Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Andy Ritchie
Geologist with the USGS Pacific Coastal and Marine Science Center
Science and Products
Remote Sensing Coastal Change
Exploring the USGS Science Data Life Cycle in the Cloud
Suspended-sediment concentration and grain size in the San Lorenzo River, coastal California
Seismic sub-bottom, sediment core and radiocarbon data collected in Ozette Lake, Washington from 2019-2021
Bathymetry and acoustic-backscatter data for Ozette Lake, Washington collected during USGS field activity 2019-622-FA
Chirp sub-bottom data collected in Lake Crescent, Washington during USGS field activity 2019-622-FA
Vegetation and geomorphic surfaces in the Elwha River delta, Washington, after dam removal, derived from 2016 and 2018 aerial imagery and 2007, 2014, and 2018 field surveys
Aerial photogrammetry data and products of the North Carolina coast
Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09
Aerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09
Observations of tsunami and runup heights in Santa Cruz Harbor and surrounding beaches from the 2022 Hunga Tonga-Hunga Ha'apai tsunami
Aerial Imagery of the North Carolina Coast: 2019-11-26
Aerial Imagery of the North Carolina Coast: 2019-10-11
Aerial Imagery of the North Carolina Coast: 2019-09-08 to 2019-09-13, Post-Hurricane Dorian
Colored shaded relief bathymetry and acoustic backscatter of Ozette Lake, Washington
California State Waters Map Series: Offshore of Coal Oil Point, California
California State Waters Map Series: offshore of Santa Barbara, California
California State Waters Map Series: Offshore of Carpinteria, California
California State Waters Map Series — Offshore of Ventura, California
California State Waters Map Series: Offshore of Santa Barbara, California
California State Waters Map Series — Hueneme Canyon and vicinity, California
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
This PlaneCam video was produced by developing animation tracklines in ArcGlobe, using imagery from PlaneCam flights.
This PlaneCam video was produced by developing animation tracklines in ArcGlobe, using imagery from PlaneCam flights.
This PlaneCam video was produced by developing animation tracklines in ArcGlobe, using imagery from PlaneCam flights.
This PlaneCam video was produced by developing animation tracklines in ArcGlobe, using imagery from PlaneCam flights.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
A two-day rainstorm from January 26-28, 2021 caused numerous mudslides, debris flows, and other issues along California's coastal Highway 1 through Big Sur. This section is just north of Kirk Creek, at a drainage where mud was washed across the roadway. Plumes of the muddy runoff are clearly visible in the ocean.
A two-day rainstorm from January 26-28, 2021 caused numerous mudslides, debris flows, and other issues along California's coastal Highway 1 through Big Sur. This section is just north of Kirk Creek, at a drainage where mud was washed across the roadway. Plumes of the muddy runoff are clearly visible in the ocean.
Flooding on a road in Olympic National Park, Washington, on November 24, 2017.
Flooding on a road in Olympic National Park, Washington, on November 24, 2017.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
These PlaneCam videos were produced by developing animation tracklines in ArcGlobe, using imagery and digital elevation models (DEMs) from PlaneCam flights.
These PlaneCam videos were produced by developing animation tracklines in ArcGlobe, using imagery and digital elevation models (DEMs) from PlaneCam flights.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
USGS scientists Amy Draut (left) and Josh Logan set up a ground-based lidar (light detection and ranging) scanner to measure the topography of the lower Elwha River flood plain.
USGS scientists Amy Draut (left) and Josh Logan set up a ground-based lidar (light detection and ranging) scanner to measure the topography of the lower Elwha River flood plain.
Correction to A regime shift in sediment export from a coastal watershed during a record wet winter, California: Implications for landscape response to hydroclimatic extremes
Post-glacial stratigraphy and late Holocene record of great Cascadia earthquakes in Ozette Lake, Washington, USA
Remote sensing large-wood storage downstream of reservoirs during and after dam removal: Elwha River, Washington, USA
Accurate maps of reef-scale bathymetry with synchronized underwater cameras and GNSS
A large sediment accretion wave along a northern California littoral cell
The future of coastal monitoring through satellite remote sensing
Diverse tsunamigenesis triggered by the Hunga Tonga-Hunga Ha’apai eruption
Crowd-sourced SfM: Best practices for high resolution monitoring of coastal cliffs and bluffs
Human-in-the-Loop segmentation of earth surface imagery
Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6—Structure from motion workflow documentation
A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons
Accurate bathymetric maps from underwater digital imagery without ground control
Agisoft Metashape/Photoscan Automated Image Alignment and Error Reduction version 2.0
Science and Products
Remote Sensing Coastal Change
Exploring the USGS Science Data Life Cycle in the Cloud
Suspended-sediment concentration and grain size in the San Lorenzo River, coastal California
Seismic sub-bottom, sediment core and radiocarbon data collected in Ozette Lake, Washington from 2019-2021
Bathymetry and acoustic-backscatter data for Ozette Lake, Washington collected during USGS field activity 2019-622-FA
Chirp sub-bottom data collected in Lake Crescent, Washington during USGS field activity 2019-622-FA
Vegetation and geomorphic surfaces in the Elwha River delta, Washington, after dam removal, derived from 2016 and 2018 aerial imagery and 2007, 2014, and 2018 field surveys
Aerial photogrammetry data and products of the North Carolina coast
Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09
Aerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09
Observations of tsunami and runup heights in Santa Cruz Harbor and surrounding beaches from the 2022 Hunga Tonga-Hunga Ha'apai tsunami
Aerial Imagery of the North Carolina Coast: 2019-11-26
Aerial Imagery of the North Carolina Coast: 2019-10-11
Aerial Imagery of the North Carolina Coast: 2019-09-08 to 2019-09-13, Post-Hurricane Dorian
Colored shaded relief bathymetry and acoustic backscatter of Ozette Lake, Washington
California State Waters Map Series: Offshore of Coal Oil Point, California
California State Waters Map Series: offshore of Santa Barbara, California
California State Waters Map Series: Offshore of Carpinteria, California
California State Waters Map Series — Offshore of Ventura, California
California State Waters Map Series: Offshore of Santa Barbara, California
California State Waters Map Series — Hueneme Canyon and vicinity, California
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
This PlaneCam video was produced by developing animation tracklines in ArcGlobe, using imagery from PlaneCam flights.
This PlaneCam video was produced by developing animation tracklines in ArcGlobe, using imagery from PlaneCam flights.
This PlaneCam video was produced by developing animation tracklines in ArcGlobe, using imagery from PlaneCam flights.
This PlaneCam video was produced by developing animation tracklines in ArcGlobe, using imagery from PlaneCam flights.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
A two-day rainstorm from January 26-28, 2021 caused numerous mudslides, debris flows, and other issues along California's coastal Highway 1 through Big Sur. This section is just north of Kirk Creek, at a drainage where mud was washed across the roadway. Plumes of the muddy runoff are clearly visible in the ocean.
A two-day rainstorm from January 26-28, 2021 caused numerous mudslides, debris flows, and other issues along California's coastal Highway 1 through Big Sur. This section is just north of Kirk Creek, at a drainage where mud was washed across the roadway. Plumes of the muddy runoff are clearly visible in the ocean.
Flooding on a road in Olympic National Park, Washington, on November 24, 2017.
Flooding on a road in Olympic National Park, Washington, on November 24, 2017.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
These PlaneCam videos were produced by developing animation tracklines in ArcGlobe, using imagery and digital elevation models (DEMs) from PlaneCam flights.
These PlaneCam videos were produced by developing animation tracklines in ArcGlobe, using imagery and digital elevation models (DEMs) from PlaneCam flights.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
Timelapsed photo data is sequenced at about 1 pixel-averaged frame per day, meaning that all of the images from a given day are combined, and the RGB values for a given x/y location on the image are the average of every RGB value for that location for that day.
USGS scientists Amy Draut (left) and Josh Logan set up a ground-based lidar (light detection and ranging) scanner to measure the topography of the lower Elwha River flood plain.
USGS scientists Amy Draut (left) and Josh Logan set up a ground-based lidar (light detection and ranging) scanner to measure the topography of the lower Elwha River flood plain.