View in EDS HTML Full Text PDF Full Text

Remote Sensing Reveals Multidecadal Trends in Coral Cover at Heron Reef, Australia.

Saved in:
Bibliographic Details
Title: Remote Sensing Reveals Multidecadal Trends in Coral Cover at Heron Reef, Australia.
Authors: Carrasco Rivera, David E.1 (AUTHOR) d.carrascorivera@uq.edu.au, Diederiks, Faye F.1,2 (AUTHOR), Hammerman, Nicholas M.1,3 (AUTHOR), Staples, Timothy1,2 (AUTHOR), Kovacs, Eva1,2 (AUTHOR), Markey, Kathryn3 (AUTHOR), Roelfsema, Chris M.1 (AUTHOR)
Source: Remote Sensing. Apr2025, Vol. 17 Issue 7, p1286. 24p.
Subjects: Ecological mapping, Remote-sensing images, Remote sensing, Corals, Random forest algorithms, Coral reefs & islands
Abstract: Coral reefs are experiencing increasing disturbance regimes. The influence these disturbances have on coral reef health is traditionally captured through field-based monitoring, representing a very small reef area (<1%). Satellite-based observations offer the ability to up-scale the spatial extent of monitoring efforts to larger reef areas, providing valuable insights into benthic trajectories through time. Our aim was to demonstrate a repeatable benthic habitat mapping approach integrating field and satellite data acquired annually over 21 years. With this dataset, we analyzed the trends in benthic composition for a shallow platform reef: Heron Reef, Australia. Annual benthic habitat maps were created for the period of 2002 to 2023, using a random forest classifier and object-based contextual editing, with annual in situ benthic data derived from geolocated photoquadrats and coincident high-spatial-resolution (2–5 m pixel size) multi-spectral satellite imagery. Field data that were not used for calibration were used to conduct accuracy assessments. The results demonstrated the capability of remote sensing to map the time series of benthic habitats with overall accuracies between 59 and 81%. We identified various ecological trajectories for the benthic types, such as decline and recovery, over time and space. These trajectories were derived from satellite data and compared with those from the field data. Remote sensing offered valuable insights at both reef and within-reef scales (i.e., geomorphic zones), complementing percentage cover data with precise surface area metrics. We demonstrated that monitoring benthic trajectories at the reef scale every 2 to 3 years effectively captured ecological trends, which is crucial for balancing resource allocation. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 184440764
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Remote Sensing Reveals Multidecadal Trends in Coral Cover at Heron Reef, Australia.
– Name: Author
  Label: Authors
  Group: Au
  Data: &lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Carrasco+Rivera%2C+David+E%2E%22&quot;&gt;Carrasco Rivera, David E.&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;i&gt; d.carrascorivera@uq.edu.au&lt;/i&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Diederiks%2C+Faye+F%2E%22&quot;&gt;Diederiks, Faye F.&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Hammerman%2C+Nicholas+M%2E%22&quot;&gt;Hammerman, Nicholas M.&lt;/searchLink&gt;&lt;relatesTo&gt;1,3&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Staples%2C+Timothy%22&quot;&gt;Staples, Timothy&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Kovacs%2C+Eva%22&quot;&gt;Kovacs, Eva&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Markey%2C+Kathryn%22&quot;&gt;Markey, Kathryn&lt;/searchLink&gt;&lt;relatesTo&gt;3&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Roelfsema%2C+Chris+M%2E%22&quot;&gt;Roelfsema, Chris M.&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22Remote+Sensing%22&quot;&gt;Remote Sensing&lt;/searchLink&gt;. Apr2025, Vol. 17 Issue 7, p1286. 24p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: &lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Ecological+mapping%22&quot;&gt;Ecological mapping&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Remote-sensing+images%22&quot;&gt;Remote-sensing images&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Remote+sensing%22&quot;&gt;Remote sensing&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Corals%22&quot;&gt;Corals&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Random+forest+algorithms%22&quot;&gt;Random forest algorithms&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Coral+reefs+%26+islands%22&quot;&gt;Coral reefs &amp; islands&lt;/searchLink&gt;
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Coral reefs are experiencing increasing disturbance regimes. The influence these disturbances have on coral reef health is traditionally captured through field-based monitoring, representing a very small reef area (&lt;1%). Satellite-based observations offer the ability to up-scale the spatial extent of monitoring efforts to larger reef areas, providing valuable insights into benthic trajectories through time. Our aim was to demonstrate a repeatable benthic habitat mapping approach integrating field and satellite data acquired annually over 21 years. With this dataset, we analyzed the trends in benthic composition for a shallow platform reef: Heron Reef, Australia. Annual benthic habitat maps were created for the period of 2002 to 2023, using a random forest classifier and object-based contextual editing, with annual in situ benthic data derived from geolocated photoquadrats and coincident high-spatial-resolution (2–5 m pixel size) multi-spectral satellite imagery. Field data that were not used for calibration were used to conduct accuracy assessments. The results demonstrated the capability of remote sensing to map the time series of benthic habitats with overall accuracies between 59 and 81%. We identified various ecological trajectories for the benthic types, such as decline and recovery, over time and space. These trajectories were derived from satellite data and compared with those from the field data. Remote sensing offered valuable insights at both reef and within-reef scales (i.e., geomorphic zones), complementing percentage cover data with precise surface area metrics. We demonstrated that monitoring benthic trajectories at the reef scale every 2 to 3 years effectively captured ecological trends, which is crucial for balancing resource allocation. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: &lt;i&gt;Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=184440764
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/rs17071286
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 24
        StartPage: 1286
    Subjects:
      – SubjectFull: Ecological mapping
        Type: general
      – SubjectFull: Remote-sensing images
        Type: general
      – SubjectFull: Remote sensing
        Type: general
      – SubjectFull: Corals
        Type: general
      – SubjectFull: Random forest algorithms
        Type: general
      – SubjectFull: Coral reefs & islands
        Type: general
    Titles:
      – TitleFull: Remote Sensing Reveals Multidecadal Trends in Coral Cover at Heron Reef, Australia.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Carrasco Rivera, David E.
      – PersonEntity:
          Name:
            NameFull: Diederiks, Faye F.
      – PersonEntity:
          Name:
            NameFull: Hammerman, Nicholas M.
      – PersonEntity:
          Name:
            NameFull: Staples, Timothy
      – PersonEntity:
          Name:
            NameFull: Kovacs, Eva
      – PersonEntity:
          Name:
            NameFull: Markey, Kathryn
      – PersonEntity:
          Name:
            NameFull: Roelfsema, Chris M.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 04
              Text: Apr2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 20724292
          Numbering:
            – Type: volume
              Value: 17
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: Remote Sensing
              Type: main
ResultId 1