Very high-resolution mapping of emerging biogenic reefs using airborne optical imagery and neural network: the honeycomb worm (Sabellaria alveolata) case study. Issue 17 (2nd September 2018)
- Record Type:
- Journal Article
- Title:
- Very high-resolution mapping of emerging biogenic reefs using airborne optical imagery and neural network: the honeycomb worm (Sabellaria alveolata) case study. Issue 17 (2nd September 2018)
- Main Title:
- Very high-resolution mapping of emerging biogenic reefs using airborne optical imagery and neural network: the honeycomb worm (Sabellaria alveolata) case study
- Authors:
- Collin, Antoine
Dubois, Stanislas
Ramambason, Camille
Etienne, Samuel - Abstract:
- ABSTRACT: Biogenic reefs provide a wide spectrum of ecosystem functions and services, such as biodiversity hotspot, coastal protection, and fishing practices. Honeycomb worm ( Sabellaria alveolata ) reefs, in the Bay of Mont-Saint-Michel (France), constitute the largest intertidal bioconstruction in Europe but undergo anthropogenic pressures (aquaculture-stemmed food/space competition and siltation, fishing-driven trampling). Very high-resolution (VHR) airborne optical data enable cost-efficient biophysical measurements of reef colonies, strongly expected for conservation approaches. A synergy of remotely sensed airborne optical imagery, calibration/validation photoquadrat ground-truth (202/101, respectively), and artificial neural network (ANN) modelling is first used to map S. alveolata relative abundance, over the largest bioconstruction in Europe. The best prediction of S. alveolata abundance was reached with the infrared–red–green (IRRG) spectral combination and ANN model structured with six neurons ( R 2 = 0.72, RMSE = 0.08, and r = 0.85). The six hyperbolic tangent formulas were applied to the three input spectral bands (IRRG) in order to build six hidden neuronal images, resulting in VHR digital S. alveolata abundance model (6547 × 6566 pixels with 0.5 m pixel size). The innovative model revealed undescribed spatial patterns, namely a reef polarization (perpendicular to the shoreline) of S. alveolata abundance: high abundance on forereef and low abundance onABSTRACT: Biogenic reefs provide a wide spectrum of ecosystem functions and services, such as biodiversity hotspot, coastal protection, and fishing practices. Honeycomb worm ( Sabellaria alveolata ) reefs, in the Bay of Mont-Saint-Michel (France), constitute the largest intertidal bioconstruction in Europe but undergo anthropogenic pressures (aquaculture-stemmed food/space competition and siltation, fishing-driven trampling). Very high-resolution (VHR) airborne optical data enable cost-efficient biophysical measurements of reef colonies, strongly expected for conservation approaches. A synergy of remotely sensed airborne optical imagery, calibration/validation photoquadrat ground-truth (202/101, respectively), and artificial neural network (ANN) modelling is first used to map S. alveolata relative abundance, over the largest bioconstruction in Europe. The best prediction of S. alveolata abundance was reached with the infrared–red–green (IRRG) spectral combination and ANN model structured with six neurons ( R 2 = 0.72, RMSE = 0.08, and r = 0.85). The six hyperbolic tangent formulas were applied to the three input spectral bands (IRRG) in order to build six hidden neuronal images, resulting in VHR digital S. alveolata abundance model (6547 × 6566 pixels with 0.5 m pixel size). The innovative model revealed undescribed spatial patterns, namely a reef polarization (perpendicular to the shoreline) of S. alveolata abundance: high abundance on forereef and low abundance on backreef. … (more)
- Is Part Of:
- International journal of remote sensing. Volume 39:Issue 17(2018)
- Journal:
- International journal of remote sensing
- Issue:
- Volume 39:Issue 17(2018)
- Issue Display:
- Volume 39, Issue 17 (2018)
- Year:
- 2018
- Volume:
- 39
- Issue:
- 17
- Issue Sort Value:
- 2018-0039-0017-0000
- Page Start:
- 5660
- Page End:
- 5675
- Publication Date:
- 2018-09-02
- Subjects:
- Remote sensing -- Periodicals
Télédétection -- Périodiques
621.3678 - Journal URLs:
- http://www.tandfonline.com/toc/tres20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/01431161.2018.1484964 ↗
- Languages:
- English
- ISSNs:
- 0143-1161
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.528000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 7265.xml