Open Source Tools and Technology Innovations
This talk will demonstrate how we can perform large scale raster analysis using GeoPySpark in a Jupyter Notebook. GeoPySpark was created to enable access to GeoTrellis to people with knowledge of Python. GeoTrellis is a geographic data processing library for high performance applications. It is written in Scala and uses Spark to work with raster and other geospatial data. GeoTrellis 1.0 was recently released under LocationTech, marking a major achievement for the community that has helped to build the project. It is open source under the Apache 2.0 license.
Open source is gleefully rewriting the rules of the GIS industry at all levels of industry and government. Adoption of open source in is well underway, with success stories illustrating the benefits. This decade we are going further - fostering a healthy, sustainable, working relationship between industry/government and open source:
GeoServer is an open source server that allows users to share and publish spatial data over the web.
In this tutorial, attendees will learn how to load, publish, style, and share spatial data with GeoServer. Discussion will include navigating the GeoServer user interface, loading and publishing data, OGC web services, and styling.
This is a popular workshop geared toward those with no prior GeoServer experience. Familiarity with basic GIS concepts is suggested.
This presentation will describe a technical framework, based on open source tools, for performing point-based exploratory data analysis and analytics over a range of viewing scales, together with examples of its usefulness. The technical development was divided into two phases: first, compiling the geographic data themes in a point grid designed to encode and access data; second, visualizing and analyzing the themes on a map by developing a Web application, offering on-demand visual and API services.
California has been described as a dry place, with some unusual wet years. The last five years of drought – and precipitation this winter – support this. Per capita water availability is often reported at the state level, yet this spatial scale is not well suited to how we actually can use water. Looking a watershed level gives a different picture of how much water would naturally be available within area.
Any GIS becomes more useful when you can connect it to other programs and data services. In this workshop, you will learn how to connect QGIS to spatial databases, work with data from data services, use QGIS in conjunction with programming languages like R and Python, use plugins, and work with algorithms and processing tools from other GIS programs from the Processing Toolbox. We’ll also specifically address how to get help and resources for learning on your own. We recommend that participants have intermediate-level experience (equivalent of an introductory college course) with GIS con