Landsat-derived estimates of mangrove extents in the Sierra Leone coastal landscape complex during 1990-2016

Sensors (Switzerland)

Volumn 18, Issue 1, 2018, Pages

  Mondal, Pinki ^a   Trzaska, Sylwia ^a   De Sherbinin, Alex ^a  

^a Center for International Forestry Research   (United States)

Author keywords

Landsat; Low elevation coastal zone; Mangrove; Spatiotemporal change; West Africa

Indexed keywords

COASTAL ZONES; ECOSYSTEMS; REMOTE SENSING;

COMPUTATIONAL TECHNIQUE; HIGH RESOLUTION IMAGE; LANDSAT; MANAGEMENT STRATEGIES; MANGROVE; SPATIO-TEMPORAL CHANGES; UNSUPERVISED CLASSIFICATION; WEST AFRICA;

ESTUARIES;

ARTICLE; COASTAL WATERS; ESTUARY; FIELD STUDY; LAND USE; MANGROVE; NONHUMAN; QUANTITATIVE ANALYSIS; REGENERATION; SATELLITE IMAGERY; SEASHORE; SIERRA LEONE;

EID: 85039710755     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s18010012     Document Type: Article

References (57)

1. Giri, C.; Ochieng, E.; Tieszen, L.L.; Zhu, Z.; Singh, A.; Loveland, T.; Masek, J.; Duke, N. Status and distribution of mangrove forests of the world using earth observation satellite data. Glob. Ecol. Biogeogr. 2011, 20, 154-159.
2. Murdiyarso, D.; Purbopuspito, J.; Kauffman, J.B.; Warren, M.W.; Sasmito, S.D.; Donato, D.C.; Manuri, S.; Krisnawati, H.; Taberima, S.; Kurnianto, S. The potential of Indonesian mangrove forests for global climate change mitigation. Nat. Clim. Chang. 2015, 5, 1089-1092.
3. Danielsen, F.; Sørensen, M.K.; Olwig, M.F.; Selvam, V.; Parish, F.; Burgess, N.D.; Hiraishi, T.; Karunagaran, V.M.; Rasmussen, M.S.; Hansen, L.B. The Asian tsunami: A protective role for coastal vegetation. Science 2005, 310, 643.
4. Kathiresan, K.; Rajendran, N. Coastal mangrove forests mitigated tsunami. Estuar. Coast. Shelf Sci. 2005, 65, 601-606.
5. FAO. The World’s Mangroves 1980-2005; FAO: Rome, Italy, 2007.
6. Ellison, J.C. Climate Change Vulnerability Assessment and Adaptation Planning for Mangrove Systems; World Wildlife Fund (WWF): Washington, DC, USA, 2012.
7. Blasco, F.; Gauquelin, T.; Rasolofoharinoro, M.; Denis, J.; Aizpuru, M.; Caldairou, V. Recent advances in mangrove studies using remote sensing data. Mar. Freshw. Res. 1998, 49, 287-296.
8. Giri, C. Observation and Monitoring of Mangrove Forests Using Remote Sensing: Opportunities and Challenges. Remote Sens. 2016, 8, 783.
9. Heumann, B.W. Satellite remote sensing of mangrove forests: Recent advances and future opportunities. Prog. Phys. Geogr. 2011, 35, 87-108.
10. Almahasheer, H.; Aljowair, A.; Duarte, C.M.; Irigoien, X. Decadal stability of Red Sea mangroves. Estuar. Coast. Shelf Sci. 2016, 169, 164-172.
11. Dan, T.T.; Chen, C.F.; Chiang, S.H.; Ogawa, S. Mapping and change analysis in mangrove forest by using Landsat imagery. In Xxiii Isprs Congress, Commission Viii; Halounova, L., Safar, V., Raju, P.L.N., Planka, L., Zdimal, V., Kumar, T.S., Faruque, F.S., Kerr, Y., Ramasamy, S.M., Comiso, J., et al., Eds.; Copernicus Gesellschaft MBH: Gottingen, Germany, 2016; Volume 3, pp. 109-116.
12. Dutta, D.; Das, P.K.; Paul, S.; Sharma, J.R.; Dadhwal, V.K. Assessment of ecological disturbance in the mangrove forest of Sundarbans caused by cyclones using MODIS time-series data (2001-2011). Nat. Hazards 2015, 79, 775-790.
13. Dutta, D.; Das, P.K.; Paul, S.; Sharma, J.R.; Dhadwal, V.K. Spatio-temporal assessment of ecological disturbance and its intensity in the mangrove forest using MODIS derived disturbance index. In ISPRS Technical Commission Viii Symposium; Dadhwal, V.K., Diwakar, P.G., Seshasai, M.V.R., Raju, P.L.N., Hakeem, A., Eds.; Copernicus Gesellschaft MBH: Gottingen, Germany, 2014; Volume XL-8, pp. 555-559.
14. Fatoyinbo, T.E.; Simard, M.; Washington-Allen, R.A.; Shugart, H.H. Landscape-scale extent, height, biomass, and carbon estimation of Mozambique’s mangrove forests with Landsat ETM+ and Shuttle Radar Topography Mission elevation data. J. Geophys. Res. Biogeosci. 2008, 113.
15. Fromard, F.; Vega, C.; Proisy, C. Half a century of dynamic coastal change affecting mangrove shorelines of French Guiana. A case study based on remote sensing data analyses and field surveys. Mar. Geol. 2004, 208, 265-280.
16. Ghosh, M.K.; Kumar, L.; Roy, C. Mapping Long-Term Changes in Mangrove Species Composition and Distribution in the Sundarbans. Forests 2016, 7, 305.
17. Giri, C.; Long, J.; Abbas, S.; Murali, R.M.; Qamer, F.M.; Pengra, B.; Thau, D. Distribution and dynamics of mangrove forests of South Asia. J. Environ. Manag. 2015, 148, 101-111.
18. Giri, C.; Muhlhausen, J. Mangrove forest distributions and dynamics in Madagascar (1975-2005). Sensors 2008, 8, 2104-2117.
19. Hamilton, S. Assessing the role of commercial aquaculture in displacing mangrove forest. Bull. Mar. Sci. 2013, 89, 585-601.
20. Hirata, Y.; Tabuchi, R.; Patanaponpaiboon, P.; Poungparn, S.; Yoneda, R.; Fujioka, Y. Estimation of aboveground biomass in mangrove forests using high-resolution satellite data. J. For. Res. 2014, 19, 34-41.
21. Kamal, M.; Phinn, S.; Johansen, K. Object-Based Approach for Multi-Scale Mangrove Composition Mapping Using Multi-Resolution Image Datasets. Remote Sens. 2015, 7, 4753-4783.
22. Kamthonkiat, D.; Rodfai, C.; Saiwanrungkul, A.; Koshimura, S.; Matsuoka, M. Geoinformatics in mangrove monitoring: Damage and recovery after the 2004 Indian Ocean tsunami in Phang Nga, Thailand. Nat. Hazards Earth Syst. Sci. 2011, 11, 1851-1862.
23. Kanniah, K.D.; Sheikhi, A.; Cracknell, A.P.; Goh, H.C.; Tan, K.P.; Ho, C.S.; Rasli, F.N. Satellite Images for Monitoring Mangrove Cover Changes in a Fast Growing Economic Region in Southern Peninsular Malaysia. Remote Sens. 2015, 7, 14360-14385.
24. Kirui, K.B.; Kairo, J.G.; Bosire, J.; Viergever, K.M.; Rudra, S.; Huxham, M.; Briers, R.A. Mapping of mangrove forest land cover change along the Kenya coastline using Landsat imagery. Ocean Coast. Manag. 2013, 83, 19-24.
25. Kovacs, J.M.; de Santiago, F.F.; Bastien, J.; Lafrance, P. An Assessment of Mangroves in Guinea, West Africa, Using a Field and Remote Sensing Based Approach. Wetlands 2010, 30, 773-782.
26. Kuenzer, C.; van Beijma, S.; Gessner, U.; Dech, S. Land surface dynamics and environmental challenges of the Niger Delta, Africa: Remote sensing-based analyses spanning three decades (1986-2013). Appl. Geogr. 2014, 53, 354-368.
27. Leimgruber, P.; Kelly, D.S.; Steininger, M.K.; Brunner, J.; Muller, T.; Songer, M. Forest cover change patterns in Myanmar (Burma) 1990-2000. Environ. Conserv. 2005, 32, 356-364.
28. LeMarie, M.; van der Zaag, P.; Menting, G.; Bacluete, E.; Schotanus, D. The use of remote sensing for monitoring environmental indicators: The case of the Incomati estuary, Mozambique. Phys. Chem. Earth 2006, 31, 857-863.
29. Liu, K.; Liu, L.; Liu, H.X.; Li, X.;Wang, S.G. Exploring the effects of biophysical parameters on the spatial pattern of rare cold damage to mangrove forests. Remote Sens. Environ. 2014, 150, 20-33.
30. Macamo, C.C.F.; Massuanganhe, E.; Nicolau, D.K.; Bandeira, S.O.; Adams, J.B. Mangrove’s response to cyclone Eline (2000): What is happening 14 years later. Aquat. Bot. 2016, 134, 10-17.
31. Manna, S.; Mondal, P.P.; Mukhopadhyay, A.; Akhand, A.; Hazra, S.; Mitra, D. Vegetation cover change analysis from multi-temporal satellite data in Jharkhali Island, Sundarbans, India. Indian J. Geo-Mar. Sci. 2013, 42, 331-342.
32. Misra, A.; Murali, R.M.; Vethamony, P. Assessment of the land use/land cover (LU/LC) and mangrove changes along the Mandovi-Zuari estuarine complex of Goa, India. Arab. J. Geosci. 2015, 8, 267-279.
33. Monzon, A.K.; Reyes, S.R.; Veridiano, R.K.; Tumaneng, R.; De Alban, J.D. Synergy of optical and SAR data for mapping and monitoring mangroves. In XXIII ISPRS Congress, Commission VI; Halounova, L., Safar, V., Gong, J., Hanzl, V., Wu, H., Vyas, A., Wang, L., Musikhin, I., Tsai, F., Gruen, A., et al., Eds.; Copernicus Gesellschaft MBH: Gottingen, Germany, 2016; Volume 41, pp. 259-266.
34. Omo-Irabor, O.O.; Olobaniyi, S.B.; Akunna, J.; Venus, V.; Maina, J.M.; Paradzayi, C. Mangrove vulnerability modelling in parts of Western Niger Delta, Nigeria using satellite images, GIS techniques and Spatial Multi-Criteria Analysis (SMCA). Environ. Monit. Assess. 2011, 178, 39-51.
35. Otero, V.; Quisthoudt, K.; Koedam, N.; Dahdouh-Guebas, F. Mangroves at Their Limits: Detection and Area Estimation of Mangroves along the Sahara Desert Coast. Remote Sens. 2016, 8, 512.
36. Reddy, C.S.; Satish, K.V.; Pasha, S.V.; Jha, C.S.; Dadhwal, V.K. Assessment and monitoring of deforestation and land-use changes (1976-2014) in Andaman and Nicobar Islands, India using remote sensing and GIS. Curr. Sci. 2016, 111, 1492-1499.
37. Salami, A.T.; Akinyede, J.; de Gier, A. A preliminary assessment of NigeriaSat-1 for sustainable mangrove forest monitoring. Int. J. Appl. Earth Obs. Geoinf. 2010, 12, S18-S22.
38. Seto, K.C.; Fragkias, M. Mangrove conversion and aquaculture development in Vietnam: A remote sensing-based approach for evaluating the Ramsar Convention on Wetlands. Glob. Environ. Chang. 2007, 17, 486-500.
39. Shapiro, A.C.; Trettin, C.C.; Kuchly, H.; Alavinapanah, S.; Bandeira, S. The Mangroves of the Zambezi Delta: Increase in Extent Observed via Satellite from 1994 to 2013. Remote Sens. 2015, 7, 16504-16518.
40. Wang, L.; Sousa, W.P.; Gong, P. Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery. Int. J. Remote Sens. 2004, 25, 5655-5668.
41. Hamilton, S.E.; Casey, D. Creation of a high spatio-temporal resolution global database of continuous mangrove forest cover for the 21st century (CGMFC-21). Glob. Ecol. Biogeogr. 2016, 25, 729-738.
42. Olson, D.M.; Dinerstein, E.; Wikramanayake, E.D.; Burgess, N.D.; Powell, G.V.N.; Underwood, E.C.; D’amico, J.A.; Itoua, I.; Strand, H.E.; Morrison, J.C.; et al. Terrestrial ecoregions of the world: A new map of life on earth: A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. BioScience 2001, 51, 933-938.
43. Spalding, M.; Kainuma, M.; Collins, L. World Atlas of Mangroves; Earthscan: London, UK, 2010.
44. Hansen, M.C.; Potapov, P.V.; Moore, R.; Hancher, M.; Turubanova, S.A.; Tyukavina, A.; Thau, D.; Stehman, S.V.; Goetz, S.J.; Loveland, T.R.; et al. High-resolution global maps of 21st-century forest cover change. Science 2013, 342, 850-853.
45. Fatoyinbo, T.E.; Simard, M. Height and biomass of mangroves in Africa from ICESat/GLAS and SRTM. Int. J. Remote Sens. 2013, 34, 668-681.
46. World Bank. World Development Indicators. Available online: http://databank.worldbank.org/data/ reports.aspx?source=2&country=SLE (accessed on 31 July 2017).
47. Blinker, L. Country Environment Profile (CEP) Sierra Leone; European Commission: Cardiff, UK, 2006.
48. GoSL (Government of Sierra Leone). Conservation and Wildlife Policy 2010; Government of Sierra Leone: Freetown, Sierra Leone, 2010.
49. Heymans, J.J.; Vakily, J.M. Structure and Dynamics of the Marine Ecosystem off Sierra Leone for Three Time Periods: 1964, 1978, 1990; Fisheries Centre, UBC: Vancouver, BC, Canada, 2004.
50. GCLME (Guinea Current Large Marine Ecosystem). Regional Coordinating Unit. In Towards Ecosystem-Based Management of the Guinea Current Large Marine Ecosystem; United Nations Development Programme (UNDP): New York, NY, USA, 2013.
51. IUCN. Strategies for Conservation and Sustainable Management of Mangrove Forest in Sierra Leone; IUCN: Gland, Switzerland, 2007.
52. Trzaska, S.; de Sherbinin, A.; Kim-Blanco, P.; Mara, V.; Schnarr, E.; Jaiteh, M.; Mondal, P. Climate Change Vulnerability Assessment in Mangrove Regions of Sierra Leone; USAID: Washington, DC, USA, 2017. Available online: http://www.ciesin.columbia.edu/wa-bicc/wa-bicc-ccva-abridged-ff.pdf (accessed on 20 December 2017).
53. Chander, G.; Markham, B.L.; Helder, D.L. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sens. Environ. 2009, 113, 893-903.
54. Zhu, Z.; Wang, S.; Woodcock, C.E. Improvement and expansion of the Fmask algorithm: Cloud, cloud shadow, and snow detection for Landsats 4-7, 8, and Sentinel 2 images. Remote Sens. Environ. 2015, 159, 269-277.
55. Zhu, Z.; Woodcock, C.E. Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sens. Environ. 2012, 118, 83-94.
56. GitHub. fmask. Available online: https://github.com/prs021/fmask (accessed on 31 July 2017).
57. Arthur, D.; Vassilvitskii, S. k-means++: The advantages of careful seeding. In Proceedings of the eighteenth Annual ACM-SIAM Symposium on Discrete Algorithm, Society for Industrial and Applied Mathematics, New Orleans, Louisiana, 7-9 January 2007; pp. 1027-1035.