A Decade of Optical Remote Sensing Applications in Marine Biodiversity and Benthic Habitat Monitoring: A Systematic Review.

Saved in:
Bibliographic Details
Title: A Decade of Optical Remote Sensing Applications in Marine Biodiversity and Benthic Habitat Monitoring: A Systematic Review.
Authors: Martín-García, Laura1 (AUTHOR), Casas, Enrique2 (AUTHOR), Hernández-Leal, Pedro A.2,3 (AUTHOR), Botelho, Andrea Z.3,4 (AUTHOR), Arbelo, Manuel1,2 (AUTHOR) marbelo@ull.es
Source: Remote Sensing. Jun2026, Vol. 18 Issue 12, p1917. 37p.
Subjects: Optical remote sensing, Marine biodiversity, Drone aircraft, Seagrass restoration, Hyperspectral imaging systems, Multispectral imaging, Coral reefs & islands, Benthic zone
Abstract: Highlights: What are the main findings? Optical remote sensing (ORS) applications for benthic biodiversity are primarily based on multispectral satellite sensors, with an increasing use of unmanned aerial vehicles (UAVs) and hyperspectral approaches. Pre-processing and validation methods remain highly heterogeneous. Studies mainly focus on broad benthic habitat classifications and dominant coastal ecosystems such as coral reefs and seagrasses, in tropical and subtropical regions. What are the implications of the main findings? ORS is a key tool for multi-scale, repeatable monitoring supporting marine conservation and policy frameworks. Improving methodological standardisation, taxonomic coverage, and global research equity is essential for enhancing comparability and operational use. Monitoring biodiversity in coastal and marine ecosystems is essential for supporting conservation strategies, sustaining ecosystem services, and meeting policy commitments at multiple scales, including the European Union's Habitats Directive, Sustainable Development Goal 14 (SDG 14, Life Below Water), and the Kunming–Montreal Global Biodiversity Framework (GBF). However, many benthic habitats remain insufficiently mapped or monitored due to the spatial, temporal, and logistical limitations of traditional field-based approaches. Optical Remote Sensing (ORS), based on the use of optical sensors to retrieve spectral information from shallow-water environments, has emerged as a powerful tool for mapping and monitoring these ecosystems. This study presents a systematic review aimed at providing a comprehensive synthesis of above-water ORS applications for benthic biodiversity and habitat monitoring over the period 2014–2023. A total of 179 peer-reviewed studies were analyzed to identify temporal trends, geographic patterns, target ecosystems, and methodological workflows. The review considered observation platforms including satellite, airborne, unmanned aerial vehicles (UAVs), and field spectrometry systems, together with key preprocessing procedures required for reliable benthic detection, such as atmospheric correction, water column correction, and sunglint removal, alongside validation using independent measurements. The analysis reveals a rapid expansion of ORS applications, with a strong geographic concentration in tropical and subtropical regions. Studies focusing on specific benthic groups predominantly target coral reefs and seagrass ecosystems, although many adopt integrative benthic habitat classifications that incorporate multiple benthic components at the habitat level. However, significant limitations persist, including inconsistent preprocessing workflows, limited reporting transparency, and the underrepresentation of several ecologically important taxa (e.g., annelids, mollusks, echinoderms). Despite these challenges, ORS has become a cornerstone of large-scale and repeatable coastal monitoring. By analyzing methodological practices, ecological targets, and geographic biases, this review provides a critical foundation for improving the robustness, scalability, and global applicability of ORS in benthic habitat mapping, biodiversity monitoring, and ecosystem-based management. [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: 194915050
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A Decade of Optical Remote Sensing Applications in Marine Biodiversity and Benthic Habitat Monitoring: A Systematic Review.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Martín-García%2C+Laura%22">Martín-García, Laura</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Casas%2C+Enrique%22">Casas, Enrique</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hernández-Leal%2C+Pedro+A%2E%22">Hernández-Leal, Pedro A.</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Botelho%2C+Andrea+Z%2E%22">Botelho, Andrea Z.</searchLink><relatesTo>3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Arbelo%2C+Manuel%22">Arbelo, Manuel</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> marbelo@ull.es</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Jun2026, Vol. 18 Issue 12, p1917. 37p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Optical+remote+sensing%22">Optical remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Marine+biodiversity%22">Marine biodiversity</searchLink><br /><searchLink fieldCode="DE" term="%22Drone+aircraft%22">Drone aircraft</searchLink><br /><searchLink fieldCode="DE" term="%22Seagrass+restoration%22">Seagrass restoration</searchLink><br /><searchLink fieldCode="DE" term="%22Hyperspectral+imaging+systems%22">Hyperspectral imaging systems</searchLink><br /><searchLink fieldCode="DE" term="%22Multispectral+imaging%22">Multispectral imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Coral+reefs+%26+islands%22">Coral reefs & islands</searchLink><br /><searchLink fieldCode="DE" term="%22Benthic+zone%22">Benthic zone</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Highlights: What are the main findings? Optical remote sensing (ORS) applications for benthic biodiversity are primarily based on multispectral satellite sensors, with an increasing use of unmanned aerial vehicles (UAVs) and hyperspectral approaches. Pre-processing and validation methods remain highly heterogeneous. Studies mainly focus on broad benthic habitat classifications and dominant coastal ecosystems such as coral reefs and seagrasses, in tropical and subtropical regions. What are the implications of the main findings? ORS is a key tool for multi-scale, repeatable monitoring supporting marine conservation and policy frameworks. Improving methodological standardisation, taxonomic coverage, and global research equity is essential for enhancing comparability and operational use. Monitoring biodiversity in coastal and marine ecosystems is essential for supporting conservation strategies, sustaining ecosystem services, and meeting policy commitments at multiple scales, including the European Union's Habitats Directive, Sustainable Development Goal 14 (SDG 14, Life Below Water), and the Kunming–Montreal Global Biodiversity Framework (GBF). However, many benthic habitats remain insufficiently mapped or monitored due to the spatial, temporal, and logistical limitations of traditional field-based approaches. Optical Remote Sensing (ORS), based on the use of optical sensors to retrieve spectral information from shallow-water environments, has emerged as a powerful tool for mapping and monitoring these ecosystems. This study presents a systematic review aimed at providing a comprehensive synthesis of above-water ORS applications for benthic biodiversity and habitat monitoring over the period 2014–2023. A total of 179 peer-reviewed studies were analyzed to identify temporal trends, geographic patterns, target ecosystems, and methodological workflows. The review considered observation platforms including satellite, airborne, unmanned aerial vehicles (UAVs), and field spectrometry systems, together with key preprocessing procedures required for reliable benthic detection, such as atmospheric correction, water column correction, and sunglint removal, alongside validation using independent measurements. The analysis reveals a rapid expansion of ORS applications, with a strong geographic concentration in tropical and subtropical regions. Studies focusing on specific benthic groups predominantly target coral reefs and seagrass ecosystems, although many adopt integrative benthic habitat classifications that incorporate multiple benthic components at the habitat level. However, significant limitations persist, including inconsistent preprocessing workflows, limited reporting transparency, and the underrepresentation of several ecologically important taxa (e.g., annelids, mollusks, echinoderms). Despite these challenges, ORS has become a cornerstone of large-scale and repeatable coastal monitoring. By analyzing methodological practices, ecological targets, and geographic biases, this review provides a critical foundation for improving the robustness, scalability, and global applicability of ORS in benthic habitat mapping, biodiversity monitoring, and ecosystem-based management. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>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.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=194915050
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/rs18121917
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 37
        StartPage: 1917
    Subjects:
      – SubjectFull: Optical remote sensing
        Type: general
      – SubjectFull: Marine biodiversity
        Type: general
      – SubjectFull: Drone aircraft
        Type: general
      – SubjectFull: Seagrass restoration
        Type: general
      – SubjectFull: Hyperspectral imaging systems
        Type: general
      – SubjectFull: Multispectral imaging
        Type: general
      – SubjectFull: Coral reefs & islands
        Type: general
      – SubjectFull: Benthic zone
        Type: general
    Titles:
      – TitleFull: A Decade of Optical Remote Sensing Applications in Marine Biodiversity and Benthic Habitat Monitoring: A Systematic Review.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Martín-García, Laura
      – PersonEntity:
          Name:
            NameFull: Casas, Enrique
      – PersonEntity:
          Name:
            NameFull: Hernández-Leal, Pedro A.
      – PersonEntity:
          Name:
            NameFull: Botelho, Andrea Z.
      – PersonEntity:
          Name:
            NameFull: Arbelo, Manuel
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 20724292
          Numbering:
            – Type: volume
              Value: 18
            – Type: issue
              Value: 12
          Titles:
            – TitleFull: Remote Sensing
              Type: main
ResultId 1