PSNC geospatial toolkit brings together a set of tools provided by LocationTech projects and other location aware technologies. The main objective of the PSNC geospatial services is to bring massive, parallel and scalable computational power into geospatial processing scenarios. This enables analysis of the large scale, geospatial data, greatly reducing time required for computation. Due to compliance with commonly accepted GIS standards, computational results can be directly utilized by other existing tools for further visualization and analytics.
SERVICE DESCRIPTION
PSNC geospatial toolkit brings together a set of tools provided by LocationTech projects and other location aware technologies. The main objective of the PSNC geospatial services is to bring massive, parallel and scalable computational power into geospatial processing scenarios.
The toolkit is including but not limited to: RasterFrames RasterFrames provides a DataFrame-centric view over arbitrary Earth-observation (EO) data, enabling spatiotemporal queries, map algebra raster operations, and compatibility with the ecosystem of Apache Spark ML algorithms. It provides APIs in Python, SQL, and Scala, and can scale from a laptop computer to a large distributed cluster, enabling global analysis with satellite imagery in a wholly new, flexible, and convenient way.
It also includes support for working with vector data, such as GeoJSON. RasterFrames vector data operations let you filter with geospatial relationships like contains or intersects, mask cells, convert vectors to rasters, and more. RasterFrames builds upon several other LocationTech projects: GeoTrellis, GeoMesa, JTS, and SFCurve GeoMesa.
GeoMesa is an open source suite of tools that enables large-scale geospatial querying and analytics on distributed computing systems. GeoMesa provides spatio-temporal indexing on top of the Accumulo, HBase, Google Bigtable and Cassandra databases for massive storage of point, line, and polygon data. GeoMesa also provides near real time stream processing of spatio-temporal data by layering spatial semantics on top of Apache Kafka.
Through GeoServer, GeoMesa facilitates integration with a wide range of existing mapping clients over standard OGC (Open Geospatial Consortium) APIs and protocols such as WFS and WMS. GeoMesa supports Apache Spark for custom distributed geospatial analytics. GeoMesa features include the ability to: Store gigabytes to petabytes of spatial data (tens of billions of points or more), serve up tens of millions of points in seconds, ingest data faster than 10,000 records per second per node, scale horizontally easily (add more servers to add more capacity), support Spark analytics, drive a map through GeoServer or other OGC Clients .
GeoTrellis reads, writes, and operates on raster data as fast as possible. It implements many Map Algebra operations as well as vector to raster or raster to vector operations. GeoTrellis also provides tools to render rasters into PNGs or to store metadata about raster files as JSON. It aims to provide raster processing at web speeds (sub-second or less) with RESTful endpoints as well as provide fast batch processing of large raster data sets.
Raster processing has traditionally been a slow task, which has prompted advances in vector data processing as an alternative. Raster data isn’t going anywhere, however, with more and more satellite data made public every year. GeoTrellis is an answer to the growing need for raster processing at scale. Data sets processed by Geotrellis are only bound by the theoretical limits of Apache Spark. GeoServer is a Java-based software server that allows users to view and edit geospatial data.
Using open standards set forth by the Open Geospatial Consortium (OGC), GeoServer allows for great flexibility in map creation and data sharing. GeoServer allows you to display your spatial information to the world. Implementing the Web Map Service (WMS) standard, GeoServer can create maps in a variety of output formats. OpenLayers, a free mapping library, is integrated into GeoServer, making map generation quick and easy. GeoServer is built on GeoTools, an open source Java GIS toolkit.
There is much more to GeoServer than nicely styled maps. GeoServer conforms to the Web Feature Service (WFS) standard, and Web Coverage Service (WCS) standard which permits the sharing and editing of the data that is used to generate the maps. GeoServer also uses the Web Map Tile Service standard to split your published maps into tiles for ease of use by web mapping and mobile applications. Elasticsearch.
Elasticsearch is a distributed, open source search and analytics engine for all types of data, including textual, numerical, geospatial, structured, and unstructured. With geospatial support Elasticsearch allows users to index geo-data for optimizing geo-point and geo-shape based search, provides geo-aggregations and bucket reducers for spatial visualization and analytics and time-based indexing, aliasing, and percolation for complex space-time querying.
SPECIAL ACCESS CONDITIONS
User credential, Currently only limited to PSNC cloud services and infrastructure.
PREREQUISITES
No
CASE EXAMPLES
Sentinel2 and Landsat satellite image processing, multispectral raster analysis, reflection index calculations, vector processing, feature extraction.
SERVICE CAN BE COMBINED WITH
Currently only limited to PSNC cloud services and infrastructure.
