Abstract

The Improvement of Data Production Efficiency by Python and ArcGIS
Track: Analysis
Authors: wentao che

It is always a key issue for a GIS specialist to handle a large amount of raster and vector data within the limited time period to meet the requests from different clients. It is ideal to give an answer within 12 hours which means one can fully use the night hours from 9pm to 9am. A better workflow plays an important role in this kind of jobs. This paper explains with 3 examples how to use Python and ArcGIS 10.1's latest techniques to significantly improve the data production efficiency. Example one shows how to use Mosaic Dataset to project 1TB orthophos with 10cm resolution from UTM to geographical coordinates for web applications. Example two shows how to use LAS Dataset to process billions of Lidar points to Grids and shade relief maps. Example three shows how to use Python's dictionary to fill the road section IDs automatically along the centerline.