Using Imagery for Intelligence Analysis. Jim Michel Renee Bernstein

Transcription

1 Using Imagery for Intelligence Analysis Jim Michel Renee Bernstein

2 Deriving Value from GIS and Imagery Capabilities Evolved Along Separate but Parallel Paths GIS Imagery brings value Imagery Contextual relationships Visual integration Data Management Spatial Analysis GIS bring value Timely, rich information Measurements & analysis Authoritative source Earlier integration and Use Brings Maximum Value

3 ArcGIS Is A Powerful Platform For Imagery Management, Analysis, Visualization and Dissemination Fast Visualization Analysis Highly Accurate Measurement Advanced Processing Integrates Video (FMV) Any Imagery Dynamic Mosaicking (Including NTM & LIDAR) Massively Scalable Automatic Enhancement...Simplifies Workflows and Automates Processing

4 What This Means To Me Optimizing the Value and Use of Imagery Reduces the Time To Use Problem - Direct from the sensor Dynamic Mosaic - Dynamic rendering Reduces Resource Requirements - One copy of raw images On-the-Fly Processing - Multiple image services from raw images - Analysis using dynamic image service Improves Productivity - Accelerated display Fast Display, Easy Access - Better looking Imagery - Image Metadata and indexing for easy access

5 What Exactly is Imagery and Raster Data A Key Part of the Intelligence Puzzle Data stored in a matrix of regularly spaced cells (pixels) - Arranged in rows and columns cell value represents information Stored in many file formats or within a database - NITF, JPG, TIF, DEM, many others Single to multiple bands Usually large in size Panchromatic RGB color Multi-spectral Elevation Single band 3 bands Many bands Single band (16/32 bit)

6 Image Analysis Window

7 Image Analysis window Collection of commonly used display capabilities and processes Display - Enhance the appearance of data Processing - One-click/On-the-fly processing Mensuration - Geometric imagery measurements Dockable window

8 Image Analysis window layer list Lists raster layers in active data frame - Raster dataset layer - Mosaic dataset layer - Image service layer - WCS layers (Raster catalog layers not supported) Allows you to - Access layer properties dialog - Remove layer - Accelerate layer

9 Image Analysis window display panel Contains display enhancement tools - Contrast, brightness, gamma, transparency - Dynamic range adjustment (DRA) - Background - Top Up - Stretch - Resample - One-to-one - Comparing two layers - Swipe - Flicker

10 Image Analysis window processing panel One-click access to several commonly used image processing techniques - Orthorectification, pan-sharpening, convolution filters, clipping,

11 Image Analysis window Mensuration Panel Perform imagery mensuration - Distance - Location - Centroid - Height - Base to top - Top to shadow - Base to shadow (with sensor info)

12 Image Analysis Window Demo

13 Image classification Process of extracting pixels into classes Types - Supervised classification - Uses spectral signatures obtained from training samples - Requires user intervention - Unsupervised classification - Finds spectral classes (or clusters) in a multiband image without user intervention Output can be used to create thematic maps

14 Image classification toolbar Provides integrated environment - Supervised classification - Uses spectral signatures obtained from training samples - Requires user intervention - Unsupervised classification - Finds spectral classes (or clusters) in a multiband image without user intervention Requires Spatial Analyst extension

15 Integrates and Manages LiDAR Transforms Lidar Data Into Useful Information Products Rasters TINs LAS Files Dynamic On-the-Fly Integration Point Clouds Supporting Improved Visualization and Analysis

16 Image Classification and Lidar Demo

17 Mosaic Dataset

18 The New Mosaic Dataset Management of Small and Large Collections of Imagery New data type at 10, has three main purposes: - Cataloging images and metadata - Dynamic Mosaicking - On-the-fly Processing Stored in geodatabase - References original pixels - Authored and accessible directly in ArcGIS Desktop, or served via ArcGIS Server All Without Changing the Source Imagery

19 The New Mosaic Dataset Resolves Traditional Image Management Issues Processing Time Reduces processing Overlapping Imagery Maintain original information t1 t2 t3 t4 t5 Storage Reduces storage by removing redundancy Multi-resolution Data No need to sample up or down Disparate Datasets Handle large NoData areas Image Quality Reduces resampling Maintenance Add imagery as required Maintain Metadata Valuable information

20 Benefits of the Mosaic Dataset Catalog Imagery and Metadata Quickly catalog what imagery you have where - Different sensors and types - Different coordinate systems Define properties for - Header file information/metadata - Processing to be applied - Default viewing rules

21 Benefits of the Mosaic Dataset Dynamic Mosaic Capability Combine overlapping imagery from multiple sources User control of Image Order - By Date: Latest, Closest to May By Attribute: Highest Sun Angle - By Viewpoint: North, South, East, West - Seamline: Feathered blend - User Query: Landsat imagery, with no cloud, later than June 2001

22 Benefits of the Mosaic Dataset On-Demand Processing of Imagery Define processing functions as part of Mosaic Dataset & imagery processed as accessed Processes - Orthorectify - Pansharpen - Extract (specify) Bands - Vegetation Index - Color Correction - Etc... Create Multiple Products From a Single Source

23 Demonstration The Mosaic Dataset

24 Web Based GIS Light weight applications for Image Exploitation Image Exploitation ICW Web ELT

25 Questions?

26 Don t Miss These Attractions In the GIS Solutions EXPO Exhibitors I am GIS Photo Booth & Trading Cards Hands-On Learning & Coaching Labs Design Studio Spatial Outlet Esri Showcase GIS Technical & Extended Support 2 Demo theaters Drinks & snacks

27 Tuesday Evening Reception Smithsonian American Art Museum and National Portrait Gallery 6:30 PM 9:30 PM Walking distance from convention center Conference Badge needed for reception Coat check available in courtyard Serving hot hors d oeuvres and beverages

28 Wednesday Closing Session Closing and Hosted Lunch 11:30 AM 1:30 PM Ballrooms A C, Third Level Join conference attendees for lunch and closing session Closing Speaker Todd Park, U.S. CTO Wrap-up and request for feedback with Jack Dangermond.

29 Upcoming Events esri.com/events Date Event Location March 21, 2013 Esri DC Meet Up Big Data & Location Analytics Washington, DC April 18, 2013 Esri DC Meet Up Washington, DC March 23 26, 2013 Esri Partner Conference Palm Springs, CA March 25 28, 2013 Esri Developer Summit Palm Springs, CA July 6 9, 2013 Esri National Security Summit San Diego, CA July 8 12, 2013 Esri International User Conference San Diego, CA

30 Thank You Please complete a session evaluation form. #FedGIS Jim Michel Jmichel@esri.com Renee Bernstein Rbernstein@esri.com