Scientific and Multidimensional Raster Support in ArcGIS

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1 Scientific and Multidimensional Raster Support in ArcGIS Sudhir Raj Shrestha

2 Brief breakdown Scientific Multidimensional data Ingesting Scientific MultiDim Data in ArcGIS Ingesting and Managing Sharing Managing Visualizing and Analyzing Disseminating and Consuming Scientific Computing Demo: Application(s) and Use case Visualizing Analyzing

3 Scientific Multidimensional Data

4 ArcGIS An Open, Interoperable, and Standards-Compliant Platform Product Integration Any System Open Standards and Formats WMS OPeNDAP REST LERC IFC GML SLD JSON NetCDF ISO HDF SQL WaterML OneGeology CityGML WCS SOAP KML LAS Shapefiles GeoPackage WWW CSW WFS Web Scene (I3S) INSPIRE Many OGC Certifications GRIB WMTS WPS Adobe Creative Cloud MS Office SQL Server AWS IBM Cognos Azure Open Software Netezza Oracle Open Data Access Open APIs & SDKs AutoCAD Extensible Architecture Embeddable Components SAP HANA Open-Source Contributions (500+) Open-Source Integration SharePoint Teradata... Successfully Integrated into Thousands of Systems

5 Diverse Scientific Multidimensional Data Oceanographic Meteorological Salinity Temperature Sea surface temperature Water Vapor/Precipitation Ocean current Wind speed/direction Terrestrial Soil moisture NDVI Land cover

6 GIS workflows that scale Designed for the characteristics of Earth Observations scientific data Ingest Manage Analyze Visualize Share raster types crawl disk link to pixels mosaic dataset geoprocessing tools optimization consumption multidimensional filter raster functions Interactive/dynamic scalable/extensible animate over slices sophisticated renderers vector & scalar fields dynamic web services web maps & apps web based analytics Data Service

7 Ingesting and Managing Scientific Data

8 Multidimensional Mosaic Dataset mosaic mosaic dataset table HDF GRIB netcdf d-aware rasters spatially-indexed catalog multi-resolution, multivariate, multidimensional reduce storage redundancy & pixel resampling defines information products on-demand processing raster pixels Representing multivariate collection of multidimensional rasters in ArcGIS

9 Multidimensional Data Model Multidimensional Mosaic Dataset in Geodatabase Ingest variables from netcdf, HDF & GRIB using raster types - Aggregate multiple variables, multiple files Support on-the-fly processing

10 Raster Types for Multidimensional data data on disk raster type mosaic dataset netcdf HDF GRIB d-aware rasters crawls disk identifies rasters extracts metadata attaches processing stores no pixels references rasters stores processing & metadata Format-agnostic direct ingestion of rasters into a mosaic dataset

11 Creating a Multidimensional Mosaic Dataset Using Geoprocessing Tools Create a empty mosaic dataset Add select variables

12 Demo Create multidimensional Mosaic Dataset Populate Mosaic dataset using NetCDF Raster type Ingest Multidim data using Make NetCDF raster layer GP tool Ingest data using Multidimensional raster layer

13 Visualizing and Analyzing Scientific Data

14 Slicing your data Slicing By variable, using variable selector Processing Templates By dimension using Select by Dimension Geoprocessing tool Visualizing Time slider Range slider Vector field renderer

15 Demo Visualize multidimensional data using time slider and range slider Slicing your Mosaic dataset with Select by Dimension GP Tool Parse data using Variable filter and Processing templates Visualize Wind data with vector field renderer

16 Raster Analysis Geoprocessing Tools (GP) Tons of GP tools GP tools, Python scripting and ModelBuilder perfect automation of data management and analysis. Dynamic On-the-Fly Processing using Raster Functions Manage and analyze large collection of rasters on the fly as the data is accessed and viewed Quick and save time by not required to write the processed product to disk Functions can be applied to various rasters (images) including: Raster dataset layers Mosaic datasets Image service layers

17 Raster Function: Transforming Raster Data raster function raster-valued transformation piecewise, scale-aware local / focal on-demand processing unary, binary,, n-ary, polyadic Learn more at: github.com/esri/raster-functions Choose from dozens of built-in functions or implement your own algorithm using Python

18 Modeling and Chaining Raster Functions Elevation Slope Conservation area Soil Type Soil Acidity to compose a complex analytic model

19 Raster Function Templates Variable 1 Variable 2 raster variables A portable & reusable chain of raster functions

20 Demo Transforming your scientific data using Raster Functions

21 Disseminating and Consuming

22 Disseminating Desktop Web Device Apps professional geospatial analysts Access / Identity multivariate multidimensional mosaic dataset Services Server Online Content and Services

23 Serving Multidimensional Data Multidimensional Image Services Serve data (not a picture) LERC compression to maintain data quality Perform analysis and analysis through the web Multiple clients: Desktop clients Web Map Viewers JavaScript etc. WMS/WCS Time=t1&Elevation=z1 DIM_Time=t1&DIM_depth

24 Sharing data & information products Mosaic Dataset Share As Web Layer Enable access to a dynamic representation of your information product as an image service

25 Consuming your services In any ArcGIS application or any WMS client In a web map Identify web services driven by maps or datasets Bring service layers into a web map In a map-based application Configurable apps Story Maps Web AppBuilder Custom web apps using ArcGIS API for JavaScript

26 Near real time High Resolution Rapid Refresh (HRRR) Data Ingest: Metadata References to Source Approx 30 records/sec Create Mosaic Dataset Publish Mosaic Dataset Time t Model Generation HRRR Dataset (GRIB) Download Time for HRRR 2D Surface Levels data: 2.2GB 2376 rec/md Server Accessible HRRR Dataset (GRIB) ArcGIS Image Server Download Build Mosaic Restart Service Standard Workflow 80sec 123Sec 30sec Total= 233 Sec Pre-Generate Workflow 80sec 0Sec 30sec Total= 110sec Pre-Generate Workflow 0sec 0Sec 30sec Total= 30sec

27 Demo Publish the scientific data (Image, WCS, WMS capability) Dynamic scientific computing in web Using image service layer in ArcGIS Online map viewer Web Map Application: HRRR, Hycom

28 3 Take Away 1. Mosaic Dataset is a robust data model that allows you to manage your large collections of scientific multidimensional data and is a quick way to build the live web service 2. Raster function(s) can help with your efficient on the fly computing that saves Time and Resources 3. Make your scientific data and research output usable with repeatable workflow to your larger community

29 Join our session on Analysis of Earth Science Data Analyzing Multidimensional Scientific Data in ArcGIS (Room 144 B) When: March 21, :00-12:00 PM.

30 Please Take Our Survey in the Esri Events App Download the Esri Events app and find your event Select the session you attended Scroll down to find the feedback section Complete Answers and Select Submit

31 Print Your Certificate of Attendance Print stations located in the 140 Concourse Tuesday 12:30 pm 6:30 pm GIS Solutions Expo Hall B Wednesday 10:30 am 5:15 pm GIS Solutions Expo Hall B 5:00 pm 6:30 pm GIS Solutions Expo Social Hall B 6:30 pm 9:00 pm Networking Reception Smithsonian National Portrait Gallery

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