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PyCon 2011 Atlanta

March 9th–17th

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Using Python scripts for the automation of biological monitoring site characterization in ArcGIS 10

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Novice / Poster
Python 2.6 and ArcGIS 10 were used to develop a series of 10 scripts which would characterize the landscape aspects of biological monitoring sites used in assessing water quality throughout the State of Georgia. Similar to that of EPA’s ATtILA program, the script produces a table populated with information critical to assessing biological monitoring sites.


A series of 10 scripts written in Python 2.6 and distributed in the ArcGIS 10 ArcToolbox environment uses watersheds, the Georgia Land Use Trends (GLUT), roads, streams, and water impoundments geospatial data and outputs a table with monitoring station information, land use classification, and density of roads and hydrography. This process is similar to, but a greatly simplified version of, EPA’s Analytical Tools Interface for Landscape Assessments (ATtILA) which is an extension to the outdated ESRI’s ArcView 3x. This series of scripts allows the user to quickly compile common physical aspects of the landscape upstream of a biological monitoring site into a dbf table that can be imported into any Microsoft Access database.