{"project":{"acronym":"","projectId":33623,"title":"SparkRS - Spark for Remote Sensing","primaryTaxonomyNodes":[{"taxonomyNodeId":10833,"taxonomyRootId":8816,"parentNodeId":10831,"level":3,"code":"TX11.4.2","title":"Intelligent Data Understanding","definition":"Intelligent data understanding technologies provide the ability to automatically mine and analyze datasets that are large, noisy, and of varying modalities, including discrete, continuous, text, and graphics, and extract or discover information that can be used for further analysis or decision making.","exampleTechnologies":"Intelligent data collection and prioritization toolset, event detection and intelligent action toolset, data on demand toolset, intelligent data search and mining toolset, data fusion toolset, information representation standards for persistent data, artificial intelligence (AI), robot-automated cross-program standardization","hasChildren":false,"hasInteriorContent":true}],"startTrl":1,"currentTrl":3,"endTrl":3,"benefits":"Each of the datasets listed in this SBIR's description and their corresponding applications are all potential candidates for use by Spark-RS since they involve large multi-spectral and hyper-spectral raster-based observations. These include HyspIRI, JPSS-1, NPP, SDO, MRO, MERRA, MERRA2, LandSat among many, many others. Thus, any NASA datacenter that has a Hadoop-based cluster will benefit from the proposed innovation, Spark-RS.
Spark-RS can equally be applied to myriad other remote sensing and GIS applications across U.S. government agencies moving towards big data platforms like Hadoop and Spark. There are at least 28 different U.S. government agencies that utilize or produce geospatial data. Not all utilize raster datasets, but many do. In particular, the Department of Defense (Army, Air Force, Navy, USMC) and the Intelligence Community (NSA, CIA, NGA, DIA, etc.) all produce and consume large amounts of image-based data. With the increasing amount of non-ortho-rectified oblique imagery-based datasets from sensors from aerial photography (WAMI/FMV), Spark-RS could also play a critical role. In addition, domestic agencies like USGS, FBI, EPA, FEMA, etc. also have vast quantities of raster-based datasets. Lastly, industrial applications including GIS mapping companies, aerial photography companies & medial imaging companies all can benefit and, importantly, contribute back to the sustained success of Spark-RS.","description":"The proposed innovation is Spark-RS, an open source software project that enables GPU-accelerated remote sensing workflows in an Apache Spark distributed computing cluster. Current state-of-the-art parallel systems like Hadoop and Spark offer horizontally scalable analytics and reduced costs for enterprises, but weren't built to natively consume and process large remote sensing raster datasets. Conversely, GPUs can vastly accelerate image processing operations. Some open source projects have arisen that showcase hybrid Hadoop/GPU computing. However, there are no mature open source projects that utilize GPUs within Spark (an eventual replacement of MapReduce) and none that were built to process large remote sensing imagery. This is the primary role of the proposed innovation, Spark-RS. Spark-RS contains three primary components. One is a parallel large image loading component that quickly loads large multi-band imagery into a Spark cluster. The second component is a remote sensing library for Spark applications. It provides an API for reading and writing large images and wraps many common image operations from existing open source and NASA-built remote sensing libraries. The third component is a GPU management library for Spark. It simplifies and abstracts utilization of GPUs within a Spark application.","startYear":2015,"startMonth":6,"endYear":2015,"endMonth":12,"statusDescription":"Completed","principalInvestigators":[{"contactId":472293,"canUserEdit":false,"firstName":"Todd","lastName":"Pehle","fullName":"Todd Pehle","fullNameInverted":"Pehle, Todd","primaryEmail":"Tpehle@Spiritus-Inc.Com","publicEmail":true,"nacontact":false}],"programDirectors":[{"contactId":206378,"canUserEdit":false,"firstName":"Jason","lastName":"Kessler","fullName":"Jason L Kessler","fullNameInverted":"Kessler, Jason L","middleInitial":"L","primaryEmail":"jason.l.kessler@nasa.gov","publicEmail":true,"nacontact":false}],"programExecutives":[{"contactId":215154,"canUserEdit":false,"firstName":"Jennifer","lastName":"Gustetic","fullName":"Jennifer L Gustetic","fullNameInverted":"Gustetic, Jennifer L","middleInitial":"L","primaryEmail":"jennifer.l.gustetic@nasa.gov","publicEmail":true,"nacontact":false}],"programManagers":[{"contactId":62051,"canUserEdit":false,"firstName":"Carlos","lastName":"Torrez","fullName":"Carlos Torrez","fullNameInverted":"Torrez, Carlos","primaryEmail":"carlos.torrez@nasa.gov","publicEmail":true,"nacontact":false}],"projectManagers":[{"contactId":96166,"canUserEdit":false,"firstName":"Daniel","lastName":"Duffy","fullName":"Daniel Q Duffy","fullNameInverted":"Duffy, Daniel Q","middleInitial":"Q","primaryEmail":"daniel.q.duffy@nasa.gov","publicEmail":true,"nacontact":false},{"contactId":461333,"canUserEdit":false,"firstName":"Theresa","lastName":"Stanley","fullName":"Theresa M Stanley","fullNameInverted":"Stanley, Theresa M","middleInitial":"M","primaryEmail":"theresa.m.stanley@nasa.gov","publicEmail":true,"nacontact":false}],"website":"","libraryItems":[{"file":{"fileExtension":"pdf","fileId":298300,"fileName":"SBIR_2015_1_BC_S5.03-9352","fileSize":30526,"objectId":294834,"objectType":{"lkuCodeId":889,"code":"LIBRARY_ITEMS","description":"Library Items","lkuCodeTypeId":182,"lkuCodeType":{"codeType":"OBJECT_TYPE","description":"Object Type"}},"objectTypeId":889,"fileSizeString":"29.8 KB"},"files":[{"fileExtension":"pdf","fileId":298300,"fileName":"SBIR_2015_1_BC_S5.03-9352","fileSize":30526,"objectId":294834,"objectType":{"lkuCodeId":889,"code":"LIBRARY_ITEMS","description":"Library Items","lkuCodeTypeId":182,"lkuCodeType":{"codeType":"OBJECT_TYPE","description":"Object Type"}},"objectTypeId":889,"fileSizeString":"29.8 KB"}],"id":294834,"title":"Briefing Chart","description":"SparkRS - 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The NASA SBIR and STTR programs fund the research, development, and demonstration of innovative technologies that fulfill NASA needs as described in the annual Solicitations and have significant potential for successful commercialization. If you are a small business concern (SBC) with 500 or fewer employees or a non-profit RI such as a university or a research laboratory with ties to an SBC, then NASA encourages you to learn more about the SBIR and STTR programs as a potential source of seed funding for the development of your innovations.
The SBIR and STTR programs have 3 phases:
The SBIR and STTR Phase I contracts last for 6 months with a maximum funding of $125,000, and Phase II contracts last for 24 months with a maximum funding of $750,000 - $1.5 million.
Opportunity for Continued Technology Development Post-Phase II:
The NASA SBIR/STTR Program currently has in place two initiatives for supporting its small business partners past the basic Phase I and Phase II elements of the program that emphasize opportunities for commercialization. Specifically, the NASA SBIR/STTR Program has the Phase II Enhancement (Phase II-E) and Phase II eXpanded (Phase II-X) contract options.
Please review the links below to obtain more information on the SBIR/STTR programs.
Provides an overview of the SBIR and STTR programs as implemented by NASA
Provides access to the annual SBIR/STTR Solicitations containing detailed information on the program eligibility requirements, proposal instructions and research topics and subtopics
Schedule and links for the SBIR/STTR solicitations and selection announcements
Federal and non-Federal sources of assistance for small business
Search our complete archive of awarded project abstracts to learn about what NASA has funded
Still have questions? Visit the program FAQs
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