NASA Earth Exchange (NEX) Earth Science Division/NASA Advanced Supercomputing (NAS) Ames Research Center

Project Goal To improve availability of Earth Science data, models, analysis tools and scientific results through a platform that fosters knowledge sharing, collaboration, innovation and direct access to compute resources. Project Goal To improve availability of Earth Science data, models, analysis tools and scientific results through a platform that fosters knowledge sharing, collaboration, innovation and direct access to compute resources. NASA Earth Exchange (NEX)

NASA Earth Exchange components

NEX Resources  Computing  Supercomputing and storage through NASA Advanced Supercomputing Division (NAS)  Almost 3PB storage, ,000 CPU cores  Possible to extend far beyond 8,000 cores if needed  Data  Global MODIS, AVHRR, Landsat, GCM Scenarios, weather data, etc.  Models  Publicly available models  Software Utilities  Open source and commercial (pending licensing)  Collaboration Facilitation/Knowledge Network  Based on DASHlink social network site  Audio/Visual Real-time Collaboration (Adobe Connect)  Large-scale Data visualization at NAS on hyperwall-2 + building custom visualization facility  Computing  Supercomputing and storage through NASA Advanced Supercomputing Division (NAS)  Almost 3PB storage, ,000 CPU cores  Possible to extend far beyond 8,000 cores if needed  Data  Global MODIS, AVHRR, Landsat, GCM Scenarios, weather data, etc.  Models  Publicly available models  Software Utilities  Open source and commercial (pending licensing)  Collaboration Facilitation/Knowledge Network  Based on DASHlink social network site  Audio/Visual Real-time Collaboration (Adobe Connect)  Large-scale Data visualization at NAS on hyperwall-2 + building custom visualization facility

Knowledge Network  Users can search for related activities  Who is doing what where?  Map interface  Categorized by discipline  Categorized by geographic region  Users can create projects and link to other projects  Users can control the visibility of their project  Users can control access to the project and the level of sharing  Users can share algorithms, data, knowledge  Users can search for related activities  Who is doing what where?  Map interface  Categorized by discipline  Categorized by geographic region  Users can create projects and link to other projects  Users can control the visibility of their project  Users can control access to the project and the level of sharing  Users can share algorithms, data, knowledge

Example End-to-End Usage  User registers and specifies resource requirements:  Data, tools, models and computing resources  A custom environment is created containing the requested resources  Within this environment user can:  Run existing models  Bring in new data, models, and algorithms  Extend existing models  Share models and data with community  Provide access to the results and the environment  When work is completed resources are recycled  The specific environment (including models, data, etc.) can be completely saved and reloaded and re-run in the future reproducing the results  User registers and specifies resource requirements:  Data, tools, models and computing resources  A custom environment is created containing the requested resources  Within this environment user can:  Run existing models  Bring in new data, models, and algorithms  Extend existing models  Share models and data with community  Provide access to the results and the environment  When work is completed resources are recycled  The specific environment (including models, data, etc.) can be completely saved and reloaded and re-run in the future reproducing the results

Creating solutions for resource management Agricultural Water Management

MODIS-LANDSAT integration For monitoring crop growth, irrigation scheduling, deforestation, and natural disasters Daily at 250/500m from MODIS Once every 8 days at 30m from Landsat

DAY 144DAY 155DAY 185DAY 192 StarFM Algorithm MOSAT LANDSAT MODIS

Forecasting California Agricultural Water Needs

TOPS - Mobile Computing Interface

KALPANA, Indian GOES

NEX Benefits  Lowers the barrier of entry.  Faster algorithm/product development.  Collaboration among multiple disciplines (remote sensing, machine learning).  Scaling up, going global.  Lowers the barrier of entry.  Faster algorithm/product development.  Collaboration among multiple disciplines (remote sensing, machine learning).  Scaling up, going global.