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LEVERAGING OUR CURRENT AND PAST WORK TO BUILD THE GEO G20 GLOBAL AGRICULTURAL MONITORING (GEOGLAM) INITIATIVE  THE CURRENT PROPOSAL IS ESSENTIAL TO THE CONTINUED IMPLEMENTATION AND DEVELOPMENT OF GEOGLAM  WHICH HAS ACHIEVED UNPRECEDENTED SUCCESS IN ENGAGING END-USERS INVOLVED WITH CROP PRODUCTION MONITORING AND FORECASTING. THROUGH THIS PROPOSAL  THE CROP MONITORS LED BY UMD WILL CONTINUE TO DELIVER EO-DERIVED INFORMATION TO THE AGRICULTURAL MARKET INFORMATION SYSTEM (AMIS)  AN INTERNATIONAL BODY OF CHIEF ECONOMISTS FROM MAJOR CROP EXPORT COUNTRIES  AND PROVIDE A MONTHLY BULLETIN OF CROP CONDITIONS FOR FOOD INSECURE COUNTRIES WITH AN EXPANDING GROUP OF INTERNATIONAL AND NATIONAL FOOD SECURITY ORGANIZATIONS. THE FSAC END USER ENGAGEMENT WILL BE BROAD - ADDRESSING NOT ONLY INTERNATIONAL CROP PRODUCTION FORECASTS  MARKETS  AND TRADE  ALONGSIDE REGIONAL/NATIONAL FOOD SECURITY  EARLY WARNING  DISASTER RESPONSE AND POLICY - BUT ALSO DOMESTIC COMMERCIAL AGRICULTURE AND FARM MANAGEMENT  AND SMALLHOLDER FARM MANAGEMENT  RESILIENCE AND MICRO-INSURANCE. IT WILL INCLUDE STRATEGIC  SYSTEMATIZED ENGAGEMENT OF NON-TRADITIONAL USERS OF NASA DATA (INSURANCE INDUSTRY  HUMANITARIAN ORGANIZATIONS AND INTELLIGENCE). THE FSAC MEMBERS WERE SELECTED STRATEGICALLY FOR THEIR EXPERTISE AND RELATIONSHIPS WITH A BROAD RANGE OF USER-GROUPS. OUR APPLICATIONS R&D WILL FOCUS ON CROP CONDITION MONITORING AND RISK ASSESSMENT  CROPLAND  CROP TYPE AND AREA MAPPING  CROP YIELD AND PRODUCTION MODELING AND FORECASTING AND LINKING EO PRODUCTS TO SOCIO-ECONOMIC DATA TO ADDRESS FOOD SECURITY QUESTIONS. THE RESULTING SUITE OF INNOVATIVE PRODUCTS AND SERVICES WILL COMBINE EO PRODUCTS FROM DIFFERENT SENSORS WITH METEOROLOGICAL  GROUND AND SURVEY DATA. OTHER MAJOR WORK ELEMENTS WILL INCLUDE: THE ECONOMIC AND SOCIAL VALUATION OF THE BENEFITS OF EO THROUGH ECONOMIC ANALYSIS OF EO FOR PRODUCTION FORECASTING AND REPRESENTATIVE END USER CASE STUDIES; LINKAGE TO NEW NASA SENSORS  ENHANCING THE EARLY ADOPTERS PROGRAM; DEVELOPMENT OF AN FSAC PORTAL FOR INFORMATION COLLECTION  DISSEMINATION  AND INNOVATIVE COMBINATION; AND A PROFESSIONAL COMMUNICATIONS INITIATIVE GIVING BROAD OUTREACH FOR THE PROGRAM. THE DOMESTIC AGRICULTURE COMPONENT OF THE PROPOSAL WILL TEST NEW EO-BASED APPLICATIONS TO IMPROVE FARM MANAGEMENT AND HELP USDA NASS IMPROVE THE RELIABILITY OF ITS US STATISTICS (AREA/YIELD). FSAC WILL HOLD A SERIES OF THEMATIC  COMMUNITY WORKSHOPS IN THE US  ESTABLISHING A US GEOGLAM COMMUNITY OF PRACTICE (COP) TO COMPLEMENT THE INTERNATIONAL COP. THESE ACTIVITIES TOGETHER WILL DELIVER NASA AN OUTSTANDING  COORDINATED  AND WELL-BALANCED PROGRAM APPLYING EO TO FOOD SECURITY AND AGRICULTURE  WITH STRONG CONNECTIONS TO RELEVANT NASA PROGRAMS  SCIENCE TEAMS  AND NEW MISSIONS. A GOAL OF THE FSAC IN ADDITION TO RESPONDING TO THE RFP  IS TO EXPAND ITS ACTIVITIES  PARTNERSHIPS  AND COLLABORATIONS WITH NON-NASA FUNDING  SUSTAINING THE CONSORTIUM AND ITS FUNCTIONS BEYOND THE 5-YEAR FUNDING PERIOD.","funder_award_id":"80NSSC18M0039","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G8355369167","display_name":"THE INCREASED TEMPORAL COVERAGE AFFORDED BY THE ESA SENTINEL SYSTEMS PROVIDES NEW OPPORTUNITIES FOR HIGH TEMPORAL FREQUENCY MODERATE RESOLUTION REMOTE SENSING  ENABLING A NEW GENERATION OF DATA PRODUCTS TO BE GENERATED FOR THE STUDY OF LAND COVER AND LAND USE. ALTHOUGH AGRICULTURAL APPLICATIONS PROVIDED A STRONG RATIONALE FOR THE LANDSAT MISSIONS  THE 16-DAY COVERAGE IS A SERIOUS LIMITATION FOR OBTAINING CLOUD-FREE OBSERVATIONS. LANDSAT-8 IN COMBINATION WITH SENTINEL-2 INCREASES THE OPPORTUNITY FOR CLOUD-FREE OPTICAL DATA  AND SENTINEL-1 PROVIDES FREELY AVAILABLE MODERATE RESOLUTION MICROWAVE COVERAGE AND AN UNPRECEDENTED OPPORTUNITY FOR NEW PRODUCTS FOR AGRICULTURAL LAND USE. BUILDING ON EXPERIENCE GAINED WITH MODIS  THIS PROPOSAL PROTOTYPES A NEW CROP YIELD PRODUCT FOR WHEAT  CORN AND SOYBEAN  WHICH CAN BE GENERALLY APPLIED TO MAJOR CROP GROWING REGIONS. WE WILL UTILIZE ROBUST FEATURES FROM MULTI-TEMPORAL OPTICAL AND MICROWAVE IMAGERY AND GENERALIZED CLASSIFICATION MODELS FOR CROP MAPPING TO GENERATE CROP SPECIFIC MASKS. A-PRIORI KNOWLEDGE ON CROP CALENDARS AND METEOROLOGICAL DATA INFLUENCING CROP GROWTH (E.G. GROWING DEGREE DAYS) WILL BE USED TO RUN AND TEST GENERALIZED CLASSIFIERS THAT WILL BE APPLICABLE TO MULTIPLE AGRICULTURE CONDITIONS  PROVIDING THE POSSIBILITY OF GENERATING DEDICATED PRODUCTS AT CONTINENTAL TO GLOBAL SCALES. CROP YIELD MAPPING AND ASSESSMENT WILL BE PERFORMED BY FIRST BUILDING GENERALIZED CROP YIELD MODELS USING COARSE RESOLUTION DATA (MODIS) THAT HAVE A LONG DATA RECORD (FROM 2001)  AND THEN EXTRAPOLATING THE YIELD MODELS TO MODERATE RESOLUTION DATA (LANDSAT-8 AND SENTINEL-2) TO PROVIDE YIELD MAPS AT 30M. MULTIPLE SATELLITE-DERIVED FEATURES  SUCH AS VEGETATION INDICES AND BIOPHYSICAL PARAMETERS ESTIMATED AT A SINGLE DATE OR ACCUMULATED OVER THE CROP GROWTH PERIOD  WILL BE ANALYZED  WITH AN NDVI-BASED APPROACH SERVING AS A BENCHMARK  TO CONNECT THEM WITH CROP YIELD AT REGIONAL AND FIELD SCALES TO TARGET A 5-10% ERROR. SINCE TEMPERATURE IS A PRIMARY FACTOR AFFECTING THE RATE OF CROP DEVELOPMENT  METEOROLOGICAL DATA AND PHOTOSYNTHETICALLY ACTIVE RADIATION (PAR) WILL BE INCORPORATED INTO THE YIELD MODELS. WE WILL ADVANCE THE CURRENT SCIENCE BY ESTIMATING UNCERTAINTIES OF CROP YIELD ESTIMATES  AS PREVIOUS APPROACHES USUALLY DO NOT REPORT ASSOCIATED UNCERTAINTIES. FOR THIS  WE WILL UTILIZE NON-LINEAR REGRESSION MODELS BASED ON GAUSSIAN PROCESSES (GPS) THAT PRODUCE BOTH THE ESTIMATE AND ITS UNCERTAINTY. INCORPORATION OF MICROWAVE DATA FROM SENTINEL-1 WILL BE PERFORMED BY INVERSION OF THE RADAR SIGNAL IN MULTIPLE POLARIZATIONS TO THE BIOPHYSICAL PARAMETERS  USING THE SEMI-EMPIRICAL WATER CLOUD MODEL (WCM). SARDERIVED PARAMETERS  SUCH AS LAI  CAN BE USED AS A BASIS FOR INTEGRATING WITH OPTICAL-DERIVED PARAMETERS USED FOR CROP YIELD MAPPING. CROP TYPE AND CROP YIELD MAPS WILL BE GENERATED FOR ADMINISTRATIVE REGIONS (WITH AREA RANGING FROM 28 000 TO 308 000 SQ. KM) FOR 7 COUNTRIES (ARGENTINA  CANADA  FRANCE  SOUTH AFRICA  TANZANIA  UKRAINE AND US). WE WILL VALIDATE THESE REGIONAL PRODUCTS AT REGIONAL AND FIELD SCALES FOR TEST SITES IN THESE COUNTRIES  EXHIBITING DIFFERENT AGRICULTURE PRACTICES AND CONDITIONS (FIELD SIZES: 0.5 HA TO 500 HA  YIELD RANGE: 1.5 T/HA TO 10 T/HA) WHERE THE THREE MAJOR CROPS ARE GROWN AND WHERE WE HAVE VALIDATION DATA AND STRONG PARTNER COLLABORATION. THE PROJECT WILL WORK WITH INTERNATIONAL COLLABORATORS WHO ARE ACTIVELY INVOLVED IN CROP MONITORING  USING LANDSAT-8 AND SENTINEL-1/2 DATA. THE INTERNATIONAL COLLABORATION WILL FOCUS ON THE EVALUATION AND VALIDATION OF THE PRODUCTS IN THE FRAMEWORK OF THE GEOGLAM PROGRAM. THE NEW PRODUCTS OF CROP MAPS AND CROP YIELD MAPS WILL HAVE A NUMBER OF POTENTIAL USERS FROM LOCAL AUTHORITIES DEALING WITH FOOD SECURITY  FARMERS TO ADDRESS AGRICULTURAL MANAGEMENT PRACTICES (E.G. YIELD GAPS) AND INSURANCE COMPANIES CONCERNED WITH FARM YIELD INSURANCE CONTRACTS.","funder_award_id":"80NSSC18K0336","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"}],"funders":[{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"},{"id":"https://openalex.org/F4320311090","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78"},{"id":"https://openalex.org/F4320332165","display_name":"National Geospatial-Intelligence Agency","ror":"https://ror.org/02k4pxv54"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3135523315.pdf","grobid_xml":"https://content.openalex.org/works/W3135523315.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1963959300","https://openalex.org/W1964409545","https://openalex.org/W1966845328","https://openalex.org/W1987415163","https://openalex.org/W2004611847","https://openalex.org/W2011500029","https://openalex.org/W2013629773","https://openalex.org/W2023336635","https://openalex.org/W2038782607","https://openalex.org/W2056435747","https://openalex.org/W2074025929","https://openalex.org/W2081048660","https://openalex.org/W2089305706","https://openalex.org/W2097110832","https://openalex.org/W2110803570","https://openalex.org/W2111752896","https://openalex.org/W2116563724","https://openalex.org/W2118182941","https://openalex.org/W2139709933","https://openalex.org/W2143481518","https://openalex.org/W2253154013","https://openalex.org/W2344328155","https://openalex.org/W2414117070","https://openalex.org/W2532003389","https://openalex.org/W2534655245","https://openalex.org/W2569351272","https://openalex.org/W2751786729","https://openalex.org/W2793728001","https://openalex.org/W2795269446","https://openalex.org/W2890565173","https://openalex.org/W2897285410","https://openalex.org/W2902273998","https://openalex.org/W2907854285","https://openalex.org/W2942992951","https://openalex.org/W2946844285","https://openalex.org/W2966744467","https://openalex.org/W2982943610","https://openalex.org/W3100645060","https://openalex.org/W3106223330","https://openalex.org/W4251622304","https://openalex.org/W6641849199","https://openalex.org/W6715652707","https://openalex.org/W6756636416"],"related_works":["https://openalex.org/W2535248569","https://openalex.org/W1968901811","https://openalex.org/W2087241461","https://openalex.org/W1609312116","https://openalex.org/W4252715641","https://openalex.org/W2098219828","https://openalex.org/W2045907675","https://openalex.org/W2360114125","https://openalex.org/W2028054326","https://openalex.org/W2023226251"],"abstract_inverted_index":{"Crop":[0],"yield":[1,51,171,201,244,280],"monitoring":[2],"is":[3,108,193],"an":[4],"important":[5,240],"component":[6],"in":[7,164,335],"agricultural":[8],"assessment.":[9],"Multi-spectral":[10],"remote":[11],"sensing":[12],"instruments":[13],"onboard":[14],"space-borne":[15],"platforms":[16],"such":[17,342],"as":[18,173,343],"Advanced":[19],"Very":[20],"High":[21],"Resolution":[22,26],"Radiometer":[23,34],"(AVHRR),":[24],"Moderate":[25],"Imaging":[27,33],"Spectroradiometer":[28],"(MODIS),":[29],"and":[30,46,101,129,137,145,149,155,205,222,232,253,266,309,346],"Visible":[31],"Infrared":[32],"Suite":[35],"(VIIRS)":[36],"have":[37],"shown":[38],"to":[39,65,85,104,152,175,195,213,229,300,312,360],"be":[40],"useful":[41],"for":[42,182,203,275,279,304,316,323],"efficiently":[43],"generating":[44],"timely":[45],"synoptic":[47],"information":[48,95],"on":[49,96,117],"the":[50,59,72,119,165,199,226,238,260,292,305,331,357,363],"status":[52],"of":[53,121,168,190,198,217,264,269,288,294,330],"crops":[54,97],"across":[55],"regional":[56],"levels.":[57],"However,":[58],"coarse":[60],"spatial":[61,82,188,351],"resolution":[62,83,189,215],"data":[63,172,216,273],"inherent":[64],"these":[66],"sensors":[67],"provides":[68],"little":[69],"utility":[70],"at":[71,99,158,348],"management":[73],"level.":[74],"Recent":[75],"satellite":[76,123],"imagery":[77,187,359],"collection":[78],"advances":[79],"toward":[80],"finer":[81],"(down":[84],"1":[86],"m)":[87],"alongside":[88,356],"increased":[89],"observational":[90],"cadence":[91],"(near":[92],"daily)":[93],"implies":[94],"obtainable":[98],"field":[100],"within-field":[102,200],"scales":[103,160],"support":[105],"farming":[106],"needs":[107],"now":[109],"possible.":[110],"To":[111],"test":[112],"this":[113],"premise,":[114],"we":[115,284],"focus":[116],"assessing":[118],"efficiency":[120],"multiple":[122],"sensors,":[124],"namely":[125],"WorldView-3,":[126],"Planet/Dove-Classic,":[127],"Sentinel-2,":[128],"Landsat":[130,134],"8":[131,271],"(through":[132],"Harmonized":[133],"Sentinel-2":[135],"(HLS)),":[136],"investigate":[138],"their":[139],"spatial,":[140],"spectral":[141,241],"(surface":[142],"reflectance":[143,333],"(SR)":[144],"vegetation":[146],"indices":[147],"(VIs)),":[148],"temporal":[150,262],"characteristics":[151],"estimate":[153],"corn":[154,204],"soybean":[156],"yields":[157],"sub-field":[159],"within":[161],"study":[162],"sites":[163],"US":[166],"state":[167],"Iowa.":[169],"Precision":[170],"referenced":[174],"combine":[176],"harvesters\u2019":[177],"GPS":[178],"systems":[179],"were":[180,246],"used":[181],"validation.":[183],"We":[184,235],"show":[185,210,236],"that":[186,211,237],"3":[191,317],"m":[192,224,307,318],"critical":[194],"explaining":[196,243],"100%":[197],"variability":[202,228,245],"soybean.":[206],"Our"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