Shoreline Extraction
Journal of Geographic Information System, 2011, *, ** doi:****/jgis.2011.***** Published Online ** 2011 (http://www.scirp.org/journal/jgis)
Algorithmic Foundation and Software Tools for Extracting Shoreline Features from Remote Sensing Imagery and LiDAR Data
Hongxing Liu
Department of Geography, University of Cincinnati Cincinnati, USA E-mail: Hongxing.Liu@uc.edu
Douglas J. Sherman
Department of Geography, Texas A&M University College Station, USA E-mail: sherman@geog.tamu.edu
Lei Wang
Department of Geography & Anthropology Louisiana State University, Baton Rouge, USA Email: leiwang@lsu.edu
Qiusheng Wu, Haibin Su
Department of Geography, University of Cincinnati Cincinnati, USA E-mail: { wuqe, suhn }@mail.uc.edu
Abstract
This paper presents algorithmic components and corresponding software routines for extracting shoreline features from remote sensing imagery and LiDAR data. Conceptually, shoreline features are treated as boundary lines between land objects and water objects. Numerical algorithms have been identified and devised to segment and classify remote sensing imagery and LiDAR data into land and water pixels, to form and enhance land and water objects, and to trace and vectorize the boundaries between land and water objects as shoreline features. A contouring routine is developed as an alternative method for extracting shoreline features from LiDAR data. While most of numerical algorithms are implemented using C++ programming language, some algorithms use available functions of ArcObjects in ArcGIS. Based on VB .NET and ArcObjects programming, a graphical user’s interface has been developed to integrate and organize shoreline extraction routines into a software package. This product represents the first comprehensive software tool dedicated for extracting shorelines from remotely sensed data. Radarsat SAR image, QuickBird multispectral image, and airborne LiDAR data have been used to demonstrate how these software routines can be
Algorithmic Foundation and Software Tools for Extracting Shoreline Features from Remote Sensing Imagery and LiDAR Data
Hongxing Liu
Department of Geography, University of Cincinnati Cincinnati, USA E-mail: Hongxing.Liu@uc.edu
Douglas J. Sherman
Department of Geography, Texas A&M University College Station, USA E-mail: sherman@geog.tamu.edu
Lei Wang
Department of Geography & Anthropology Louisiana State University, Baton Rouge, USA Email: leiwang@lsu.edu
Qiusheng Wu, Haibin Su
Department of Geography, University of Cincinnati Cincinnati, USA E-mail: { wuqe, suhn }@mail.uc.edu
Abstract
This paper presents algorithmic components and corresponding software routines for extracting shoreline features from remote sensing imagery and LiDAR data. Conceptually, shoreline features are treated as boundary lines between land objects and water objects. Numerical algorithms have been identified and devised to segment and classify remote sensing imagery and LiDAR data into land and water pixels, to form and enhance land and water objects, and to trace and vectorize the boundaries between land and water objects as shoreline features. A contouring routine is developed as an alternative method for extracting shoreline features from LiDAR data. While most of numerical algorithms are implemented using C++ programming language, some algorithms use available functions of ArcObjects in ArcGIS. Based on VB .NET and ArcObjects programming, a graphical user’s interface has been developed to integrate and organize shoreline extraction routines into a software package. This product represents the first comprehensive software tool dedicated for extracting shorelines from remotely sensed data. Radarsat SAR image, QuickBird multispectral image, and airborne LiDAR data have been used to demonstrate how these software routines can be