Contribution of L-band SAR to systematic global mangrove monitoring
Richard Lucas A M , Lisa-Maria Rebelo B , Lola Fatoyinbo C , Ake Rosenqvist D , Takuya Itoh E , Masanobu Shimada F , Marc Simard G , Pedro Walfir Souza-Filho H , Nathan Thomas A , Carl Trettin I , Arnon Accad J , Joao Carreiras K and Lammert Hilarides L
+ Author Affiliations
- Author Affiliations
A Centre for Ecosystem Science, The University of New South Wales, High Street, Kensington, NSW 2052, Australia.
B International Water Management Institute, Regional Office for Southeast Asia and the Mekong, PO Box 4199, Vientiane, Lao People’s Democratic Republic.
C Biospheric Sciences Laboratory, Code 618, NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, USA.
D Solo Earth Observation (soloEO), TTT Mid-Tower 5006, Kachidoki 6-3-2, Chuo-ku,Tokyo 104-0054, Japan.
E Remote Sensing Technology Center of Japan (RESTEC), Roppongi First Building 12F, 1-9-9 Roppongi, Minato-ku, Tokyo 106-0032, Japan.
F Japan Aerospace Exploration Agency, Earth Observation Research Center, Sengen 2-1-1 Tsukuba Ibaraki, 305-8505, Japan.
G Jet Propulsion Laboratory, MS 300-319D, 4800 Oak Grove Drive, Pasadena, California (CA 90039), USA.
H Universidade Federal do Pará Instituto de Geociências, Av. Augusto Correa 1, Caixa Postal 8608, CEP. 66075-110, Belém, Pará, Brasil; and Vale Institute of Tecnology, Rua Boaventura da Silva 955, 66055-090, Belém, Brazil.
I Center for Forested Wetlands Research, US Forest Service, Southern Research Station, 3734 Hwy 402, Cordesville, SC 29434, USA.
J Queensland Herbarium, Department of Science, Information Technology, Innovation and the Arts, Brisbane Botanic Gardens, Mt Coot-tha, Mt Coot-tha Road, Toowong, Qld 4066, Australia.
K Tropical Research Institute, Travessa do Conde da Ribeira, 9, 1400-142, Lisbon, Portugal.
L Wetlands International, PO Box 471, 6700 AL, Wageningen, The Netherlands.
M Corresponding author. Email: rml@aber.ac.uk
Marine and Freshwater Research 65(7) 589-603 https://doi.org/10.1071/MF13177
Submitted: 5 July 2013 Accepted: 23 January 2014 Published: 20 June 2014
Abstract
Information on the status of and changes in mangroves is required for national and international policy development, implementation and evaluation. To support these requirements, a component of the Japan Aerospace Exploration Agency’s (JAXA) Kyoto and Carbon (K&C) initiative has been to design and develop capability for a Global Mangrove Watch (GMW) that routinely monitors and reports on local to global changes in the extent of mangroves, primarily on the basis of observations by Japanese L-band synthetic aperture radar (SAR). The GMW aims are as follows: (1) to map progression of change within or from existing (e.g. Landsat-derived) global baselines of the extent of mangroves by comparing advanced land-observing satellite 2 (ALOS-2) phased array L-band SAR 2 (PALSAR-2) data from 2014 with that acquired by the Japanese earth resources satellite (JERS-1) SAR (1992–1998) and ALOS PALSAR (2006–2011); (2) to quantify changes in the structure and associated losses and gains of carbon on the basis of canopy height and above-ground biomass (AGB) estimated from the shuttle radar topographic mission (SRTM; acquired 2000), the ice, cloud and land-elevation satellite (ICESAT) geoscience laser altimeter system (GLAS; 2003–2010) and L-band backscatter data; (3) to determine likely losses and gains of tree species diversity through reference to International Union for the Conservation of Nature (IUCN) global thematic layers on the distribution of mangrove species; and (4) to validate maps of changes in the extent of mangroves, primarily through comparison with dense time-series of Landsat sensor data and to use these same data to describe the causes and consequences of change. The paper outlines and justifies the techniques being implemented and the role that the GMW might play in supporting national and international policies that relate specifically to the long-term conservation of mangrove ecosystems and the services they provide to society.
Additional keywords: climate change, forest dynamics, international conventions, remote sensing.
References
Allison, M. A., and Lee, M. T. (2004). Sediment exchange between Amazon mudbanks and shore-fringing mangroves in French Guiana. Marine Geology 208, 169–190.| Sediment exchange between Amazon mudbanks and shore-fringing mangroves in French Guiana.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXmtlSjsrs%3D&md5=f6b6592f0488bc0fe2e2bf831fd61ddbCAS |
Alongi, D. (2008). Mangrove forests: resilience, protection from tsunamis, and responses to global climate change. Estuarine, Coastal and Shelf Science 76, 1–13.
| Mangrove forests: resilience, protection from tsunamis, and responses to global climate change.Crossref | GoogleScholarGoogle Scholar |
Bandaranayake, W. M. (1998). Traditional and medicinal uses of mangroves. Mangroves and Salt Marshes 2, 133–148.
| Traditional and medicinal uses of mangroves.Crossref | GoogleScholarGoogle Scholar |
Barbier, E. B., and Cox, M. (2004). An economic analysis of shrimp farm expansion and mangrove conversion in Thailand. Land Economics 80, 389–407.
| An economic analysis of shrimp farm expansion and mangrove conversion in Thailand.Crossref | GoogleScholarGoogle Scholar |
Beaumont, L. J., Pitman, A., Perkins, S., Zimmermann, N. E., Yoccoz, N. G., and Thuiller, W. (2011). Impacts of climate change on the world’s most exceptional ecoregions. Proceedings of the National Academy of Sciences, USA 108, 2306–2311.
| Impacts of climate change on the world’s most exceptional ecoregions.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXitFKqtbo%3D&md5=cb76190e644c9760e9359bd299ec0221CAS |
Butchart, S., Walpole, M., Collen, B., van Strien, A., Scharlemann, J. P. W., Almond, R. E. A., Baillie, J. E. M., Bomhard, B., Brown, C., Bruno, J., Carpenter, K. E., Carr, G. M., Chanson, J., Chenery, A. M., Csirke, J., Davidson, N. C., Dentener, F., Foster, M., Galli, A., Galloway, J. N., Genovesi, P., Gregory, R. D., Hockings, M., Kapos, V., Lamarque, J.-F., Leverington, F., Loh, J., McGeoch, M. A., McRae, L., Minasyan, A., Morcillo, M. H., Oldfield, T. E. E., Pauly, D., Quader, S., Revenga, C., Sauer, J. R., Skolnik, B., Spear, D., Stanwell-Smith, D., Stuart, S. N., Symes, A., Tierney, M., Tyrrell, T. D., Vié, J.-C., and Watson, R. (2010). Global biodiversity: indicators of recent declines. Science 328, 1164–1168.
| Global biodiversity: indicators of recent declines.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXmsVGjsb0%3D&md5=29e46a1a2b14e9e0347722cd09fea1a2CAS | 20430971PubMed |
Convention on Biological Diversity (2010). ‘Decision X/3, the Strategic Plan for Biodiversity, 2011–2020 and the Aichi Biodiversity Targets.’ (Nagoya, Japan.), CBD Secretariat, Montreal, Canada.
Comley, B. W. T., and McGuinness, K. A. (2005). Above and below ground biomass, and allometry, of four common northern Australian mangroves. Australian Journal of Botany 53, 431–436.
| Above and below ground biomass, and allometry, of four common northern Australian mangroves.Crossref | GoogleScholarGoogle Scholar |
Daru, B. H., Yessoufou, K., Mankga, L. T., and Davies, J. (2013). A global trend towards the loss of evolutionarily unique species in mangrove ecosystems. PLoS ONE , .
| A global trend towards the loss of evolutionarily unique species in mangrove ecosystems.Crossref | GoogleScholarGoogle Scholar | 23805263PubMed |
Dittmar, T., Hertkorn, N., Kattner, G., and Lara, R. J. (2006). Mangroves, a major source of dissolved organic carbon to the oceans. Global Biogeochemical Cycles 20, GB1012.
| Mangroves, a major source of dissolved organic carbon to the oceans.Crossref | GoogleScholarGoogle Scholar |
Donato, D.C., Kauffman, B., Murdiyarso, D., Kurnianto, S., Stidham, M., and Kanninem, M. (2011). Mangroves among the most carbon-rich forests in the tropics. Nature Geoscience 4, 293–297.
| Mangroves among the most carbon-rich forests in the tropics.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXltlyrsb4%3D&md5=73ef4c210daba22f3b474ff3574c0399CAS |
Fatoyinbo, T. E., and Simard, M. (2013). Height and biomass of mangroves in Africa from ICESat/GLAS and SRTM International Journal of Remote Sensing 34, 668–681.
| Height and biomass of mangroves in Africa from ICESat/GLAS and SRTMCrossref | GoogleScholarGoogle Scholar |
Fatoyinbo, T. E., Simard, M., Washington-Allen, R. A., and Shugart, H. H. (2008). Landscape-scale extent, height, biomass, and carbon estimation of Mozambique’s mangrove forests with Landsat ETM+ and shuttle radar topography mission elevation data. Journal of Geophysical Research 113, G02S06.
| Landscape-scale extent, height, biomass, and carbon estimation of Mozambique’s mangrove forests with Landsat ETM+ and shuttle radar topography mission elevation data.Crossref | GoogleScholarGoogle Scholar |
Finlayson, C. M., Davidson, N. C., Spiers, A. G., and Stevenson, N. J. (1999). Global wetland inventory – current status and future priorities. Marine and Freshwater Research 50, 717–727.
Food and Agricultural Organisation (FAO) (2007). ‘The World’s Mangroves, 1980–2005. FAO Forestry Paper 153.’ (FAO: Rome.)
Food and Agricultural Organisation (FAO) (2010). ‘Global Forest Resources Assessment: Main Report. FAO Forestry Paper 163.’ (FAO: Rome.)
Giri, C., Zhu, Z., Tieszen, L. L., Singh, A., Gillette, S., and Kelmelis, J. A. (2008). Mangrove forest distributions and dynamics (1975–2005) of the tsunami-affected region of Asia. Journal of Biogeography 35, 519–528.
| Mangrove forest distributions and dynamics (1975–2005) of the tsunami-affected region of Asia.Crossref | GoogleScholarGoogle Scholar |
Giri, G., Ochieng, E., Tieszen, L. L., Zhu, Z., Singh, A., Loveland, T., Masek, J., and Duke, N. (2011). Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecology and Biogeography 20, 154–159.
| Status and distribution of mangrove forests of the world using earth observation satellite data.Crossref | GoogleScholarGoogle Scholar |
Glaser, M. (2003). Interrelations between mangrove ecosystem, local economy and social sustainability in Caeté Estuary, north Brazil. Wetlands Ecology and Management 11, 265–272.
| Interrelations between mangrove ecosystem, local economy and social sustainability in Caeté Estuary, north Brazil.Crossref | GoogleScholarGoogle Scholar |
Guimarães, A. S., Travassos, P., Souza-Filho, P. W. M., Gonçalves, F. D., and Costa, F. (2010). Impact of aquaculture on mangrove areas in the northern Pernambuco Coast (Brazil) using remote sensing and geographic information system. Aquaculture and Research 41, 828–838.
| Impact of aquaculture on mangrove areas in the northern Pernambuco Coast (Brazil) using remote sensing and geographic information system.Crossref | GoogleScholarGoogle Scholar |
Heinsohn, G. E., Marsh, H., and Anderson, P. K. (1979). Australian dugong. Oceans 12, 48–52.
Held, A., Ticehurst, C., Lymburner, L., and Williams, N. (2003). High resolution mapping of tropical mangrove ecosystems using hyperspectral and radar remote sensing. International Journal of Remote Sensing 24, 2739–2759.
| High resolution mapping of tropical mangrove ecosystems using hyperspectral and radar remote sensing.Crossref | GoogleScholarGoogle Scholar |
Hogarth, P. J. (1999). ‘The Biology of Mangroves.’ (Oxford University Press: Oxford, UK.)
Hutchison, J., Manica, A., Swetnam, R., Balmford, A., and Spalding, M. (2013). Predicting global patterns in mangrove forest biomass. Conservation Letters , .
IUCN (2014). IUCN Red List of Threatened Species, Version 2010.4. http://www.iucnredlist.org/technical-documents/spatial-data#mangrove
Japan Aerospace Exploration Agency (JAXA) (2013). ‘K&C Global Mangrove Watch.’ Available at http://www.eorc.jaxa.jp/ALOS/en/kyoto/mangrovewatch.htm. [Accessed 16 April 2013]
Lawrence, A. (2012). Blue carbon: a new concept for reducing the impacts of climate change by conserving coastal ecosystems in the coral triangle. WWF Australia report, Brisbane, Australia.
Lucas, R. M., Mitchell, A., Donnelly, B., Milne, A. K., Ellison, J., and Finlaysson, M. (2002). Use of stereo aerial photography for assessing changes in the extent and height of mangrove canopies in tropical Australia. Wetlands Ecology and Management 10, 159–173.
| Use of stereo aerial photography for assessing changes in the extent and height of mangrove canopies in tropical Australia.Crossref | GoogleScholarGoogle Scholar |
Lucas, R. M., Mitchell, A. L., Rosenqvist, A., Proisy, C., Melius, A., and Ticehurst, C. (2007). The potential of L-band SAR for quantifying mangrove characteristics and change: case studies from the tropics. Aquatic Conservation: Marine and Freshwater Ecosystems 17, 245–264.
| The potential of L-band SAR for quantifying mangrove characteristics and change: case studies from the tropics.Crossref | GoogleScholarGoogle Scholar |
MacKay, H., Finlayson, C. M., Fernandez-Prieto, D., Davidson, N., Pritchard, D., and Rebelo, L.-M. (2009). The role of earth observation (EO) technologies in supporting implementation of the Ramsar Convention on Wetlands Journal of Environmental Management 90, 2234–2242.
| The role of earth observation (EO) technologies in supporting implementation of the Ramsar Convention on WetlandsCrossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD1MzivFylug%3D%3D&md5=a4d1f95d12593dab1cb04fa1782df272CAS | 18462862PubMed |
Martin, T. E., and Finch, D. M. (1995). ‘Ecology and Management of Neotropical Migratory Birds: a Synthesis and Review of Critical Issues.’ (Oxford University Press: Oxford, UK.)
Millenium Ecosystem Assessment (MEA) (2005). ‘Ecosystems and Human Well-being: Wetlands and Water. Synthesis.’ (World Resources Institute: Washington DC.)
Mitchell, A. L., Lucas, R. M., Donnelly, B. E., Pfizner, K., Milne, A. K., and Finlayson, M. (2007). A new map of mangroves for Kakadu National Park, northern Australia, based on stereo aerial photography. Wetlands Ecology and Management 17, 446–467.
Mumby, P. J. (2006). Connectivity of reef fish between mangroves and coral reefs: algorithms for the design of marine reserves at seascape scales. Biological Conservation 128, 215–222.
| Connectivity of reef fish between mangroves and coral reefs: algorithms for the design of marine reserves at seascape scales.Crossref | GoogleScholarGoogle Scholar |
Murray, B. C., Pendleton, L., Jenkins, W. A., and Sifleet, S. (2012). Green payments for blue carbon. Economic incentives for protecting threatened coastal habitats. Report N1 R 11-04. Nicholas Institute for Environmental Policy Solutions. Durham, NC 27708, USA.
Nascimento, W. R., Souza-Filho, P. W. M., Proisy, C., Lucas, R. M., and Rosenqvist, A. (2013). Mapping changes in the largest continuous Amazonian mangrove belt using object-based classification of multisensor satellite imagery. Estuarine, Coastal and Shelf Science 117, 83–93.
| Mapping changes in the largest continuous Amazonian mangrove belt using object-based classification of multisensor satellite imagery.Crossref | GoogleScholarGoogle Scholar |
Naylor, R. L., Goldburg, R. J., Primavera, J. H., Kautsky, N., Beveridge, M. C. M., Clay, J., Folke, C., Lubchenco, J., Mooney, H., and Troell, M. (2000). Effect of aquaculture on world fish supplies. Nature 405, 1017–1024.
| 1:CAS:528:DC%2BD3cXkvFKlsrg%3D&md5=942a6768b2dc6ad88e5531499021dc21CAS | 10890435PubMed |
Allen, J. A., Ewel, K. C., and Jack, J. (2001). Patterns of natural and anthropogenic disturbance of the mangroves on the Pacific Island of Kosrae. Wetlands Ecology and Management 9, 291–301.
Neukermans, G., Dahdouh-Guebas, F., Kairo, J. G., and Koedam, N. (2008). Mangrove species and stand mapping in Gazi Bay (Kenya) using Quickbird satellite imagery. Journal of Spatial Science 53, 75–86.
| Mangrove species and stand mapping in Gazi Bay (Kenya) using Quickbird satellite imagery.Crossref | GoogleScholarGoogle Scholar |
Omar, H., Hamzah, K. A., and Ismail, M. H. (2014). L-band ALOS PALSAR for biomass estimation of Matang mangroves, Malaysia. Remote Sensing of Environment , .
Pereira, H. M., Ferrier, S., Walters, M., Geller, G., Jongman, R. H. G., Scholes, R. J., Bruford, M. W., Brummitt, N., Butchart, S. H. M., Cardoso, A. C., Coops, N. C., Dulloo, E., Faith, D. P., Freyhof, J., Gregory, R. D., Heip, C., Höft, R., Hurtt, G., Jetz, W., Karp, D. S., McGeoch, M. A., Obura, D., Onoda, Y., Pettorelli, N., Reyers, B., Sayre, R., Scharlemann, J. P. W., Stuart, S. N., Turak, E., Walpole, M., and Wegmann, M. (2013). Essential biodiversity variables Science 339, 277–278.
| Essential biodiversity variablesCrossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhslagsbc%3D&md5=2538bab1f7d8a2053bfbf4bcb860d7b0CAS | 23329036PubMed |
Polidoro, B. A., Carpenter, K. E., Collins, L., Duke, N. C., Ellison, A. M., Ellison, J. C., Farnsworth, E. J., Fernando, E. S., Kathiresan, K., Koedam, N. E., Livingstone, S. R., Miyagi, T., Moore, G. E., Ngoc Nam, V., Ong, J. E., Primavera, J. H., Salmo, S. G., Sanciangco, J. C., Sukardjo, S., Wang, Y., and Yong, J. W. H. (2010). The loss of species: mangrove extinction risk and geographic areas of global concern. PLoS ONE 5, e10095.
| The loss of species: mangrove extinction risk and geographic areas of global concern.Crossref | GoogleScholarGoogle Scholar | 20386710PubMed |
PRCM (2012). ‘Strategy 2012–2016.’ Available at http://prcmarine.org/new/sites/all/images/PRCM-Strategie-2012-2016-final-eng-synthese.pdf. [Accessed 24 December 2013]
Proisy, C., Couteron, P., and Fromard, F. (2007). Predicting and mapping mangrove biomass from canopy grain analysis using Fourier-based textural ordination of IKONOS images. Remote Sensing of Environment 109, 379–392.
| Predicting and mapping mangrove biomass from canopy grain analysis using Fourier-based textural ordination of IKONOS images.Crossref | GoogleScholarGoogle Scholar |
Ramsar (2005). ‘Resolution IX.1 Annex D, Resolution IX.1 Annex D: Ecological ‘Outcome-oriented’ Indicators for Assessing the Implementation Effectiveness of the Ramsar Convention. Available at http://www.ramsar.org/cda/en/ramsar-documents-resol-resolution-ix-1-annex-d/main/ramsar/1-31-107%5E23547_4000_0__. [Accessed 13 May 2013]
Ramsar (2012). ‘Resolution XI.6, Partnerships and Synergies with Multilateral Environmental Agreements and Other Institutions.’ (Ramsar: Bucharest, Romania.) Available at http://www.ramsar.org/cda/en/ramsar-documents-cops-cop11-cop11-resolutions/main/ramsar/1-31-58-500%5E25837_4000_0__. [Accessed 13 May 2013]
Rasolofoharinoro, M., Blasco, F., Bellan, M. F., Aizpuru, M., Gauquelin, T., and Denis, J. A. (1998). Remote sensing based methodology of mangrove studies in Madagascar. International Journal of Remote Sensing 19, 1873–1886.
| Remote sensing based methodology of mangrove studies in Madagascar.Crossref | GoogleScholarGoogle Scholar |
Rosenqvist, A., Shimada, M., Chapman, B., Freeman, A., De Grandi, G., Saatchi, S., and Rauste, Y. (2000). The global rain forest mapping : a review. International Journal of Remote Sensing 21, 1375–1387.
| The global rain forest mapping : a review.Crossref | GoogleScholarGoogle Scholar |
Rosenqvist, A., Shimada, M., and Watanabe, M. (2007a). ALOS PALSAR: a pathfinder mission for global-scale monitoring of the environment. IEEE Transactions on Geoscience and Remote Sensing 45, 3307–3316.
| ALOS PALSAR: a pathfinder mission for global-scale monitoring of the environment.Crossref | GoogleScholarGoogle Scholar |
Rosenqvist, A., Finlayson, M., Lowry, J., and Taylor, D. (2007b). The potential of long wavelength satellite borne radar to support implementation of the Ramsar Wetlands Convention. Journal of Aquatic Conservation: Marine and Freshwater Ecosystems 17, 229–244.
| The potential of long wavelength satellite borne radar to support implementation of the Ramsar Wetlands Convention. Crossref | GoogleScholarGoogle Scholar |
Rosenqvist, A., Shimada, M., Chapman, B., Paillou, P., Hess, L., and Lowry, J. (2010). The Kyoto & Carbon initiative: a brief summary. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing 3, 551–553.
| The Kyoto & Carbon initiative: a brief summary.Crossref | GoogleScholarGoogle Scholar |
Shimada, M., and Ohtaki, T. (2010). Generating large-scale high-quality SAR mosaic datasets: application to PALSAR data for global monitoring. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 3, 637–656.
| Generating large-scale high-quality SAR mosaic datasets: application to PALSAR data for global monitoring.Crossref | GoogleScholarGoogle Scholar |
Shimada, M., Tadono, T., and Rosenqvist, A. (2010). Advanced land observing satellite (ALOS) and monitoring global environmental change. Proceedings of the IEEE 98, 780–799.
| 1:CAS:528:DC%2BC3cXnsl2gu7o%3D&md5=f731fd82ec298a205b771c6cced99eafCAS |
Sandilyan, S., and Kathiresan, K. (2012). Mangrove conservation: a global perspective. Biodiversity and Conservation 21, 3523–3542.
| Mangrove conservation: a global perspective.Crossref | GoogleScholarGoogle Scholar |
Siikamäki, J., Sanchirico, J. N., and Jardine, S. L. (2012). Global economic potential for reducing carbon dioxide emissions from mangrove loss. Proceedings of the National Academy of Sciences, USA (PNAS) Early Edition 109, 14 369–14 374.
| Global economic potential for reducing carbon dioxide emissions from mangrove loss.Crossref | GoogleScholarGoogle Scholar |
Simard, M., Zhang, K. Q., Rivera-Monroy, V. H., Ross, M. S., Ruiz, P. L., Castaneda-Moya, E., Twilley, R. R., and Rodriguez, E. (2006). Mapping height and biomass of mangrove forests in Everglades National Park with SRTM elevation data. Photogrammetric Engineering and Remote Sensing 72, 299–311.
| Mapping height and biomass of mangrove forests in Everglades National Park with SRTM elevation data.Crossref | GoogleScholarGoogle Scholar |
Simard, M., Rivera-Monroy, V. H., Mancera-Pineda, J. E., Castaneda-Moya, E., and Twilley, R. R. (2008). A systematic method for 3d mapping of mangrove forests based on shuttle radar topography mission elevation data, ICESat/GLAS waveforms and field data: application to Cienaga Grande De Santa Marta, Colombia. Remote Sensing of Environment 112, 2131–2144.
| A systematic method for 3d mapping of mangrove forests based on shuttle radar topography mission elevation data, ICESat/GLAS waveforms and field data: application to Cienaga Grande De Santa Marta, Colombia.Crossref | GoogleScholarGoogle Scholar |
Souza-Filho, P. W. M., and Paradella, W. R. (2003). Use of synthetic aperture radar for recognition of coastal geomorphological features, land-use assessment and shoreline changes in Bragança coast, Pará, northern Brazil. Annals of the Brazilian Academy of Sciences 75, 341–356.
| Use of synthetic aperture radar for recognition of coastal geomorphological features, land-use assessment and shoreline changes in Bragança coast, Pará, northern Brazil.Crossref | GoogleScholarGoogle Scholar |
Spalding, M., Blasco, F., and Field, C. (1997). ‘World Mangrove Atlas.’ (International Society for Mangrove Ecosystems: Okinawa, Japan.)
Spalding, M., Kainuma, M., and Collins, L. (2010). ‘World Atlas of Mangroves.’ 2nd edn. (Earthscan: London.)
Vo, Q. T., Kuenzer, C., Vo, Q. M., Moder, F., and Oppelt, N. (2012). Review of valuation methods for mangrove ecosystem services. Ecological Indicators 23, 431–446.
| Review of valuation methods for mangrove ecosystem services.Crossref | GoogleScholarGoogle Scholar |
Wang, L., Sousa-Filho, W. P., and Gong, P. (2004). Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery. International Journal of Remote Sensing 25, 5655–5668.
| Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery.Crossref | GoogleScholarGoogle Scholar |
Wang, L., Silvan-Cardenas, J. L., and Sousa, W. P. (2008). Neural network classification of mangrove species from multi-seasonal IKONOS imagery. Photogrammetric Engineering and Remote Sensing 74, 921–927.
| Neural network classification of mangrove species from multi-seasonal IKONOS imagery.Crossref | GoogleScholarGoogle Scholar |
World Mangrove Network (2012). Western Indian Ocean Mangrove Network/United States Forest Service Workshop report, Maputo, Mozambique, 29–31 October 2012.
Zhu, Z., and Woodcock, C. E. (2012). Continuous monitoring of forest disturbance using all available Landsat imagery. Remote Sensing of Environment 122, 75–91.
| Continuous monitoring of forest disturbance using all available Landsat imagery.Crossref | GoogleScholarGoogle Scholar |
