2014 ESIP Summer Meeting July 8 11 2014

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2014 ESIP Summer Meeting July 8– 11, 2014 | Frisco, Colorado Advancing Scientific Data

2014 ESIP Summer Meeting July 8– 11, 2014 | Frisco, Colorado Advancing Scientific Data Support in Arc. GIS Nawajish Noman

Outline • Arc. GIS and Scientific Data • Ingest and aggregation • Visualization and

Outline • Arc. GIS and Scientific Data • Ingest and aggregation • Visualization and Analysis • Service, Ready-to-Use Maps, Web Applications • Extending Analytical Capabilities using Python • OPe. NDAP and Future Direction

Arc. GIS Platform Desktop Web Device Arc. GIS Server Online Content and Services

Arc. GIS Platform Desktop Web Device Arc. GIS Server Online Content and Services

Scientific Data • Stored in net. CDF, GRIB, and HDF formats • Multidimensional •

Scientific Data • Stored in net. CDF, 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 Arc. GIS - Vision direct ingest data management share Arc. GIS

Scientific Data in Arc. GIS - Vision direct ingest data management share Arc. GIS analysis visualization

Ingesting Scientific data in Arc. GIS • Directly reads net. CDF file using Make

Ingesting Scientific data in Arc. GIS • Directly reads net. CDF file using Make Net. CDF Raster Layer o Make Net. CDF Feature Layer o Make Net. CDF Table View o • Directly reads HDF and GRIB data as raster

What about Aggregation? • Create a seamless multi-dimensional cube from o files representing different

What about Aggregation? • Create a seamless multi-dimensional cube from o files representing different regions o files representing different time steps/slices

Scientific data support in Mosaic Dataset • Supports net. CDF, HDF and GRIB Spatial

Scientific data support in Mosaic Dataset • Supports net. CDF, HDF and GRIB Spatial Aggregation o Temporal Aggregation o On-the-fly analysis o • Accessible as Map Service • Accessible as Image Service • Supports direct ingest • Eliminates data conversion • Eliminates data processing • Improves workflow performance • Integrates with service oriented architecture

Multidimensional Mosaic Datasets Aggregate (mosaic) spatial, time, and vertical dimensions • Raster Types for

Multidimensional Mosaic Datasets Aggregate (mosaic) spatial, time, and vertical dimensions • Raster Types for net. CDF, HDF & GRIB • Define variables when adding Rasters • Each Row is a 2 D Raster with variables and dimension values • Define on-the-fly processing • Serve as Multidimensional o Image Service o Map Service o WMS

Using Scientific Data in Arc. GIS Behaves the same as any layer or table

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

Multidimensional Mosaic Dataset - Visualization • Visualize temporal change of a variable • Visualize

Multidimensional Mosaic Dataset - Visualization • Visualize temporal change of a variable • Visualize a variable at any vertical dimension • Visualize flow direction and magnitude variables

Visualization of Raster as Vectors • New Vector Field renderer for raster o Supports

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

Spatial and Temporal Analysis Several hundreds analytical tools available for raster, features, and table

Spatial and Temporal Analysis Several hundreds analytical tools available for raster, features, and table • Temporal Modeling • o Looping and iteration in Model. Builder and Python

Modeling with Raster function template (RFT) • • • o o

Modeling with Raster function template (RFT) • • • o o

Sharing / WMS Support (for multi-dimensions) • Map Service (supports WMS) o • Image

Sharing / WMS Support (for multi-dimensions) • Map Service (supports WMS) o • Image Service (supports WMS) o • Exposes the analytic capability of Arc. GIS to the web. Map Package o • Provides access to raster data through a web service. Geoprocessing Service o • Makes maps available to the web. To share complete map documents and the data referenced by the layer it contains. Geoprocessing Package o To share your geoprocessing workflow.

Publishing a WMS on Arc. GIS Server • Enable WMS capabilities on Service Editor

Publishing a WMS on Arc. GIS Server • Enable WMS capabilities on Service Editor or Manager

Multi-dimensional data support in WMS • get. Capabilities o • Supports time, elevation and

Multi-dimensional data support in WMS • get. Capabilities o • Supports time, elevation and other dimensions (e. g. depth) get. Map o Returns map for any dimension value &DIM_<dimension. Name>=<value>& o Supports CURRENT for time dimension &TIME=CURRENT& • get. Feature. Info o Returns information about feature for any dimension value

Multi-dimensional WMS in Arc. Map • Supports WMS layer like any other layer •

Multi-dimensional WMS in Arc. Map • Supports WMS layer like any other layer • Animates a time enabled WMS layer using time-slider • Slices for any dimension value are accessible with Arc. Objects Public Sub Update. WMSService. Layer. Dimension. Value() 'UID for wms service layer type Dim p. Uid As New uid p. Uid = "{27 ABB 9 EC-7 A 26 -4 cf 8 -8 BD 4 -70 EC 1 D 274 E 17}" Dim p. WMSMap. Layer 2 As IWMSMap. Layer 2 'calling a function to find the layer from active dataframe Set p. WMSMap. Layer 2 = Get. Layer(p. Uid, "my. WMSLayer") 'setting values to dimensions Dim p. Dim. Name. Values As IProperty. Set p. Dim. Name. Values = New Property. Set p. Dim. Name. Values. Set. Property "Depth", "500" 'dimension#1 p. Dim. Name. Values. Set. Property "T 1", "500" 'dimension#2 Set p. WMSMap. Layer 2. Dimension. Values = p. Dim. Name. Values 'calling a function to redraw the layer Refresh. Active. Data. Frame End Sub

WMS in Dapple Earth Explorer

WMS in Dapple Earth Explorer

Multi-dimensional WMS in a Web Application Depth Time http: //dtc-sci 01. esri. com/Multi. Dim.

Multi-dimensional WMS in a Web Application Depth Time http: //dtc-sci 01. esri. com/Multi. Dim. WMSViewer/

Arc. GIS Online • • Curated, authoritative content provided by Esri o Ready To

Arc. GIS Online • • Curated, authoritative content provided by Esri o Ready To Use o Highly scalable o Global to National Authoritative content provided by the community o Hosted in your Arc. GIS Online Organization account o Hosted on your hardware and shared to Arc. GIS Online > 100 Tb of data > 150 millions maps per day

Ready-to-Use Maps http: //www. arcgis. com/features/maps/index. html

Ready-to-Use Maps http: //www. arcgis. com/features/maps/index. html

Ready-To-Use Analysis Services • Esri hosted analysis on Esri hosted data o Simplify job

Ready-To-Use Analysis Services • Esri hosted analysis on Esri hosted data o Simplify job of GIS Professionals o Can be used in models and scripts just like any other tool o Extend spatial analysis to a much broader audience o Available in Desktop or as REST service Best practices published to the Resource Center

Ready-to-Use Scientific Data Maps • GLDAS Noah Land Surface Model Outputs o Evapotranspiration o

Ready-to-Use Scientific Data Maps • GLDAS Noah Land Surface Model Outputs o Evapotranspiration o Soil Moisture o Snow Pack o Other

Web Application

Web Application

Web Application

Web Application

Python and Geoprocessing Tools • net. CDF 4 -python and Sci. Py are included

Python and Geoprocessing Tools • net. CDF 4 -python and Sci. Py are included in 10. 3/Pro Supplemental tools • OPe. NDAP to Net. CDF • Make Net. CDF Regular Point Layer • Make Net. CDF Station Point Layer • Make Net. CDF Trajectory Point Layer • Describe Multidimensional Dataset • Get Variable Statistics Over Dimension • Multidimensional Zonal Statistics As Table http: //blogs. esri. com/esri/arcgis/2013/05/24/introducing-the-multidimension-supplemental-tools-2/

Create Space-Time Cube & Emerging Hot Spot Analysis

Create Space-Time Cube & Emerging Hot Spot Analysis

Creating your own tool

Creating your own tool

OPe. NDAP to Net. CDF

OPe. NDAP to Net. CDF

Next: Make OPe. NDAP Layer • Ingest OPe. NDAP Service • Output dynamic multidimensional

Next: Make OPe. NDAP Layer • Ingest OPe. NDAP Service • Output dynamic multidimensional raster • Support Sub-setting

Tell the story of your scientific data – Create Story Maps http: //dtc-sci 01.

Tell the story of your scientific data – Create Story Maps http: //dtc-sci 01. esri. com/Dead. Zone. Story. Map/