Skip to main content
SpringerLink
Log in

Spatial Ecology of Mangrove Forests: A Remote Sensing Perspective

  • Chapter
  • First Online:
Mangrove Ecosystems: A Global Biogeographic Perspective

Abstract

Over the past few decades, a diverse range of remote sensing data have been acquired over mangrove areas in different modes and with varying spatial resolutions and temporal frequencies, with these used to advance our understanding of mangrove ecosystems and their response to natural and human-induced change. Detailed information on the floristic composition, structure, biomass and growth stage of mangroves and changes in these attributes over time and at different scales of observation has been obtained and the knowledge gained has been to better inform on, for example, carbon dynamics, floral and faunal diversity, connectivity with adjacent environments, and responses to changing hydrological regimes and climate. Significant opportunities also exist for more effective use of these data for actively managing mangroves and the services they provide and ensuring that they are not overexploited and their integrity within the coastal environment is maintained. The benefits of including these data in mangrove characterization, mapping and monitoring programs are demonstrated using case studies from a wide range of locations, including in Australia, Southeast Asia and central America, and instruments such as radar, lidar and optical sensors. Local to global efforts aimed at monitoring mangrove dynamics using remote sensing data are also increasing, with these leading to more informed decisions in relation to conservation, management and sustainable use.

The authors would like to acknowledge Jorg Hacker of Airborne Research Australia (ARA) for providing LIDAR data for the Gulf of Carpentaria and the Japanese Space Exploration Agency (JAXA) for access to Japanese L-band SAR data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alfaro AC (2010) Effects of mangrove removal on benthic communities and sediment characteristics at Mangawhai Harbour, northern New Zealand. ICES J Mar Sci 67(6):1087–1104

    Article  Google Scholar 

  • Anthony EJ, Gardel A, Proisy C, Fromard F, Gensac E, Peron C, Walcker R, Lesourd S (2013) The role of fluvial sediment supply and river-mouth hydrology in the dynamics of the muddy, Amazon-dominated Amapá–Guianas coast, South America: a three-point research agenda. J S Am Earth Sci 44:18–24. doi:10.1016/j.jsames.2012.06.005

    Article  Google Scholar 

  • Asbridge E, Lucas R, Accad A, Dowling R (2015) Mangrove response to environmental changes predicted under varying climates: case studies from Australia. Curr Forest Rep 1(3):178–194

    Article  Google Scholar 

  • Baret F, Vanderbilt VC, Steven MD, Jacquemoud S (1994) Use of spectral analogy to evaluate canopy reflectance sensitivity to leaf optical properties. Remote Sens Environ 48(2):253–260

    Article  Google Scholar 

  • Bird M, Fifield L, Chua S, Goh B (2004) Calculating sediment compaction for radiocarbon dating of intertidal sediments. Radiocarbon 46(1):421–436

    Article  CAS  Google Scholar 

  • Blaschke T (2010) Object based image analysis for remote sensing. ISPRS J Photogramm Remote Sens 65(1):2–16

    Article  Google Scholar 

  • Blasco F, Gauquelin T, Rasolofoharinoro M, Denis J, Aizpuru M, Caldairou V (1998) Recent advances in mangrove studies using remote sensing data. Mar Freshw Res 49:287–296

    Article  CAS  Google Scholar 

  • Chadwick J (2011) Integrated LiDAR and IKONOS multispectral imagery for mapping mangrove distribution and physical properties. Int J Remote Sens 32(21):6765–6781

    Article  Google Scholar 

  • Chmura GL, Anisfeld SC, Cahoon DR, Lynch JC (2003) Global carbon sequestration in tidal, saline wetland soils. Glob Biogeochem Cycles 17:1111

    Article  Google Scholar 

  • Conchedda G, Durieux L, Mayaux P (2008) An object-based method for mapping and change analysis in mangrove ecosystems. ISPRS J Photogramm Remote Sens 63(5):578–589

    Article  Google Scholar 

  • Couteron P (2002) Quantifying change in patterned semi-arid vegetation by Fourier analysis of digitized aerial photographs. Int J Remote Sens 23:3407–3425

    Article  Google Scholar 

  • Da Cruz CC, Mendoza UN, Queiroz JB, Berrêdo JF, Neto SVDC, Lara RJ (2013) Distribution of mangrove vegetation along inundation, phosphorus, and salinity gradients on the Bragança Peninsula in Northern Brazil. Plant Soil 370(1–2):393–406

    Article  Google Scholar 

  • Davis BA, Jensen JR (1998) Remote sensing of mangrove biophysical characteristics. Geocarto Int 13(4):55–64

    Article  Google Scholar 

  • Demuro M, Chisholm L (2003) Assessment of Hyperion for characterizing mangrove communities. In: Proceedings of the International Conference the AVIRIS 2003 Workshop, pp 18–23

    Google Scholar 

  • Díaz BM, Blackburn GA (2003) Remote sensing of mangrove biophysical properties: evidence from a laboratory simulation of the possible effects of background variation on spectral vegetation indices. Int J Remote Sens 24(1):53–73

    Article  Google Scholar 

  • Dissanayake N, Chandrasekara U (2014) Effects of mangrove zonation and the physicochemical parameters of soil on the distribution of macrobenthic fauna in Kadolkele mangrove forest, a tropical mangrove forest in Sri Lanka. Adv Ecol 2014

    Google Scholar 

  • Eckert S (2012) Improved forest biomass and carbon estimations using texture measures from WorldView-2 satellite data. Remote Sens 4:810–829

    Article  Google Scholar 

  • Ellison JC (1999) Impacts of sediment burial on mangroves. Mar Pollut Bull 37(8):420–426

    Article  Google Scholar 

  • Ellison AM, Mukherjee BB, Karim A (2000) Testing patterns of zonation in mangroves: scale dependence and environmental correlates in the Sundarbans of Bangladesh. J Ecol 88(5):813–824. doi:10.1046/j.1365-2745.2000.00500.x

    Article  Google Scholar 

  • Fatoyinbo TE, Simard M (2013) Height and biomass of mangroves in Africa from ICESat/GLAS and SRTM. Int J Remote Sens 34(2):668–681

    Article  Google Scholar 

  • Feliciano E, Wdowinski S, Potts M (2012) Vegetation structure, tree volume and biomass estimation using terrestrial laser scanning remote sensing: a case study of the mangrove forests in the Everglades National Park. In: AGU Fall Meeting Abstracts, p 0358

    Google Scholar 

  • Feliciano E, Wdowinski S, Potts M (2014) Assessing mangrove above-ground biomass and structure using terrestrial laser scanning: a case study in the Everglades National Park. Wetlands 34(5):955–968. doi:10.1007/s13157-014-0558-6

    Article  Google Scholar 

  • Fromard F (1998) Mangrove research discussion list communication.

    Google Scholar 

  • Fromard F, Vega C, Proisy C (2004) 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 208(2):265–280

    Article  Google Scholar 

  • Gausman H, Allen W, Cardenas R (1969) Reflectance of cotton leaves and their structure. Remote Sens Environ 1(1):19–22

    Article  Google Scholar 

  • Giri C, Pengra B, Zhu Z, Singh A, Tieszen LL (2007) Monitoring mangrove forest dynamics of the Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000. Estuar Coastal Shelf Sci 73(1):91–100

    Article  Google Scholar 

  • Giri C, Ochieng E, Tieszen LL, Zhu Z, Singh A, Loveland T, Masek J, Duke N (2010) Status and distribution of mangrove forests of the world using earth observation satellite data. Glob Ecol Biogeogr 20:154–159

    Article  Google Scholar 

  • Green EP, Mumby PJ (2000) Mapping mangroves. Remote sensing handbook for tropical coastal management. UNESCO Publishing, Paris

    Google Scholar 

  • Green EP, Clark CD, Mumby PJ, Edwards AJ, Ellis A (1998) Remote sensing techniques for mangrove mapping. Int J Remote Sens 19(5):935–956

    Article  Google Scholar 

  • Hardisky M, Gross M, Klemas V (1986) Remote sensing of coastal wetlands. Bioscience 36:453–460

    Google Scholar 

  • Hay T, Gribble N, de Vries C, Danaher K, Dunning M, Hearnden M, Caley P (2005) Methods for monitoring the abundance and habitat of the Northern Australian mud crab Scylla serrata, Fishery report no. 80. Northern Territory Department of Business, Industry and Resource Development, Darwin

    Google Scholar 

  • Heenkenda MK, Joyce KE, Maier SW, Bartolo R (2014) Mangrove species identification: comparing WorldView-2 with aerial photographs. Remote Sens 6(7):6064–6088

    Article  Google Scholar 

  • Held A, Ticehurst C, Lymburner L, Williams N (2003) High resolution mapping of tropical mangrove ecosystems using hyperspectral and radar remote sensing. Int J Remote Sens 24(13):2739–2759

    Article  Google Scholar 

  • Jensen R, Mausel P, Dias N, Gonser R, Yang C, Everitt J, Fletcher R (2007) Spectral analysis of coastal vegetation and land cover using AISA+ hyperspectral data. Geocarto Int 22(1):17–28

    Article  Google Scholar 

  • Jiali F, Kai L, Yuanhui Z, Yong L, Liu L, Meng L (2015) Application of unmanned aerial vehicles to mangrove resources monitoring. Trop Geogr 35:35–42

    Google Scholar 

  • Kamal M (2015) Remote sensing for multi-scale mangrove mapping. The University of Queensland, Brisbane

    Book  Google Scholar 

  • Kamal M, Phinn S (2011) Hyperspectral data for mangrove species mapping: a comparison of pixel-based and object-based approach. Remote Sens 3(10):2222–2242

    Article  Google Scholar 

  • Kamal M, Phinn S, Johansen K (2014) Characterizing the spatial structure of mangrove features for optimizing image-based mangrove mapping. Remote Sens 6(2):984–1006

    Article  Google Scholar 

  • Kamal M, Phinn S, Johansen K (2015) Object-based approach for multi-scale mangrove composition mapping using multi-resolution image datasets. Remote Sens 7(4):4753–4783

    Article  Google Scholar 

  • Kayitakire F, Hamel C, Defourny P (2006) Retrieving forest structure variables based on image texture analysis and IKONOS-2 imagery. Remote Sens Environ 102(3):390–401

    Article  Google Scholar 

  • Knipling EB (1970) Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation. Remote Sens Environ 1(3):155–159

    Article  Google Scholar 

  • Kuenzer C, Tuan VQ (2013) Assessing the ecosystem services value of Can Gio Mangrove Biosphere Reserve: combining earth-observation-and household-survey-based analyses. Appl Geogr 45:167–184

    Article  Google Scholar 

  • Kuenzer C, Bluemel A, Gebhardt S, Quoc TV, Dech S (2011) Remote sensing of mangrove ecosystems: a review. Remote Sens 3(5):878–928

    Article  Google Scholar 

  • Le Toan T, Quegan S, Davidson M, Balzter H, Paillou P, Papathanassiou K, Plummer S, Rocca F, Saatchi S, Shugart H (2011) The BIOMASS mission: mapping global forest biomass to better understand the terrestrial carbon cycle. Remote Sens Environ 115(11):2850–2860

    Article  Google Scholar 

  • Lee S-K, Fatoyinbo TE (2015) TanDEM-X Pol-InSAR inversion for mangrove canopy height estimation. IEEE J Sel Top Appl Earth Obs Remote Sens 8(7):3608–3618

    Article  Google Scholar 

  • Lee SY, Primavera JH, Dahdouh-Guebas F, McKee K, Bosire JO, Cannicci S, Diele K, Fromard F, Koedam N, Marchand C (2014) Ecological role and services of tropical mangrove ecosystems: a reassessment. Glob Ecol Biogeogr 23(7):726–743

    Article  Google Scholar 

  • Leung JY (2015) Habitat heterogeneity determining the macrobenthic infaunal community in a mangrove swamp in South China: implication for plantation and plant invasion. J Coast Res 31(3):624–633

    Article  Google Scholar 

  • Liu K, Li X, Shi X, Wang S (2008) Monitoring mangrove forest changes using remote sensing and GIS data with decision-tree learning. Wetlands 28(2):336–346

    Article  CAS  Google Scholar 

  • Lovelock CE, Sorrell BK, Hancock N, Hua Q, Swales A (2010) Mangrove forest and soil development on a rapidly accreting shore in New Zealand. Ecosystems 13:437–451

    Article  CAS  Google Scholar 

  • Lucas RM, Ellison J, Mitchell A, Donnelly B, Finlayson M, Milne A (2002) Use of stereo aerial photography for quantifying changes in the extent and height of mangroves in tropical Australia. Wetl Ecol Manag 10(2):159–173

    Article  Google Scholar 

  • Lucas RM, Mitchell AL, Rosenqvist A, Proisy C, Melius A, Ticehurst C (2007) The potential of L-band SAR for quantifying mangrove characteristics and change: case studies from the tropics. Aquat Conserv Mar Freshwat Ecosyst 17(3):245–264

    Article  Google Scholar 

  • Lucas R, Rebelo L-M, Fatoyinbo L, Rosenqvist A, Itoh T, Shimada M, Simard M, Souza-Filho PW, Thomas N, Trettin C (2014) Contribution of L-band SAR to systematic global mangrove monitoring. Mar Freshw Res 65(7):589–603

    Article  Google Scholar 

  • Luther DA, Greenberg R (2009) Mangroves: a global perspective on the evolution and conservation of their terrestrial vertebrates. Bioscience 59(7):602–612

    Article  Google Scholar 

  • M’rabu E, Bosire JO, Cannicci S, Koedam N, Dahdouh-Guebas F (2012) Mangrove die-back due to massive sedimentation and its impact on associated biodiversity. In: Meeting on Mangrove Ecology, Functioning and Management (MMM3) 2–6 July 2012, Galle, Sri Lanka, p 104

    Google Scholar 

  • Manson F, Loneragan N, Harch B, Skilleter G, Williams L (2005) A broad-scale analysis of links between coastal fisheries production and mangrove extent: a case-study for northeastern Australia. Fish Res 74(1):69–85

    Article  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

    Article  Google Scholar 

  • Mitchell AL, Lucas RM, Donnelly BE, Pfitzner K, Milne AK, Finlayson M (2007) A new map of mangroves for Kakadu National Park, Northern Australia, based on stereo aerial photography. Aquat Conserv Mar Freshwat Ecosyst 17(5):446–467

    Article  Google Scholar 

  • de la Morinière EC, Nagelkerken I, Van Der Meij H, Van Der Velde G (2004) What attracts juvenile coral reef fish to mangroves: habitat complexity or shade? Mar Biol 144(1):139–145

    Article  Google Scholar 

  • Mougin E, Proisy C, Marty G, Fromard F, Puig H, Betoulle JL, Rudant JP (1999) Multifrequency and multipolarization radar backscattering from mangrove forests. IEEET Trans Geosci Remote Sens 37(1):94–102

    Article  Google Scholar 

  • Mumby P, Edwards A, Arlas-Gonzalez J, Lindeman K, Blackwell P, Gall A, Gorczynska M, Harbone A, Pescod C, Renken H, Wabnitz C, Llewellyn G (2004) Mangroves enhance the biomass of coral reef fish communities in the Caribbean. Nature 427:533–536

    Article  CAS  PubMed  Google Scholar 

  • Murray MR, Zisman SA, Furley PA, Munro DM, Gibson J, Ratter J, Bridgewater S, Minty CD, Place CJ (2003) The mangroves of Belize: part 1 Distribution, composition and classification. For Ecol Manag 174:265–279

    Article  Google Scholar 

  • Myint SW, Giri CP, Wang L, Zhu Z, Gillette SC (2008) Identifying mangrove species and their surrounding land use and land cover classes using an object-oriented approach with a lacunarity spatial measure. GISci Remote Sens 45:188–208

    Google Scholar 

  • Nagelkerken I, Blaber S, Bouillon S, Green P, Haywood M, Kirton L, Meynecke J-O, Pawlik J, Penrose H, Sasekumar A (2008) The habitat function of mangroves for terrestrial and marine fauna: a review. Aquat Bot 89(2):155–185

    Article  Google Scholar 

  • Pascual-Hortal LY, Saura S (2006) Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation. Landsc Ecol 21:959–967

    Article  Google Scholar 

  • Ploton P, Pélissier R, Proisy C, Flavenot T, Barbier N, Rai SN, Couteron P (2012) Assessing above ground tropical forest biomass using Google earth canopy images. Ecol Appl 22(3):993–1003

    Article  PubMed  Google Scholar 

  • Polidoro BA, Carpenter KE, Collins L, Duke NC, Ellison AM, Ellison JC, Farnsworth EJ, Fernando ES, Kathiresan K, Koedam NE (2010) The loss of species: mangrove extinction risk and geographic areas of global concern. PLoS One 5(4):e10095

    Article  PubMed  PubMed Central  Google Scholar 

  • Prasad NV (2011) Remote sensing of mangrove wetlands: concept, methods, ecology, zonation, dynamics. VDM Verlag Dr. Müller, Saarbrucken

    Google Scholar 

  • Proisy C, Mougin E, Fromard F, Karam M (2000) Interpretation of polarimetric radar signatures of mangrove forests. Remote Sens Environ 71(1):56–66

    Article  Google Scholar 

  • Proisy C, Mougin E, Fromard F, Trichon V, Karam MA (2002) On the influence of canopy structure on the polarimetric radar response from mangrove forest. Int J Remote Sens 23(20): 4197-4210

    Google Scholar 

  • Rahman AF, Dragoni D, Didan K, Barreto-Munoz A, Hutabarat JA (2013) Detecting large scale conversion of mangroves to aquaculture with change point and mixed-pixel analyses of high-fidelity MODIS data. Remote Sens Environ 130:96–107

    Article  Google Scholar 

  • Rakotomavo A, Fromard F (2010) Dynamics of mangrove forests in the Mangoky River delta, Madagascar, under the influence of natural and human factors. For Ecol Manag 259(6):1161–1169. doi:10.1016/j.foreco.2010.01.002

    Article  Google Scholar 

  • Ramsey EW III, Jensen JR (1996) Remote sensing of mangrove wetlands: relating canopy spectra to site-specific data. Photogramm Eng Remote Sens 62:939–948

    Google Scholar 

  • Rasolofoharinoro M, Blasco F, Bellan MF, Aizpuru M, Gauquelin T, Denis J (1998) A remote sensing based methodology for mangroves studies in Madagascar. Int J Remote Sens 10(19):1873–1886

    Article  Google Scholar 

  • Reigber A, Moreira A (2000) First demonstration of airborne SAR tomography using multi-baseline L-band data. IEEE Trans Geosci Remote Sens 38(5):2142–2152

    Article  Google Scholar 

  • Rodríguez-Zúñiga MT, Troche-Souza C, Vázquez-Lule AD, Márquez-Mendoza JD, Vázquez-Balderas B, Valderrama-Landeros L, Velázquez-Salazar S, Cruz-López MI, Ressl R, Uribe-Martínez A, Cerdeira-Estrada S, Acosta-Velázquez J, Díaz-Gallegos J, Jiménez-Rosenberg R, Fueyo-Mac Donald LY, Galindo-Leal C (2013) Manglares de México/Extensión, distribución y monitoreo. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad, México

    Google Scholar 

  • Rodríguez-Zúñiga MT, Troche-Souza C, Vázquez-Lule AD, Márquez-Mendoza JD, Vázquez-Balderas B, Valderrama-Landeros L, Velázquez-Salazar S, Uribe-Martínez A, Acosta-Velázquez J, Díaz-Gallegos J, Cruz-López MI, Ressl R (2012) Los Manglares de México: Estado Actual y Establecimiento de un Programa de Monitoreo a Largo Plazo: 2ª y 3era etapas. Informe final del proyecto GQ004. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad. México

    Google Scholar 

  • Rönnbäck P, Troell M, Kautsky N, Primavera JH (1999) Distribution pattern of shrimps and fish among Avicennia and Rhizophora microhabitats in the Pagbilao mangroves, Philippines. Estuar Coastal Shelf Sci 48:223–234

    Article  Google Scholar 

  • Saintilan N, Wilson N, Rogers K, Rajkaran A, Krauss KW (2014) Mangrove expansion and salt marsh decline at mangrove poleward limits. Glob Chang Biol 20(1):147–157

    Article  PubMed  Google Scholar 

  • Sanders CJ, Smoak JM, Naidu AS, Sanders LM, Patchineelam SR (2010) Organic carbon burial in a mangrove forest, margin and intertidal mud flat. Estuar Coastal Shelf Sci 90(3):168–172. doi:10.1016/j.ecss.2010.08.013

    Article  CAS  Google Scholar 

  • Saura S, Torné J (2009) Conefor Sensinode 2.2: a software package for quantifying the importance of habitat patches for landscape connectivity. Environ Model Softw 24(1):135–139. doi:10.1016/j.envsoft.2008.05.005

    Article  Google Scholar 

  • Saura S, Estreguil C, Mouton C, Rodríguez-Freire M (2011) Network analysis to assess landscape connectivity trends: application to European forests (1990–2000). Ecol Indic 11(2):407–416. doi:10.1016/j.ecolind.2010.06.011

    Article  Google Scholar 

  • Simard M, Zhang K, Rivera-Monroy VH, Ross MS, Ruiz PL, Castañeda-Moya E, Twilley RR, Rodriguez E (2006) Mapping height and biomass of mangrove forests in everglades national park with SRTM elevation data. Photogramm Eng Remote Sens 3(72):299–311

    Article  Google Scholar 

  • Smith TJI (1992) Forest structure. Tropical mangrove ecosystems. American Geophysical Union, Washington, DC

    Google Scholar 

  • Spalding M, Kainuma M, Collins L (2010) World atlas of mangroves. Earthscan, London

    Google Scholar 

  • Thomas N, Lucas R, Itoh T, Simard M, Fatoyinbo L, Bunting P, Rosenqvist A (2014) An approach to monitoring mangrove extents through time-series comparison of JERS-1 SAR and ALOS PALSAR data. Wetl Ecol Manag:1–15. doi:10.1007/s11273-014-9370-6

  • Tomlinson PB (1986) The botany of mangroves. Cambridge University Press, Cambridge

    Google Scholar 

  • UNEP (2014) The importance of mangroves to people: a call to action. United Nations Environment Programme World Conservation Monitoring Centre, Cambridge

    Google Scholar 

  • Vaiphasa C, Ongsomwang S, Vaiphasa T, Skidmore AK (2005) Tropical mangrove species discrimination using hyperspectral data: a laboratory study. Estuar Coastal Shelf Sci 65:371–379

    Article  Google Scholar 

  • Vaiphasa C, Skidmore AK, de Boer WF (2006) A post-classifier for mangrove mapping using ecological data. ISPRS J Photogramm Remote Sens 61:1–10

    Article  Google Scholar 

  • Valderrama L, Troche C, Rodriguez MT, Marquez D, Vázquez B, Velázquez S, Vázquez A, Cruz I, Ressl R (2014) Evaluation of mangrove cover changes in Mexico during the 1970–2005 period. Wetlands 34:747–758

    Article  Google Scholar 

  • Vázquez-Lule AD (2012) Exploración de parámetros biofísicos con series de tiempo de productos modis y estimación de biomasa con imágenes de radar en los manglares de laguna Pom Atasta. Tesis Maestria, Campeche y laguna Agua brava, Nayarit, México

    Google Scholar 

  • Verheyden A, Dahdouh-Guebas F, Thomaes K, De Genst W, Hettiarachchi S, Koedam N (2002) High resolution vegetation data for mangrove research as obtained from aerial photography. Remote sensing and GIS in the sustainable management of tropical coastal ecosystems. Environ Dev Sustain 4:113–133

    Google Scholar 

  • Vo QT, Kuenzer C, Ming VQ, Oppelt N (2012) Review of valuation methods for mangrove ecosystem services. J Ecol Indic 23:431–446

    Article  Google Scholar 

  • Vo QT, Oppelt N, Kuenzer C (2013) Remote sensing in mapping mangrove ecosystems – an object-based approach. Remote Sens 5(1):183–201

    Article  Google Scholar 

  • Vo QT, Kuenzer C, Oppelt N (2015) How remote sensing supports mangrove ecosystem service valuation: a case study in Ca Mau Province, Vietnam. Ecosyst Serv 14:67–75

    Article  Google Scholar 

  • Vogt J, Skóra A, Feller IC, Piou C, Coldren G, Berger U (2012) Investigating the role of impoundment and forest structure on the resistance and resilience of mangrove forests to hurricanes. Aquat Bot 97(1):24–29

    Article  Google Scholar 

  • Wang L, Sousa WP, Gong P, Biging GS (2004) Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama. Remote Sens Environ 91:432–440

    Article  Google Scholar 

  • Wang L, Silván-Cárdenas JL, Sousa WP (2008) Neural network classification of mangrove species from multi-seasonal Ikonos imagery. Photogramm Eng Remote Sens 74:921–927

    Article  Google Scholar 

  • Wannasiri W, Nagai M, Honda K, Santitamnont P, Miphokasap P (2013) Extraction of mangrove biophysical parameters using airborne LiDAR. Remote Sens 5:1787–1808

    Article  Google Scholar 

  • Wolanski E (1995) Transport of sediment in mangrove swamps. Hydrobiologia 295:31–42

    Article  Google Scholar 

  • Yang S-C, Shih S-S, Hwang G-W, Adams JB, Lee H-Y, Chen C-P (2013) The salinity gradient influences on the inundation tolerance thresholds of mangrove forests. Ecol Eng 51:59–65

    Article  Google Scholar 

  • Zhang K, Houle P, Ross M, Ruiz P, Simard M (2006) Airborne laser mapping of mangroves on the Biscayne Bay Coast, Miami, Florida. In: Proceedings of the Geoscience and Remote Sensing Symposium IGARSS 2006, July 31, 2006–August 4, 2006, pp 3750–3754

    Google Scholar 

Download references

Acknowledgement

The authors would like to thank Jorg Hacker of Airborne Research Australia for the provision of the LIDAR mosaic for the Leichardt River.

Author information

Authors and Affiliations

  1. Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, The University of New South Wales, High Street, Kensington, NSW, 2052, Australia

    Richard Lucas & Emma Asbridge

  2. Department of Plant and Soil Sciences, University of Delaware, 531 S. College Avenue, 152 Townsend Hall, Newark, DE, 19716, Mexico

    Alma Vázquez Lule

  3. Geomatics, National Commission for the Knowledge and Use of Biodiversity (CONABIO), 14010, Mexico City, Mexico

    María Teresa Rodríguez

  4. Remote Sensing Research Centre, School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, QLD 4072, Australia

    Muhammad Kamal

  5. Geography and Earth Sciences, Aberystwyth University, Aberystwyth, SY23 3DB, UK

    Nathan Thomas

  6. German Remote Sensing Data Centre, DFD of the German Aerospace Centre, DLR, Oberpfaffenhofen, D-82234, Wessling, Germany

    Claudia Kuenzer

Authors
  1. Richard Lucas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alma Vázquez Lule
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. María Teresa Rodríguez
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Muhammad Kamal
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nathan Thomas
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Emma Asbridge
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Claudia Kuenzer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Richard Lucas .

Editor information

Editors and Affiliations

  1. Department of Oceanography and Coastal Sciences, College of the Coast and Environment, Louisiana State University, Baton Rouge, Louisiana, USA

    Victor H. Rivera-Monroy

  2. School of Environment, Griffith University, Southport, Queensland, Australia

    Shing Yip Lee

  3. Department of Biology, University of Southern Denmark, Odense, Denmark

    Erik Kristensen

  4. Department of Oceanography and Coastal Sciences, College of the Coast and Environment, Louisiana State University, Baton Rouge, Louisiana, USA

    Robert R. Twilley

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Lucas, R. et al. (2017). Spatial Ecology of Mangrove Forests: A Remote Sensing Perspective. In: Rivera-Monroy, V., Lee, S., Kristensen, E., Twilley, R. (eds) Mangrove Ecosystems: A Global Biogeographic Perspective. Springer, Cham. https://doi.org/10.1007/978-3-319-62206-4_4

Download citation

Publish with us

Policies and ethics

Search

Navigation