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Use of Remote Sensing in Valuation of Blue Carbon and Its Co-benefits

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 14287

Special Issue Editor

Dr. Gail L. Chmura

E-Mail Website
Guest Editor
Department of Geography, McGill University, Montreal, QC, Canada
Interests: blue carbon and its cobenefits

Special Issue Information

Dear Colleagues,

This issue welcomes submissions that demonstrate how advances in remote sensing can be used to establish the value of salt marshes, mangrove swamps, and seagrass meadows. These ecosystems are now widely recognized as highly efficient sinks for atmospheric carbon dioxide. The carbon they store, termed “blue carbon”, is found in biomass aboveground, but the most significant stocks are held in the soil of salt marshes, mangrove swamps, and seagrass meadows (also termed blue carbon habitats). Remote sensing has clear applications for assessing aboveground stocks of carbon, for instance, through indices that indicate production and vegetation height. To date, assessment of soil stocks or rates of carbon sequestration requires field- and lab-based measurements which must be paired with measurements of wetland area. Wetland boundaries were first mapped through interpretation of aerial photography, and advances in remote sensing are expected to continue to improve our ability to determine the area of blue carbon ecosystems. For this issue, we look for advances in both methods to assess aboveground carbon stocks and extent of blue carbon habitats. In addition to sequestration of atmospheric carbon dioxide, there are many other “ecosystem services”, or “co-benefits”, of salt marshes, mangrove swamps and seagrass meadows. Submissions on advancements in documenting these co-benefits through remote sensing can serve as additional tools for support of conservation of blue carbon habitats and other relevant topics are also welcome.

Dr. Gail L. Chmura
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Salt marsh
  • Mangrove
  • Seagrass
  • Ecosystem services
  • Organic carbon
  • Climate mitigation
  • lidar
  • hyperspectral
  • SAVs
  • multisprectral
  • ENVI
  • photography
  • satellite imagery
  • remote sensing

Published Papers (4 papers)

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Research

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16 pages, 1050 KiB  
Article
Above- and Belowground Biomass Carbon Stock and Net Primary Productivity Maps for Tidal Herbaceous Marshes of the United States
by Victoria L. Woltz, Camille LaFosse Stagg, Kristin B. Byrd, Lisamarie Windham-Myers, Andre S. Rovai and Zhiliang Zhu
Remote Sens. 2023, 15(6), 1697; https://doi.org/10.3390/rs15061697 - 21 Mar 2023
Cited by 4 | Viewed by 2772
Abstract
Accurate assessments of greenhouse gas emissions and carbon sequestration in natural ecosystems are necessary to develop climate mitigation strategies. Regional and national-level assessments of carbon sequestration require high-resolution data to be available for large areas, increasing the need for remote sensing products that [...] Read more.
Accurate assessments of greenhouse gas emissions and carbon sequestration in natural ecosystems are necessary to develop climate mitigation strategies. Regional and national-level assessments of carbon sequestration require high-resolution data to be available for large areas, increasing the need for remote sensing products that quantify carbon stocks and fluxes. The Intergovernmental Panel on Climate Change (IPCC) provides guidelines on how to quantify carbon flux using land cover land change and biomass carbon stock information. Net primary productivity (NPP), carbon uptake, and storage in vegetation, can also be used to model net carbon sequestration and net carbon export from an ecosystem (net ecosystem carbon balance). While biomass and NPP map products for terrestrial ecosystems are available, there are currently no conterminous United States (CONUS) biomass carbon stock or NPP maps for tidal herbaceous marshes. In this study, we used peak soil adjusted vegetation index (SAVI) values, derived from Landsat 8 composites, and five other vegetation indices, plus a categorical variable for the CONUS region (Pacific Northwest, California, Northeast, Mid-Atlantic, South Atlantic-Gulf, or Everglades), to model spatially explicit aboveground peak biomass stocks in tidal marshes (i.e., tidal palustrine and estuarine herbaceous marshes) for the first time. Tidal marsh carbon conversion factors, root-to-shoot ratios, and vegetation turnover rates, were compiled from the literature and used to convert peak aboveground biomass to peak total (above- and belowground) biomass and NPP. An extensive literature search for aboveground turnover rates produced sparse and variable values; therefore, we used an informed assumption of a turnover rate of one crop per year for all CONUS tidal marshes. Due to the lack of turnover rate data, the NPP map is identical to the peak biomass carbon stock map. In reality, it is probable that turnover rate varies by region, given seasonal length differences; however, the NPP map provides the best available information on spatially explicit CONUS tidal marsh NPP. This study identifies gaps in the scientific knowledge, to support future studies in addressing this lack of turnover data. Across CONUS, average total peak biomass carbon stock in tidal marshes was 848 g C m−2 (871 g C m−2 in palustrine and 838 g C m−2 in estuarine marshes), and based on a median biomass turnover rate of 1, it is expected that the mean NPP annual flux for tidal marshes is similar (e.g., 848 g C m−2 y−1). Peak biomass carbon stocks in tidal marshes were lowest in the Florida Everglades region and highest in the California regions. These are the first fine-scale national maps of biomass carbon and NPP for tidal wetlands, spanning all of CONUS. These estimates of CONUS total peak biomass carbon stocks and NPP rates for tidal marshes can support regional- and national-scale assessments of greenhouse gas emissions, as well as natural resource management of coastal wetlands, as part of nature-based climate solution efforts. Full article
(This article belongs to the Special Issue Use of Remote Sensing in Valuation of Blue Carbon and Its Co-benefits)
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17 pages, 45461 KiB  
Article
Characterising the Aboveground Carbon Content of Saltmarsh in Jervis Bay, NSW, Using ArborCam and PlanetScope
by Elizabeth Warwick-Champion, Kevin P. Davies, Paul Barber, Naviin Hardy and Eleanor Bruce
Remote Sens. 2022, 14(8), 1782; https://doi.org/10.3390/rs14081782 - 07 Apr 2022
Cited by 5 | Viewed by 2293
Abstract
Coastal ecosystems, including saltmarsh, provide important ecosystem services, including blue carbon storage, nutrient cycling, and coastal protection. The loss or degradation of saltmarsh ecosystems may undermine their capacity to provide these services and drive carbon emission increases. The accurate mapping and monitoring of [...] Read more.
Coastal ecosystems, including saltmarsh, provide important ecosystem services, including blue carbon storage, nutrient cycling, and coastal protection. The loss or degradation of saltmarsh ecosystems may undermine their capacity to provide these services and drive carbon emission increases. The accurate mapping and monitoring of the aboveground carbon content in these ecosystems supports protection and rehabilitation activities. Previous studies have used medium resolution satellites (e.g., Landsat and Sentinel-2) to characterise saltmarsh communities; however, these platforms are not well suited to the fine-scale patchiness of the saltmarsh ecosystems found in Australia. Here we explore the potential of a very high spatial resolution (0.15 m), seven-band multispectral ArborCam airborne sensor and 3 m images captured by the PlanetScope satellite constellation for mapping and monitoring the aboveground carbon content of a saltmarsh ecosystem in Jervis Bay National Park, Australia. The Normalized Difference Vegetation Index (NDVI) derived from an ArborCam image was calibrated to aboveground carbon content using field survey data. Strong linear relationships between the ArborCam NDVI and aboveground carbon content were found when survey data were partitioned by species. The mean aboveground carbon content derived from the calibrated ArborCam image was 1.32 Mg C ha−1 across the study area; however, this is likely to have been underestimated. A monthly NDVI time series derived from 12 PlanetScope images was analysed to investigate the short-term temporal variation in saltmarsh phenology, and significant intra-annual variation was found. An exploration of potential drivers for the variation found that local rainfall was a potential driver. The combination of the very high spatial resolution airborne ArborCam image and the regular 3 m capture by PlanetScope satellites was found to have potential for accurate mapping and monitoring of aboveground carbon in saltmarsh communities. Future work will focus on improving aboveground carbon estimates by including a very high spatial resolution species distribution map and investigating the influence of temporal variations in saltmarsh spectral response on these estimates. Full article
(This article belongs to the Special Issue Use of Remote Sensing in Valuation of Blue Carbon and Its Co-benefits)
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18 pages, 6620 KiB  
Article
Applying Airborne LiDAR to Map Salt Marsh Inland Boundaries
by Lee B. van Ardenne and Gail L. Chmura
Remote Sens. 2021, 13(21), 4245; https://doi.org/10.3390/rs13214245 - 22 Oct 2021
Viewed by 2035
Abstract
The determination of rates and stocks of carbon storage in salt marshes, as well as their protection, require that we know where they and their boundaries are. Marsh boundaries are conventionally mapped through recognition of plant communities using aerial photography or satellite imagery. [...] Read more.
The determination of rates and stocks of carbon storage in salt marshes, as well as their protection, require that we know where they and their boundaries are. Marsh boundaries are conventionally mapped through recognition of plant communities using aerial photography or satellite imagery. We examined the possibility of substituting the use of 1 m resolution LiDAR-derived digital elevation models (DEMs) and tidal elevations to establish salt marsh upper boundaries on the New Brunswick coasts of the Gulf of St. Lawrence and the Bay of Fundy, testing this method at tidal ranges from ≤2 to ≥4 m. LiDAR-mapped marsh boundaries were verified with high spatial resolution satellite imagery and a subset through field mapping of the upland marsh edge based upon vegetation and soil characteristics, recording the edge location and elevation with a Differential Geographic Positioning System. The results show that the use of high-resolution LiDAR and tidal elevation data can successfully map the upper boundary of salt marshes without the need to first map plant species. The marsh map area resulting from our mapping was ~30% lower than that in the province’s aerial-photograph-based maps. However, the difference was not primarily due to the location of the upper marsh boundaries but more so because of the exclusion of mudflats and large creeks (features that are not valued as carbon sinks) using the LiDAR method that are often mapped as marsh areas in the provincial maps. Despite some minor limitations, the development of DEMs derived from LiDAR can be applied to update and correct existing salt marsh maps along extensive sections of coastlines in less time than required to manually trace from imagery. This is vital information for governments and NGOs seeking to conserve these environments, as accurate mapping of the location and area of these ecosystems is a necessary basis for conservation prioritization indices. Full article
(This article belongs to the Special Issue Use of Remote Sensing in Valuation of Blue Carbon and Its Co-benefits)
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Review

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18 pages, 3751 KiB  
Review
A Blueprint for the Estimation of Seagrass Carbon Stock Using Remote Sensing-Enabled Proxies
by Jamie Simpson, Eleanor Bruce, Kevin P. Davies and Paul Barber
Remote Sens. 2022, 14(15), 3572; https://doi.org/10.3390/rs14153572 - 25 Jul 2022
Cited by 6 | Viewed by 5179
Abstract
Seagrass ecosystems sequester carbon at disproportionately high rates compared to terrestrial ecosystems and represent a powerful potential contributor to climate change mitigation and adaptation projects. However, at a local scale, rich heterogeneity in seagrass ecosystems may lead to variability in carbon sequestration. Differences [...] Read more.
Seagrass ecosystems sequester carbon at disproportionately high rates compared to terrestrial ecosystems and represent a powerful potential contributor to climate change mitigation and adaptation projects. However, at a local scale, rich heterogeneity in seagrass ecosystems may lead to variability in carbon sequestration. Differences in carbon sequestration rates, both within and between seagrass meadows, are related to a wide range of interrelated biophysical and environmental variables that are difficult to measure holistically using traditional field surveys. Improved methods for producing robust, spatially explicit estimates of seagrass carbon storage across large areas would be highly valuable, but must capture complex biophysical heterogeneity and variability to be accurate and useful. Here, we review the current and emerging literature on biophysical processes which shape carbon storage in seagrass beds, alongside studies that map seagrass characteristics using satellite remote sensing data, to create a blueprint for the development of remote sensing-enabled proxies for seagrass carbon stock and sequestration. Applications of satellite remote sensing included measuring seagrass meadow extent, estimating above-ground biomass, mapping species composition, quantifying patchiness and patch connectivity, determining broader landscape environmental contexts, and characterising seagrass life cycles. All of these characteristics may contribute to variability in seagrass carbon storage. As such, remote sensing methods are uniquely placed to enable proxy-based estimates of seagrass carbon stock by capturing their biophysical characteristics, in addition to the spatiotemporal heterogeneity and variability of these characteristics. Though the outlined approach is complex, it is suitable for accurately and efficiently producing a full picture of seagrass carbon stock. This review has drawn links between the processes of seagrass carbon sequestration and the capabilities of remote sensing to detect and characterise these processes. These links will facilitate the development of remote sensing-enabled proxies and support spatially explicit estimates of carbon stock, ensuring climate change mitigation and adaptation projects involving seagrass are accounted for with increased accuracy and reliability. Full article
(This article belongs to the Special Issue Use of Remote Sensing in Valuation of Blue Carbon and Its Co-benefits)
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