Post-tsunami adjustment of coral reef platform and other morphometric changes in Landfall Island, North Andaman—An integrated field and remote sensing-based approach

2021 ◽  
pp. 101975
Author(s):  
Manik Das Adhikari ◽  
Sabyasachi Maiti ◽  
Anup Bera ◽  
Nandini Ray Chaudhury
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Reef Platform

Coral reef remote sensing applications

1986 ◽  
Vol 1 (4) ◽  
pp. 3-15 ◽  
Author(s):  
Deborah A. Kuchler ◽  
David L.B. Jupp ◽  
Daniel B. van R. Claasen ◽  
William Bour
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Sensing Applications ◽  
Remote Sensing Applications

scholarly journals Reconstructing High-Precision Coral Reef Geomorphology from Active Remote Sensing Datasets: A Robust Spatial Variability Modified Ordinary Kriging Method

2022 ◽  
Vol 14 (2) ◽  
pp. 253
Author(s):  
Qi Wang ◽  
Han Xiao ◽  
Wenzhou Wu ◽  
Fenzhen Su ◽  
Xiuling Zuo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Coral Reefs ◽  
Spatial Variability ◽  
High Precision ◽  
Ordinary Kriging ◽  
Surface Model ◽  
Smoothing Effect ◽  
Geomorphological Parameters ◽  
Reef Geomorphology

Active remote sensing technology represented by multi-beam and lidar provides an important approach for the effective acquisition of underwater coral reef geomorphological information. A spatially continuous surface model of coral reef geomorphology reconstructed from active remote sensing datasets can provide important geomorphological parameters for the research of coral reef geomorphological and ecological changes. However, the surface modeling methods commonly used in previous studies, such as ordinary kriging (OK) and natural neighborhood (NN), often represent a “smoothing effect”, which causes the strong spatial variability of coral reefs to be imprecisely reflected by the reconstructed surfaces, thus affecting the accurate calculation of subsequent geomorphological parameters. In this study, a spatial variability modified OK (OK-SVM) method is proposed to reduce the impact of the “smoothing effect” on the high-precision reconstruction of the complex geomorphology of coral reefs. The OK-SVM adopts a collaborative strategy of global parameter transformation, local residual correction, and extremum correction to modify the spatial variability of the reconstructed model, while maintaining high local accuracy. The experimental results show that the OK-SVM has strong robustness to spatial variability modification. This method was applied to the geomorphological reconstruction of the northern area of a coral atoll in the Nansha Islands, South China Sea, and the performance was compared with that of OK and NN. The results show that OK-SVM has higher numerical accuracy and attribute accuracy in detailed morphological fidelity, and is more adaptable in the geomorphological reconstruction of coral reefs with strong spatial variability. This method is relatively reliable for achieving high-precision reconstruction of complex geomorphology of coral reefs from active remote sensing datasets, and has potential to be extended to other geomorphological reconstruction applications.

scholarly journals Coral Reef Ecosystem Monitoring Using Remote Sensing Data: Case Study in Owi Island, Biak, Papua

2016 ◽  
Vol 33 ◽  
pp. 600-606 ◽  
Author(s):  
Dominggus Samuel H.L.M.K. Awak ◽  
Jonson Lumban Gaol ◽  
Beginer Subhan ◽  
Hawis H. Madduppa ◽  
Dondy Arafat
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Remote Sensing Data ◽  
Coral Reef Ecosystem ◽  
Ecosystem Monitoring ◽  
Sensing Data ◽  
Reef Ecosystem

scholarly journals Confidence Levels, Sensitivity, and the Role of Bathymetry in Coral Reef Remote Sensing

2020 ◽  
Vol 12 (3) ◽  
pp. 496 ◽  
Author(s):  
James A. Goodman ◽  
Mui Lay ◽  
Luis Ramirez ◽  
Susan L. Ustin ◽  
Paul J. Haverkamp
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Coral Reefs ◽  
Water Depth ◽  
Data Availability ◽  
Sensor Technology ◽  
Internal Quality ◽  
Benthic Habitat ◽  
Model Output ◽  
Confidence Levels

Remote sensing is playing an increasingly important role in the monitoring and management of coastal regions, coral reefs, inland lakes, waterways, and other shallow aquatic environments. Ongoing advances in algorithm development, sensor technology, computing capabilities, and data availability are continuing to improve our ability to accurately derive information on water properties, water depth, benthic habitat composition, and ecosystem health. However, given the physical complexity and inherent variability of the aquatic environment, most of the remote sensing models used to address these challenges require localized input parameters to be effective and are thereby limited in geographic scope. Additionally, since the parameters in these models are interconnected, particularly with respect to bathymetry, errors in deriving one parameter can significantly impact the accuracy of other derived parameters and products. This study utilizes hyperspectral data acquired in Hawaii in 2000–2001 and 2017–2018 using NASA’s Classic Airborne Visible/Infrared Imaging Spectrometer to evaluate performance and sensitivity of a well-established semi-analytical inversion model used in the assessment of coral reefs. Analysis is performed at several modeled spatial resolutions to emulate characteristics of different feasible moderate resolution hyperspectral satellites, and data processing is approached with the objective of developing a generalized, scalable, automated workflow. Accuracy of derived water depth is evaluated using bathymetric lidar data, which serves to both validate model performance and underscore the importance of image quality on achieving optimal model output. Data are then used to perform a sensitivity analysis and develop confidence levels for model validity and accuracy. Analysis indicates that derived benthic reflectance is most sensitive to errors in bathymetry at shallower depths, yet remains significant at all depths. The confidence levels provide a first-order method for internal quality assessment to determine the physical extent of where and to what degree model output is considered valid. Consistent results were found across different study sites and different spatial resolutions, confirming the suitability of the model for deriving water depth in complex coral reef environments, and expanding our ability to achieve automated widespread mapping and monitoring of global coral reefs.

The scientific issues surrounding remote detection of submerged coral ecosystems

1998 ◽  
Vol 22 (2) ◽  
pp. 190-221 ◽  
Author(s):  
Heather Holden ◽  
Ellsworth LeDrew
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Coral Reefs ◽  
Large Scale ◽  
Aerial Photographs ◽  
Coastal Zones ◽  
Global Status ◽  
Coral Reef Ecosystems ◽  
Remote Estimation

According to the 1993 colloquium on the ‘Global status of coral reefs', our understanding of the global role of coral reefs is inadequate. To increase our understanding, an accurate large-scale mapping and monitoring programme is necessary. Historically, coastal zones have been mapped using traditional surveying tools such as topographic maps, nautical charts, existing aerial photographs and direct observations. Although less expensive than digital imagery, exclusive use of these traditional tools may not be practical for monitoring large or remote coral reef ecosystems accurately. Researchers are attempting to develop an adequate coral reef mapping system based on digital remote sensing, but are impeded by issues such as effects of the intervening water column and spectral distinction of bottom types. The two variables discussed, which will contribute to our understanding of the global role of coral reefs, are: 1) remote sensing of submerged coral reefs in general; and 2) remote sensing of coral bleaching in particular. A summary of radiative transfer theory is presented and case studies of attempts at mapping remotely the geographic extent and health of submerged ecosystems, as well as a discussion of the remote estimation of water depth and quality. Problems in the translation and delivery of information to the end user are presented, and possible solutions suggested.

Hyperspectral Remote Sensing and Radiative Transfer Simulation as a Tool for Monitoring Coral Reef Health

2002 ◽  
Vol 36 (1) ◽  
pp. 4-13 ◽  
Author(s):  
Hiroya Yamano ◽  
Masayuki Tamura ◽  
Yoshimitsu Kunii ◽  
Michio Hidaka
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Radiative Transfer ◽  
Feasibility Studies ◽  
Hyperspectral Remote Sensing ◽  
Hyperspectral Data ◽  
Dead Coral ◽  
Hyperspectral Sensors ◽  
Reef Health ◽  
Radiative Transfer Modeling

Recent advances in the remote sensing of coral reefs include hyperspectral remote sensing and radiative transfer modeling. Hyperspectral data can be regarded as continuous and the derivative spectroscopy is effective for extracting coral reef components, including sand, macroalgae, and healthy, bleached, recently dead, and old dead coral. Radiative transfer models are effective for feasibility studies of satellite or airborne remote sensing. Using these techniques, we simulate and analyze the apparent reflectance of coral reef benthic features associated with bleaching events, obtained by hyperspectral sensors on various platforms (ROV, boat, airplane, and satellite), and suggest that the coral reef health on reef flats can be discriminated precisely. Remote sensing using hyperspectral sensors should significantly contribute to mapping and monitoring coral reef health.

Sign in / Sign up

Export Citation Format

Share Document