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SBC LTER: Time series of quarterly NetCDF files of kelp biomass in the canopy from Landsat 5, 7 and 8, since 1984 (ongoing)

General Information
Data Package:
Local Identifier:knb-lter-sbc.74.17
Title:SBC LTER: Time series of quarterly NetCDF files of kelp biomass in the canopy from Landsat 5, 7 and 8, since 1984 (ongoing)
Alternate Identifier:DOI PLACE HOLDER
Abstract:

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+), and Landsat 8 Operational Land Imager (OLI) 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 (m2) data are given for individual 30 x 30 meter pixels for all coastal areas of Baja California, Mexico, California, and Oregon, 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 biomass means for each Landsat pixel across the three sensors. Relevant metadata such as number of Landsat estimates from which the mean was derived, the number of estimates from each sensor, standard error for each quarterly estimate, spatial coordinates, and date are all included in the file. For assistance with the data, please contact sbclter@msi.ucsb.edu.

Short Name:Kelp canopy area and biomass from Landsat (ongoing dataset)
Publication Date:2022-01-10
Language:English
For more information:
Visit: https://sbclter.msi.ucsb.edu/
Visit: DOI PLACE HOLDER

Time Period
Begin:
1984-03-23
End:
2021-12-31

People and Organizations
Contact:Information Manager, Santa Barbara Coastal LTER [  email ]
Organization:Santa Barbara Coastal LTER
Creator:Bell, Tom W 
Creator:Cavanaugh, Kyle C 
Creator:Siegel, David A 

Data Entities
Other Name:
Satellite kelp biomass since 1984
Description:
Canopy area (m2) of bull kelp (Nereocystis luetkeana) and giant kelp (Macrocystis pyrifera) and wet biomass (kg) of giant kelp from Landsat 5, 7 and 8 imagery, along coastal areas of California, Oregon USA and Baja California and Baja California Sur, Mexico.
Detailed Metadata

Data Entities

Non-Categorized Data Resource

Name:Satellite kelp biomass since 1984
Entity Type:otherEntity
Description:Canopy area (m2) of bull kelp (Nereocystis luetkeana) and giant kelp (Macrocystis pyrifera) and wet biomass (kg) of giant kelp from Landsat 5, 7 and 8 imagery, along coastal areas of California, Oregon USA and Baja California and Baja California Sur, Mexico.
Physical Structure Description:
Object Name:kelpCanopyFromLandsat_2021_v2.nc
Size:136788162 byte
Authentication:669ec71bd14e837b84a178c0838c11f2 Calculated By MD5
Externally Defined Format:
Format Name:NetCDF
Data:https://pasta-s.lternet.edu/package/data/eml/knb-lter-sbc/74/17/c2bea785267fa434c40a22e2239bb337

Data Package Usage Rights

This data package is released under the Creative Commons License Attribution 4.0 International (CC BY 4.0, see https://creativecommons.org/licenses/by/4.0/). This license states that consumers ("Data Users" herein) may distribute, adapt, reuse, remix, and build upon this work, as long as they give appropriate credit, provide a link to the license, and indicate if changes were made. If redistributed, a Data User may not apply additional restrictions or technological measures that prevent access.

The Data User has an ethical obligation to cite the data source appropriately in any publication or product that results from its use, and notify the data contact or creator. Communication, collaboration, or co-authorship (as appropriate) with the creators of this data package is encouraged to prevent duplicate research or publication. The Data User is urged to contact the authors of these data if any questions about methodology or results occur. The Data User should realize that these data may be actively used by others for ongoing research and that coordination may be necessary to prevent duplication or inappropriate use. The Data User should realize that misinterpretation may occur if data are used outside of the context of the original study. The Data User should be aware that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data.

While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. This data package (with its components) is made available “as is” and with no warranty of accuracy or fitness for use. The creators of this data package and the repository where these data were obtained shall not be liable for any damages resulting from misinterpretation, use or misuse of the data package or its components.

Keywords

By Thesaurus:
LTER Core Research Areaspopulations
LTER Controlled Vocabulary v1biomass, canopy, LTER, populations, Santa Barbara Coastal
SBC-LTER Controlled VocabularyKelp Forest, nearshore ocean, populations, remote sensing
Santa Barbara Coastal LTER PlacesAnacapa Island, San Clemente Island, San Miguel Island, San Nicolas Island, Santa Barbara Channel Islands, Santa Barbara County, Santa Barbara Island, Santa Catalina Island, Santa Cruz Island, Santa Rosa Island
Global Change Master Directory (GCMD) v6.0.0.0.0Biomass, Biomass Dynamics
Knowledge Network for BiocomplexityBiomass
NBII BiocomplexityBiomass
nonebiomass, kelp biomass, Landsat 5, Landsat 7, Landsat 8, LTER, remote sensing, satellite, wet weight

Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

Methods and protocols used in the collection of this data package
Description:

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. 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.

Some detailed method can refer to these articles:

Cavanaugh KC, Siegel DA, Reed DC, Dennison PE (2011) Environmental controls of giant-kelp biomass in the Santa Barbara Channel, California. Mar Ecol Prog Ser 429:1-17. https://doi.org/10.3354/meps09141

Bell, T.W., Allen, J.A., Cavanaugh, K.C., Siegel, D.A. (2019) Three decades of variability in California's giant kelp forests from the Landsat satellites. Remote Sensing of Environment. 238, 110811. https://doi.org/10.1016/j.rse.2018.06.039

Hamilton, S., Bell, T.W., Watson, J., Grorud-Colvert, K., Menge, B. (2020) Remote Sensing: Generation of Long-Term Kelp Forest Datasets for Evaluation of Impacts of Climatic Variation. Ecology, 101, e03031. https://doi.org/10.1002/ecy.3031

Protocol:
Author: Bell
Title: Giant Kelp and Bull Kelp Canopy Dynamics from the Landsat Satellite Sensors (TM, ETM+, OLI), Santa Barbara Coastal LTER 2020
Url:https://sbclter.msi.ucsb.edu/external/Reef/Protocols/kelp_biomass_landsat/SBC_LTER_Landsat_Protocol_2021.pdf

People and Organizations

Publishers:
Organization:Environmental Data Initiative
Email Address:
info@environmentaldatainitiative.org
Web Address:
https://environmentaldatainitiative.org
Id:https://ror.org/0330j0z60
Creators:
Organization:Santa Barbara Coastal LTER
Address:
Marine Science Institute University of California,
Santa Barbara, CA 93106 USA
Email Address:
sbclter@msi.ucsb.edu
Individual: Tom W Bell
Address:
Woods Hole Oceanographic Institution 266 Woods Hole Road,
Woods Hole, MA 02543 US
Email Address:
tbell@whoi.edu
Id:https://orcid.org/0000-0002-0173-2866
Individual: Kyle C Cavanaugh
Address:
Department of Geography University of California,
Los Angeles, CA 90095 US
Email Address:
kcavanaugh@geog.ucla.edu
Id:https://orcid.org/0000-0002-3313-0878
Individual: David A Siegel
Address:
Earth Research Institute University of California,
Santa Barbara, CA 93106-3060 US
Phone:
805-893-4547
Email Address:
davesiegel@ucsb.edu
Id:https://orcid.org/0000-0003-1674-3055
Contacts:
Position:Information Manager, Santa Barbara Coastal LTER
Address:
Marine Science Institute,
University of California,
Santa Barbara, California 93106-6150 United States
Phone:
805 893 2071 (voice)
Email Address:
sbclter@msi.ucsb.edu
Web Address:
https://sbclter.msi.ucsb.edu/

Temporal, Geographic and Taxonomic Coverage

Temporal, Geographic and/or Taxonomic information that applies to all data in this dataset:

Time Period
Begin:
1984-03-23
End:
2021-12-31
Geographic Region:
Description:West Coast: Coastal areas along California, and Oregon in the United States and Baja California and Baja California Sur in Mexico. Coastal areas of offshore islands within this range.
Bounding Coordinates:
Northern:  45.9353Southern:  26.702
Western:  -124.790Eastern:  -113.540

Project

Parent Project Information:

Title:Santa Barbara Coastal Long Term Ecological Research Project
Personnel:
Individual:Dr. Robert Miller
Address:
Marine Science Institute,
University of California,
Santa Barbara, California 93106-6150 United States
Phone:
805 893 6174 (voice)
Email Address:
miller@msi.ucsb.edu
Role:Principal Investigator
Individual:Dr. Dan Reed
Address:
Marine Science Institute,
University of California,
Santa Barbara, California 93106-6150 United States
Phone:
805 893 8363 (voice)
Email Address:
dan.reed@lifesci.ucsb.edu
Role:Co-principal Investigator
Individual:Dr. Adrian Stier
Address:
Department of Ecology, Evolution and Marine Biology,
University of California,
Santa Barbara, California 93106-9260 United States
Phone:
805 893 5467 (voice)
Email Address:
adrian.stier@lifesci.ucsb.edu
Role:Co-principal Investigator
Individual:Dr. Gretchen Hoffman
Address:
Department of Ecology, Evolution and Marine Biology,
University of California,
Santa Barbara, California 93106-9620 United States
Phone:
805 893 6175 (voice)
Email Address:
hofmann@lifesci.ucsb.edu
Role:Co-principal Investigator
Individual:Dr. David Siegel
Address:
Institute for Computational Earth System Science,
University of California,
Santa Barbara, California 93106-3060 United States
Phone:
805 893 4547 (voice)
Email Address:
davey@icess.ucsb.edu
Role:Co-principal Investigator
Abstract:

The Santa Barbara Coastal LTER (SBC LTER) is an interdisciplinary research and education program established in April 2000 with the goal of developing a predictive understanding of how environmental drivers interact with terrestrial and oceanic processes to alter material flows and influence the ecology of coastal ecosystems. SBC LTER's principal study domain is the semi-arid coast and nearshore waters of the Santa Barbara Channel in southern California, and its diverse and productive marine forests of giant kelp (Macrocystis pyrifera) serve as the focal study ecosystem. Analyses of our long-term data have identified many of the environmental drivers and ecological processes underlying the production and community dynamics of kelp forests. The research proposed to address this question is integrated in a conceptual framework that focuses on the causes and ecological consequences of the dynamics of a relatively short-lived foundation species in a setting of long-term climate change and human use.

Funding:

NSF Award OCE-9982105, OCE-0620276, OCE-1232779, OCE-1831937

Other Metadata

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