Package hydroScalingAPI.modules.networkExtraction.objects

Clases on this package perform DEM analysis to extract the direction matrix and derive a river network structure.

See:
          Description

Class Summary
ExternalNetworkExtraction This is the Thread used by the NetworkExtractionOptimizer to call external procedures that process pieces of the original DEM
GeomorphCell_0 A cell object that associates properites to a location in the DEM.
GeomorphCell_1 A cell object that associates properites to a location in the DEM.
GeomorphCell_2 A cell object that associates properites to a location in the DEM.
GetGeomorphologyRAM This class implements the downstream-travel algorithm over the network to calculate important netwotk features (geomorphical and topological) for all locations in the DEM.
GetGeomorphologyROM This class implements a ROM version of the the downstream-travel algorithm over the network to calculate important netwotk features (geomorphical and topological) for all locations in the DEM.
GetRasterNetwork This class implements a series of mechanisms for Network pruning.
NetworkExtractionModule This class controls the procedures associated to River Network Extraction from DEMs.
NetworkExtractionOptimizer This was a rough attempt to optimize the network extraction code.
Pit This class represent a DEM PIT.
RasterNetworkBlueLines This object implements a group of static methods to handle a river network derived from a Blue Lines map
WorkRectangle This class is used to identify a region in the DEM where correction action must be taken.
 

Package hydroScalingAPI.modules.networkExtraction.objects Description

Clases on this package perform DEM analysis to extract the direction matrix and derive a river network structure. Relevant geomorphic analysis are also performed and derived matrixes are created by this modules. The Classes in this package were develed mainly by Jorge M. Ramirez at the Universidad Nacional de Colombia.



CUENCAS was initially developed by Ricardo Mantilla at the University of Colorado under the supervision of Dr. Vijay K. Gupta. We wish to recognize the support from the National Science Fundation.