24.4.10 Seagrass

Chapter Contents (Back)
Seagrass.

Macleod, R.D., Congalton, R.G.,
Quantitative Comparison of Change-Detection Algorithms for Monitoring Eelgrass from Remotely-Sensed Data,
PhEngRS(64), No. 3, March 1998, pp. 207-216. 9803
BibRef

Lathrop, R.G.[Richard G.], Montesano, P.[Paul], Haag, S.[Scott],
A Multi-scale Segmentation Approach to Mapping Seagrass Habitats Using Airborne Digital Camera Imagery,
PhEngRS(72), No. 6, June 2006, pp. 665-676.
WWW Link. 0610
BibRef

Yang, D., Yang, Y., Yang, C., Zhao, J., Sun, Z.,
Detection of seagrass in optical shallow water with quickbird in the Xincun Bay, Hainan province, China,
IET-IPR(5), No. 5, 2011, pp. 363-368.
DOI Link 1108
BibRef

Lyons, M., Phinn, S.R., Roelfsema, C.M.,
Integrating Quickbird Multi-Spectral Satellite and Field Data: Mapping Bathymetry, Seagrass Cover, Seagrass Species and Change in Moreton Bay, Australia in 2004 and 2007,
RS(3), No. 1, January 2011, pp. 42-64.
DOI Link 1203
BibRef

Lyons, M.B.[Mitchell B.], Phinn, S.R.[Stuart R.], Roelfsema, C.M.[Chris M.],
Long term land cover and seagrass mapping using Landsat and object-based image analysis from 1972 to 2010 in the coastal environment of South East Queensland, Australia,
PandRS(71), No. 1, July 2012, pp. 34-46.
Elsevier DOI 1208
Time series; Land cover; Seagrass; Landsat BibRef

Pu, R.L.[Rui-Liang], Bell, S.[Susan],
A protocol for improving mapping and assessing of seagrass abundance along the West Central Coast of Florida using Landsat TM and EO-1 ALI/Hyperion images,
PandRS(83), No. 1, 2013, pp. 116-129.
Elsevier DOI 1308
Image optimization BibRef

Borfecchia, F.[Flavio], Micheli, C.[Carla], Carli, F.[Filippo], de Martis, S.C.[Selvaggia Cognetti], Gnisci, V.[Valentina], Piermattei, V.[Viviana], Belmonte, A.[Alessandro], de Cecco, L.[Luigi], Martini, S.[Sandro], Marcelli, M.[Marco],
Mapping Spatial Patterns of Posidonia oceanica Meadows by Means of Daedalus ATM Airborne Sensor in the Coastal Area of Civitavecchia (Central Tyrrhenian Sea, Italy),
RS(5), No. 10, 2013, pp. 4877-4899.
DOI Link 1311
BibRef

Hogrefe, K.R.[Kyle R.], Ward, D.H.[David H.], Donnelly, T.F.[Tyrone F], Dau, N.[Niels],
Establishing a Baseline for Regional Scale Monitoring of Eelgrass (Zostera marina) Habitat on the Lower Alaska Peninsula,
RS(6), No. 12, 2014, pp. 12447-12477.
DOI Link 1412
BibRef

Hannam, M.[Michael], Moskal, L.M.[L. Monika],
Terrestrial Laser Scanning Reveals Seagrass Microhabitat Structure on a Tideflat,
RS(7), No. 3, 2015, pp. 3037-3055.
DOI Link 1504
BibRef

Toro-Farmer, G.[Gerardo], Muller-Karger, F.E.[Frank E.], Vega-Rodríguez, M.[Maria], Melo, N.[Nelson], Yates, K.[Kimberly], Cerdeira-Estrada, S.[Sergio], Herwitz, S.R.[Stanley R.],
Characterization of Available Light for Seagrass and Patch Reef Productivity in Sugarloaf Key, Lower Florida Keys,
RS(8), No. 2, 2016, pp. 86.
DOI Link 1603
BibRef

Hamana, M.[Masahiro], Komatsu, T.[Teruhisa],
Real-Time Classification of Seagrass Meadows on Flat Bottom with Bathymetric Data Measured by a Narrow Multibeam Sonar System,
RS(8), No. 2, 2016, pp. 96.
DOI Link 1603
BibRef

Misbari, S.[Syarifuddin], Hashim, M.[Mazlan],
Change Detection of Submerged Seagrass Biomass in Shallow Coastal Water,
RS(8), No. 3, 2016, pp. 200.
DOI Link 1604
BibRef

Koedsin, W.[Werapong], Intararuang, W.[Wissarut], Ritchie, R.J.[Raymond J.], Huete, A.[Alfredo],
An Integrated Field and Remote Sensing Method for Mapping Seagrass Species, Cover, and Biomass in Southern Thailand,
RS(8), No. 4, 2016, pp. 292.
DOI Link 1604
BibRef

Traganos, D.[Dimosthenis], Aggarwal, B.[Bharat], Poursanidis, D.[Dimitris], Topouzelis, K.[Konstantinos], Chrysoulakis, N.[Nektarios], Reinartz, P.[Peter],
Towards Global-Scale Seagrass Mapping and Monitoring Using Sentinel-2 on Google Earth Engine: The Case Study of the Aegean and Ionian Seas,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Corbí, H.[Hugo], Riquelme, A.[Adrian], Megías-Baños, C.[Clara], Abellan, A.[Antonio],
3-D Morphological Change Analysis of a Beach with Seagrass Berm Using a Terrestrial Laser Scanner,
IJGI(7), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Chen, Q.[Qi], Yu, R.H.[Rui-Hong], Hao, Y.L.[Yan-Ling], Wu, L.H.[Lin-Hui], Zhang, W.X.[Wen-Xing], Zhang, Q.[Qi], Bu, X.[Xunan],
A New Method for Mapping Aquatic Vegetation Especially Underwater Vegetation in Lake Ulansuhai Using GF-1 Satellite Data,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Stramska, M.[Malgorzata], Aniskiewicz, P.[Paulina],
Recent Large Scale Environmental Changes in the Mediterranean Sea and Their Potential Impacts on Posidonia Oceanica,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Dierssen, H.M.[Heidi M.], Bostrom, K.J.[Kelley J.], Chlus, A.[Adam], Hammerstrom, K.[Kamille], Thompson, D.R.[David R.], Lee, Z.P.[Zhong-Ping],
Pushing the Limits of Seagrass Remote Sensing in the Turbid Waters of Elkhorn Slough, California,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Ha, N.T.[Nam Thang], Manley-Harris, M.[Merilyn], Pham, T.D.[Tien Dat], Hawes, I.[Ian],
A Comparative Assessment of Ensemble-Based Machine Learning and Maximum Likelihood Methods for Mapping Seagrass Using Sentinel-2 Imagery in Tauranga Harbor, New Zealand,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Perez, D.[Daniel], Islam, K.[Kazi], Hill, V.[Victoria], Zimmerman, R.[Richard], Schaeffer, B.[Blake], Shen, Y.Z.[Yu-Zhong], Li, J.[Jiang],
Quantifying Seagrass Distribution in Coastal Water with Deep Learning Models,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Mohamed, H.[Hassan], Nadaoka, K.[Kazuo], Nakamura, T.[Takashi],
Semiautomated Mapping of Benthic Habitats and Seagrass Species Using a Convolutional Neural Network Framework in Shallow Water Environments,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Xu, S.C.[Shao-Chun], Xu, S.[Shuai], Zhou, Y.[Yi], Yue, S.D.[Shi-Dong], Zhang, X.M.[Xiao-Mei], Gu, R.T.[Rui-Ting], Zhang, Y.[Yu], Qiao, Y.L.[Yong-Liang], Liu, M.J.[Ming-Jie],
Long-Term Changes in the Unique and Largest Seagrass Meadows in the Bohai Sea (China) Using Satellite (1974-2019) and Sonar Data: Implication for Conservation and Restoration,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Hobley, B.[Brandon], Arosio, R.[Riccardo], French, G.[Geoffrey], Bremner, J.[Julie], Dolphin, T.[Tony], Mackiewicz, M.[Michal],
Semi-Supervised Segmentation for Coastal Monitoring Seagrass Using RPA Imagery,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Benmokhtar, S.[Salma], Robin, M.[Marc], Maanan, M.[Mohamed], Bazairi, H.[Hocein],
Mapping and Quantification of the Dwarf Eelgrass Zostera noltei Using a Random Forest Algorithm on a SPOT 7 Satellite Image,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Ha, N.T.[Nam-Thang], Manley-Harris, M.[Merilyn], Pham, T.D.[Tien-Dat], Hawes, I.[Ian],
Detecting Multi-Decadal Changes in Seagrass Cover in Tauranga Harbour, New Zealand, Using Landsat Imagery and Boosting Ensemble Classification Techniques,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Krause, J.R.[Johannes R.], Hinojosa-Corona, A.[Alejandro], Gray, A.B.[Andrew B.], Watson, E.B.[Elizabeth Burke],
Emerging Sensor Platforms Allow for Seagrass Extent Mapping in a Turbid Estuary and from the Meadow to Ecosystem Scale,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Chen, J.D.[Jun-Dong], Sasaki, J.[Jun],
Mapping of Subtidal and Intertidal Seagrass Meadows via Application of the Feature Pyramid Network to Unmanned Aerial Vehicle Orthophotos,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Shin, J.[Jisun], Lee, J.S.[Jong-Seok], Jang, L.H.[Lee-Hyun], Lim, J.[Jinwook], Khim, B.K.[Boo-Keun], Jo, Y.H.[Young-Heon],
Sargassum Detection Using Machine Learning Models: A Case Study with the First 6 Months of GOCI-II Imagery,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Descloitres, J.[Jacques], Minghelli, A.[Audrey], Steinmetz, F.[François], Chevalier, C.[Cristèle], Chami, M.[Malik], Berline, L.[Léo],
Revisited Estimation of Moderate Resolution Sargassum Fractional Coverage Using Decametric Satellite Data (S2-MSI),
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Chand, S.[Subhash], Bollard, B.[Barbara],
Detecting the Spatial Variability of Seagrass Meadows and Their Consequences on Associated Macrofauna Benthic Activity Using Novel Drone Technology,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Price, D.M.[David M.], Felgate, S.L.[Stacey L.], Huvenne, V.A.I.[Veerle A. I.], Strong, J.[James], Carpenter, S.[Stephen], Barry, C.[Chris], Lichtschlag, A.[Anna], Sanders, R.[Richard], Carrias, A.[Abel], Young, A.[Arlene], Andrade, V.[Valdemar], Cobb, E.[Eliceo], Le Bas, T.[Tim], Brittain, H.[Hannah], Evans, C.[Claire],
Quantifying the Intra-Habitat Variation of Seagrass Beds with Unoccupied Aerial Vehicles (UAVs),
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Carpenter, S.[Stephen], Byfield, V.[Val], Felgate, S.L.[Stacey L.], Price, D.M.[David M.], Andrade, V.[Valdemar], Cobb, E.[Eliceo], Strong, J.[James], Lichtschlag, A.[Anna], Brittain, H.[Hannah], Barry, C.[Christopher], Fitch, A.[Alice], Young, A.[Arlene], Sanders, R.[Richard], Evans, C.[Claire],
Using Unoccupied Aerial Vehicles (UAVs) to Map Seagrass Cover from Sentinel-2 Imagery,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Kovacs, E.M.[Eva M.], Roelfsema, C.[Chris], Udy, J.[James], Baltais, S.[Simon], Lyons, M.[Mitchell], Phinn, S.[Stuart],
Cloud Processing for Simultaneous Mapping of Seagrass Meadows in Optically Complex and Varied Water,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Hamad, I.Y.[Idrissa Yussuf], Staehr, P.A.U.[Peter Anton Upadhyay], Rasmussen, M.B.[Michael Bo], Sheikh, M.[Mohammed],
Drone-Based Characterization of Seagrass Habitats in the Tropical Waters of Zanzibar,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Li, Y.Q.[Yi-Qiong], Bai, J.[Junwu], Zhang, L.[Li], Yang, Z.H.[Zhao-Hui],
Mapping and Spatial Variation of Seagrasses in Xincun, Hainan Province, China, Based on Satellite Images,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
BibRef

McKenzie, L.J.[Len J.], Langlois, L.A.[Lucas A.], Roelfsema, C.M.[Chris M.],
Improving Approaches to Mapping Seagrass within the Great Barrier Reef: From Field to Spaceborne Earth Observation,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Simpson, J.[Jamie], Bruce, E.[Eleanor], Davies, K.P.[Kevin P.], Barber, P.[Paul],
A Blueprint for the Estimation of Seagrass Carbon Stock Using Remote Sensing-Enabled Proxies,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Casas, E.[Enrique], Martín-García, L.[Laura], Hernández-Leal, P.[Pedro], Arbelo, M.[Manuel],
Species Distribution Models at Regional Scale: Cymodocea nodosa Seagrasses,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Zhou, Q.Q.[Qing-Qing], Ke, Y.H.[Ying-Hai], Wang, X.[Xinyan], Bai, J.[Junhong], Zhou, D.[Demin], Li, X.J.[Xiao-Juan],
Developing seagrass index for long term monitoring of Zostera japonica seagrass bed: A case study in Yellow River Delta, China,
PandRS(194), 2022, pp. 286-301.
Elsevier DOI 2212
Seagrass mapping, Time-series analysis, Multi-Otsu algorithm, Yellow River Delta BibRef

Bremner, J.[Julie], Petus, C.[Caroline], Dolphin, T.[Tony], Hawes, J.[Jon], Beguet, B.[Benoît], Devlin, M.J.[Michelle J.],
A Seagrass Mapping Toolbox for South Pacific Environments,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Laval, M.[Marine], Belmouhcine, A.[Abdelbadie], Courtrai, L.[Luc], Descloitres, J.[Jacques], Salazar-Garibay, A.[Adán], Schamberger, L.[Léa], Minghelli, A.[Audrey], Thibaut, T.[Thierry], Dorville, R.[René], Mazoyer, C.[Camille], Zongo, P.[Pascal], Chevalier, C.[Cristèle],
Detection of Sargassum from Sentinel Satellite Sensors Using Deep Learning Approach,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Fakiris, E.[Elias], Giannakopoulos, V.[Vasileios], Leftheriotis, G.[Georgios], Dimas, A.[Athanassios], Papatheodorou, G.[George],
Predictive Mapping of Mediterranean Seagrasses-Exploring the Influence of Seafloor Light and Wave Energy on Their Fine-Scale Spatial Variability,
RS(15), No. 11, 2023, pp. 2943.
DOI Link 2306
BibRef

Thomasberger, A.[Aris], Nielsen, M.M.[Mette Møller], Flindt, M.R.[Mogens Rene], Pawar, S.[Satish], Svane, N.[Niels],
Comparative Assessment of Five Machine Learning Algorithms for Supervised Object-Based Classification of Submerged Seagrass Beds Using High-Resolution UAS Imagery,
RS(15), No. 14, 2023, pp. 3600.
DOI Link 2307
BibRef

Dolbeth, M.[Marina], de Araújo-Costa, D.[Dimítri ], Meyer, M.[Manuel], Gonçalves, J.A.[José Alberto], Bio, A.[Ana],
Characterisation and Dynamics of an Emerging Seagrass Meadow,
RS(15), No. 16, 2023, pp. 4086.
DOI Link 2309
BibRef


Tamondong, A., Nakamura, T., Quiros, T.E.A., Nadaoka, K.,
Time Series Analysis for Monitoring Seagrass Habitat and Environment In Busuanga, Philippines Using Google Earth Engine,
ISPRS21(B3-2021: 109-116).
DOI Link 2201
BibRef

Noman, M.K.[Md Kislu], Islam, S.M.S.[Syed Mohammed Shamsul], Abu-Khalaf, J.[Jumana], Lavery, P.[Paul],
Multi-species Seagrass Detection Using Semi-supervised Learning,
IVCNZ21(1-6)
IEEE DOI 2201
Training, Image resolution, Semisupervised learning, Convolutional neural networks, Semi-supervised learning BibRef

Noman, M.K.[Md Kislu], Islam, S.M.S.[Syed Mohammed Shamsul], Abu-Khalaf, J.[Jumana], Lavery, P.[Paul],
Seagrass Detection from Underwater Digital Images using Faster R-CNN with NASNet,
DICTA21(1-6)
IEEE DOI 2201
Deep learning, Digital images, Diversity reception, Detectors, Object detection, Generative adversairal networks, Deep learning, Seagrass BibRef

Raine, S.[Scarlett], Marchant, R.[Ross], Moghadam, P.[Peyman], Maire, F.[Frederic], Kettle, B.[Brett], Kusy, B.[Brano],
Multi-species Seagrass Detection and Classification from Underwater Images,
DICTA20(1-8)
IEEE DOI 2201
Training, Robot vision systems, Training data, Manuals, Substrates, Robots, Testing BibRef

Forsey, D., Leblon, B., LaRocque, A., Skinner, M., Douglas, A.,
Eelgrass Mapping In Atlantic Canada Using Worldview-2 Imagery,
ISPRS20(B3:685-692).
DOI Link 2012
BibRef

Sani, D.A., Hashim, M.,
Satellite-based Mapping of Above-ground Blue Carbon Storage in Seagrass Habitat Within The Shallow Coastal Water,
GGT19(587-593).
DOI Link 1912
BibRef

Muhamad, M.A.H., Che Hasan, R.,
Seagrass Habitat Suitability Map At Merambong Shoal, Johor: A Preliminary Study Using Multibeam Echosounder and Maxent Modelling,
GGT19(463-470).
DOI Link 1912
BibRef

Traganos, D., Cerra, D., Reinartz, P.,
Cubesat-derived Detection of Seagrasses Using Planet Imagery Following Unmixing-based Denoising: Is Small the Next Big?,
Hannover17(283-287).
DOI Link 1805
BibRef

Rahnemoonfar, M.[Maryam], Yari, M.[Masoud], Rahman, A.[Abdullah], Kline, R.[Richard],
The First Automatic Method for Mapping the Pothole in Seagrass,
PBVS17(267-274)
IEEE DOI 1709
Adaptive optics, Image segmentation, Optical imaging, Optical sensors, Remote sensing, Sonar, Wavelet, transforms BibRef

Bakirman, T., Gumusay, M.U., Tuney, I.,
Mapping Of The Seagrass Cover Along The Mediterranean Coast Of Turkey Using Landsat 8 Oli Images,
ISPRS16(B8: 1103-1105).
DOI Link 1610
BibRef

Urbanski, J.A.,
Using ArcGIS Model Builder for object-based image classification of seagrass meadows,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Waves, Ocean Waves, Wave Heights, Sea Surface Effects .


Last update:Mar 16, 2024 at 20:36:19