NASA SBIR 2005 Solicitation

FORM B - PROPOSAL SUMMARY


PROPOSAL NUMBER:05 S7.01-7622
SUBTOPIC TITLE:Geospatial Data Analysis Processing and Visualization Technologies
PROPOSAL TITLE:Automated Extraction of Crop Area Statistics from Medium-Resolution Imagery

SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
GDA Corp.
200 Innovation Blvd., Suite 234
State College ,PA 16803 - 6602
(814) 237 - 4060

PRINCIPAL INVESTIGATOR/PROJECT MANAGER (Name, E-mail, Mail Address, City/State/Zip, Phone)
Dmitry L. Varlyguin
dmitry@gdacorp.com
200 Innovation Blvd., Suite 234
State College, PA  16803 -6602
(814) 237 - 4060

TECHNICAL ABSTRACT (LIMIT 200 WORDS)
This project will focus on the strategic, routine incorporation of medium-resolution satellite imagery into operational agricultural assessments for the global crop market. Automated algorithms for rapid extraction of field-level crop area statistics from Landsat and Landsat-class imagery (including SLC-off L7 data, AWiFS, ASTER, and NPOESS/OLI) will be developed. For prototype development, the project will collaborate with the Production Estimates and Crop Assessment Division of the USDA Foreign Agricultural Service. The algorithms, based on Bayesian Probability Theory, will incorporate multiple lines of evidence in the form of prior and conditional probabilities and will implement an innovative approach to supervised image classification allowing for automated class delineation. The knowledge-based expert classifiers prototyped during Phase I will be tested and validated at selected pilot sites across the globe. The overall results of the project will enhance global agricultural production estimates by improving the timeliness and accuracy of field-level crop area estimates. It addresses the NASA SBIR subtopic by developing unique, rapid analyses for the extraction of crop area statistics from medium-resolution imagery. The developed technologies will support both the scientific and commercial applications of ES data and will be benchmarked for practical use against an international model for agricultural production estimates.

POTENTIAL NASA COMMERCIAL APPLICATIONS (LIMIT 150 WORDS)
The effort will contribute to NASA's Applied Science Program within the Science Mission Directorate by addressing the goals of the Agricultural Efficiency and Disaster Management applications of national priority. The overall results of the project will enhance PECAD's global production estimates by improving the timeliness and accuracy of field-level crop area estimates, and provide a new method to test and utilize other Landsat-class imagery, including SLC-off L7 data, AWiFS, ASTER, and NPOESS/OLI. It addresses the NASA SBIR subtopic by developing unique, rapid analyses for the extraction of crop area statistics from medium-resolution imagery. The developed technologies will support both the scientific and commercial applications of ES data and will be benchmarked for practical use against an international model for agricultural production estimates.

POTENTIAL NON-NASA COMMERCIAL APPLICATIONS (LIMIT 150 WORDS)
Results of the proposed effort can be used to enhance economic opportunities for agricultural producers and commodities. The results of the project will aid in the provision of accurate and timely information on global crop production at a country or regional level, thereby helping producers make better marketing decisions. The results will allow for, among other things, the provision of early warning of unusual crop conditions or changes in the production outlook of a country or region, which, in turn, can assist the private marketplace in price determination and adjustment. One of the largest potential customers may include the commodity exchanges, U.S. Agribusiness, and U.S. Government agencies, particularly USDA. Other commercial applications of proposed algorithms may include land cover re-mapping activities, forest and agricultural monitoring and inventory, and assessments of agricultural/farmer compliance with environmental standards.

NASA's technology taxonomy has been developed by the SBIR-STTR program to disseminate awareness of proposed and awarded R/R&D in the agency. It is a listing of over 100 technologies, sorted into broad categories, of interest to NASA.

TECHNOLOGY TAXONOMY MAPPING
Autonomous Reasoning/Artificial Intelligence
Expert Systems


Form Printed on 09-19-05 13:12