This is the final result of using Mask R-CNN to predict the location of relict charcoal hearths (RCH) in and near State Game Lands throughout Pennsylvania. Please note that only those RCHs falling into one (or more) of the three cluster analyses is considered to be a likely true positive (i.e., an actual charcoal hearth). That is, where ClusterCT =0. Variables: id= unique identifier starting with 3-digit SGL number, PAN or PAS (projections) and, within those a unique four-digit identifier score= confidence score SGL= State Game Land number SGLImage= name of TIFF file of merged lidar tiles Confirm= Whether the predicted hearth was determined, through visual inspection, to be a likely true positive (Y) or a false positive (N) Bin#- in assessing these predictions we “binned” the results based upon the confidence score. Bin_select= 1 if this record (predicted RCH) was selected for assessment within that bin TrainID= Original ID of the training data (only training data that matched with a prediction are included). Clusters5_300= resultant clusters from DBSCAN where minimum cluster size= 5 and maximum distance= 300 meters Clusters10_500= resultant clusters from DBSCAN where minimum cluster size= 10 and maximum distance= 500 meters Clusters20_1000= resultant clusters from DBSCAN where minimum cluster size= 20 and maximum distance= 1000 meters CLUSTERCT = How many of the above clusters included the predicted RCH (0-3). Derived from the previous three variables. 3Cluster= whether or not this predicted RCH was included in all three clusters. For additional information, please see https://zenodo.org/deposit/4593788 .