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6 results for “kelp canopy”
SBC LTER: Time series of quarterly NetCDF files of kelp biomass in the canopy from Landsat 5, 7 and 8, since 1984 (ongoing)
This data file represents a time series of canopy area of giant kelp, Macrocystis pyrifera, and bull kelp, Nereocystis luetkeana, and canopy biomass of giant kelp derived from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Landsat 9 Operational Land Imager 2 satellite imagery, along with relevant metadata. The kelp canopy is composed of the portions of fronds and stipes floating on the surface of the water. Canopy area (m) data are given for individual 30 x 30 meter pixels for all coastal areas of Baja California, Mexico, California, Oregon, and the outer coast of Washington (including offshore islands). Biomass data (wet weight, kg) are given for individual 30 x 30 meter pixels in the coastal areas extending from near Ano Nuevo, CA through the southern range limit in Baja California (including offshore islands), representing the range where giant kelp is the dominant canopy forming species. Data were derived from the three Landsat sensors listed above. Observations are made on a 16 day repeat cycle, for each instrument, but the temporal coverage is irregular because of cloud cover, instrument failure, and the mission length of each sensor (TM: 1984 – 2011, ETM+: 1999 – present, OLI: 2013 – present). Estimates of canopy area are derived from the fractional cover of kelp canopy determined from satellite surface reflectance. Estimates of kelp canopy biomass are derived from the relationship between giant kelp fractional cover determined from satellite surface reflectance and empirical measurements of giant kelp canopy biomass in long-term SBC LTER study plots obtained using SCUBA. The different Landsat sensors were calibrated to each other using simulated Landsat data derived from hyperspectral imagery. Missing data due to the ETM+ scan line corrector error were filled using a synchrony-based gap filling method. Data are organized into a single NetCDF file and contain the quarterly area and
SBC LTER: Reef: California kelp canopy and environmental variable dynamics
This dataset contains time series of kelp canopy area for giant kelp, Macrocystis pyrifera, and bull kelp, Nereocystis luetkeana, and canopy biomass of giant kelp derived from Landsat satellite imagery along with time series of environmental variables known to be associated with kelp forest dynamics. Data are organized into a single NetCDF file and kelp canopy data are co-located with the nearest environmental data point.
Kelp canopy chlorophyll to carbon ratio derived from aerial hyperspectral imagery
This dataset represents a time series of giant kelp canopy chlorophyll to carbon ratio (Chl:C) derived from aerial hyperspectral imagery, along with associated environmental, canopy age determinations, and validation datasets. Additional data from a frond cohort experiment are also presented, representing empirical observations of the decline in chlorophyll pigment concentration with blade age. This dataset contains eight geotiff rasters showing canopy Chl:C at a 30-meter pixel resolution for giant kelp forests in the Santa Barbara Channel during the months of April, June, and August from 2013 – 2015.
Using Unoccupied Aerial Vehicles (UAVs) to map and monitor changes in emergent kelp canopy after an ecological regime shift
<p>Kelp forests are complex underwater habitats that form the foundation of many nearshore marine environments and provide valuable services for coastal communities. Despite their ecological and economic importance, increasingly severe stressors have resulted in declines in kelp abundance in many regions over the past few decades, including the North Coast of California, USA. Given the significant and sustained loss of kelp in this region, management intervention is likely a necessary tool to reset the ecosystem and geospatial data on kelp dynamics are needed to strategically implement restoration projects. Because canopy-forming kelp forests are distinguishable in aerial imagery, remote sensing is an important tool for documenting changes in canopy area and abundance to meet these data needs. We used small unoccupied aerial vehicles (UAVs) to survey emergent kelp canopy in priority sites along the North Coast in 2019 and 2020 to fill a key data gap for kelp restoration practitioners working at local scales. With over 4,300 hectares surveyed between 2019 and 2020, these surveys represent the two largest marine resource-focused UAV surveys conducted in California to our knowledge. We present remote sensing methods using UAVs and a repeatable workflow for conducting consistent surveys, creating orthomosaics, georeferencing data, classifying emergent kelp, and creating kelp canopy maps that can be used to assess trends in kelp canopy dynamics over space and time. We illustrate the impacts of spatial resolution on emergent kelp canopy classification between different sensors to help practitioners decide which data stream to select when asking restoration and management questions at varying spatial scales. Our results suggest that high spatial resolution data of emergent kelp canopy from UAVs have the potential to advance strategic kelp restoration and adaptive management.</p>
Using Unoccupied Aerial Vehicles (UAVs) to map and monitor changes in emergent kelp canopy after an ecological regime shift
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SBC LTER: Time series of kelp biomass in the canopy from Landsat 5, 1984 -2011
This data package has been deprecated because the models/methods have been changed. Please see the new data package using updated models: Kelp canopy biomass from Landsat 5, 7, and 8. These data are a time series of canopy biomass of the giant kelp, Macrocystis pyrifera, derived from LANDSAT 5 Thematic Mapper satellite imagery. The kelp canopy is composed of the portions of fronds floating on the surface of the water. Biomass data (wet weight, kg) are given for individual 30 x 30 meter pixels in the coastal areas extending from near Pt. Reyes, California, to Punta Abreojos, Baja California Sur, Mexico, including the Northern and Southern Channel Islands. Data were derived from Landsat 5 TM images. Observations are made on a 16 day reqeat cycle but the temporal coverage is irregular because of cloud cover and instrument failure. Estimates of kelp canopy biomass are derived from the relationship between satellite surface reflectance and empirical measurements of kelp canopy biomass in long-term SBC LTER study plots obtained using SCUBA. Data are organized into yearly files, and zipped to compress. In its entirety this dataset is large, more than 3 GB and 80 million lines. To receive an archive of all data, or for assistance with subsets (e.g., range of dates or a latitude/longitude) contact sbclter@msi.ucsb.edu.
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