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This dataset derived from mosaicked RGB imagery, targeting only exposed kelp in priority sites along the California coastline in Sonoma and Mendocino Counties. The imagery was acquired using DJI Phantom, Matrice, and Mavic series UAVs with the standard RGB sensor; sensor resolution ranged from 12.4 - 20.8 megapixels. The ground sampling distance ranged from 2.5-3.8 cm. Pilots aimed for 75-80% front/side overlap at 400ft (120m) altitude. Flights were coordinated to coincide with annual, peak biomass of Nereocystis luetkeana and the lowest tide of the month as tidal height and surface currents have been shown to impact the amount of kelp canopy exposed on the water surface (2), and these impacts can vary regionally (3). Imagery was mosaicked using a standard mapping software (i.e. DroneDeploy, Pix4D, and PhotoScan)
Kelp pixels were identified in each UAV image using a band combination between the red and blue bands (Red - Blue), as Red - Blue has been shown to best distinguish kelp from water in RGB-UAV imagery relative to other RGB vegetation indices (3). Before applying a threshold to an image, all terrestrial objects (land, intertidal rocks) were manually masked. Due to radiometric and spectral variability present in the imagery, thresholds to distinguish kelp from water were selected manually by expert classifiers. For images with high levels of spectral variability due to turbidity, sun glint, or other artifacts, a single threshold could not be used for kelp identification, as the threshold varied throughout the image. These images were gridded into subsets (ranging from 1000 x 1000 m areas to 5000 x 5000 m areas, depending on the level of variability), and each grid was assigned a unique threshold. The classified grids were mosaicked back to their original extent. All final classification mosaics were manually edited to increase accuracy. Classifications values were binary (“Kelp” or “No Kelp”) with the exception of mixed-species marine algal beds and the occasional blurred image, which were assigned “No Data” values.
The classification process yields three levels: kelp, no kelp, and no data (when applicable), where “no data” denotes areas where it was not possible to confirm the presence/absence of kelp.
The imagery for this site was collected on September 20th, 2021 between 4:33 pm - 5:40 pm PT.
DISCLAIMER: (1)Timing of the survey is important, particularly with respect to growing season, conditions in the ocean (e.g. tides and currents), storms, and harvest levels preceding the dates of imagery collection. Seasonal variability may account for differences in surveys which may not reflect a change in the bed's extent, productivity, or harvest level. (2) Statistical significance in change of area should be evaluated. (3) Survey sensors across time and space may not be consistent. (4) Because wind and weather conditions varied significantly throughout the data collection process, surveys were not restricted to a specific tidal height or current speed – and data were collected when field conditions allowed for stable UAV launch and landing. While this limitation may introduce bias into area estimates, these data still inform the location of kelp refugia on fine spatial scales.
(2)Britton-Simmons, K., Eckman, J. E. & Duggins, D. O. Effect of tidal currents and tidal stage on estimates of bed size in the kelp Nereocystis luetkeana. Marine Ecology Progress Series vol. 355 95–105 (2008)
(3)Cavanaugh, K. C., Cavanaugh, K. C., Bell, T. W., & Hockridge, E. G. (2021). An Automated Method for Mapping Giant Kelp Canopy Dynamics from UAV. Front. Environ. Sci, 8, 587354.
This dataset derived from mosaicked RGB imagery, targeting only exposed kelp in priority sites along the California coastline in Sonoma and Mendocino Counties. The imagery was acquired using DJI Phantom, Matrice, and Mavic series UAVs with the standard RGB sensor; sensor resolution ranged from 12.4 - 20.8 megapixels. The ground sampling distance ranged from 2.5-3.8 cm. Pilots aimed for 75-80% front/side overlap at 400ft (120m) altitude. Flights were coordinated to coincide with annual, peak biomass of Nereocystis luetkeana and the lowest tide of the month as tidal height and surface currents have been shown to impact the amount of kelp canopy exposed on the water surface (2), and these impacts can vary regionally (3). Imagery was mosaicked using a standard mapping software (i.e. DroneDeploy, Pix4D, and PhotoScan)
Kelp pixels were identified in each UAV image using a band combination between the red and blue bands (Red - Blue), as Red - Blue has been shown to best distinguish kelp from water in RGB-UAV imagery relative to other RGB vegetation indices (3). Before applying a threshold to an image, all terrestrial objects (land, intertidal rocks) were manually masked. Due to radiometric and spectral variability present in the imagery, thresholds to distinguish kelp from water were selected manually by expert classifiers. For images with high levels of spectral variability due to turbidity, sun glint, or other artifacts, a single threshold could not be used for kelp identification, as the threshold varied throughout the image. These images were gridded into subsets (ranging from 1000 x 1000 m areas to 5000 x 5000 m areas, depending on the level of variability), and each grid was assigned a unique threshold. The classified grids were mosaicked back to their original extent. All final classification mosaics were manually edited to increase accuracy. Classifications values were binary (“Kelp” or “No Kelp”) with the exception of mixed-species marine algal beds and the occasional blurred image, which were assigned “No Data” values.
The classification process yields three levels: kelp, no kelp, and no data (when applicable), where “no data” denotes areas where it was not possible to confirm the presence/absence of kelp.
The imagery for this site was collected on September 17, 2020 between 5:06- 5:34 pm PT.
DISCLAIMER: (1)Timing of the survey is important, particularly with respect to growing season, conditions in the ocean (e.g. tides and currents), storms, and harvest levels preceding the dates of imagery collection. Seasonal variability may account for differences in surveys which may not reflect a change in the bed's extent, productivity, or harvest level. (2) Statistical significance in change of area should be evaluated. (3) Survey sensors across time and space may not be consistent. (4) Because wind and weather conditions varied significantly throughout the data collection process, surveys were not restricted to a specific tidal height or current speed – and data were collected when field conditions allowed for stable UAV launch and landing. While this limitation may introduce bias into area estimates, these data still inform the location of kelp refugia on fine spatial scales.
(2)Britton-Simmons, K., Eckman, J. E. & Duggins, D. O. Effect of tidal currents and tidal stage on estimates of bed size in the kelp Nereocystis luetkeana. Marine Ecology Progress Series vol. 355 95–105 (2008)
(3)Cavanaugh, K. C., Cavanaugh, K. C., Bell, T. W., & Hockridge, E. G. (2021). An Automated Method for Mapping Giant Kelp Canopy Dynamics from UAV. Front. Environ. Sci, 8, 587354.
Kelp beds along the coast of California are a critical habitat for many species of invertebrates, fish, and marine mammals. Title 14, California Code of Regulations, designates 87 "Administrative Kelp Beds" (hereinafter kelp beds) for the purposes of managing commercial kelp harvest. The 87 kelp beds extend from the U.S.A.-Mexico border to the California-Oregon border and surround each of the Channel Islands. Each kelp bed falls within one of the following management categories: open, closed, leaseable, and lease only. Open kelp beds are available to commercial kelp harvest, leases cannot be issued; Closed kelp beds are closed to all kelp harvesting; Leaseable kelp beds are available for kelp harvesting until the bed is leased, at which time only the lessee may harvest; Lease only kelp beds are closed to all kelp harvesting unless an exclusive lease is obtained. Kelp beds which are leased are desiginated as such.
Updates: The kelp bed boundaries contained in this shapefile were redefined effective April 1, 2014. In addition, the status of leases were updated on Aprl 1, 2020.
Fish and Game Code 6650-6751 and Title 14, California Code of Regulations, Sections 165 and 165.5 contain regulations for the harvest of kelp.
This vector dataset is a thematic map representing mosaicked multi-spectral imagery, targeting both exposed and submerged kelp beds along the California coastline and Channel Islands. The imagery used to create this classification was acquired at a spatial resolution of 0.3 meters using a Microsoft UltraCam Eagle digital camera acquiring in the red, green, blue, and near-infrared bands. The image mosaic product used for the classification is a result of the resampling of the 0.3 meter data to 2 meter resolution. The data are projected in California Teale Albers using North American Datum 1983. Surface kelp canopy and subsurface kelp classifications are separate. The data was collected and processed by Sandoval & Associates, LLC under contract by the California Department of Fish and Wildlife (CDFW). CDFW must be credited with the distribution of these data. The imagery was collected September 3-25, 2016. This dataset is complete at this time, although the user should note any omissions.
DISCLAIMER The user is cautioned against making direct comparisons between the various kelp surveys for the following reasons: (1)Timing of the survey is important, particularly with respect to growing season, conditions in the ocean, storms, and harvest levels preceding the dates of imagery collection. Season variability may account for differences in surveys which may not reflect a change in the bed's extent, productivity, or harvest level. (2) Statisical significance in change of area should be evaluated. To do this, a variance parameter is needed, which is obtained by repeated measurements. (3) Survey methods may not be consistent. Some method of calibration between the methods should be performed in order to insure a change of area is not due to survey instrumentation and not misinterpreted as a biological change. (4) An area where no kelp data are present may represent an area devoid of kelp, or may represent an area where kelp was not detected due to poor photo quality, missing photo coverage, or other issues with data collection and processing. Image coverage is extensive for the state, but the user is advised to consult the supplementary information for each year to determine whether imagery were acquired for an area of interest.
Kelp beds along the coast of California are a critical habitat for many important sport and commercial species of invertebrates and fishes. The California Coastal Kelp Resources Survey is the most recent statewide mapping of kelp, acquired under contract by the California Department of Fish and Game (DFG) from ECOSCAN Resources.
NOTE: File reindexed to match CDFW kelp administrative kelp bed boundaries modified by changes to California Code of Regulations, Title 14, Section 165, effective April 1, 2014
Kelp beds along the coast of California are a critical habitat for many important sport and commercial species of invertebrates and fishes. The California Coastal Kelp Resources Survey is the most recent statewide mapping of kelp, acquired under contract by the California Department of Fish and Game (DFG) from ECOSCAN Resources.
NOTE: File reindexed to match CDFW kelp administrative kelp bed boundaries modified by changes to California Code of Regulations, Title 14, Section 165, effective April 1, 2014
This vector dataset represents the mosaicked multi-spectral imagery, targeting giant kelp beds along the NAVAIR Point Mugu Sea Range.Areas of kelp beds which were cut off due to inadequate overlap in aeral surveys: (a) Santa Rosa Island, outer section of Bed 115 between Sandy Point and Brockway Point (b) San Nicolas Island, outer section of Bed 108 between 119°30'29.647"W 33°16'20.798"N and 119°28'59.181"W 33°15'50.252"N. The user is cautioned to look for areas which appear truncated.
DISCLAIMER:
The user is cautioned against making direct comparisons between the various kelp surveys for the following reasons: 1) Timing of the survey is important, particularly with respect to growing season, ocean conditions, storms, and harvest levels preceding the dates of survey. Seasonal variablity may account for differences in surveys, which may not reflect a change in the bed's extent, productivity, or harvest level. 2) Statistial significance in change of area should be evaluated. To do this, a variance parameter is needed, which is obtained by repeated measurements. 3) Survey methods may not be consistent. Some method of calibration between the methods needs to be performed in order to insure a change of area is not due to survey instrumentation and not misinterpreted as a biological change. 4) An area where no kelp data are present may represent an area devoid of kelp, or may represent an area where kelp was not detected due to poor photo quality, missing photo coverage, or other issues with data collection and processing. Photo coverage is extensive for the state, but the user is advised to consult the abstract and supplementary infromation for each year to determine whether photographs were acquired for an area of interest.
Kelp beds along the coast of California are a critical habitat for many important sport and commercial species of invertebrates and fishes. The California Coastal Kelp Resources Survey is the most recent statewide mapping of kelp, acquired under contract by the California Department of Fish and Game (DFG) from ECOSCAN Resources.
NOTE: File reindexed to match CDFW kelp administrative kelp bed boundaries modified by changes to California Code of Regulations, Title 14, Section 165, effective April 1, 2014