatus comprising a plurality of sensors and being onboard a vehicle, wherein an instance of the plurality of instances of probe data comprises location information indicating a location of the corresponding probe apparatus; for each of one or more instances of the plurality of instances of probe data, determining a distance parameter based on the location information and a road segment corresponding to the location; defining a set of distance parameters based on the distance parameter determined for each of the one or more instances of the plurality of instances of probe data; analyzing the set of distance parameters to identify clusters of probe data, wherein the analyzing the set of distance parameters to identify clusters of probe data comprises: segmenting the distance parameters into a set of buckets based on the values of the distance parameters; determining if pairs of adjacent buckets of the set of buckets are spatially distinct; responsive to determining that a pair of adjacent buckets are not spatially distinct, combining the pair of adjacent buckets into one bucket; and responsive to determining that a pair of adjacent buckets are spatially distinct, defining a cluster based on at least one of the buckets of the pair of adjacent buckets; segmenting the distance parameters into a set of buckets based on the values of the distance parameters; determining if pairs of adjacent buckets of the set of buckets are spatially distinct; responsive to determining that a pair of adjacent buckets are not spatially distinct, combining the pair of adjacent buckets into one bucket; and responsive to determining that a pair of adjacent buckets are spatially distinct, defining a cluster based on at least one of the buckets of the pair of adjacent buckets; determining the number of clusters identified; comparing the number of clusters identified to a historical number of clusters; and responsive to determining that the number of clusters identified satisfies a threshold based upon the historical number of clusters, determining that there is a lane closure corresponding to the road segment.