Localized contour tree method for deriving geometric and topological properties of complex surface depressions based on high resolution topographical data

A computer-implemented method for detecting and characterizing surface depressions in a topographical area, the method comprising:

• a) providing a digital elevation model (DEM) of the topographical area, wherein the DEM is derived from high resolution digital elevation data collected by Light Detecting and Ranging (LiDAR) or Interferometric Synthetic Aperture Radar (InSAR) technology;
• b) designating a base elevation contour and a contour interval for the DEM;
• c) using the base elevation contour and interval from b), generating an elevation contour representation of the topographical area, wherein the contour representation comprises closed contour lines and excludes open contour lines;
• d) identifying one or more seed contours, defined as a lowest elevation interior contour in a set of concentric closed contours, and, beginning with the lowest elevation seed contour and hierarchically expanding to higher elevation contours until a highest elevation contour is reached, constructing a local contour tree, wherein each contour line is represented as a node in the local contour tree;
• e) repeating step (d) iteratively until all highest elevation contours are incorporated in a local contour tree;
• wherein the number of surface depressions corresponds to the number of local contour trees, a simple depression comprises a local contour tree with one seed node, and a complex depression comprises a local contour tree with more than one seed node;
• f) identifying a quasi-pour contour node for each local contour tree;
• and
• g) determining a true-pour contour node for each local contour tree, wherein an elevation of a true pour contour node is a spill elevation and an elevation of a quasi-pour contour node is less than or equal to the elevation of the true pour contour node.