• Sen2Coral
    Detection & Monitoring of Coral Bleaching from Space
  • Name: SEOM S2-4Sci Land & Water: Coral Reefs
  • Acronym: Sen2Coral
  • Kick Off: January 2016
  • Duration: 24 months
  • Related Websites: Copernicus | Sentinel | ESA | SEOM Program

Project Objectives

The objective of ESA’s SEOM Programme Sen2Coral is the preparation of the exploitation of the Sentinel-2 mission for coral reefs by developing and validating appropriate, open source algorithm available for the community.

The project objectives are the scientific exploitation and validation of the Sentinel-2 Multispectral Instrument (MSI) for mapping (habitat, bathymetry, and water quality) and detection change for coral reef health assessment and monitoring, and algorithm development dedicated to Sentinel-2 capabilities to satisfying these objectives.

Research Program

  • A critical analysis of feedback from scientists and institutions collected through consultations in ESA and Third Party workshops, symposia and conferences
  • Proposal of potential observation scenarii for Sentinel-2 in terms of required spatial coverage and repeat cycle considering user requirements, existing observation initiatives and synergy with other sensors (Landsat, SPOT sensor families)
  • Identifying scientific priority areas and providing guidance for future scientific data exploitation projects

This builds on the work presented in the paper authored by John Hedley, Chris Roelfsema, Benjamin Koetz and Stuart Phinn (2012), “Capability of the Sentinel 2 mission for tropical coral reef mapping and coral bleaching detection”, Remote Sensing of the Environment, 120, 145-155.

Project Organisation

To address the extremely interesting and challenging questions posed by this project a consortium of contractors with appropriate background knowledge and skills has been assembled. The consortium comprises:

In line with the Copernicus policy, the project has been structured with the purpose of offering to the community of users free-access to reliable and up-to-date Coral health information. It is centred on an Advisory Group, the Science Team, assisted by a Technical Team tasked to provide registered stakeholders with a number of services approved by the Project Management.

sen2coral organisation

Science Advisory Group

The consortium is complimented by a science team of consultants and partners who are recognised international scientists in the field. The members of the team are:

  • Dr. John Hedley (Numerical Optics Limited, UK)
  • Dr. Claudia Giardino (CNR-IREA, Italy)
  • Dr. Vittorio Brando (CNR-IREA, Italy)
  • Dr. Tiit Kutser (University of Tartu, Estonian Marine Institute)
  • Dr. Antoine Collin (EPHE Sorbonne, France)
  • Professor Peter Mumby (University of Queensland, Australia)
  • Professor Stuart Phinn (University of Queensland, Australia)
  • Dr. Chris Roelfsema (University of Queensland, Australia)

Technical Team

The Science Advisory Group is supported by a Technical team tasked with collecting, validating, formatting and distributing the data, software and products elaborated in the course of the project. The Technical Team comprises a number of key engineers, amongst whom the technical tasks have been distributed as follows:

  • Project management: Jean Laporte (ARGANS Ltd)
  • Project conceptual supervision: Dr FR Martin-Lauzer (ARGANS Ltd)
  • Validation and management of satellite imagery: Jan Jackson (ARGANS Ltd):
  • Web site Development: Dr Stephen Emsley (ARGANS Ltd)
  • Image processing: Romain Serra (ARGANS Ltd)
  • Production of charts: Henri Dolou, FIG/IHO/ICA Cat. A (ARGANS Ltd)
  • Software package & ATBD manual: Julien Malik, Philippe Bryere, CS-SI
Fatu Huku, Marquesas
Project Image
Heron, Great Barrier Reef
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Lampi, Myanmar
Project Image
Palau, Western Pacific
Project Image
Kepple Coral Reef


The degradation of coral reefs is a fact, with 55% of reefs being affected by overfishing and destructive fishing methods, which as the most pervasive threats, whereas 25% of reefs are affected by coastal development and pollution from land, including nutrients from farming and sewage, while one tenth suffer from marine-based pollution (local pressures are most severe in South-East Asia, where nearly 95 per cent of coral reefs are threatened).

In addition the coral reefs’ ecosystems appear to be the first to respond to global climate changes, such as increased sea surface temperature (SST), ultraviolet radiation (UV) and acidification of seawater that results from higher levels of atmospheric CO2 concentration.

Sentinel-2 MSI Data Acquisition

The Copernicus Sentinel-2 Multispectral Instrument (MSI) offers several potential technical advantages in the remote sensing of coral reefs due to:

  • 10 meter spatial resolution allowing improvement in visual interpretation of reef features, classification accuracy and bathymetry.
  • Additional water penetrating optical band improving consistency under varying water conditions, reducing uncertainty in bottom type and bathymetric mapping, deeper bathymetric accuracy and ability to determine water optical properties.
  • Additional NIR/SWIR bands enabling more consistent and accurate determination of atmospheric and surface glint correction.
  • Short re-visit time enabling the use of image series to determine fundamental uncertainties for change detection.
  • Addresses the current limited remote sensing acquisition plan covering the coast areas.
Sentinel-2 MSI swath
S2 Process Chain

Algorithm Development & Data Processing

The objective “to develop and validate new algorithms relevant for coral reef monitoring based on Sentinel-2 observations” will be addressed by parameterising existing models for processing hyper-spectral & multi-spectral data and developing pre-processors for these models to build Sentinel-2 data processing algorithms for the retrieval of coral reefs’ static and dynamic characteristics. The code developed will be made available open source.

Validation & uncertainty analysis will involve both comparing Sentinel MSI performance versus Landsat 8 on coral reef mapping objectives and comparing coral reef monitoring products against in situ data from reef sites representative of different composition and structure.

Product Development

To design, verify and validate three coral reef monitoring products making the best use of Sentinel-2 MSI mission characteristics:

  • Habitat mapping of coral reefs
  • Coral reef change detection
  • Bathymetry over coral reefs

Scientific Approach: Review of objectives & methodologies

Coral reef monitoring programs based on in situ field surveys have several caveats that restrict its use and the relevance of its outcomes. These are:

  • cost-related: detailed, continuous monitoring of coral reefs by field survey is expensive and substantial reef areas are located in developing countries with limited resources
  • scale-related: reefs are highly heterogeneous systems therefore even with sufficient resources monitoring programs provide scattered information in time and space, with some areas being more intensively sampled than others and less easily accessible areas are typically under-sampled.

Using satellite remote sensing within a monitoring program potentially addresses both of these issues. Remote sensing should be seen as a complementary technique to in-situ field surveys. The two approaches produce different types of data which together can be used to build a picture of reef ecology across a wide range of spatial and temporal scales.

Reef Spatial Scales

Coral Reef Applications & Methodologies

All published methods appropriate for coral reef applications and methodologies have been reviewed. These include:

  • surface glint removal
  • water column correction
  • depth invariant indices
  • habitat mapping
  • physics based inversion (e.g. SDB)

Radiometric changes and bleaching detection have also been reviewed extensively.

Water Column Correction

The most practical water column correction techniques are those based on band combinations, which in many cases are entirely image-based. Many of these algorithms are quite similar and typically involve the assumption that the attenuation of light with depth is a negative exponential, i.e. over a constant bottom reflectance, \[R_{i} \propto \exp\left({-k_{i}z}\right)\] where \(R_{i}\) is the atmospherically corrected above-water reflectance in band \(i\), \(k_{i}\) is the water attenuation coefficient for that band and \(z\) is the depth. The attenuation \(k_{i}\) depends on constituents of the water and is general unknown, but by combining bands the problem can be reduced to determining relative parameters that can be estimated from the image itself.

Sun Glint Removal

Deglint is a pre-processing algorithm aimed at removing the direct reflection of the sun from the air-water interface or ‘sun glint’.

Landsat 8 before de-glint

Landsat 8 with glint

Landsat 8 after de-glint

Landsat 8 without glint, revealing benthic features

Sentinel 2 before de-glint

Sentinel 2 with glint

Sentinel 2 after de-glint

Sentinel 2 without glint

Habitat Mapping

Habitat classification is the most common objective for coral reef mapping from satellite data. Only standard methods of per-pixel classification will be considered. however due to the submerged nature of the reef special pre-processing techniques for removal of surface glint and the effect of variable depth will be the focus within Sen2Coral.

Habitat Mapping

Benthic habitat classes used for high spatial resolution bottom type classification. Class 8 (reef slope) is used only in the Yucatán site map (shown)

Satellite Derived Bathymetry

Nautical Chart

IHO-compliant nautical chart of Yucatán generated from SDB

Algorithm Implementation

Sen2Coral intends to implement a selection of practical tools based on visual interpretation of time series and pixel based differences. A processing chain comprising ten distinct algorithm modules will be tested and validated to address the Sen2Coral objectives. Access to Implementation details of the selected algorithms available in the Sentinel 2 Toolbox will be granted, including but not limited to:

  • spatial registration
  • surface & cloud masking
  • classification
  • atmospheric correction

Comprehensive information on proprietary applications not yet included in the Toolbox will be provided. These will address:

  • de-glint
  • radiometric normalisation
  • depth invariant indices
  • satellite derived bathymetry
  • physics based model inversion
  • change & bleaching detection
Process Chart

Proposed processing chain modules to be used, either pre-existing or to be implemented in the Sentinel 2 Toolbox

Spatial Registration

Change detection requires that image pairs or sequences are spatially aligned.

Spatial Registration

Land, cloud & white cap mask

For many of the processing steps in the proposed modular system it is advantageous to exclude pixels of land, clouds, cloud shadows and breaking waves (white caps).

Image Masking

Depth Invariant Indices

Calculation of depth invariant indices is a water column correction step that is frequently a useful pre-processing step for benthic classification. Attenuation of the reflectance is approximately inverse exponential with water depth, therefore the transform, \[X_{i} = \ln\left(R_{i}{-R_{i}^{deep}}\right)\]approximately linearises the effect of depth on reflectance. \(R_{i}\) is the pixel reflectance in band \(i\), and \(R_{i}^{deep}\), is the deep water reflectance in that band.

Image Masking

Atmospheric Correction

The potential of the Sentinel-2 for coral reef applications increases with the possibility to have data corrected for the atmospheric effects.

Atmospheric Correction

Change & Bleaching Detection

Image registration and multi-temporal radiometric corrections are perhaps the most important and indispensable steps in change-detection methods. For change detection, we adopt the common approach used within the ‘land’ remote sensing domain.

Change Detection

Physics Based Removal

The main recent development in coral reef remote sensing algorithms is that of physics-based model inversion approaches. These methods work by establishing a forward model for the spectral water-leaving remote sensing reflectance,\(R_{rs}(\lambda)\), based on the depth, optical properties of the water and bottom type. The majority of methods are based on a set of equations derived by Lee et al (1998; 1999) which can be represented by a function, \[R_{rs}(\lambda) \approx f\left({P,G,X,H,R(\lambda),\lambda}\right)\]Where \(P\),\(G\),\(X\) represent the amount of phytoplankton, dissolved organic matter (CDOM) and particulate backscatter, \(H\) is the depth and \(R(\lambda)\) is the bottom type reflectance – which can be taken from a spectral library or linear mixtures thereof..

Test Areas

Fatu Huku Test Area Heron & Lizard Islands GBR, Australia
Lampi Test Area Lampi Island Mergui Archipelago, Myanmar
Heron Test Area Primeiras & Segundas Mozambique
Palau Test Area Lighthouse & Ngederak Reef Palau, West Pacific
Heron Test Area Fatu Huku Marquesas Archipeligo

Validation Approaches

Objective Validation Data Considerations for interpretation Accuracy presentation
Categorical habitat mapping Transect of point data of bottom cover Geolocation accuracy (assessed visually near habitat boundaries) Confusion matrices. Overall accuracy
Bathymetry Echo sounder point data Tide corrections. Plumes or other anomolies (assess visually). Geolocation (see above) Correlation plots of estimated vs. sonar bathymetry
Change and bleaching detection Bleaching incidence data (if available). Visual interpretation Plumes or other anomalies (assess visually) Confusion matrices. Times series plots
Water optical properties Data on known IOP ranges None Tabulated results