Geospatial
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Philadelphia Bursts with Resources and Support for Women in Tech (Part 2)
Continuing our discussion on the immense resources and support for women in tech in Philadelphia, we interviewed Yasmine Mustafa, the founder and co-organizer of Girl Develop It Philadelphia to learn about what makes Philadelphia a great place for women in tech.
Philadelphia Bursts with Resources and Support for Women in Tech (Part 1)
In this blog, we highlight unique opportunities, resources, and groups for women in tech throughout the Philadelphia region.
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Legacy of Roger Tomlinson, Father of GIS, Continues
Roger Tomlinson was a geographer and researcher who created the first computerized Geographic Information System while working for the Canadian government.
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A World of Projection Distortions
We discuss common map projections and projection distortions.
Evolution of GIS Attribute Data from Collection to Cleaning
Step by step guide to prepping GIS attribute data, from data collection to cleaning, in the context of an Azavea Summer of Maps project completed for the Pennsylvania Horticultural Society.
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Five Technology Trends Every Nonprofit Needs to Know
We sought to identify 5 actual technology trends (not just buzz) that will have a significant impact on the nonprofit sector.
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How to Manipulate Big Data for Use in ArcMap
How to use the open source program PGAdmin to prep large data sets for use in ArcMap.
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Using Raster Analysis in ArcMap to Create a Normalized Weighted Risk Index
Learn how to conduct a raster analysis in Esri Arcmap to create a normalized weighted risk index, explained in the context of an Azavea Summer of Maps project completed for the Delaware Valley Association for the Education of Young Children.
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Accounting for Uncertainty with Empirical Bayes Smoothing
In this blog, we describe our experience accounting for uncertainty with empirical bayes smoothing.
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Using GTFS Data to Generate Bus Routes with Travel Time
We outline our work on a tool that allows the DPR’s GIS department to input the type of recreation (such as playgrounds, basketball courts, swimming pools, etc.), buffer around those locations and summarize the population within those buffers using GTFS data.
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