This is a set of 2135 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the letters "cam", and where {YYYYMMDDHHMMSS_ss} is the image acquisition time in {YearMonthDayHourMinuteSecond_hundredths} expressed in 24-hour time, as recorded by the camera's internal clock and written to the SubSecondDateTime field in the image EXIF data (for example CAM001_202009182311_50 would be the timestamp for an image with a SubSecondDateTime EXIF time/date stamp of September 18th, 2020 at 11:11.50 pm.

Natural color representation of NAIP 2022 60cm resolution aerial imagery. Band1=R, Band2=G, Band3=B.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

This digital ortho-imagery dataset is a survey of coastal California. The project area consists of approximately 3774 square miles. The project design of the digital ortho-imagery data acquisition was developed to achieve a 30 cm pixel resolution. Fugro EarthData, Inc. acquired 289 flight lines in 36 lifts from August 26, 2010 through November 29, 2010. Digital ortho-imagery data collection was performed with Conquest and King Air aircrafts, utilizing a Leica ADS40-SH52 sensor. During the time of image acquisition at least two dual frequency GPS receivers are utilized. One receiver, acting as the remote, was operated on board the aircraft with the antenna located over the camera. For differential GPS processing, a second receiver was used on land as the base station. These receivers were in constant operation during the imagery collection and GPS phase data was collected at an epoch rate of at least 1 second. After processing the differential GPS solution by using the remote and master station a final estimated trajectory is generated. The smoothed best estimate trajectory, or sbet, is then in combination with ground surveyed points to strengthen the geospatial accuracy of the imagery. The digital ortho-imagery was cut to tiles measuring 1500 meters by 1500 meters. Original contact information: Contact Org: NOAA Office for Coastal Management Phone: 843-740-1202 Email: coastal.info@noaa.gov

A Normalized Difference Vegetation Index (NDVI) was applied to the source NAIP 2022 60cm imagery. NDVI=(NearIR-Red)/(NearIR+Red). The color ramp (produced by ESRI) goes from brown (less healthy vegetation) to red to green (healthier vegetation or more "greenness").This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

This service delivers all 4 bands of the NAIP 2022 60cm aerial imagery and may be slower than other related NAIP 2022 services because of the amount and/or format of data being served. Band1=R, Band2=G, Band3=B, Band4=NearIR.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

Color infrared (CIR) representation of NAIP 2018 60-cm resolution aerial imagery. Band1=NearIR, Band2=R, Band3=G.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

Oblique and nadir imagery was acquired to assess shoreline impacts and landslide threats of various areas in California. The aerial photography missions were conducted by the NOAA Remote Sensing Division. The images were acquired using a Digital Sensor System (DSS) version 6.

This is a set of 2876 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the letters "cam", and where {YYYYMMDDHHMMSS_ss} is the image acquisition time in {YearMonthDayHourMinuteSecond_hundredths} expressed in 24-hour time, as recorded by the camera's internal clock and written to the SubSecondDateTime field in the image EXIF data (for example CAM001_202009182311_50 would be the timestamp for an image with a SubSecondDateTime EXIF time/date stamp of September 18th, 2020 at 11:11.50 pm.

This service delivers all 4 bands of the NAIP 2016 60cm aerial imagery and may be slower than other related NAIP 2016 services because of the amount and/or format of data being served. Band1=R, Band2=G, Band3=B, Band4=NearIR.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

This service delivers all 4 bands of the NAIP 2009 aerial imagery. This service may be slower than other related NAIP 2009 services because of the amount and/or format of data being served. Band1=R, Band2=G, Band3=B, Band4=NearIR.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

This service delivers all 4 bands of the NAIP 2010 aerial imagery. This service may be slower than other related NAIP 2010 services because of the amount and/or format of data being served. Band1=R, Band2=G, Band3=B, Band4=NearIR.

Aerial imagery was acquired to support response efforts for the California fires. The aerial photography missions were conducted by the NOAA Remote Sensing Division. The images were acquired using a Digital Sensor System (DSS) version 6.

This is a set of 1108 oblique aerial photogrammetric images and their derivatives, collected from Santa Rosa Island with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the letters "cam", and where {YYYYMMDDHHMMSS_ss} is the image acquisition time in {YearMonthDayHourMinuteSecond_hundredths} expressed in 24-hour time, as recorded by the camera's internal clock and written to the SubSecondDateTime field in the image EXIF data (for example CAM001_202009182311_50 would be the timestamp for an image with a SubSecondDateTime EXIF time/date stamp of September 18th, 2020 at 11:11.50 pm.

This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively an...

This dataset is part of the larger data collection, “Aerial imagery object identification dataset for building and road detection, and building height estimation”, linked to in the references below and can be accessed here: https://dx.doi.org/10.6084/m9.figshare.c.3290519. For a full description of the data, please see the metadata: https://dx.doi.org/10.6084/m9.figshare.3504413.

Imagery data from the United States Geological Survey (USGS); building and road shapefiles are from OpenStreetMaps (OSM) (these OSM data are made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/); and the Lidar data are from U.S. National Oceanic and Atmospheric Administration (NOAA), the Texas Natural Resources Information System (TNRIS).

This raster dataset was developed for the Sea Grant South Coast MPA Baseline Program as part of the project “Nearshore Substrate Mapping and Change Analysis using Historical and Concurrent Multispectral Imagery” (#R/MPA 30 10-049). The study region is the South Coast Region (SCR). Imagery was acquired on October 05, 2012 at a spatial resolution of 0.3 meters using a Microsoft UltraCam-X digital camera acquiring in the red, green, blue and near-infrared bands. Information on the UltraCam-X camera system and wavelengths for each ban can be found in the file "The Microsoft Vexcel UltraCam X.pdf" included in the Support folder on the image data delivery media and on the OceanSpaces.org server. This image mosaic product is a result of the resampling of the 0.3 meter data to 1 meter GSD. Details on this system and the data processing are below in the Lineage section of this document. Individual UCX image tiles were mosaicked into sections based on the islands covered and local coastal regions as well as the SCR MPA zones in order to generate this multispectral image product. These imagery were subsequently used to generate habitat classification thematic maps of the SCR's intertidal region and kelp beds from Point Conception to Imperial Beach, CA. The imagery files deliverd are in GeoTIFF format. More information on the classes resolved and processing methods are in the Lineage section of this document. This raster dataset contains a habitat classification of either offshore giant kelp beds and/or the intertidal zone along the California South Coast Region (SCR) from from Point Conception, CA down to Imperial beach, CA. This specific raster classification includes the Long Point SMR, Blue Cavern SMCA, and the Arrow Point to Lion Head Point SMCA. This dataset was originally uploaded to Oceanspaces (http://oceanspaces.org/) and the Knowledge Network for Biocomplexity (KNB, https://knb.ecoinformatics.org/data) in 2013 as part of the South Coast baseline monitoring program. In 2022 this dataset was moved to the California Ocean Protection Council Data Repository (https://opc.dataone.org/) by Mike Esgro (Michael.Esgro@resources.ca.gov) and Rani Gaddam (gaddam@ucsc.edu). At that time the GIS analysis products were added to the dataset. The long-term California MPA boundary and project info tables can be found as a separate dataset here: https://opc.dataone.org/view/doi:10.25494/P64S3W.

This service delivers all 4 bands of the NAIP 2018 60-cm resolution aerial imagery and may be slower than other related NAIP 2018 services because of the amount and/or format of data being served. Band1=R, Band2=G, Band3=B, Band4=NearIR.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

Color infrared (CIR) imagery acquired during NAIP 2005 flights. The source CIR 1-meter resolution imagery was purchased from the North West Group (NWG) by three state agencies (California Dept. of Fish and Game, California Dept. of Transportation, and California Dept. of Water Resources). No access constraints, but there are use constraints. CIR coverage was not available in all areas. THIS CIR IMAGERY IS NOT A NAIP PRODUCT. Band1=NearIR, Band2=R, Band3=G.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services