Analyzing Multidimensional Scientific Data in ArcGIS. Nawajish Noman Deng Ding

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Transcription:

Analyzing Multidimensional Scientific Data in ArcGIS Nawajish Noman Deng Ding

Outline Part I - ArcGIS Platform - Scientific Multidimensional Data - Ingest and Data Management Part II - Data Exploration and Visualization - Analysis - Extending Analytical Capabilities using Python Part III - Publishing and Sharing Services - Consuming Services

ArcGIS An Integrated Web GIS Platform Desktop Web Device Identity Security Portal Providing Mapping, Analysis, Data Management, and Collaboration Server Online Content and Services Available on the Open Web...... and On-Premises

Scientific Multidimensional Data Stored in netcdf, GRIB, and HDF formats Multidimensional Ocean data Sea temperature, salinity, ocean current Weather data Temperature, humidity, wind Land Soil moisture, NDVI, land cover

Scientific Data in ArcGIS - Vision direct ingest share data management ArcGIS analysis visualization

Challenges Manage Analyze Share variety of formats volume & velocity redundancy portability scalability reproducibility integration standards accessibility

Representing Scientific Data in ArcGIS Data is represented as Raster Feature Table Direct read Exports GIS data to netcdf

Ingesting Scientific data in ArcGIS Directly reads netcdf file using - Make NetCDF Raster Layer - Make NetCDF Feature Layer - Make NetCDF Table View Ingest OPeNDAP Service - Output dynamic multidimensional raster - Support Sub-setting Scientific data formats are supported in mosaic dataset - netcdf - HDF - GRIB

CF Convention Climate and Forecast (CF) Convention http://cf-pcmdi.llnl.gov/ Initially developed for Climate and forecast data Atmosphere, surface and ocean model-generated data Also for observational datasets CF is now the most widely used conventions for geospatial netcdf data. It has the best coordinate system handling. Current version 1.6 You can use Compliance checker utility to check a netcdf file. http://cf-pcmdi.llnl.gov/conformance/compliance-checker/

NetCDF and Coordinate Systems Geographic Coordinate Systems (GCS) - X dimension units: degrees_east - Y dimension units: degrees_north Projected Coordinate Systems (PCS) - X dimension standard_name: projection_x_coordinate - Y dimension standard_name: projection_y_coordinate - Variable has a grid_mapping attribute. - CF 1.6 conventions currently supports thirteen predefined coordinate systems (Appendix F: Grid Mappings) Undefined - If not GCS or PCS ArcGIS writes (and recognizes) PE String as a variable attribute.

Demo: Ingest

What about Aggregation? Create a seamless multi-dimensional cube from - files representing different regions - files representing different time steps/slices Mosaic dataset supports multiple files and variables, normalize time and depth

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

Tabular View Raster Shape Variable StdTime StdZ Temperature 3/22/2016-10 Temperature 3/23/2016-10 Temperature 3/24/2016-10 Salinity 3/22/2016-10 Salinity 3/23/2016-10 Salinity 3/24/2016-10 Temperature 3/22/2016-20 Temperature 3/23/2016-20 Tabular view of items in a multivariate multidimensional mosaic dataset

Scientific data support in Mosaic Dataset Supports netcdf, HDF and GRIB - Spatial Aggregation - Temporal Aggregation - On-the-fly analysis Serve as Multidimensional - Image Service - Map Service - WMS Supports direct ingest Eliminates data conversion Eliminates data processing Improves workflow performance Integrates with service oriented architecture

Demo: Management

Using Scientific Data in ArcGIS Behaves the same as any layer or table Display - Same display tools for raster and feature layers will work on multidimensional raster and feature layers. Graphing - Driven by the table just like any other chart. Animation - Multi-dimensional data can be animated through time dimension. Analysis Tools - Will work just like any other raster layer, feature layer, or table. (e.g. create buffers around points, reproject rasters, query tables, etc.)

Visualization of Scientific Data Slicing Temporal animation using Time Slider Dimensional animation using Range Slider Predefined renderer

Changing Time Slice 143 243 343 443 Y 141 241 341 441 142 242 342 132 232 332 122 222 322 442 432 422 133 233 333 123 223 323 113 213 313 433 423 413 Time 131 231 331 431 112 212 312 412 121 221 321 421 Time = 1 111 211 311 411 X

Animating through Time using Time Slider

Animating through Depth using Range Slider

Visualization of Raster as Vectors New Vector Field renderer for raster - Supports U-V and Magnitude-direction - Dynamic thinning - On-the-fly vector calculation Eliminates raster to feature conversion Eliminates data processing Improves workflow performance

Demo: Visualization

Spatial and Temporal Analysis Hundreds of analytical tools available for raster, features, and table Temporal Modeling - Looping and iteration in ModelBuilder and Python

On-the-Fly Processing using Raster Functions Several analytical functions are available out of the box Functions are chained together to create complex model Used to perform on-the-fly analysis Extend analytical capability using Python Raster Function

Modeling with Raster Function Template (RFT) A scientific model = a raster function template Windchill = 35.74 + 0.6215T - 35.75(V^0.16) + 0.4275T(V^0.16) RFT - Created using - Contains Query, GroupName, Variables - Set Mosaic dataset properties - Used during adding raster data

Python Package: netcdf4-python, SciPy netcdf4-python is included in 10.3/Pro Read and write netcdf file Conversion time values to date Multi-file aggregasion Compression SciPy Python Raster Function https://www.unidata.ucar.edu/software/netcdf/workshops/2012/netcdf_python/netcdf4python.pdf

Create Space-Time Cube & Emerging Hot Spot Analysis Analyzing Multidimensional Scientific Data in ArcGIS

Python Extending Analytical Capabilities Supplemental tools OPeNDAP to NetCDF Make NetCDF Regular Point Layer Make NetCDF Station Point Layer Make NetCDF Trajectory Point Layer Describe Multidimensional Dataset Get Variable Statistics Get Variable Statistics Over Dimension Multidimensional Zonal Statistics Multidimensional Zonal Statistics As Table http://blogs.esri.com/esri/arcgis/2013/05/24/introducing-the-multidimension-supplemental-tools-2/

Community Developed Tools Marine Geospatial Ecology Tools (MGET) Developed at Duke Univ. Over 180 tools for import management, and analysis of marine data http://mgel.env.duke.edu/mget Australian Navy tools (not publicly available)

Demo: Analysis

Disseminating Desktop Web Device professional geospatial analysts multivariate multidimensional mosaic dataset Server Online Content and Services

Sharing / WMS Support (for multi-dimensions) Map Service (supports WMS) - Makes maps available to the web. Image Service (supports WMS) - Provides access to raster data through a web service. Geoprocessing Service - Exposes the analytic capability of ArcGIS to the web.

Sharing Your Map as Map Services File Share As Service Features overlaid on rasters Static vs Dynamic map service Multidimensional WMS

Sharing Data & Information Products as Image Service Mosaic Dataset Share As Image Service Pixels & item metadata On-demand server-side processing Raster models: predefined or client-specified Multidimensional info, filtering, vector fields Enable access to a dynamic representation of your information product as an image service

Publishing a WMS on ArcGIS Server Enable WMS capabilities on Service Editor or Manager

Multi-dimensional data support in WMS getcapabilities - Supports time, elevation and other dimensions (e.g. depth) getmap - Returns map for any dimension value &DIM_<dimensionName>=<value>& - Supports CURRENT for time dimension &TIME=CURRENT& getfeatureinfo - Returns information about feature for any dimension value

Multi-dimensional WMS in ArcMap Supports WMS layer like any other layer Animates a time enabled WMS layer using time-slider Slices for any dimension value are accessible with ArcObjects Public Sub UpdateWMSServiceLayerDimensionValue() 'UID for wms service layer type Dim puid As New uid puid = "{27ABB9EC-7A26-4cf8-8BD4-70EC1D274E17}" Dim pwmsmaplayer2 As IWMSMapLayer2 'calling a function to find the layer from active dataframe Set pwmsmaplayer2 = GetLayer(pUid, "mywmslayer") 'setting values to dimensions Dim pdimnamevalues As IPropertySet Set pdimnamevalues = New PropertySet pdimnamevalues.setproperty "Depth", "500" 'dimension#1 pdimnamevalues.setproperty "T1", "500" 'dimension#2 Set pwmsmaplayer2.dimensionvalues = pdimnamevalues 'calling a function to redraw the layer RefreshActiveDataFrame End Sub

ArcGIS Online: The Living Atlas www.arcgis.com

The Living Atlas Imagery Basemaps Demographics & Lifestyle Boundaries & Places Landscape Community Maps Transportation Urban Systems Earth Observations Historic Maps

Services of Scientific Data Online Imagery content that can be directly used: MODIS data - MODIS land cover 2000-2011 - MODIS Vegetation Analysis - MODIS Greenland Sea Ice Live NOAA wind service NASA Global Land Data Assimilation (GLDS) - Soil moisture - Evapotranspiration - Snow pack More

Demo: Publishing SUBHEAD INFORMATION

Consuming Scientific Data Services ArcGIS Desktop/Pro/Server Web Map Viewer Web Applications Story maps Operational Dashboard

Corrected Reflectance Consumed in ArcGIS Desktop

WMS in Dapple Earth Explorer

Tell the story of your scientific data Create Story Maps http://dtc-sci01.esri.com/deadzonestorymap/

Demo: Consumption