THE OVERARCHING GOAL OF THIS PROPOSAL IS TO DEVELOP AN AUTOMATED SHORELINE EXTRACTION TECHNIQUE USING SMALLSAT IMAGERY THAT WILL ENABLE MAPPING OF HIGH-RESOLUTION SHORELINE POSITIONS ACROSS REGIONAL-TO-CONTINENTAL SCALES. THIS NOVEL TECHNIQUE WILL FACILITATE COASTAL MONITORING AT SPATIAL RESOLUTIONS COMPARABLE TO AIRBORNE SURVEYS BUT AT THE DESIRED TEMPORAL FREQUENCY OF A SATELLITE CONSTELLATION. THIS ADVANTAGEOUS COMBINATION WILL SIGNIFICANTLY ENHANCE OUR ABILITY TO GATHER TIMELY INFORMATION ABOUT SHORELINE CHANGES IN THE AFTERMATH OF MAJOR STORMS AND DETECT ONGOING SMALL-SCALE CHANGES IN RESPONSE TO SEA LEVEL RISE AMONG OTHER APPLICATIONS. OBJECTIVES: THE CENTRAL OBJECTIVES OF THIS PROPOSAL INCLUDE (1) DEVELOPING AN AUTOMATED SHORELINE MAPPING METHODOLOGY USING EMERGING IMAGE ANALYSIS TECHNIQUES (MACHINE LEARNING) AND GEOSPATIAL PLATFORMS (GOOGLE EARTH ENGINE) (2) ASSESSING THE ACCURACY OF SHORELINE POSITIONS DERIVED FROM SMALLSAT IMAGERY BY COMPARISON TO MEAN HIGH WATER SHORELINE POSITIONS INTERPRETED FROM UNMANNED AIRCRAFT SYSTEM (UAS) IMAGERY AND (3) IDENTIFYING THE SMALLSAT DATA PRODUCT BEST SUITED FOR COASTAL MONITORING BASED ON SHORELINE ACCURACY AND SURVEY FREQUENCY. METHODS: THE FIRST COMPONENT INVOLVES ACQUISITION OF UAS IMAGERY AT THREE COASTAL STUDY AREAS IN SOUTHERN CALIFORNIA THAT WILL SERVE AS VALIDATION DATASETS FOR THE SMALLSAT-DERIVED SHORELINE POSITIONS. THE SECOND COMPONENT INVOLVES THE GENERATION OF UAS PHOTOGRAMMETRY PRODUCTS AND VALIDATION DATA. THE UAS IMAGERY WILL BE USED TO GENERATE GEOREFERENCED DIGITAL SURFACE MODELS (DSM) FROM WHICH MEAN HIGH WATER (MHW) SHORELINE POSITIONS WILL BE INTERPRETED AND USED TO ASSESS THE ACCURACY OF SHORELINES INTERPRETED FROM SMALLSAT IMAGERY. ULTRA-HIGH RESOLUTION ORTHOPHOTO MOSAICS WILL ALSO BE GENERATED FROM THE UAS IMAGERY WHICH WILL BE USED TO ASSESS THE PERFORMANCE OF THE MACHINE LEARNING CLASSIFIER USED TO AUTOMATICALLY INTERPRET THE SHORELINE POSITION. THE THIRD AND FINAL COMPONENT IS DEVELOPING THE AUTOMATED SHORELINE EXTRACTION TECHNIQUE USING MACHINE LEARNING CLASSIFICATION. ALL OF THE IMAGE PROCESSING AND ANALYSIS TASKS WILL BE PERFORMED IN GOOGLE EARTH ENGINE AND SCRIPTS WILL BE DISSEMINATED TO PUBLIC REPOSITORIES TO ENCOURAGE FUTURE USE. FINALLY THE ACCURACY OF SHORELINES DERIVED FROM THE VARIOUS SMALLSAT PRODUCTS WILL BE ASSESSED BY COMPARISON TO THE UAS MHW SHORELINE POSITION. SIGNIFICANCE TO CSDAP: THIS PROPOSAL FALLS WITHIN THE GENERAL SCOPE OF A.42 AND ADDRESSES STRATEGIC GOAL 1 OF NASA S 2018 STRATEGIC PLAN. THE MOST IMPORTANT OUTCOME OF THIS PROPOSAL WILL BE ITS CONTRIBUTION AS A SOCIETAL BENEFIT AND APPLICATION FOR NATURAL HAZARD PREPAREDNESS AND RESPONSE. SANDY COASTLINES ARE BECOMING INCREASINGLY SUSCEPTIBLE TO GLOBAL SEA-LEVEL RISE AND IT'S PREDICTED THAT HALF OF THE WORLD'S BEACHES COULD BE COMPLETELY ERODED BY 2100. CALIFORNIA S DUNE-BACKED SHORELINES ARE ESPECIALLY VULNERABLE AND THE U.S. GEOLOGICAL SURVEY HAS ESTABLISHED A COASTAL CHANGE HAZARDS PORTAL TO PROVIDE SCIENTIFICALLY CREDIBLE DATA TO HELP MANAGE THESE COASTAL HAZARDS. THE MOST RECENT STATEWIDE SHORELINE MAPPED BY THE USGS WAS IN 2002 DUE TO THE HIGH ACQUISITION COSTS OF AIRBORNE SURVEYING AND AS SUCH THERE IS A CRITICAL NEED FOR A SHORELINE MAPPING TECHNIQUE THAT TAKES ADVANTAGE OF MODERN SATELLITE TECHNOLOGY AND DATA ANALYSIS TECHNIQUES. THE PRODUCTS OF THIS RESEARCH WILL SIGNIFICANTLY ASSIST COASTAL LAND USE MANAGERS AND OTHER DECISION MAKERS WITH IDENTIFYING EROSIONAL HOT SPOTS THAT SHOULD BE TARGETED FOR RESTORATION EFFORTS. THE PROPOSED WORK WILL ALSO ADVANCE OUR UNDERSTANDING OF EARTH SYSTEM SCIENCE AS IT WILL PROVIDE A GROUNDBREAKING TECHNIQUE FOR ASSESSING GLOBAL COASTAL CHANGE. HAVING THIS NEWFOUND CAPABILITY TO DETECT HIGH SPATIAL RESOLUTION (&LT;5 M) SHORELINE POSITION CHANGES ACROSS CONTINENTAL-SCALE STUDY AREAS WILL FACILITATE INVESTIGATIONS INTO THE RELATIONSHIP BETWEEN THE EARTH S CLIMATE SYSTEM AND GEOSPHERE