Jin-Si Over is a geographer with the Woods Hole Coastal and Marine Science Center. A drone pilot and structure-from-motion specialist, she supports the Remote Sensing Coastal Change group and Aerial Imaging and Mapping group with GIS and surveying experience.
I have a background in micro-paleontology and working in coastal paleo-environments but gained more modern coastal mapping experience through the NOAA Hollings Scholars program in Hawaii - the beach stole my heart.
Now, as a geographer, my job enables me support coastal data collection, management, and scientific dissemination surrounding coastal responses to storms and hurricanes. This centers around GIS data, aerial imagery and stationary imagery, and processing imagery using structure-from-motion. I focus on datasets on Cape Cod National Seashore and on the Outer Banks. I am also a DOI and FAA licensed drone-pilot and assist in operations at beaches and marshes.
Additionally, I am active in science communication and mentoring efforts on the local scale and am passionate about fostering an inclusive and diverse scientific community.
Professional Experience
Geographer, U.S. Geological Survey, Woods Hole Coastal and Marine Science Center, 2020-Present
Geomorphologist and GIS specialist, Geoscientists in the Parks Program/Rutgers University, Gateway National Recreation Area, 2019-2020
Education and Certifications
M.Sc. Earth and Ocean Sciences, University of Victoria, B.C., 2019
B.S. Geology with minor in Oceanography, University of North Carolina at Wilmington, 2016
Science and Products
Human-in-the-Loop segmentation of earth surface imagery
Labeling poststorm coastal imagery for machine learning: Measurement of interrater agreement
Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6—Structure from motion workflow documentation
IntroductionStructure from motion (SFM) has become an integral technique in coastal change assessment; the U.S. Geological Survey (USGS) used Agisoft Metashape Professional Edition photogrammetry software to develop a workflow that processes coastline aerial imagery collected in response to storms since Hurricane Florence in 2018. This report details step-by-step instructions to create three-dimen
A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons
Remote Sensing Coastal Change
DUNEX Aerial Imagery of the Outer Banks
DUNEX Pea Island Experiment
Aerial Imaging and Mapping
Aerial photogrammetry data and products of the North Carolina coast
Topographic and bathymetric data, structure from motion imagery, and ground control data collected at Marconi Beach, Wellfleet, MA in March 2022, U.S Geological Survey Field Activity 2022-014-FA
Topographic and bathymetric data, structure from motion imagery, and ground control data collected at Head of the Meadow Beach, Truro, MA in March 2022, U.S. Geological Survey Field Activity 2022-015-FA
Grain-size analysis data of sediment samples from the beach and nearshore environments at the Pea Island National Wildlife Refuge DUNEX site, North Carolina in 2021
DUNEX topographic, bathymetric, and supporting GPS data collected in Pea Island National Wildlife Refuge, North Carolina 2020-2021
Aerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09
Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09
Topographic and bathymetric data, structure from motion imagery, and ground control data collected at Head of the Meadow, Truro in February 2021, U.S Geological Survey Field Activity 2021-014-FA
Structure from motion products associated with UAS flights in Sandwich, Massachusetts between January 2016 - September 2017
Aerial Photogrammetry Data and Products of the North Carolina coast: 2018-10-06 to 2018-10-08, post-Hurricane Florence
Topographic and bathymetric data, sediment samples, and imagery collected at Head of the Meadow Beach, Truro in March 2020, U.S Geological Survey Field Activity 2020-015-FA
Science and Products
- Publications
Human-in-the-Loop segmentation of earth surface imagery
Segmentation, or the classification of pixels (grid cells) in imagery, is ubiquitously applied in the natural sciences. Manual methods are often prohibitively time-consuming, especially those images consisting of small objects and/or significant spatial heterogeneity of colors or textures. Labeling complicated regions of transition that in Earth surface imagery are represented by collections of miLabeling poststorm coastal imagery for machine learning: Measurement of interrater agreement
Classifying images using supervised machine learning (ML) relies on labeled training data—classes or text descriptions, for example, associated with each image. Data-driven models are only as good as the data used for training, and this points to the importance of high-quality labeled data for developing a ML model that has predictive skill. Labeling data is typically a time-consuming, manual procProcessing coastal imagery with Agisoft Metashape Professional Edition, version 1.6—Structure from motion workflow documentation
IntroductionStructure from motion (SFM) has become an integral technique in coastal change assessment; the U.S. Geological Survey (USGS) used Agisoft Metashape Professional Edition photogrammetry software to develop a workflow that processes coastline aerial imagery collected in response to storms since Hurricane Florence in 2018. This report details step-by-step instructions to create three-dimen
ByEcosystems Mission Area, Natural Hazards Mission Area, Coastal and Marine Hazards and Resources Program, Maryland-Delaware-D.C. Water Science Center, Pacific Coastal and Marine Science Center, Southwest Biological Science Center, St. Petersburg Coastal and Marine Science Center, Woods Hole Coastal and Marine Science CenterA survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons
Hurricanes are known to play a critical role in reshaping coastlines, but often only impacts on the open ocean coast are considered, ignoring seaward-directed forces and responses. The identification of subaerial evidence for storm-induced seaward transport is a critical step towards understanding its impact on coastal resiliency. The visual features, found in the National Oceanic and Atmospheric - Science
Remote Sensing Coastal Change
We use remote-sensing technologies—such as aerial photography, satellite imagery, structure-from-motion (SfM) photogrammetry, and lidar (laser-based surveying)—to measure coastal change along U.S. shorelines.DUNEX Aerial Imagery of the Outer Banks
The During Nearshore Event Experiment (DUNEX) project is a large collaborative scientific study focusing on understanding the consequences of coastal storms on the morphology of coastal ecosystems. By flying large sections of the coast and collecting still images using structure from motion (SfM) techniques, we hope to contribute high resolution (20cm) elevation maps for time series comparisons...DUNEX Pea Island Experiment
The DUring Nearshore Event eXperiment (DUNEX) is an aggregation of multiple scientific organizations collaborating to increase understanding of nearshore processes. The U.S. Geological Survey (USGS) has chosen Pea Island National Wildlife Refuge as a study location to investigate and characterize the magnitude and timing of changes to coastal morphology (i.e., dunes, shorelines), bathymetry, and...Aerial Imaging and Mapping
The Aerial Imaging and Mapping group (AIM), at the U.S. Geological Survey Woods (USGS) Hole Coastal and Marine Science Center provides UAS services to scientists to advance the science mission of the Coastal and Marine Geology Program. Scientists at the Woods Hole Coastal and Marine Science Center have been using UASs to acquire imagery of coastal and wetland environments, which is then used to... - Data
Aerial photogrammetry data and products of the North Carolina coast
This data release presents structure-from-motion (SfM) products derived from aerial imagery collected along the North Carolina coast in response to storm events and the recovery process. U.S. Geological Survey (USGS) researchers use the aerial imagery and products to assess future coastal vulnerability, nesting habitats for wildlife, and provide data for hurricane impact models. This research is pTopographic and bathymetric data, structure from motion imagery, and ground control data collected at Marconi Beach, Wellfleet, MA in March 2022, U.S Geological Survey Field Activity 2022-014-FA
The data in this release map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide updated environmental context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2022-014-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor tTopographic and bathymetric data, structure from motion imagery, and ground control data collected at Head of the Meadow Beach, Truro, MA in March 2022, U.S. Geological Survey Field Activity 2022-015-FA
These data map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA, providing updated regional context for the 2019 CoastCam installation. CoastCam CACO-01 are two video cameras aimed at the beach that view the coast shared by beachgoers, shorebirds, seals, and sharks. These data were collected as part of field activity 2022-015-FA and a collaboration with the National ParGrain-size analysis data of sediment samples from the beach and nearshore environments at the Pea Island National Wildlife Refuge DUNEX site, North Carolina in 2021
These data provide grain-size measurements from sediment samples collected as part of the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study nearshore coastal processes during storm events. USGS participation in DUNEX will contributeDUNEX topographic, bathymetric, and supporting GPS data collected in Pea Island National Wildlife Refuge, North Carolina 2020-2021
The data in this release characterize the beach and nearshore environment in Pea Island National Wildlife Refuge, NC at the USGS DUring Nearshore Event eXperiment (DUNEX) site and Basnight Bridge. Data include GPS surveys, reference points, and ground control points; imagery and structure-from-motion products; bathymetry data, and merged topographic and bathymetric grids. To cite a specific dataAerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods.Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods.Topographic and bathymetric data, structure from motion imagery, and ground control data collected at Head of the Meadow, Truro in February 2021, U.S Geological Survey Field Activity 2021-014-FA
These data map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA, providing updated regional context for the 2019 CoastCam installation. CoastCam CACO-01 are two video cameras aimed at the beach that view the coast shared by beachgoers, shorebirds, seals, and sharks. These data were collected as part of field activity 2021-014-FA and aStructure from motion products associated with UAS flights in Sandwich, Massachusetts between January 2016 - September 2017
Low-altitude (80-100 meters above ground level) Unmanned Aircraft Systems (UAS) imagery of Town Neck Beach in Sandwich, Massachusetts, were used in a structure-from-motion (SfM) photogrammetry workflow to create high-resolution topographic datasets. Imagery was collected at close to low tide on twelve days to observe changes in beach and dune morphology. Ground control points (GCPs), which are temAerial Photogrammetry Data and Products of the North Carolina coast: 2018-10-06 to 2018-10-08, post-Hurricane Florence
This data release presents structure-from-motion products derived from imagery taken along the North Carolina coast in response to storm events and the recovery process. USGS researchers use the aerial photogrammetry data and products to assess future coastal vulnerability, nesting habitats for wildlife, and provide data for hurricane impact models. This research is part of the Remote Sensing CoasTopographic and bathymetric data, sediment samples, and imagery collected at Head of the Meadow Beach, Truro in March 2020, U.S Geological Survey Field Activity 2020-015-FA
The data in this release map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide environmental context for the camera calibration information for the 2019 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2020-015-FA and a collaboration with the National Park Service at C - Multimedia
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