Shoreline Extraction

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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 utilized and combined to extract shoreline features from different types of input data sources: panchromatic or single band imagery, color or multi-spectral image, and LiDAR elevation data. Our software package is freely available for the public through the internet. Keywords: Shoreline extraction, Remote sensing imagery, LiDAR data, ArcGIS, ArcObjects, VB .NET

1. Introduction
A shoreline is a spatially continuous line of contact between the land and a body of water (sea or lake). The terms “shoreline” and “coastline” are often interchangeably used in geosciences and coastal research communities [1]. It has been long recognized that information about shoreline position, orientation, and geometric shape is essential for coastal scientists, engineers and managers. Depending on the application context, the requirements for shoreline information vary in terms of shoreline positional accuracy, spatial resolution and coverage, and temporal frequency in survey and Copyright © 2011 SciRes.

mapping. In the design of shipping structures, coastal defense and protection infrastructure, coastal engineers often need the precise geographical position and detailed shape of shorelines within a certain coastal stretch [2]. Coastal managers and land use planners rely on up-to-date shoreline information at regional scales for establishing legal property boundary definition and building setback lines [3, 4], estimating recreational beach width and volume [5], inventorying wetland and agricultural land resources [6, 7], delineating flood and hurricane hazard zones, and assessing the coastal vulnerability and response management strategies to climate changes [8-10]. Coastal scientists and geomor-

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phologists have utilized multi-temporal shoreline data for estimating sediment transport and budgets [11], examining coastal erosion and accretion [12, 13], quantifying historical shoreline retreating or advancing rates [12, 14, 15], and assessing sea level...
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