As is the case with many modern technologies, there is not a single standard distributed computing framework that is used ubiquitously. While many function similarly, there are numerous options and in practice, there are generally performance tradeoffs that can make a certain framework better for a given task.
The volume and velocity of spatial data is growing every day and applications from self-driving cars to insurance companies to global suppliers are turning to cloud-based geospatial solutions to provide real-time, scalable analytics and processing. The question is, how do you get started building your own state-of-the art geo-enabled cloud stack? Will it handle billions of features? Will it handle trillions?
Loading your GeoTools SimpleFeatures into your cloud or database never seems as easy as it should be. There's Twitter streams, FTP servers, inboxes, dropboxes, and all sorts of other data that you need to parse, convert to SimpleFeatures, and then ingest into your GeoTools datastore. Luckily, GeoMesa has teamed with HortonWorks DataFlow to provide a fully open source tool to ease the pain of ingesting data into ANY GeoTools datastore. It's as easy as drag and drop! Literally!
For 27 years the Institute for Sustainable Forestry has worked to promote the long term economic, ecological and social well being of forest based communities through sustainable forest management. In recent years, several negative environmental trends have emerged in California's Coastal temperate rainforest watersheds including declining Summer instream flows, extreme anthropogenic sediment yields, and susceptibility to catastrophic wildfires.
Recently, an upsurge in the use of unmanned aerial remote sensing systems (drones) has enabled a greater understanding of localized environments, especially in the areas of land management and precision agriculture. Extracting useful information from the data these devices collect often requires advanced knowledge of remote sensing and geographic information systems, which most small-scale land managers and farmers in Kentucky simply do not possess.
Learn how to use Geoblaze in your own applications!
The field of AI assistants and concierge services is growing rapidly. Whether it's planning a big family vacation, finding the perfect cocktail spot to keep the party going, or running a humanitarian operation, traditional decision making processes will be disrupted by new interfaces. VOICE is quickly becoming a primary method for interacting with the world around you, rather than staid desktop interfaces or frustrating mobile websites. This new market is bringing emerging technologies into the traditional GIS stack.
Learn how to build highly scalable services and iterate on them rapidly by leveraging all Kubernetes and Jenkins have to offer. Kubernetes provides all the abstractions necessary to manage a database, scale stateless apps, run cron jobs and handle network ingress. At the same time it provides a powerful API that is ripe for integration with an automation tool like Jenkins. Learn how we have used Kubernetes to help a small team scale itself to many users and different microservices without sacrificing velocity.
The network is the computer, especially when the data is already in the Cloud. This workshop walks through the actual methods used to build Cloud Optimized GeoTIFFs for the USDA NAIP dataset, part of the Earth on AWS program(https://aws.amazon.com/earth/). CoGs are GeoTIFFS that are internally structured to support efficient HTTP range-gets (partial file requests) such that they can be used in-situ in object stores such as Amazon S3.
In this talk, we will outline the steps to develop a point cloud filtering algorithm using PDAL's Python extension. We will show how PDAL can be installed via Conda, and in a Jupyter notebook will work through the algorithm development process, showing how the finished algorithm can be distributed and executed using the PDAL command line interface.
Open source technologies are sometimes questioned because of how they may scale or may be easily adopted in an enterprise commercial environment. To enable full adoption across the enterprise in an environment that previously used another user-based licensing models there are a few steps that need to be considered. Hybrid models are good but can delay adoption across the company if not chosen carefully. At Monsanto we have gone over a full rework of our geospatial environment in less than 12 months to adopt open source standards.
OpenStreetMap (OSM) is a collaborative project to create a free editable map of the world. It is being recognized as a useful dataset for training machine learning algorithms, deriving analytics on mapping behaviors, providing vital datasets to first responders to natural disasters, and a casual place for geonerds to continue to contribute to a living map of the world.
Maybe you've gotten a sweet Leaflet map or PostGIS database working on your laptop. You're feeling ready to share your web map or mapping service with others. Now how do you get that local sweetness into a production environment on the web? Maybe you've heard about Docker but don't see how to connect the pieces from a local PostGIS to deployed Docker container Or, maybe you are a system administrator trying to make your enterprise GIS as efficient, clear, and maintainable as possible. In this talk I will give a beginner-friendly introduction to rolling your own mapping stack using cont
Both Facebook's Presto and ESRI's Geometry API for Java were made open in 2013. In 2016, an Uber engineer, Zhenxiao Luo, who had worked with Presto while at Netflix, combined the two to support distributed spatial SQL. Later that same year, AWS announced a new service called Amazon Athena, a fully managed Presto service that makes it easy to run interactive SQL against BIG data in Amazon Simple Storage Service (S3). Athena now supports those same geospatial functions powered by ESRI's Geometry API.
Geospatial data is available in a multitude of formats each with their own strengths and weaknesses, optimizing for often competing goals. For example, data is available in HDF4, HDF5, NetCDF, MRF, Cloud Optimized GeoTIFFs, regular GeoTIFFs, CSVs, Excel spreadsheets, and more. As more and more of this data moves to the cloud, the idea of bringing compute to massive amounts of data, as opposed to moving data, becomes a reality.
The agricultural industry often uses aircraft to survey and collect information on fields and crops. Data Scientists use imagery collected by these aircraft to gather several metrics that may include: plant height, plant count, plant health, presence of nutrients, presence of disease, presence of weeds, relative biomass estimates, and 3D / volumetric data.
Gerrymandering is a growing national concern. Prior to the 1960s, Congressional districts often respected county and municipal boundaries, but wildly differing populations among districts led to the establishment of the one person, one vote standard. In an effort to conform to the requirements of one person, one vote, Congressional districts became increasingly less compact, and increasingly more gerrymandered.
This workshop will give a hands-on tutorial of the OGC® SensorThings API, an OGC standard API that simplifies and accelerates the development of Internet of Things (IoT) applications. The OGC SensorThings API has been very quickly and widely adopted around the world. There are more than eight server implementations, including both open source and proprietary, and many many more client implementations.