An object-based conceptual framework and computational method for representing and analyzing coastal morphological changes

This article presents an object-based conceptual framework and numerical algorithms for representing and analyzing coastal morphological and volumetric changes based on repeat airborne light detection and ranging (LiDAR) surveys. This method identifies and delineates individual zones of erosion and deposition as discrete objects. The explicit object representation of erosion and deposition zones is consistent with the perception and cognition of human analysts and geomorphologists. The extracted objects provide ontological and epistemological foundation to localize, represent, and interpret erosion and deposition patches for better coastal resource management and erosion control. The discrete objects are much better information carriers than the grid cells in the field-based representation of source data. A set of spatial and volumetric attributes are derived to characterize and quantify location, area, shape, orientation, depth, volume, and other properties of erosion and deposition objects. Compared with the conventional cell-by-cell differencing approaches, our object-based method gives a concise and high-level representation of information and knowledge about coastal morphological dynamics. The derived attributes enable the discrimination of true morphological changes from artifacts caused by data noise and processing errors. Furthermore, the concise object representation of erosion and deposition zones facilitates overlay analysis in conjunction with other GIS data layers for understanding the causes and impacts of morphological and volumetric changes. We have implemented a software tool for our object-based morphological analysis, which will be freely available for the public. An example is used to demonstrate the utility and effectiveness of this new method.

[1]  Hongxing Liu,et al.  Automated Extraction of Shorelines from Airborne Light Detection and Ranging Data and Accuracy Assessment Based on Monte Carlo Simulation , 2007 .

[2]  M. Teague.  Image analysis via the general theory of moments , 1980 .

[3]  Yong Wang,et al.  Using LIDAR to Monitor a Beach Nourishment Project at Wrightsville Beach, North Carolina, USA , 2006 .

[4]  Jan Flusser,et al.  Pattern recognition by affine moment invariants , 1993, Pattern Recognit..

[5]  David K. Arctur,et al.  Designing Geodatabases: Case Studies in GIS Data Modeling , 2004 .

[6]  L. Wright,et al.  Morphodynamic variability of surf zones and beaches: A synthesis , 1984 .

[7]  D. Whitman,et al.  Quantification of Beach Changes Caused by Hurricane Floyd Along Florida's Atlantic Coast Using Airborne Laser Surveys , 2005 .

[8]  Andrew W. Fitzgibbon,et al.  Direct Least Square Fitting of Ellipses , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Milan Sonka,et al.  Image processing analysis and machine vision [2nd ed.] , 1999 .

[10]  Geoffrey J. Hay,et al.  Image objects and geographic objects , 2008 .

[11]  Antony Galton,et al.  Fields and Objects in Space, Time, and Space-time , 2004, Spatial Cogn. Comput..

[12]  Max J. Egenhofer,et al.  Object-Oriented Modeling for GIS , 2003 .

[13]  Michael F. Goodchild,et al.  Extending geographical representation to include fields of spatial objects , 2002, Int. J. Geogr. Inf. Sci..

[14]  Michael F. Goodchild,et al.  Towards a general theory of geographic representation in GIS , 2007, Int. J. Geogr. Inf. Sci..

[15]  Bruce Parker,et al.  The Difficulties in Measuring a Consistently Defined Shoreline? The Problem of Vertical Referencing , 2002 .

[16]  Douglas J. Sherman,et al.  Dynamics of beach-dune systems , 1993 .

[17]  R. Reyment,et al.  Statistics and Data Analysis in Geology. , 1988 .

[18]  Michael F. Goodchild,et al.  Geographical data modeling , 1992 .

[19]  Ling Bian,et al.  Object-Oriented Representation of Environmental Phenomena: Is Everything Best Represented as an Object? , 2007 .

[20]  P. Burrough,et al.  Geographic Objects with Indeterminate Boundaries , 1996 .

[21]  Donna J. Peuquet,et al.  Representations of Geographic Space: Toward a Conceptual Synthesis , 1988 .

[22]  M. Fenster,et al.  Temporal analysis of shoreline recession and accretion , 1991 .

[23]  Herbert Süße,et al.  A new efficient algorithm for fitting of rectangles and squares , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[24]  Paul L. Rosin.  Measuring shape: ellipticity, rectangularity, and triangularity , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[25]  E. Ziegel.  Statistics and Data Analysis in Geology (3rd ed.) , 2005 .

[26]  Benoit B. Mandelbrot,et al.  Fractal Geometry of Nature , 1984 .

[27]  Kumar Navulur,et al.  Object-Based Image Analysis , 2006 .

[28]  Paul L. Rosin.  Ellipse fitting by accumulating five-point fits , 1993, Pattern Recognit. Lett..

[29]  William K. Pratt,et al.  Digital image processing (2nd ed.) , 1991 .

[30]  Thomas Blaschke,et al.  Object-Based Image Analysis , 2008 .

[31]  H. Liu,et al.  Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods , 2004 .

[32]  R. Holman,et al.  Evaluation of Airborne Topographic Lidar* for Quantifying Beach Changes , 2003 .

[33]  K. McGarigal,et al.  FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. , 1995 .

[34]  Brian D. Andrews,et al.  Techniques for GIS modeling of coastal dunes , 2002 .

[35]  Milan Sonka,et al.  Image Processing, Analysis and Machine Vision , 1993, Springer US.

[36]  Kwong-Sak Leung,et al.  A generic concept-based object-oriented geographical information system , 1999, Int. J. Geogr. Inf. Sci..

[37]  E. L. Usery.  Category Theory and the Structure of Features in Geographic Information Systems , 1993 .

[38]  Ian J. Walker,et al.  Flow dynamics over a foredune at Prince Edward Island, Canada , 2005 .

[39]  Helen Couclelis,et al.  People Manipulate Objects (but Cultivate Fields): Beyond the Raster-Vector Debate in GIS , 1992, Spatio-Temporal Reasoning.

[40]  K. C. Slatton,et al.  Airborne Laser Swath Mapping: Quantifying changes in sandy beaches over time scales of weeks to years , 2005 .

[41]  Michael F. Worboys,et al.  Object-Oriented Approaches to Geo-Referenced Information , 1994, Int. J. Geogr. Inf. Sci..

[42]  Marco A. Casanova,et al.  FIELDS AND OBJECTS ALGEBRAS FOR GIS OPERATIONS1 , 1995 .

[43]  Jonathan Raper,et al.  Development of a Geomorphological Spatial Model Using Object-Oriented Design , 1995, Int. J. Geogr. Inf. Sci..

[44]  R. Gardner,et al.  Quantitative Methods in Landscape Ecology , 1991 .

[45]  K. Mulchrone,et al.  Fitting an ellipse to an arbitrary shape: implications for strain analysis , 2004 .

[46]  John C. Brock,et al.  Barrier Island Morphodynamic Classification Based on Lidar Metrics for North Assateague Island, Maryland , 2004 .

[47]  D. Peuquet.  It's About Time: A Conceptual Framework for the Representation of Temporal Dynamics in Geographic Information Systems , 1994 .

[48]  Josef Strobl,et al.  What’s wrong with pixels? Some recent developments interfacing remote sensing and GIS , 2001 .

[49]  A. Galton.  Space, Time, and the Representation of Geographical Reality , 2001 .

[50]  S. Stewart,et al.  Comparative testing of ellipse-fitting algorithms: implications for analysis of strain and curvature , 2005 .

[51]  C. Finkl,et al.  Interpretation of Seabed Geomorphology Based on Spatial Analysis of High-Density Airborne Laser Bathymetry , 2005 .

[52]  E. Lynn Usery,et al.  A Spatial Data Model Design for Feature-Based Geographical Information Systems , 1996, Int. J. Geogr. Inf. Sci..

[53]  Bernard O. Bauer,et al.  A general framework for modeling sediment supply to coastal dunes including wind angle, beach geometry, and fetch effects , 2003 .

[54]  Mark Gahegan,et al.  Specifying the transformations within and between geographic data models , 1996, Trans. GIS.

[55]  P. Burrough.  Fractal dimensions of landscapes and other environmental data , 1981, Nature.

[56]  John R. Andrews,et al.  PRECISE AIRBORNE LIDAR SURVEYING FOR COASTAL RESEARCH AND GEOHAZARDS APPLICATIONS , 2001 .

[57]  Yong Wang,et al.  Utilizing DEMs derived from LIDAR data to analyze morphologic change in the North Carolina coastline , 2003 .

[58]  Ashok Samal,et al.  A simple method for fitting of bounding rectangle to closed regions , 2007, Pattern Recognit..

[59]  Ling Bian,et al.  Object-oriented representation for modelling mobile objects in an aquatic environment , 2000, Int. J. Geogr. Inf. Sci..

[60]  Pierre Dutilleul,et al.  Advances in the implementation of the box-counting method of fractal dimension estimation , 1999, Appl. Math. Comput..

[61]  Barry Smith,et al.  Do Mountains Exist? Towards an Ontology of Landforms , 2003 .