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 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.

scholarly journals Coral reef monitoring in Panjang Island, Central Bangka

2021 ◽  
Vol 926 (1) ◽  
pp. 012099
Author(s):  
W Adi ◽  
I Akhrianti ◽  
M Hudatwi
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Coral Reefs ◽  
Satellite Imagery ◽  
Good Condition ◽  
Aerial Photographs ◽  
Visual Interpretation ◽  
Composite Band ◽  
Sentinel 2A ◽  
Color Composite

Abstract Bangka Island is the largest tin producer in Indonesia and since the granting of tin mining freedom in 2000, unconventional tin mining (TI) is increasingly prevalent. The existence of mining activities will directly or indirectly damage the environment both on land and at sea. Especially the high biodiversity of coral reef ecosystem. The purpose of this research was to analyze a map of the distribution of coral reef based on Sentinel 2A satellite imagery data. Analyze the extent of the coral reefs in shallow waters of Putri Island, and analyze of the condition coral reefs (percentage cover, mortality index and genus diversity) with using collaboration betwen the coral diving data and remote sensing data. Studies of changes in coral reef ecosystems have been ongoing since several decades ago. The combination of satellite imagery and aerial photographs is capable of making long-term and continuous observations on mapping and change detection. Remote sensing technology has several advantages overconventional sampling to monitor a large area in time almost simultaneously and continuously including the difficult to explore areas. This research was conducted with visual interpretation by using standard true color composite band (483) and false color composite band (843) of Sentinel 2A and also using lyzenga transformation. Estimation of coral reefs area based on result is 475,96 ha (2016) and decreased to 475 ha (2021). The condition of coral reefs at the research location is a good condition.

scholarly journals ANALISIS HABITAT DAN PERUBAHAN LUASAN TERUMBU KARANG DI PULAU MENJANGAN BESAR, KEPULAUAN KARIMUNJAWA MENGGUNAKAN CITRA SATELIT

2016 ◽  
Vol 5 (4) ◽  
pp. 302-310
Author(s):  
Rio Januardi ◽  
Agus Hartoko ◽  
Pujiono Wahyu Purnomo
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Coral Reefs ◽  
Good Condition ◽  
Landsat 8 ◽  
Geometric Center ◽  
Sensing Technology ◽  
Coral Reef Area ◽  
Short Time ◽  
Line Intercept

ABSTRAK Perairan Indonesia menyimpan keanekaragaman hayati laut karang tertinggi, diperkirakan luas ekosistem terumbu karang Indonesia mencapai 50.000 km2 yaitu 25 persen dari luas terumbu karang dunia. Penggunaan teknologi penginderaan jauh merupakan salah satu alternatif yang tepat untuk mendeteksi terumbu karang bagi negara yang mempunyai wilayah yang sangat luas dan memerlukan waktu yang relatif singkat serta biaya murah. Penelitian ini bertujuan untuk mengetahui jenis, kondisi, perubahan luasan dan tingkat akurasi monitoring terumbu karang di Pulau Menjangan Besar menggunakan citra satelit Landsat 8. Penelitian dilaksanakan pada November 2015-Januari 2016 di Pulau Menjangan Besar dan di Laboratorium Marine Geometric Center, Jurusan Perikanan UNDIP. Metode penelitian yang digunakan yaitu metode eksploratif untuk mengetahui jenis dan kondisi terumbu karang menggunakan metode Line Intersept Transect dan metode koreksi kolom air atau Lyzenga. Hasil penelitian  menemukan kondisi terumbu karang di Pulau Menjangan Besar masih dalam kondisi baik dengan persentase penutupan karang sebesar 51,6 persen. Jenis terumbu karang yang terdapat di Pulau Menjangan Besar yaitu Acropora sp, Stylopora sp, Porites sp, Favia sp, Heliopora sp, Euphylia sp, Pocilopora sp, Goniopora sp dan Favites sp dengan nilai keaneragaman sebesar 1.28 tergolong sedang/moderat dan nilai dominasi sebesar 0.58. Terumbu karang mengalami penurunan luasan sebesar 7,92 Ha dari tahun 2013-2015. Tingkat akurasi penggunaan citra satelit Landsat 8 yaitu 81,25 persen. Kata kunci :Persentase penutupan karang; Luasan habitat; Menjangan Besar; Penginderaan jauh ABSTRACTThe ocean of Indonesia has the highest biodiversity of Coral Reef, the extent of Indonesian’s coral reefs widely predicted 50.000 km2 which is about 25% of the world’s. The use of remote sensing technology is one the alternatives that is appropriate for the detection of coral reefs for a country that has a very wide area and requires a relatively short time and reasonable cost. This study aimed to determine the type; condition; changes in the area; and the level of monitoring coral reefs accuracy in Menjangan Besar Island used Landsat 8 satellite. The study was conducted on November 2015 until January 2016 in Menjangan Besar Island and the Marine Geometric Center, Fisheries Department at Diponegoro University. This research uses an explorative method to determine the type and condition of coral reefs using line intercept transect method and correction on water column method or Lyzenga. The result of this research is the condition of coral reefs in Menjangan Besar in the good condition with the cover percentage of coral at 51.6%. The species of Coral reefs in Menjangan Besar are identified as Acropora sp, Stylopora sp, Porites sp, Favia sp, Heliopora sp, Euphylia sp, Pocilopora sp, Goniopora sp and Favites sp with the value of diversity about 1.28 classified as moderate and the value of dominance of 0.58. The coral reef area decreased by 7.92 ha of the year 2013 to 2015. The accuracy level used Landsat 8 imagery satellite is 81.25%. This level of accuracy using Landsat 8 satellite imagery is 81.25%. Keywords :Percentages of coral reef cover; Extents habitat; Menjangan Besar; Remote sensing.

scholarly journals Ordinary kriging vs inverse distance weighting: spatial interpolation of the sessile community of Madagascar reef, Gulf of Mexico

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e4078 ◽  
Author(s):  
Salvador Zarco-Perello ◽  
Nuno Simões
Keyword(s):  
Remote Sensing ◽  
Gulf Of Mexico ◽  
Spatial Variability ◽  
Ordinary Kriging ◽  
Spatial Interpolation ◽  
Prediction Errors ◽  
Interpolation Methods ◽  
Distance Weighting ◽  
Inverse Distance

Information about the distribution and abundance of the habitat-forming sessile organisms in marine ecosystems is of great importance for conservation and natural resource managers. Spatial interpolation methodologies can be useful to generate this information from in situ sampling points, especially in circumstances where remote sensing methodologies cannot be applied due to small-scale spatial variability of the natural communities and low light penetration in the water column. Interpolation methods are widely used in environmental sciences; however, published studies using these methodologies in coral reef science are scarce. We compared the accuracy of the two most commonly used interpolation methods in all disciplines, inverse distance weighting (IDW) and ordinary kriging (OK), to predict the distribution and abundance of hard corals, octocorals, macroalgae, sponges and zoantharians and identify hotspots of these habitat-forming organisms using data sampled at three different spatial scales (5, 10 and 20 m) in Madagascar reef, Gulf of Mexico. The deeper sandy environments of the leeward and windward regions of Madagascar reef were dominated by macroalgae and seconded by octocorals. However, the shallow rocky environments of the reef crest had the highest richness of habitat-forming groups of organisms; here, we registered high abundances of octocorals and macroalgae, with sponges, Millepora alcicornis and zoantharians dominating in some patches, creating high levels of habitat heterogeneity. IDW and OK generated similar maps of distribution for all the taxa; however, cross-validation tests showed that IDW outperformed OK in the prediction of their abundances. When the sampling distance was at 20 m, both interpolation techniques performed poorly, but as the sampling was done at shorter distances prediction accuracies increased, especially for IDW. OK had higher mean prediction errors and failed to correctly interpolate the highest abundance values measured in situ, except for macroalgae, whereas IDW had lower mean prediction errors and high correlations between predicted and measured values in all cases when sampling was every 5 m. The accurate spatial interpolations created using IDW allowed us to see the spatial variability of each taxa at a biological and spatial resolution that remote sensing would not have been able to produce. Our study sets the basis for further research projects and conservation management in Madagascar reef and encourages similar studies in the region and other parts of the world where remote sensing technologies are not suitable for use.

scholarly journals CORAL REEF HABITAT CHANGING ASSESSMENT OF DERAWAN ISLANDS, EAST KALIMANTAN, USING REMOTE SENSING DATA

2010 ◽  
Vol 2 (-) ◽  
Author(s):  
MARLINA NURLIDIASARI ◽  
SYARIF BUDIMAN
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Coral Reefs ◽  
Change Detection ◽  
Remote Sensing Data ◽  
Landsat Tm ◽  
East Kalimantan ◽  
Marine Diversity ◽  
Multi Temporal ◽  
Remote Sensing Techniques

Coral reefs in Dcrawan Islands are astonishingly rich in the marine diversity. However, these reefs are threatened by humans. Destructive fishing methods, such as trawl, blasting and cyanide fishing practise, are found to be the main cause of this degradation. The coral reefs habitat reduction is also caused by tourism activities due to trampling over the reef and charging organic and anorganic wastes. The capabilities of satellite remote sensing techniques combined with field data collection have been assessed for the coral reef mapping and the change detection of Derawan Island. Multi-temporal Landsat TM and ETM images (1991 and 2002) have been used. Comparison of the classified images of 1991 and 2002 shows spatial changes of the habitat. The changes were in accordance with the known changes in the reef conditions. The analysis shows the decrease of the coral reef and patchy seagrass percentage, while the increase of the algae composite and patchy reef percentage. Keywords : Coral Reef, Change Detection, Landsat-TM, Derawan

Analysis of the Coral Reef Evolution Based on Satellite Remote Sensing Images

2013 ◽  
Vol 333-335 ◽  
pp. 1719-1723
Author(s):  
Ming Xiao Xie ◽  
Yin Cai ◽  
Meng Guo Li
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Coral Reefs ◽  
Satellite Remote Sensing ◽  
Minimum Distance ◽  
Remote Sensing Images ◽  
Evolution Characteristics ◽  
Biological Environment ◽  
The Stability

Based on analysis of the ETM+ and TM remote sensing images of LandSAT satellites, the stability and evolution characteristics of the nearshore coral reefs at Changjiang, China was investigated. The results showed that the maximum distance from the outside edge of the coral reefs to the shoreline is 1.1km, and the corresponding minimum distance is 200m. From 1973 to 2013, the locations of coral reef chain are relatively stable with maximum variation 50m. Generally, the natural tidal currents and waves can not destroy the coral reefs, and the human activities do not change the biological environment of the coastal area. Therefore, the Changjiang coral reefs could keep stable in the long term.

scholarly journals Remote Sensing of Coral Reefs: Uncertainty in the Detection of Benthic Cover, Depth, and Water Constituents Imposed by Sensor Noise

2018 ◽  
Vol 8 (12) ◽  
pp. 2691 ◽  
Author(s):  
Steven Ackleson ◽  
Wesley Moses ◽  
Marcos Montes
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Coral Reef ◽  
Coral Reefs ◽  
Dissolved Organic Matter ◽  
Parameter Uncertainty ◽  
Sensor Noise ◽  
Water Constituents ◽  
Bottom Depth ◽  
The Impact

Coral reefs are biologically diverse and economically important ecosystems that are on the decline worldwide in response to direct human impacts and climate change. Ocean color remote sensing has proven to be an important tool in coral reef research and monitoring. Remote sensing data quality is driven by factors related to sensor design and environmental variability. This work explored the impact of sensor noise, defined as the signal to noise ratio (SNR), on the detection uncertainty of key coral reef ecological properties (bottom depth, benthic cover, and water quality) in the absence of environmental uncertainties. A radiative transfer model for a shallow reef environment was developed and Monte Carlo methods were employed to identify the range in environmental conditions that are spectrally indistinguishable from true conditions as a function of SNR. The spectrally averaged difference between remotely sensed radiance relative to sensor noise, ε, was used to quantify uncertainty in bottom depth, the fraction of benthic cover by coral, algae, and uncolonized sand, and the concentration of water constituents defined as chlorophyll, dissolved organic matter, and suspended calcite particles. Parameter uncertainty was found to increase with sensor noise (decreasing SNR) but the impact was non-linear. The rate of change in uncertainty per incremental change in SNR was greatest for SNR < 500 and increasing SNR further to 1000 resulted in only modest improvements. Parameter uncertainty was complicated by the bottom depth and benthic cover. Benthic cover uncertainty increased with bottom depth, but water constituent uncertainty changed inversely with bottom depth. Furthermore, water constituent uncertainty was impacted by the type of constituent material in relation to the type of benthic cover. Uncertainty associated with chlorophyll concentration and dissolved organic matter increased when the benthic cover was coral and/or benthic algae while uncertainty in the concentration of suspended calcite increased when the benthic cover was uncolonized sand. While the definition of an optimal SNR is subject to user needs, we propose that SNR of approximately 500 (relative to 5% Earth surface reflectance and a clear maritime atmosphere) is a reasonable engineering goal for a future satellite sensor to support research and management activities directed at coral reef ecology and, more generally, shallow aquatic ecosystems.

scholarly journals Using Remote Sensing and in situ Measurements for Efficient Mapping and Optimal Sampling of Coral Reefs

2021 ◽  
Vol 8 ◽  
Author(s):  
Alberto Candela ◽  
Kevin Edelson ◽  
Michelle M. Gierach ◽  
David R. Thompson ◽  
Gail Woodward ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Coral Reefs ◽  
Decision Theory ◽  
Sample Selection ◽  
Global Scale ◽  
Global Mapping ◽  
And Performance ◽  
Reef Condition

Coral reefs are of undeniable importance to the environment, yet little is known of them on a global scale. Assessments rely on laborious, local in-water surveys. In recent years remote sensing has been useful on larger scales for certain aspects of reef science such as benthic functional type discrimination. However, remote sensing only gives indirect information about reef condition. Only through combination of remote sensing and in situ data can we achieve coverage to understand reef condition and monitor worldwide condition. This work presents an approach to global mapping of coral reef condition that intelligently selects local, in situ measurements that refine the accuracy and resolution of global remote sensing. To this end, we apply new techniques in remote sensing analysis, probabilistic modeling for coral reef mapping, and decision theory for sample selection. Our strategy represents a fundamental change in how we study coral reefs and assess their condition on a global scale. We demonstrate feasibility and performance of our approach in a proof of concept using spaceborne remote sensing together with high-quality airborne data from the NASA Earth Venture Suborbital-2 (EVS-2) Coral Reef Airborne Laboratory (CORAL) mission as a proxy for in situ samples. Results indicate that our method is capable of extrapolating in situ features and refining information from remote sensing with increasing accuracy. Furthermore, the results confirm that decision theory is a powerful tool for sample selection.

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