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
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.
Exploring the USGS Science Data Life Cycle in the Cloud
Executive Summary Traditionally in the USGS, data is processed and analyzed on local researcher computers, then moved to centralized, remote computers for preservation and publishing (ScienceBase, Pubs Warehouse). This approach requires each researcher to have the necessary hardware and software for processing and analysis, and also to bring all external data required for the workflow over the int
Former Lake Mills timelapse
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.
Elwha River Mouth timelapse
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.
Elwha River Mouth virtual flyover and timelapse
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.
Glines Canyon Dam timelapse
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.
Lake Aldwell Delta timelapse
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.
Lake Mills Delta timelapse
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.
Lower Lake Aldwell timelapse
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.
Big Sur coast just north of Kirk Creek
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
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.
Lower Lake Mills from Glines Canyon Dam timelapse
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.
Glines Canyon virtual flythrough
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.
Elwha Dam timelapse
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.
Glines Canyon timelapse
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.
Lidar survey of the Elwha River
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.
Science and Products
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.
Exploring the USGS Science Data Life Cycle in the Cloud
Executive Summary Traditionally in the USGS, data is processed and analyzed on local researcher computers, then moved to centralized, remote computers for preservation and publishing (ScienceBase, Pubs Warehouse). This approach requires each researcher to have the necessary hardware and software for processing and analysis, and also to bring all external data required for the workflow over the int
Former Lake Mills timelapse
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.
Elwha River Mouth timelapse
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.
Elwha River Mouth virtual flyover and timelapse
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.
Glines Canyon Dam timelapse
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.
Lake Aldwell Delta timelapse
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.
Lake Mills Delta timelapse
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.
Lower Lake Aldwell timelapse
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.
Big Sur coast just north of Kirk Creek
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
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.
Lower Lake Mills from Glines Canyon Dam timelapse
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.
Glines Canyon virtual flythrough
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.
Elwha Dam timelapse
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.
Glines Canyon timelapse
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.
Lidar survey of the Elwha River
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.