P00001 SUMMARY: SURFACE MINERAL MAPPING AND ROCK TYPE/LITHOLOGICAL INFORMATION ARE VERY CRUCIAL STEP FOR MINERAL EXPLORATION. THE MINERAL MAPPING AND LITHOLOGICAL IDENTIFICATION CAN BE PERFORMED BY IDENTIFYING THE UNIQUE SPECTRAL SIGNATURES AND ITS SPATIAL DISTRIBUTIONS USING REMOTE SENSING TECHNIQUES. PARTICULARLY, STUDIES HAVE DEMONSTRATED THE APPLICABILITY OF HYPERSPECTRAL REMOTE SENSING FOR IDENTIFYING THE UNIQUE SPECTRAL SIGNATURES OF MINERALS AND ROCK TYPES. NASA AND THE INDIAN SPACE RESEARCH ORGANIZATION (ISRO) ARE GENERATING EARTH SURFACE FEATURES DATA USING AIRBORNE VISIBLE/INFRARED IMAGING SPECTROMETER-NEXT GENERATION (AVIRIS-NG) WITHIN 380 TO 2500 NM SPECTRAL RANGE. THIS RESEARCH FOCUSES ON THE UTILIZATION OF SUCH DATA TO DEVELOP AN IMPROVED MATHEMATICAL FRAMEWORK TO BETTER UNDERSTAND THE MINERAL POTENTIAL IN INDIA. THE PRIMARY FOCUS AREA OF THIS RESEARCH IS THE HUTTI-MASKI GREENSTONE BELT, LOCATED IN KARNATAKA, INDIA. THE AVIRIS-NG DATA WILL BE INTEGRATED WITH FIELD ANALYZED DATA (LABORATORY SCALED COMPOSITIONAL ANALYSIS, MINERALOGY, AND SPECTRAL LIBRARY) TO CHARACTERIZE MINERALS AND ROCK TYPES. AN EXPERT SYSTEM WILL BE DEVELOPED TO AUTOMATICALLY PRODUCE MINERAL MAPS FROM AVIRIS-NG DATA. THE GROUND TRUTH DATA FROM THE STUDY AREAS WILL BE OBTAINED FROM THE EXISTING LITERATURE, AND PI'S EXISTING COLLABORATORS FROM INDIA. BAYESIAN SPECTRAL UNMIXING ALGORITHM WILL BE USED IN AVIRIS-NG DATA FOR ENDMEMBER SELECTION. THE CLASSIFICATION MAPS OF THE MINERALS AND ROCK TYPES WILL BE DEVELOPED USING SUPPORT VECTOR MACHINE ALGORITHM. THE GROUND TRUTH DATA WILL BE USED TO VERIFY THE MINERAL MAPS. THE MAJOR OBJECTIVE OF THIS STUDY IS TO DEMONSTRATE APPLICATION OF SPECTRAL DATA IN ROCK TYPE DISCRIMINATION AND MAPPING FOR MINERAL EXPLORATION BY USING AUTOMATED MAPPING TECHNIQUES. THE EXPECTED OUTCOME OF THIS RESEARCH WILL BE (A) UNDERSTANDING THE SPECTRAL CHARACTERISTICS OF MINERAL ASSEMBLAGES IN STUDY AREAS AND (B) A CLASSIFIED MINERAL MAP OF THE STUDY AREA. BAYESIAN UNMIXING ALGORITHM WILL ALSO PROVIDE AN UNCERTAINTY VALUE WITH THE ESTIMATED MINERAL MAPS. THIS UNCERTAINTY WITH GROUND TRUTH DATA WILL HELP TO EVALUATE THE RELIABILITY OF THE ESTIMATED MINERAL MAPS. Funding Only Action $35.0k 9/11/18 Not listed SUMMARY: SURFACE MINERAL MAPPING AND ROCK TYPE/LITHOLOGICAL INFORMATION ARE VERY CRUCIAL STEP FOR MINERAL EXPLORATION. THE MINERAL MAPPING AND LITHOLOGICAL IDENTIFICATION CAN BE PERFORMED BY IDENTIFYING THE UNIQUE SPECTRAL SIGNATURES AND ITS SPATIAL DISTRIBUTIONS USING REMOTE SENSING TECHNIQUES. PARTICULARLY STUDIES HAVE DEMONSTRATED THE APPLICABILITY OF HYPERSPECTRAL REMOTE SENSING FOR IDENTIFYING THE UNIQUE SPECTRAL SIGNATURES OF MINERALS AND ROCK TYPES. NASA AND THE INDIAN SPACE RESEARCH ORGANIZATION (ISRO) ARE GENERATING EARTH SURFACE FEATURES DATA USING AIRBORNE VISIBLE/INFRARED IMAGING SPECTROMETER-NEXT GENERATION (AVIRIS-NG) WITHIN 380 TO 2500 NM SPECTRAL RANGE. THIS RESEARCH FOCUSES ON THE UTILIZATION OF SUCH DATA TO DEVELOP AN IMPROVED MATHEMATICAL FRAMEWORK TO BETTER UNDERSTAND THE MINERAL POTENTIAL IN INDIA. THE PRIMARY FOCUS AREA OF THIS RESEARCH IS THE HUTTI-MASKI GREENSTONE BELT LOCATED IN KARNATAKA INDIA. THE AVIRIS-NG DATA WILL BE INTEGRATED WITH FIELD ANALYZED DATA (LABORATORY SCALED COMPOSITIONAL ANALYSIS MINERALOGY AND SPECTRAL LIBRARY) TO CHARACTERIZE MINERALS AND ROCK TYPES. AN EXPERT SYSTEM WILL BE DEVELOPED TO AUTOMATICALLY PRODUCE MINERAL MAPS FROM AVIRIS-NG DATA. THE GROUND TRUTH DATA FROM THE STUDY AREAS WILL BE OBTAINED FROM THE EXISTING LITERATURE AND PI'S EXISTING COLLABORATORS FROM INDIA. BAYESIAN SPECTRAL UNMIXING ALGORITHM WILL BE USED IN AVIRIS-NG DATA FOR ENDMEMBER SELECTION. THE CLASSIFICATION MAPS OF THE MINERALS AND ROCK TYPES WILL BE DEVELOPED USING SUPPORT VECTOR MACHINE ALGORITHM. THE GROUND TRUTH DATA WILL BE USED TO VERIFY THE MINERAL MAPS. THE MAJOR OBJECTIVE OF THIS STUDY IS TO DEMONSTRATE APPLICATION OF SPECTRAL DATA IN ROCK TYPE DISCRIMINATION AND MAPPING FOR MINERAL EXPLORATION BY USING AUTOMATED MAPPING TECHNIQUES. THE EXPECTED OUTCOME OF THIS RESEARCH WILL BE (A) UNDERSTANDING THE SPECTRAL CHARACTERISTICS OF MINERAL ASSEMBLAGES IN STUDY AREAS AND (B) A CLASSIFIED MINERAL MAP OF THE STUDY AREA. BAYESIAN UNMIXING ALGORITHM WILL ALSO PROVIDE AN UNCERTAINTY VALUE WITH THE ESTIMATED MINERAL MAPS. THIS UNCERTAINTY WITH GROUND TRUTH DATA WILL HELP TO EVALUATE THE RELIABILITY OF THE ESTIMATED MINERAL MAPS. $35.0k 9/11/18 Not listed SUMMARY: SURFACE MINERAL MAPPING AND ROCK TYPE/LITHOLOGICAL INFORMATION ARE VERY CRUCIAL STEP FOR MINERAL EXPLORATION. THE MINERAL MAPPING AND LITHOLOGICAL IDENTIFICATION CAN BE PERFORMED BY IDENTIFYING THE UNIQUE SPECTRAL SIGNATURES AND ITS SPATIAL DISTRIBUTIONS USING REMOTE SENSING TECHNIQUES. PARTICULARLY STUDIES HAVE DEMONSTRATED THE APPLICABILITY OF HYPERSPECTRAL REMOTE SENSING FOR IDENTIFYING THE UNIQUE SPECTRAL SIGNATURES OF MINERALS AND ROCK TYPES. NASA AND THE INDIAN SPACE RESEARCH ORGANIZATION (ISRO) ARE GENERATING EARTH SURFACE FEATURES DATA USING AIRBORNE VISIBLE/INFRARED IMAGING SPECTROMETER-NEXT GENERATION (AVIRIS-NG) WITHIN 380 TO 2500 NM SPECTRAL RANGE. THIS RESEARCH FOCUSES ON THE UTILIZATION OF SUCH DATA TO DEVELOP AN IMPROVED MATHEMATICAL FRAMEWORK TO BETTER UNDERSTAND THE MINERAL POTENTIAL IN INDIA. THE PRIMARY FOCUS AREA OF THIS RESEARCH IS THE HUTTI-MASKI GREENSTONE BELT LOCATED IN KARNATAKA INDIA. THE AVIRIS-NG DATA WILL BE INTEGRATED WITH FIELD ANALYZED DATA (LABORATORY SCALED COMPOSITIONAL ANALYSIS MINERALOGY AND SPECTRAL LIBRARY) TO CHARACTERIZE MINERALS AND ROCK TYPES. AN EXPERT SYSTEM WILL BE DEVELOPED TO AUTOMATICALLY PRODUCE MINERAL MAPS FROM AVIRIS-NG DATA. THE GROUND TRUTH DATA FROM THE STUDY AREAS WILL BE OBTAINED FROM THE EXISTING LITERATURE AND PI'S EXISTING COLLABORATORS FROM INDIA. BAYESIAN SPECTRAL UNMIXING ALGORITHM WILL BE USED IN AVIRIS-NG DATA FOR ENDMEMBER SELECTION. THE CLASSIFICATION MAPS OF THE MINERALS AND ROCK TYPES WILL BE DEVELOPED USING SUPPORT VECTOR MACHINE ALGORITHM. THE GROUND TRUTH DATA WILL BE USED TO VERIFY THE MINERAL MAPS. THE MAJOR OBJECTIVE OF THIS STUDY IS TO DEMONSTRATE APPLICATION OF SPECTRAL DATA IN ROCK TYPE DISCRIMINATION AND MAPPING FOR MINERAL EXPLORATION BY USING AUTOMATED MAPPING TECHNIQUES. THE EXPECTED OUTCOME OF THIS RESEARCH WILL BE (A) UNDERSTANDING THE SPECTRAL CHARACTERISTICS OF MINERAL ASSEMBLAGES IN STUDY AREAS; AND (B) A CLASSIFIED MINERAL MAP OF THE STUDY AREA. BAYESIAN UNMIXING ALGORITHM WILL ALSO PROVIDE AN UNCERTAINTY VALUE WITH THE ESTIMATED MINERAL MAPS. THIS UNCERTAINTY WITH GROUND TRUTH DATA WILL HELP TO EVALUATE THE RELIABILITY OF THE ESTIMATED MINERAL MAPS. $127.8k 9/5/17 Not listed SUMMARY: SURFACE MINERAL MAPPING AND ROCK TYPE/LITHOLOGICAL INFORMATION ARE VERY CRUCIAL STEP FOR MINERAL EXPLORATION. THE MINERAL MAPPING AND LITHOLOGICAL IDENTIFICATION CAN BE PERFORMED BY IDENTIFYING THE UNIQUE SPECTRAL SIGNATURES AND ITS SPATIAL DISTRIBUTIONS USING REMOTE SENSING TECHNIQUES. PARTICULARLY, STUDIES HAVE DEMONSTRATED THE APPLICABILITY OF HYPERSPECTRAL REMOTE SENSING FOR IDENTIFYING THE UNIQUE SPECTRAL SIGNATURES OF MINERALS AND ROCK TYPES. NASA AND THE INDIAN SPACE RESEARCH ORGANIZATION (ISRO) ARE GENERATING EARTH SURFACE FEATURES DATA USING AIRBORNE VISIBLE/INFRARED IMAGING SPECTROMETER-NEXT GENERATION (AVIRIS-NG) WITHIN 380 TO 2500 NM SPECTRAL RANGE. THIS RESEARCH FOCUSES ON THE UTILIZATION OF SUCH DATA TO DEVELOP AN IMPROVED MATHEMATICAL FRAMEWORK TO BETTER UNDERSTAND THE MINERAL POTENTIAL IN INDIA. THE PRIMARY FOCUS AREA OF THIS RESEARCH IS THE HUTTI-MASKI GREENSTONE BELT, LOCATED IN KARNATAKA, INDIA. THE AVIRIS-NG DATA WILL BE INTEGRATED WITH FIELD ANALYZED DATA (LABORATORY SCALED COMPOSITIONAL ANALYSIS, MINERALOGY, AND SPECTRAL LIBRARY) TO CHARACTERIZE MINERALS AND ROCK TYPES. AN EXPERT SYSTEM WILL BE DEVELOPED TO AUTOMATICALLY PRODUCE MINERAL MAPS FROM AVIRIS-NG DATA. THE GROUND TRUTH DATA FROM THE STUDY AREAS WILL BE OBTAINED FROM THE EXISTING LITERATURE, AND PI'S EXISTING COLLABORATORS FROM INDIA. BAYESIAN SPECTRAL UNMIXING ALGORITHM WILL BE USED IN AVIRIS-NG DATA FOR ENDMEMBER SELECTION. THE CLASSIFICATION MAPS OF THE MINERALS AND ROCK TYPES WILL BE DEVELOPED USING SUPPORT VECTOR MACHINE ALGORITHM. THE GROUND TRUTH DATA WILL BE USED TO VERIFY THE MINERAL MAPS. THE MAJOR OBJECTIVE OF THIS STUDY IS TO DEMONSTRATE APPLICATION OF SPECTRAL DATA IN ROCK TYPE DISCRIMINATION AND MAPPING FOR MINERAL EXPLORATION BY USING AUTOMATED MAPPING TECHNIQUES. THE EXPECTED OUTCOME OF THIS RESEARCH WILL BE (A) UNDERSTANDING THE SPECTRAL CHARACTERISTICS OF MINERAL ASSEMBLAGES IN STUDY AREAS; AND (B) A CLASSIFIED MINERAL MAP OF THE STUDY AREA. BAYESIAN UNMIXING ALGORITHM WILL ALSO PROVIDE AN UNCERTAINTY VALUE WITH THE ESTIMATED MINERAL MAPS. THIS UNCERTAINTY WITH GROUND TRUTH DATA WILL HELP TO EVALUATE THE RELIABILITY OF THE ESTIMATED MINERAL MAPS. Not listed $127.8k 9/5/17