Adaptive bathymetry estimation for shallow coastal waters using Planet Dove satellites

Li, Jiwei; Knapp, David; Schill, Steven R.; Roelfsema, Christiaan M; Phinn, Stuart; Silman, Miles R.; Mascaro, Joseph; Asner, Gregory P.

doi:10.1016/j.rse.2019.111302

Cited by 108 publications

(71 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…With below-surface reflectance calculated, water bathymetry was predicted using an adaptive bathymetry estimation method with self-tuning parameters (m 0 , m 1 ) as described in Li et al [20]: H = m 0 ln(1000 * r rs blue) ln(1000 * r rs green) − m 1 ,…”

Section: Of 16mentioning

confidence: 99%

Object-Based Mapping of Coral Reef Habitats Using Planet Dove Satellites

Schill

Knapp

et al. 2019

Remote Sensing

Self Cite

View full text Add to dashboard Cite

High spatial resolution benthic habitat information is essential for coral reef protection and coastal environmental management. Satellite-based shallow benthic composition mapping offers a more efficient approach than traditional field measurements, especially given the advancements in high spatial and temporal resolution satellite imagery. The Planet Dove satellite constellation now has more than 150 instruments in orbit that offer daily coverage at high spatial resolution (3.7 m). The Dove constellation provides regularly updated imagery that can minimize cloud in tropical oceans where dense cloud cover persists. Daily image acquisition also provides an opportunity to detect time-sensitive changes in shallow benthic habitats following coral bleaching events, storms, and other disturbances. We developed an object-based coral reef habitat mapping approach for Dove and similar multispectral satellites that provides bathymetry estimation, bottom reflectance retrieval, and object-based classification to identify different benthic compositions in shallow coastal environments. We tested our approach in three study sites in the Dominican Republic using 18 Dove images. Benthic composition classification results were validated by field measurements (overall accuracy = 82%). Bathymetry and bottom reflectance significantly contributed to identifying benthic habitat classes with similar surface reflectance. This new object-based approach can be effectively applied to map and manage coral reef habitats.

show abstract

Section: Of 16mentioning

confidence: 99%

Object-Based Mapping of Coral Reef Habitats Using Planet Dove Satellites

Schill

Knapp

et al. 2019

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…The water is clear; thus, the energy arrives from the bottom through the water column and the water column is homogenous [89]. The relationship between the water-leaving reflectance and the depth is z = m· + n where m and n do not vary with depth (they are constant when the properties of the water column and the bottom are constant, too), but RBlue and RGreen do vary [60,90], since they are the reflectances below the surface with bottom influence and the reflectance below the surface without bottom influence (that is, in deep water), respectively.…”

Section: Satellite Datamentioning

confidence: 99%

“…where m and n do not vary with depth (they are constant when the properties of the water column and the bottom are constant, too), but R Blue and R Green do vary [60,90], since they are the reflectances below the surface with bottom influence and the reflectance below the surface without bottom influence (that is, in deep water), respectively. In this study, 22 Pleiades images-taken between 15 October 2012 and 5 December 2019-were used ( Table 2) ( Figure A1).…”

Section: Satellite Datamentioning

confidence: 99%

See 1 more Smart Citation

Bathymetry Time Series Using High Spatial Resolution Satellite Images

Erena

Domínguez

Atenza

et al. 2020

Water

View full text Add to dashboard Cite

The use of the new generation of remote sensors, such as echo sounders and Global Navigation Satellite System (GNSS) receivers with differential correction installed in a drone, allows the acquisition of high-precision data in areas of shallow water, as in the case of the channel of the Encañizadas in the Mar Menor lagoon. This high precision information is the first step to develop the methodology to monitor the bathymetry of the Mar Menor channels. The use of high spatial resolution satellite images is the solution for monitoring many hydrological changes and it is the basis of the three-dimensional (3D) numerical models used to study transport over time, environmental variability, and water ecosystem complexity.

show abstract

“…These methods are inherently limited to the resolution of the satellite sensor, and are unable to resolve changes in waterline positions occurring at a scale of less than a whole pixel (e.g., 10 m for Sentinel-2 or 30 m for Landsat; [28]). Although high resolution satellite data from commercial providers such as Planet Labs and DigitalGlobe are increasingly available for these applications [29,30], these sources of data are typically prohibitively expensive to implement across regional to global extents, and lack either the temporal depth or systematic revisit frequency that are available for medium resolution satellite programs with coarser pixel resolutions (e.g., Landsat imagery available since 1972, [31]). Accordingly, there is a pressing need for the development of operational methods for extracting waterline information from freely available medium resolution satellite imagery at spatial scales relevant to coastal and environmental management.…”

Section: Introductionmentioning

confidence: 99%

Sub-Pixel Waterline Extraction: Characterising Accuracy and Sensitivity to Indices and Spectra

et al. 2019

View full text Add to dashboard Cite

Accurately mapping the boundary between land and water (the 'waterline') is critical for tracking change in vulnerable coastal zones, and managing increasingly threatened water resources. Previous studies have largely relied on mapping waterlines at the pixel scale, or employed computationally intensive sub-pixel waterline extraction methods that are impractical to implement at scale. There is a pressing need for operational methods for extracting information from freely available medium resolution satellite imagery at spatial scales relevant to coastal and environmental management. In this study, we present a comprehensive evaluation of a promising method for mapping waterlines at sub-pixel accuracy from satellite remote sensing data. By combining a synthetic landscape approach with high resolution WorldView-2 satellite imagery, it was possible to rapidly assess the performance of the method across multiple coastal environments with contrasting spectral characteristics (sandy beaches, artificial shorelines, rocky shorelines, wetland vegetation and tidal mudflats), and under a range of water indices (Normalised Difference Water Index, Modified Normalised Difference Water Index, and the Automated Water Extraction Index) and thresholding approaches (optimal, zero and automated Otsu's method). The sub-pixel extraction method shows a strong ability to reproduce both absolute waterline positions and relative shape at a resolution that far exceeds that of traditional whole-pixel methods, particularly in environments without extreme contrast between the water and land (e.g., accuracies of up to 1.50-3.28 m at 30 m Landsat resolution using optimal water index thresholds). We discuss key challenges and limitations associated with selecting appropriate water indices and thresholds for sub-pixel waterline extraction, and suggest future directions for improving the accuracy and reliability of extracted waterlines. The sub-pixel waterline extraction method has a low computational overhead and is made available as an open-source tool, making it suitable for operational continental-scale or full time-depth analyses aimed at accurately mapping and monitoring dynamic waterlines through time and space.

show abstract

Adaptive bathymetry estimation for shallow coastal waters using Planet Dove satellites

Cited by 108 publications

References 58 publications

Object-Based Mapping of Coral Reef Habitats Using Planet Dove Satellites

Object-Based Mapping of Coral Reef Habitats Using Planet Dove Satellites

Bathymetry Time Series Using High Spatial Resolution Satellite Images

Sub-Pixel Waterline Extraction: Characterising Accuracy and Sensitivity to Indices and Spectra

Contact Info

Product

Resources

About