CEOS System Engineering Toolset (CSET) CSET is a Software Framework + Suite of Tools (Apps) that leverages a Common Architecture, Unified Data Model, Common User Experience (App continuity) Data Management and Data Integration Tools o Space Data Management System (SDMS) - Extensible Data Management framework Analysis Tools, Data Visualization & Presentation Tools o Rapid Acquisition Tool - Determines when satellites may get acquisitions of regions/locations o Coverage Analyzer - Determines number of actual acquisitions with given cloudiness threshold o COVE Google Earth visualization tool for satellites - Displays potential and coincidence paths for Earth Observing Satellites. Data presentation, reporting, and charts Informational Tools : Mission Instrument Browser, Data Policy portal, Labs… History: CEOS Visualization Environment (COVE) started in 2009 –Web-based suite of tools for searching, analyzing and visualizing actual & potential satellite sensor coverage –Philosophy: Simple, intuitive, easily accessible –2014 COVE Stats: ~2500 users, 20K page views, broadly utilized by countries worldwide Space Data Management System (SDMS) 1 2 3

CSET Application Portal Analysis & Visualization Apps Data Management (SDMS) Apps Live in late November 2014

Space Data Management System (SDMS) SDMS is a flexible Data Integration & Data Management Framework – Key is the ability to quickly create applications (e.g., country/organization specific applications): –Common Architecture & Data model, Security model, Project Model –Search & Data Discovery Capability o Can pull in and search archives by metadata, criteria o Search the entire federated database –Analysis & Tool Execution Capability o Tool Integration framework (Java/JS based tool wrapping) o Existing and custom tools to analyze data, e.g.: GDAL, Google Earth Engine, Open Foris o Flexibility to work with different workflows/use-cases (mix-and-match) o GIS Tools –Data Visualization and Presentation Capability –Big Data Framework (Hadoop – Local Big Data Cluster) Working toward model for low bandwidth connections –Data housed, fetched, and processed remotely –Tiered solution for different bandwidth levels SDMS is not the cure all… SDMS Framework Columbia GFOI FAO Community Capabilities

SDMS Interface Global SDMS Data & Tools User-specific SDMS Data & Tools (Analysis Case) Context specific Work Area 4 Search & Filter Project (Analysis) … Data … Tools … Output

SDMS Tool Execution (Script Editor) 2 3 User-specific Data & Tools Script Editor 4 Execution Console >> Initializing… 1 Global SDMS Data & Tools

SDMS Tool Execution (Terminal Interface) Global SDMS Data & Tools User-specific Data & Tools Terminal Interface

GFOI SDMS Prototype

SDMS Integration - Google Earth Engine Google Earth Engine Demonstrator: – GEE is powerful satellite data acquisition and processing system – SDMS has JavaScript wrappers to the GEE API (small subset) o Allows heavy-lifting to be done at Google data centers o Can download result subsets at user specified bounds and resolutions – Benefits of integration: o Data: Provides additional source of data (SDMS Unified Data Model) o Tools: Additional processing capabilities o Workflow: Can be a source of data that is then processed by other tools –Current demonstrator prototype o Allows fetching of Landsat 7,8 band TIF files and combined thumbnail data o Focus is on cloud cover removal

SDMS Status CSET / SDMS development has been ongoing over the last year Our initial release is a prototype/demonstrator (Amazon servers) Alpha release to a small user group in December 2014 Looking for feedback, hoping CEOS SEO tools continue to be of use to the broader community SDMS Live Demonstration 1.SDMS Interface Prototype – Concept of Operations 2.Google Earth Engine Prototype – L8 Cloud removal 3.GFOI Prototype - Kenya POC: Brian Killough, Ph.D. Brian Williams, Ph.D Sanjay Gowda, Ph.D.

10 Data Services Prototypes... Kenya Demo  SEO is developing an online version of a generic data services tool for future testing.  A demo of this tool is being worked with FAO to test processing and product development for one Kenya scene. DEMO Details  Location: Kenya (Mt. Kenya National Park)  Dataset: Landsat 7, (Path-168, Row-60)  Step #1: LEDAPS Processing - TOA reflectance, cloud screening (ACCA), Atmospheric Correction to SR  Step #2: BRDF Correction - Use MODIS data?  Step #3: Cloud/Shadow Removal - Tag pixels with a value or color for statistics and viewing  Step #4: SLC Gap Removal - Tag pixels with a value or color for statistics and viewing  Step #5: Forest Classifier (unsupervised, or MODIS Vegetation Continuous Fields (VCF), or Random Forest)  Final Product: Forest Map with Statistics (Clouds, SLC Gaps, Forest, Non-Forest)