22.5.9 Seagrass

Chapter Contents (Back)

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

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

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

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

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

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

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

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

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

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

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

Chen, Q.[Qi], Yu, R.H.[Rui-Hong], Hao, Y.L.[Yan-Ling], Wu, L.[Linhui], 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

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

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

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

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

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

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

Rahnemoonfar, M.[Maryam], Yari, M.[Masoud], Rahman, A.[Abdullah], Kline, R.[Richard],
The First Automatic Method for Mapping the Pothole in Seagrass,
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

Urbanski, J.A.,
Using ArcGIS Model Builder for object-based image classification of seagrass meadows,
PDF File. 0607

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Last update:Oct 19, 2020 at 15:02:28