Sentinel-2 mapping of a turbid intertidal seagrass meadow in Southern Vietnam

References

• Achanta R, Susstrunk S. 2017. Superpixels and polygons using simple non-iterative clustering. In Proceedings of the IEEE conference on computer vision and pattern recognition. 4651–4660.
   Google Scholar
• Baumstark R, Duffey R, Pu R. 2016. Mapping seagrass and colonized hard bottom in Springs Coast, Florida using WorldView-2 satellite imagery. Estuar Coast Shelf Sci. 181:83–92.
   Web of Science ®Google Scholar
• Borfecchia F, Micheli C, Carli F, de Martis SC, Gnisci V, Piermattei V, Belmonte A, de Cecco L, Martini S, Marcelli M. 2013. Mapping spatial patterns of posidonia oceanica meadows by means of daedalus ATM airborne sensor in the coastal area of Civitavecchia (Central Tyrrhenian Sea, Italy). Remote Sens. 5(10):4877–4899. [accessed 2022 November 21].
   Google Scholar
• Cao VL, Nguyen VT, Komatsu T, Nguyen DV, Dam DT. 2012. Status and threats on seagrass beds using GIS in Vietnam. Remote Sens Marine Environ II. 8525(October):852512.
   Google Scholar
• Carpenter S, Byfield V, Felgate SL, Price DM, Andrade V, Cobb E, Strong J, Lichtschlag A, Brittain H, Barry C, et al. 2022. Using unoccupied aerial vehicles (UAVs) to map seagrass cover from sentinel-2 imagery. Remote Sens. 14(3):477. [accessed 2022 November 21].
   Google Scholar
• Costanza R, Arge R, DeGroot R, Farberk S, Grasso M, Hannon B, Limburg K, Naeem S, Neill RVO, Paruelo J, et al. 1997. The value of the world ’ s ecosystem services and natural capital. Nature. 387(May):253–260.
   Google Scholar
• Costanza R, de Groot R, Sutton P, van der Ploeg S, Anderson SJ, Kubiszewski I, Farber S, Turner RK. 2014. Changes in the global value of ecosystem services. Global Environ Change. 26(1):152–158.
   Web of Science ®Google Scholar
• Cullen-Unsworth L, Unsworth R. 2013. Seagrass meadows, ecosystem services, and sustainability. Environment. 55(3):14–28.
   Web of Science ®Google Scholar
• de Groot R, Brander L, van der Ploeg S, Costanza R, Bernard F, Braat L, Christie M, Crossman N, Ghermandi A, Hein L, et al. 2012. Global estimates of the value of ecosystems and their services in monetary units. Ecosyst Serv. 1(1):50–61.
   Web of Science ®Google Scholar
• Dewsbury BM, Bhat M, Fourqurean JW. 2016. A review of seagrass economic valuations: gaps and progress in valuation approaches. Ecosyst Serv. 18:68–77.
   Web of Science ®Google Scholar
• Dierssen HM, Bostrom KJ, Chlus A, Hammerstrom K, Thompson DR, Lee Z. 2019. Pushing the limits of seagrass remote sensing in the turbid waters of Elkhorn Slough, California. Remote Sens (Basel). 11(14):13–15.
   Web of Science ®Google Scholar
• Dierssen HM, Zimmerman RC, Leathers RA, Downes TV, Davis CO. 2003. Ocean color remote sensing of seagrass and bathymetry in the Bahamas Banks by high-resolution airborne imagery. Limnol Oceanogr. 48(1 II):444–455.
   Web of Science ®Google Scholar
• Duarte CM. 2002. The future of seagrass meadows. Environ Conserv. 29(2):192–206.
   Web of Science ®Google Scholar
• Duarte CM, Marbà N, Gacia E, Fourqurean JW, Beggins J, Barrón C, Apostolaki ET. 2010. Seagrass community metabolism: assessing the carbon sink capacity of seagrass meadows. Global Biogeochem Cycles. 24(4):1–8.
   Google Scholar
• Duffy JE, Benedetti-Cecchi L, Trinanes J, Muller-Karger FE, Ambo-Rappe R, Boström C, Buschmann AH, Byrnes J, Coles RG, Creed J, et al. 2019. Toward a Coordinated Global Observing System for Seagrasses and Marine Macroalgae. Front Mar Sci. 6:317. [accessed 2019 July 10].
   Web of Science ®Google Scholar
• Duffy JP, Pratt L, Anderson K, Land PE, Shutler JD. 2018. Spatial assessment of intertidal seagrass meadows using optical imaging systems and a lightweight drone. Estuar Coast Shelf Sci. 200:169–180.
   Web of Science ®Google Scholar
• Dushaw BD, Egbert GD, Worcester PF, Cornuelle BD, Howe BM, Metzger K. 1997. A TOPEX/POSEIDON global tidal model (TPXO.2) and barotropic tidal currents determined from long-range acoustic transmissions. Prog Oceanogr. 40(1–4):337–367.
   Web of Science ®Google Scholar
• Ellis SL, Taylor ML, Schiele M, Letessier TB. 2021. Influence of altitude on tropical marine habitat classification using imagery from fixed-wing, water-landing UAVs. Remote Sens Ecol Conserv. 7(1):50–63. [accessed 2022 January 28].
   Web of Science ®Google Scholar
• Fourqurean JW, Duarte CM, Kennedy H, Marbà N, Holmer M, Mateo MA, Apostolaki ET, Kendrick GA, Krause-Jensen D, McGlathery KJ, et al. 2012. Seagrass ecosystems as a globally significant carbon stock. Nat Geosci. 5(7):505–509.
   Web of Science ®Google Scholar
• Fyfe SK. 2003. Spatial and temporal variation in spectral reflectance: are seagrass species spectrally distinct? Limnol Oceanogr. 48(1 II):464–479.
   Web of Science ®Google Scholar
• Gillanders BM. 2007. Seagrasses, fish, and fisheries. Seagrasses: Biology, Ecology and Conservation. Dordrecht: Springer.
   Google Scholar
• Gray PC, Ridge JT, Poulin SK, Seymour AC, Schwantes AM, Swenson JJ, Johnston DW. 2018. Integrating drone imagery into high resolution satellite remote sensing assessments of estuarine environments. Remote Sens. 10(8):1257.
   Google Scholar
• Green EP, Mumby PJ, Edwards AJ, Clark CD. 2000. Remote sensing handbook for tropical coastal management. United Nations Educational, Scientific and Cultural Organization (UNESCO).
   Google Scholar
• Hansen MC. 2013. High-resolution global maps of 21st-century forest cover change. Science 342:850–854.
   PubMed Web of Science ®Google Scholar
• Hossain MS, Bujang JS, Zakaria MH, Hashim M. 2015. The application of remote sensing to seagrass ecosystems: an overview and future research prospects. Int J Remote Sens. 36(1):61–114.
   Web of Science ®Google Scholar
• Hossain MS, Hashim M. 2019. Potential of Earth Observation (EO) technologies for seagrass ecosystem service assessments. Int J Appl Earth Observ Geoinform. 77:15–29.
   Web of Science ®Google Scholar
• Hossain MS, Hashim M, Bujang JS, Zakaria MH, Muslim AM. 2019. Assessment of the impact of coastal reclamation activities on seagrass meadows in Sungai Pulai estuary, Malaysia, using Landsat data (1994–2017). Int J Remote Sens. 40(9):3571–3605. [accessed 2019 July 10].
   Web of Science ®Google Scholar
• Jia M, Wang Z, Mao D, Ren C, Wang C, Wang Y. 2021. Rapid, robust, and automated mapping of tidal flats in China using time series Sentinel-2 images and Google Earth Engine. Remote Sens Environ. 255:112285.
   Web of Science ®Google Scholar
• Koedsin W, Intararuang W, Ritchie RJ, Huete A. 2016. An integrated field and remote sensing method for mapping seagrass species, cover, and biomass in Southern Thailand. Remote Sens (Basel). 8(4):292.
   Web of Science ®Google Scholar
• Komatsu T, Hashim M, Nurdin N, Noiraksar T, Prathep A, Stankovic M Son T, Thu P, Luong C, Wouthyzen S. 2020. Practical mapping methods of seagrass beds by satellite remote sensing and ground truthing. Coast Mar Sci. 43(1):1–25.
   Google Scholar
• Lacaux JP, Tourre YM, Vignolles C, Ndione JA, Lafaye M. 2007. Classification of ponds from high-spatial resolution remote sensing: application to Rift Valley Fever epidemics in Senegal. Remote Sens Environ. 106(1):66–74.
   Web of Science ®Google Scholar
• Laengner ML, Siteur K, van der Wal D. 2019. Trends in the seaward extent of saltmarshes across Europe from long-term satellite data. Remote Sens 11(14):1653. [accessed 2022 January 28].
   Google Scholar
• Lee Z, Carder KL, Mobley CD, Steward RG, Patch JS. 1999. Hyperspectral remote sensing for shallow waters: 2 Deriving bottom depths and water properties by optimization. Appl Opt. 38(18):3831–3843.
   PubMed Web of Science ®Google Scholar
• Lefebvre A, Thompson CEL, Collins KJ, Amos CL. 2009. Use of a high-resolution profiling sonar and a towed video camera to map a Zostera marina bed, Solent, UK. Estuar Coast Shelf Sci. 82(2):323–334.
   Web of Science ®Google Scholar
• Li Q, Jin R, Ye Z, Gu J, Dan L, He J, Christakos G, Agusti S, Duarte CM, Wu J. 2022. Mapping seagrass meadows in coastal China using GEE. Geocarto Int. [Internet]. Geocarto Int. 37(26):12602-12617.https://www.tandfonline.com/action/showCitFormats?doi=10.1080%2F10106049.2022.2070672.
   Web of Science ®Google Scholar
• Lyons MB, Roelfsema CM, Kennedy EV, Kovacs EM, Borrego-Acevedo R, Markey K, Roe M, Yuwono DM, Harris DL, Phinn SR, et al. 2020. Mapping the world’s coral reefs using a global multiscale earth observation framework. Remote Sens Ecol Conserv. [Internet]6(4):557–568. [accessed 2022 January 28].
   Web of Science ®Google Scholar
• Lyzenga DR. 1978. Passive remote sensing techniques for mapping water depth and bottom features. Appl Opt. 17(3):379–383.
   PubMed Web of Science ®Google Scholar
• Lyzenga DR. 1981. Remote sensing of bottom reflectance and water attenuation parameters in shallow water using aircraft and landsat data. Int J Remote Sens. 2(1):71–82.
   Google Scholar
• Lyzenga DR, Malinas NP, Tanis FJ. 2006. Multispectral bathymetry using a simple physically based algorithm. IEEE Trans Geosci Remote Sens. 44(8):2251–2259.
   Web of Science ®Google Scholar
• Matsunaga T, Hoyano A, Mizukami Y. 2000. Monitoring of coral reefs on Ishigaki Island in Japan using multitemporal remote sensing data. Hyperspectral Remote Sens Ocean. 4154:212–222.
   Google Scholar
• McFeeters SK. 1996. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. Int J Remote Sens. 17(7):1425–1432.
   Web of Science ®Google Scholar
• McLeod E, Chmura GL, Bouillon S, Salm R, Björk M, Duarte CM, Lovelock CE, Schlesinger WH, Silliman BR. 2011. A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Front Ecol Environ. 9(10):552–560.
   Web of Science ®Google Scholar
• Merry K, Bettinger P. 2019. Smartphone GPS accuracy study in an urban environment. PLoS One. 14(7):e0219890.
   Web of Science ®Google Scholar
• Mitra A, Zaman S. 2015. Blue carbon reservoir of the blue planet. (pp. 1-299). New Delhi: Springer.
   Google Scholar
• Miyajima T, Hori M, Hamaguchi M, Shimabukuro H, Adachi H, Yamano H, Nakaoka M. 2015. Geographic variability in organic carbon stock and accumulation rate in sediments of East and Southeast Asian seagrass meadows. Global Biogeochem Cycles. 29(4):397–415.
   Web of Science ®Google Scholar
• Mumby PJ, Clark CD, Green EP, Edwards AJ. 2010. Benefits of water column correction and contextual editing for mapping coral reefs. Int J Remote Sens 19(1):203–210. https://doi.org/10.1080/014311698216521 [Internet]. [accessed 2022 January 28]
   Google Scholar
• Murray NJ, Phinn SR, DeWitt M, Ferrari R, Johnston R, Lyons MB, Clinton N, Thau D, Fuller RA. 2019. The global distribution and trajectory of tidal flats. Nature. 565(7738):222–225.
   PubMed Web of Science ®Google Scholar
• Nahirnick NK, Reshitnyk L, Campbell M, Hessing-Lewis M, Costa M, Yakimishyn J, Lee L. 2019. Mapping with confidence; delineating seagrass habitats using Unoccupied Aerial Systems (UAS). Remote Sens Ecol Conserv. 5(2):121–135. [Internet]. [accessed 2022 January 28].
   Web of Science ®Google Scholar
• Nellemann C, Corcoran E. 2009. Blue carbon : the role of healthy oceans in binding carbon : a rapid response assessment. UNEP/Earthprint.
   Google Scholar
• Nguyen VT. 2008. Seagrass in the South China Sea. Hai Phong, Vietnam: Vietnamese Academy of Science and Technology. 1–36. http://www.unepscs.org/components/com_remository_files/downloads/National-Report-Seagrass-Vietnam.pdf [accessed 2023 March 4].
   Google Scholar
• Nguyen VT. 2013. Nguon loi tham co bien Viet Nam [Seagrass resources of Viet Nam]. Khoa Hoc Tu Nhien va Cong Nghe. 35–67.
   Google Scholar
• Nguyen DTH, Tripathi NK, Gallardo WG, Tipdecho T. 2014. Coastal and marine ecological changes and fish cage culture development in Phu Quoc, Vietnam (2001 to 2011). Geocarto Int. 29(5):486–506.
   Web of Science ®Google Scholar
• Pendleton L, Donato DC, Murray BC, Crooks S, Jenkins WA, Sifleet S, Craft C, Fourqurean JW, Kauffman JB, Marbà N, et al. 2012. Estimating global “blue carbon” emissions from conversion and degradation of vegetated coastal ecosystems. PLoS One. 7(9):e43542.
   Web of Science ®Google Scholar
• Pham TD, Xia J, Ha NT, Bui DT, Le NN, Tekeuchi W. 2019. A review of remote sensing approaches for monitoring blue carbon ecosystems: mangroves, seagrassesand salt marshes during 2010–2018. Sensors (Basel). 19(8):1933.
   Web of Science ®Google Scholar
• Phinn S, Roelfsema C, Kovacs E, Canto R, Lyons M, Saunders M, Maxwell P. 2018. Mapping, monitoring and modelling seagrass using remote sensing techniques. Seagrasses of Australia: Structure, Ecology and Conservation, 445–487.
   Google Scholar
• Price DM, Felgate SL, Huvenne VAI, Strong J, Carpenter S, Barry C, Lichtschlag A, Sanders R, Carrias A, Young A, et al. 2022. Quantifying the intra-habitat variation of seagrass beds with unoccupied aerial vehicles (UAVs). Remote Sens. 14(3):480. [accessed 2022 November 21].
   Google Scholar
• Roelfsema CM, Lyons M, Kovacs EM, Maxwell P, Saunders MI, Samper-Villarreal J, Phinn SR. 2014. Multi-temporal mapping of seagrass cover, species and biomass: a semi-automated object based image analysis approach. Remote Sens Environ. 150:172–187.
   Web of Science ®Google Scholar
• Sagawa T, Boisnier E, Komatsu T, Ben Mustapha K, Hattour A, Kosaka N, Miyazaki S. 2010. Using bottom surface reflectance to map coastal marine areas: a new application method for Lyzenga’s model. Int J Remote Sens. 31(12):3051-3064.
   Web of Science ®Google Scholar
• Sen PK, Kumar Sen P. 1968. Estimates of the regression coefficient based on Kendall’s Tau. J Am Stat Assoc. 63:1379–1389. [accessed 2022 November 21].
   Web of Science ®Google Scholar
• Short FT. 2004. World atlas of seagrasses. Choice Rev. 41(06):41–3160–41-3160.
   Google Scholar
• Stankovic M, Tantipisanuh N, Rattanachot E, Prathep A. 2018. Model-based approach for estimating biomass and organic carbon in tropical seagrass ecosystems. Mar Ecol Prog Ser. 596:61–70. [accessed 2022 April 26].
   Web of Science ®Google Scholar
• Stumpf RP, Holderied K, Sinclair M. 2003. Determination of water depth with high-resolution satellite imagery over variable bottom types. Limnol Oceanogr. 48(1part2):547–556. [accessed 2022 Januay 28].
   Web of Science ®Google Scholar
• Sudo K, Quiros TEAL, Prathep A, van Luong C, Lin HJ, Bujang JS, Ooi JLS, Fortes MD, Zakaria MH, Yaakub SM, et al. 2021. Distribution, temporal change, and conservation status of tropical seagrass beds in Southeast Asia: 2000–2020. Front Mar Sci. 8(July):637722.
   Google Scholar
• Tamondong AM, Blanco AC, Fortes MD, Nadaoka K. 2013. Mapping of seagrass and other benthic habitats in Bolinao, Pangasinan using Worldview-2 satellite image. International Geoscience and Remote Sensing Symposium (IGARSS):1579–1582.
   Google Scholar
• Tamondong AM, Cruz CA, Guihawan J, Garcia M, Quides RR, Cruz JA, Blanco AC. 2018. Remote sensing-based estimation of seagrass percent cover and LAI for above ground carbon sequestration mapping. 1077803.
   Google Scholar
• Theil H. 1950. A rank-invariant method of linear and polynominal regression analysis (Parts 1-3). Ned Akad Wetensch Proc Ser A. 53:1397–1412. [accessed 2022 November 21].
   Google Scholar
• Traganos D, Aggarwal B, Poursanidis D, Topouzelis K, Chrysoulakis N, Reinartz P. 2018. Towards global-scale seagrass mapping and monitoring using Sentinel-2 on Google Earth Engine: the case study of the Aegean and Ionian Seas. Remote Sens (Basel). 10(8):1227.
   Web of Science ®Google Scholar
• Traganos D, Poursanidis D, Aggarwal B, Chrysoulakis N, Reinartz P. 2018. Estimating satellite-derived bathymetry (SDB) with the Google Earth Engine and sentinel-2. Remote Sens (Basel). 10(6):1–18.
   Web of Science ®Google Scholar
• Traganos D, Reinartz P. 2018. Mapping Mediterranean seagrasses with Sentinel-2 imagery. Mar Pollut Bull. 134(March):197–209.
   PubMedGoogle Scholar
• Tucker CJ. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ. 8(2):127–150.
   Web of Science ®Google Scholar
• Uhrin A v, Townsend PA. 2016. Improved seagrass mapping using linear spectral unmixing of aerial photographs. Estuar Coast Shelf Sci. 171:11–22. [accessed 2019 July 3].
   Web of Science ®Google Scholar
• Unsworth RKF, Cullen LC. 2010. Recognising the necessity for Indo-Pacific seagrass conservation. Conserv Lett. 3(2):63–73.
   Web of Science ®Google Scholar
• Unsworth RKF, McKenzie LJ, Collier CJ, Cullen-Unsworth LC, Duarte CM, Eklöf JS, Jarvis JC, Jones BL, Nordlund LM. 2019. Global challenges for seagrass conservation. Ambio. 48(8):801–815. [accessed 2019 June 25].
   PubMed Web of Science ®Google Scholar
• Unsworth RKFF, Ambo-Rappe R, Jones BL, la Nafie YA, Irawan A, Hernawan UE, Moore AM, Cullen-Unsworth LC. 2018. Indonesia’s globally significant seagrass meadows are under widespread threat. Sci Total Environ. 634:279–286.
   PubMed Web of Science ®Google Scholar
• Ventura D, Bonifazi A, Gravina MF, Belluscio A, Ardizzone G, Ventura D, Bonifazi A, Gravina MF, Belluscio A, Ardizzone G. 2018. Mapping and classification of ecologically sensitive marine Habitats Using Unmanned Aerial Vehicle (UAV) Imagery and Object-Based Image Analysis (OBIA). Remote Sens (Basel). 10(9):1331. [accessed 2019 July 2].
   Web of Science ®Google Scholar
• Vinh MK, Shrestha R, Berg H. 2008. GIS-aided marine conservation planning and management: a case study in Phuquoc Island, Vietnam. International Symposium on Geoinformatics for Spatial Infrastructure Development in Earth and Allied Sciences:6.
   Google Scholar
• Vo TT, Lau K, Liao LM, Nguyen XV. 2020. Satellite image analysis reveals changes in seagrass beds at Van Phong Bay, Vietnam during the last 30 years. Aquat Living Resour. 33(May):4.
   Google Scholar
• Waycott M, Duarte CM, Carruthers TJB, Orth RJ, Dennison WC, Olyarnik S, Calladine A, Fourqurean JW, Heck KL, Hughes AR, et al. 2009. Accelerating loss of seagrasses across the globe threatens coastal ecosystems. Proc Natl Acad Sci U S A. 106(30):12377–12381.
   PubMed Web of Science ®Google Scholar
• Wicaksono P, Fauzan MA, Kumara ISW, Yogyantoro RN, Lazuardi W, Zhafarina Z. 2019. Analysis of reflectance spectra of tropical seagrass species and their value for mapping using multispectral satellite images. Int J Remote Sens. 40(23):8955–8978.
   Web of Science ®Google Scholar
• Wicaksono P, Lazuardi W. 2018. Assessment of PlanetScope images for benthic habitat and seagrass species mapping in a complex optically shallow water environment. Int J Remote Sens. 39(17):5739–5765. [Internet]. [accessed 2022 January 28] https://doi.org/10.1080/01431161.2018.1506951
   Web of Science ®Google Scholar
• Xu H. 2006. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens. 27(14):3025–3033.
   Web of Science ®Google Scholar
• Zhao C, Qin CZ, Teng J. 2020. Mapping large-area tidal flats without the dependence on tidal elevations: a case study of Southern China. ISPRS J Photogramm Remote Sens. 159:256–270.
   Web of Science ®Google Scholar
• Zoffoli ML, Gernez P, Rosa P, Le Bris A, Brando VE, Barillé AL, Harin N, Peters S, Poser K, Spaias L, et al. 2020. Sentinel-2 remote sensing of Zostera noltei-dominated intertidal seagrass meadows. Remote Sens Environ. 251:112020.
   Web of Science ®Google Scholar