Shoreline Prediction ArcPy Tool

The objective of this project was to create a simple, data driven model to predict shoreline position in the future. The goals were to make this model interactive an environment (ArcGIS) where shoreline change analysis are already being conducted to facilitate ease of use and standardization within...

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Bibliographic Details
Main Author: Escarzaga, Stephen
Format: Article in Journal/Newspaper
Language:unknown
Published: figshare 2019
Subjects:
Online Access:https://dx.doi.org/10.6084/m9.figshare.11393139
https://figshare.com/articles/Shoreline_Prediction_ArcPy_Tool/11393139
Description
Summary:The objective of this project was to create a simple, data driven model to predict shoreline position in the future. The goals were to make this model interactive an environment (ArcGIS) where shoreline change analysis are already being conducted to facilitate ease of use and standardization within a researcher’s ROI. The included tool was written in Python with ArcPy commands that allow it to use the ArcGIS infrastructure. It was important to allow the researcher to use the same DSAS inputs and outputs they’d generate analyzing shoreline change to use in the modeling of future shoreline position. It was also important to design this model to allow for iteration. The next goal was to then test this model on a stretch of coastline along the Elson Lagoon in the North Slope of Alaska ( Figure1) for which I’ve obtained 9 years of shoreline position data from 2003 to present. This 312 meter stretch of actively eroding coastline is a mere 70 meters from a large thaw lake. Drained lakes in this region are common and are distributed among numerous mechanism of drainage including breach by coastal erosion[8]. Lakes such as this one in this study are essential habitats for migratory birds [9] and increased drainage of these lakes are great concern by to the native Arctic communities that rely on these bird species for subsistence hunting [9].