ARTICLE IN PRESS

Ocean & Coastal Management 49 (2006) 462–475

0964-5691/$ -

doi:10.1016/j

�CorrespoE-mail ad

www.elsevier.com/locate/ocecoaman

Using mangroves as a geological indicator of coastalchanges in the Braganc-a macrotidal flat, Brazilian

Amazon: A remote sensing data approach

Pedro Walfir M. Souza Filho�, Elainy do Socorro Farias Martins,Francisco Ribeiro da Costa

Laboratorio de Analise de Imagens do Tropico Umido, Centro de Geociencias, Universidade Federal do Para,

PO Box 8608, ZEP. 66075-110, Belem, Para, Brazil

Available online 27 June 2006

Abstract

A mangrove ecosystem shows close links between geomorphology and vegetation assemblage. In

addition, the vegetation can change over time as landforms can accrete or erode, which is a direct

response to coastal sedimentary processes. This demonstrates that significant changes can occur on

short time scales and mangroves provide an excellent register of these modifications. Therefore,

mangrove morphology and sedimentation are good indicators of interactions between relative sea

level changes, coastal processes and sediment supply. These interactions are responsible for landward

migration of the shoreline (erosion) and seaward migration of the shoreline (accretion), which is

possible to detect from multi-date satellite data and field observations. Mangroves are one of the best

geo-indicators in global coastal change research and they are an excellent procedure to detect and

quantify coastal modifications.

r 2006 Elsevier Ltd. All rights reserved.

1. Introduction

The Brazilian Amazon coast along the states of Para and Maranhao extends for almost480 km and represents one of the largest mangrove systems in the world, measuring almost8900 km2 [1]. Mangroves are the most prominent tropical ecosystem where geomorpho-logic, sedimentary and oceanographic processes have controlled landscape evolution. This

see front matter r 2006 Elsevier Ltd. All rights reserved.

.ocecoaman.2006.04.005

nding author. Tel.: +55 91 3201 8009; fax: +55 91 32017478.

dress: walfir@ufpa.br (P.W.M. Souza Filho).

ARTICLE IN PRESSP.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475 463

mangrove coast is extremely irregular and jagged with numerous bays and estuaries (Fig.1). The wide coastal plain presents a low gradient and reaches 25 km as a result of relativesea level highstand, associated with rapid muddy progradation of the coast in response toriverine sediment supply [2]. Natural processes and human activities have extensivelymodified mangrove communities [3], and economic and social impacts have increased overthe last two decades [4].

Airborne and orbital remotely sensed data has been extensively used for coastal changemonitoring. Aerial photographs [5], Thematic Mapper (TM) Landsat, HRV SPOT andother higher-resolution sensors [6,7] are useful sources of optical data for coastalgeomorphologic applications. The Landsat 5 TM sensor allows a variety of use, notably innatural resource surveys, land cover and land use, coastal geomorphologic changes andenvironmental monitoring [6–8]. During the last 10 years, Synthetic Aperture Radar(SAR) has been used with more frequency, principally in tropical coastal environments[9–13]. Nowadays, the RADARSAT-1 Fine Mode provides useful data for coastaldynamic studies [14]. These works emphasize the importance of using remote sensed datafor coastal zone mapping and monitoring, which represent an excellent evaluation ofshoreline changes and mapping of areas at risk of coastal erosion.

In recent years there has been much discussion about the natural (physical, chemical andbiological) environment to know what its integrity state is? What is the natural andanthropogenic pressure it has undergone? What is the significance of the changes? Andhow are we responding to the changes—what are we doing about them? [15]. Based on thegeoindicators’ approach, the aim of this paper is to establish the mangrove as one of themost important environmental indicators able to detect and quantify coastal changes inmoist tropical regions.

2. Environmental setting

Mangrove shorelines occur in a number of different environmental settings thatcomprise geophysical (climate, tides and sea level) and geomorphological (dynamic historyof the land surface and contemporary processes and biological components) [16].

The Braganc-a coastal plain has a hot and humid equatorial climate, with well-defineddry (September to December) and wet (January to August) seasons and an annual averageprecipitation around 2550mm [17]. The study area is a tide-dominated settingcharacterized by a semidiurnal macrotidal regime (6m high-tidal range, [18]). There isan extensive (more than 20 km wide) and low-gradient intertidal zone available formangrove colonization that forms a fringe wetland vegetation zone between coastalplateaus and the sea (Fig. 1). Mangrove vegetation is composed of forests with treesreaching up to 20m in height and brackish or marine waters as a result of tidal action thatregularly overflow them. Strong bi-directional tidal currents characterize the Caete Estuarywhich has a funnel-shaped mouth, straight and meandering segments and up-stream tidalchannel [19]. The digital integration of RADARSAT-1 Fine Beam Mode and Landsat TMdata allows the recognition of nineteen geobotanical units in the Braganc-a coastal plain:estuarine channels, submerged sand banks, sandflats, old estuarine sandbanks, mudflats,ebb-tidal deltas, barrier-beach ridges, coastal dunes, chenier sand ridges, young intertidalmangroves, intertidal and supratidal mangroves, outer and inner marshes, fluvial floodplains, coastal plateau, degraded and regenerated mangroves, and an artificial lagoon [13].

ARTICLE IN PRESS

Fig. 1. Localization map based on topographic surface showing a irregular and jagged shoreline in Amazon

mangrove coast, and coastal features observed along the Braganc-a coastal plain.

P.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475464

3. Data sets and methodology

The methodology applied to assess the geomorphologic changes was supported bymulti-date remote-sensed data. The investigation was based on orbital remote-sensed data.The orbital SAR corresponded to C–HH band imagery related to the 1998 RADARSAT-1Fine Mode with a 10-meter nominal ground resolution. Orbital optical data correspond toLandsat 5 TM and SPOT 4 HRV images with nominal resolution around 30m. Table 1provides details of the remotely sensed data.

ARTICLE IN PRESS

Table 1

Characteristics of remotely sensed data

Platform Sensor/bands Acquisition data Spatial resolution (m) Pixel size (m) Image format

Landsat-5 TM 1–5, 7 August 1985 30� 30 30� 30 8-bits

Landsat-5 TM 1–5, 7 October 1988 30� 30 30� 30 8-bits

Landsat-5 TM 1–5, 7 December 1991 30� 30 30� 30 8-bits

Radarsat F1 Fine Mode 1 September 1998 9.1� 8.4 6,25� 6,25 16-bits

Spot 4 HRV pan July 2000 10� 10 10� 10 8-bits

P.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475 465

The digital image processing was carried out based on the PCI Geomatic [20]. Previousstudies in the Amazon have shown that specific approaches with SAR need to be applieddue to the unique radar-viewing geometry, causing specific induced-relief geometricdistortions, and the presence of speckle [21,22]. Due to the fact that the area is related to anextremely low topographic relief, the RADARSAT-1 and Landsat TM images weregeometrically corrected through an ortho-rectification scheme assuming a flat terrainmodel [23,24]. Fifty-one features on the image were selected on the terrain and thecorrespondent geographical information was acquired during a global position system(GPS) field campaign. The ground control points (GCPs) were used as input for thegeometric modeling. The ortho-rectification statistics indicated a total accuracy error asreflected by the Root Mean Square Error (RMSE) residuals around 12m to RADARSATdata and 25m to Landsat TM, and the value of 12m was used as the pixel size for the geo-referenced scene. This geometric correction was based on cubic convolution and UTMgeo-referencing. The radiometric correction of the Landsat TM data was related to theattenuation of atmospheric effects and was based on the minimum histogram pixelapproach [25].

Finally, the images were linearly stretched in order to enhance contrasts between thecoastal features, and visually interpreted based on conventional photo-interpretation keys(tone, texture, pattern, form, size and context).

In order to extract the shoreline position in 1985, 1988, 1990, 1998 and 2000, the imageswere analyzed in Arc View GIS 3.3 and the boundary between mangrove forest and coastalwater was automatically and manually extracted. The resulting land-water limit line onvector format was converted to raster, allowing an effective measurement of spatialcoastline changes using arithmetic spatial analysis along the Braganc-a coastal plainshoreline.

The mangrove ecosystems were mapped from satellite images and field observations.Fieldwork was carried out to detect the sedimentary processes responsible for coastalchanges and geomorphologic modifications observed in the images.

4. Mangroves as a geological indicator of coastal changes

Geoindicators are measures of surface or near-surface geological processes andphenomena that significantly occur over periods of less than one century and that provideinformation that is meaningful for environmental assessment [15]. They measure (mainlyphysics) variations, including those related to climate changes, shoreline positions andgeomorphologic and relative sea level changes. Coastal sedimentary landforms can be used

ARTICLE IN PRESSP.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475466

as geomorphological indicators of the environments and processes responsible for coastalzone development. Coastal zones are very sensitive to environmental changes, but multiplelinkages, feedback mechanisms, nonlinear and possibly chaotic effects combine to produceuncertainty in the meaning of these indicators [26]. There is a wide selection of potentialgeoindicators in the coastal zone, but in the Braganc-a coastal plain, mangroves coverapproximately 471 km2, almost 76.5% of the coastal study area [27]. And besides, amangrove ecosystem is very sensitive to shoreline position, erosional and depositionalprocesses, climate and sea level change.

4.1. Assessing mangrove shoreline position

Mangroves as indicators of shoreline position is derived from remotely sensed imageriesthat were used to detect the shoreline changes between 1985, 1988, 1990, 1998 and 2000.Water line positions depend on water level at the time of observations, which is verydifficult to establish in satellite imageries of macrotidal environments. Therefore, themangrove boundary and the high spring tide water line was used as reference to detectshoreline changes.Based on 1998 RADARSAT-1 and 1972 GEMS 1000 data, the Braganc-a shoreline was

subjected to recession of 31.7870.4 km2 and accretion of 20.6770.4 km2, which represent60.6% of eroded areas compared to 39.4% of added new areas [14]. Therefore, localassessment of mid-term shoreline trends shows an erosional setting in the Braganc-a coastalplain.

Fig. 2. Shoreline changes in the Braganc-a coastal plain from 1985 to 2000.

ARTICLE IN PRESSP.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475 467

Based on data analysis presented in this paper, shoreline changes from 1985 to 2000 aresubjected to strong coastal erosion (Fig. 2). During this period, erosion totaledapproximately 24.26 km2 compared to 20.13 km2 of mangrove development, whichrepresents 55% of eroded areas and 45% of accretionary areas, respectively. The erosionwas focused in a specific place, such as Maiau Point and Buc-ucanga Beach located in theextreme north of the shoreline. Meanwhile, accretionary processes can be observed in thePicanc-o Point, in response to specific geomorphologic configurations.

The shoreline short-term analysis showed that between 1985 and 1988, the Braganc-acoastal plain lost 17.01 km2 (51%) and accreted 16.23 km2 (49%) of mangrove areas(Fig. 3A), showing a light equilibrium profile. Between 1988 and 1991, the region wassubject to 20.64 km2 (62%) of erosion and 12.80 km2 (38%) of accretion (Fig. 3B). From1991 to 1998, mangrove erosion persisted over accretion, and 16.99 km2 (62%) of themangrove was removed, and only 10.55 km2 (38%) grew (Fig. 4A). The last periodanalyzed, from 1998 to 2000, shows the same behavior (15.47 km2—59% of erosion and10.74 km2—41% of accretion), but with lower rates (Fig. 4B).

The high coastal erosion rates observed in restricted points of the coastal zone have beenmonitored and the peak of coastal recession is related to equinoctial spring tides in Marchand September [28,29].

These erosional settings represent the most seaward boundary of the coastal plain (e.g.Maiau Point and Buc-ucanga Beach), which receive little or no muddy sediment, subject tostrong waves and tidal current action. The main sedimentary process responsible for theshoreline retreat is related to sandflats and ebb-tidal delta migration landward over themangrove. Mangrove vegetation has been killed by rapid sand deposition over it and themangrove terrace has been eroded (Fig. 5A). Hence, a significant sector of the shoreline,encompassing mainly, beaches, is characterized as transgressive deposits, where coastaldunes migrate over mangrove deposits (Fig. 5B) [30]. On the other hand, in protectedbarrier-beach ridge areas, it is possible to observe wide and shallow tidal shoals wheremangroves spread directly out to accreting tidal mudflats (Fig. 5C). These progradationalprocesses are responsible for the formation of mangrove fringes and islands over the tidalsand shoals. A good example of this is the island formed in the Rombada Creek (Picanc-oPoint) between 1985 and 2000 in response to sandy tidal shoal accretion (Fig. 2).Afterward, sandbanks are colonized by pioneer vegetation (spartina sp.) that increases therate of mud sedimentation, allowing the vegetated estuarine mouth bar formation. Insummary, shoreline position changes can be widely observed in the study area. Barrier-beach ridges and sandy flats are overlaying the mangrove deposits. Islands have modifiedtheir positions due to sedimentary dynamics in response to oceanographic processes,related to tides, waves and current processes.

4.2. Implications of sea level changes in mangrove and salt marsh evolution

The evolution of the mangrove and salt marsh over the last 5100 years BP suggests thatthese environments are able to achieve sustained vertical and lateral growth under rising orstillstand sea level conditions [30,31]. Mangroves grow in the upper intertidal flat seawardin response to high muddy sediment input. However, in the inner sectors of the coastalplain in contact with coastal plateaus, the mangrove has been less influenced by tidal actionthat has allowed the development of salt marshes followed by supratidal mangrove(Fig. 5D). Therefore, salt marsh represents the geomorphologic, sedimentary and

ARTICLE IN PRESS

Fig. 3. Shoreline changes in the Braganc-a coastal plain from 1985 to 1988 (A) and from 1988 to 1991 (B).

P.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475468

ARTICLE IN PRESS

Fig. 4. Shoreline changes in the Braganc-a coastal plain from 19991 to 1998 (A) and from 1998 to 2000 (B).

P.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475 469

ARTICLE IN PRESS

Fig. 5. Assessment of mangroves as geological indicator to detect coastal changes. (A) High mangrove forest died

due to rapid sand deposition over muddy substrata. (B) Mangrove terrace formed by strong tidal current and

wave attack that produce the shoreline recession. (C) Mangrove succession in response to mud progradation. (D)

Environmental succession of salt marsh overlaid by mangrove prograding landward in response to sea level

changes.

P.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475470

vegetational evolution of the mangrove ecosystem situated in the supratidal zoneinundated only by the equinoctial spring tides.Mangroves have spread seaward in front of salt marshes and other continental

vegetation on terraces formed by muddy sediment accretion. This is due to the existence ofsufficient muddy sediment supply to accrete and maintain the seaward edge. Nowadays,salt marshes are being overlaid by mangroves (Fig. 5D) [32].

4.3. Evaluating risk from coastal hazards

The impact of the natural dynamics and anthropogenic activities in the Braganc-aCoastal Plain has made fast and dramatic changes in the landscape. Critical observationsof large and small-scale coastal geomorphology and vegetation provide clues to the naturalhistory, erosion and accretion degree of the shoreline and potential risk of associatednatural hazards for any specific coastal site [33].Natural clues [3] have presented coastal-hazard risk assessing. Coastal erosion and

overwash are among the most intense short-term processes that have affected the coastalarea. Mangroves constitute low and flat areas bounded by estuaries and barrier-beachridges. Their morphology, vegetation and drainage have been strongly affected bydestructive tidal current and wave attack. On Ajuruteua Island, the barrier-beach ridge hasbeen strongly eroded and shoreline recession has changed the high spring tide linelandward. This process is responsible for houses’ exposure to waves and alongshorecurrent action in the intertidal zone (Fig. 6A). These natural processes have disturbed thelives of fishermen, hotel owners and tourists, due to severe coastal erosion and shoreline

ARTICLE IN PRESS

Fig. 6. Natural and anthropogenic impacts on coastal area. (A) Shoreline recession from Ajuruteua Beach, where

houses are situated in the intertidal zone undergone to waves and currents attack. (B) Mangrove ecosystem

deforestation along Braganc-a-Ajuruteua road.

P.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475 471

recession. Therefore, in erosional barrier-beach ridges, the back mangrove ecosystems havebeen reached and eroded.

The anthropogenic impacts are most related to the opening of roads over the mangrovesto access the beaches (Fig. 6B) and unplanned coastal land use, as well as the deposit ofsolid wastes and groundwater contamination [3]. Along the Braganc-a–Ajuruteua roadthere is an area where the mangrove ecosystems have been deforested and the geological,chemical and biological characteristics have been completely modified. These environ-mental changes are responsible for climatic modifications in mangrove ecosystems, whichwill be very difficult to discern from modifications due to anthropogenic actions andepisodic natural events [34]. Moreover, because mangrove proximity to coastal settlements,

ARTICLE IN PRESSP.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475472

they have been subject to dramatic human stressors responsible for the reduction inmangrove area [35].

4.4. Remote sensing and GIS in coastal zone management

Remote sensing and GIS have been used to study mangrove coasts [e.g., 13,14,27,36,and 37]. During the last decade, significant advances in knowledge and understanding havebeen highlighted, such as, the benefits of high and moderate spatial and spectral resolutiondata, which are better able to match the rich spatial and spectral diversity observed incoastal zones [38]. Distinct from optical sensors (e.g. Landsat TM) which extract thetarget’s information related to chemical composition and physical structure of the materialfrom the reflected sunlight, backscattered microwave energy (e.g. RADARSAT-1) fromthe Earth’s surface measured by a Synthetic Aperture Radar (SAR) provides informationabout the terrain’s physical (macro-topography, slope, roughness) and electrical properties(mainly controlled by the moisture content).As the Amazon coast is subject to rain, cloud, haze and smoke, SAR imageries are a

powerful tool to provide coastal geology information due to the enhancement of theterrain caused by the side-view geometry and all-weather sensing capability [39,40]. Hence,the delineation and changes of coastal zone features can be done in the Amazon coastalzone throughout the year.It is clear that coastal zone monitoring in the Amazon needs to be based on remote

sensing data, which has an active role as a monitoring tool in large and inaccessible areas.In this case we can evaluate the cost-effectiveness of using remote-sensing surveys, whichare based on three primary objectives of space-borne surveys: provide a background tomanagement planning, detect change in coastal environments over time, and planmonitoring strategies [41]. However, we cannot forget that remote-sensing survey needs tobe integrated with field work. It should be seen as complementary information whichmakes field surveys more cost-effective, mainly in moist tropical coastal zones,characterized by wide wetland zones.The low ratio between cost-effectiveness makes the use of remote sensing essential to

coastal managers. Therefore, to use mangroves as geological indicators of coastal changesin the Amazon coastal zone based on remote sensing and GIS analysis allows managers tomake more-informed decisions when coastal erosion becomes a problem, which threatensthe social-economic organization of a city.

5. Conclusions

Mangrove ecosystems have proven to be an excellent geological indicator in the coastalzones to detect and quantify short-term changes. They are a good marker of shorelinechanges in macrotidal dominated settings since they are easily recognized in aerialphotographs, airborne and spaceborne SAR and orbital optical sensor imageries. Theortho-rectification of remote sensing data allows the comparison of images from differentsensors (optical and microwave) on various platforms (airborne and spaceborne), showingan absolute accuracy. Digital image processing permitted the recognition of the coastalsedimentary environments which made mangrove mapping associated to field surveypossible.

ARTICLE IN PRESSP.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475 473

Mangroves as geological indicators usually represents the integrated response of thecoastal zone to a number of interacting geological parameters and environmentalvariables. It may be difficult to establish a single cause of a change in coastal positions,morphology, erosion, human impacts, or a change in the rates, frequency or intensity ofcoastal changes. However, the effective use of mangroves as indicators depends on athorough understanding of coastal processes operating in the study area, such as changesin the sea level, waves, tides, currents, sedimentary dynamics and shoreline displacement.

Coastal managers need to clearly understand that the Amazon River mouth issubmerging [32,42], it is subject to strong wave and tide energy [29], and the shoreline hasbeen moving over the last three decades, as shown in this paper. Hence, coastal managershave got to consider these coastal characteristics to plan, implement and conduct theProgram of Coastal Management in Brazil (GERCO).

There is no doubt that the sensibility of the mangrove ecosystem to register coastalchanges from year to decade time scales make it a potential geological indicator, able todetect and quantify the modification along the coastal zone. Mangroves may be used asqualitative and quantitative indicators for managing a particular stretch of coastlinerelated to natural and human action. Therefore, mangroves as geological indicators shouldhelp us assess environmental changes for attaining sustainability, and for ecosystemmanagement, environmental impact and risk/hazard assessment.

Coastal environment mapping and coastal change detection is an expensive undertakingand using remote sensing data to carry out field surveys is the most accurate and cost-effective way of reaching results for scientific and management purposes. The problem ishow can we use this tool in local initiatives for coastal management? While the officialprogram of coastal management in Brazil (GERCO) has been planned, implemented andconducted by Federal and State agencies, Municipal agencies and traditional organizedcommunities do not have access to technology and sometimes only have access to maps.To solve this problem, coastal managers need to bring the remote sensing technology toMunicipal and Village schools, as a tool of social integration and sustainable developmentbased on education.

Acknowledgments

This work is the result of the Millennium RECOS Project—Use of Coastal Resources(MCT, FINEP, and CNPq), Macrotidal Sandy Beach Project (CNPq Universal Proc. #473097/2003-6) and PIATAM mar Project (Petrobras/COPPETC/UFPA/FADESP 953,CNP CT-Petro Proc. # 502450/03-7). The authors thank the people at the Canadian SpaceAgency (CSA) and Brazilian Institute for Space Research (INPE) for providing theRADARSAT-1 and Landsat TM data, respectively, and to the two anonymous refereesfor reviewing the original manuscript. The author would like to thank CNPq (Brazil) for aresearch grant during this investigation (CNPq process # 303238/2002-0). This paper hasthe PIATAM mar contribution number 3.

References

[1] Kjerfve B, Perillo GME, Gardner LR, Rine JM, Dias GTM, Mochel FR. Morphodynamics of muddy

environments along the Atlantic coasts of North and South America. In: Healy TR, Wang Y, Healy J-A,

ARTICLE IN PRESSP.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475474

editors. Muddy Coasts of the World: Processes, Deposits and Functions. Amsterdam: Elsevier; 2002.

p. 219–39.

[2] Souza Filho PWM, El-Robrini M. As variac- oes do nıvel do mar e a estratigrafia de sequencias da Planıcie

Costeira Bragantina—Nordeste do Para, Brasil. Boletim do Museu Paraense Emılio Goeldi, Serie Ciencias

da Terra 1998;10:1–34.

[3] Souza Filho PWM. Impactos naturais e antropicos na Planıcie Costeira de Braganc-a. In: Prost M, Mendes

AC, editors. Ecossitemas Costeiros: Impactos e Gestao Ambiental. Belem: MPEG/SECTAM; 2001.

p. 133–44.

[4] Lara RJ, Szlafsztein CF, Cohen MC, Berger U, Glaser M. Implications of mangrove dynamics for private

land use in Braganc-a, North Brazil: a case study. Journal of Coastal Conservation 2002;8:97–102.

[5] Lucas RM, Ellison JC, Mitchell A, Donnelly B, Finlayson M, Milne AK. Use of stereo aerial photography

for quantifying changes in the extent and height of mangroves in tropical Australia. Wetlands Ecology and

Management 2002;10:161–75.

[6] Gowda HH, Ganesha Raj K, Padmavathy AS, Manikian B. Multidate satellite data for study of dynamic of

coastal landforms of Uttara Kannada, South India. International Journal of Remote Sensing

1995;16:2539–53.

[7] Ramsey III EW, Nelson GA, Sapkota SK. Classifying coastal resources by integrating optical and radar

imagery and color infrared photography. Mangroves and Salt Marshes 1998;2:109–19.

[8] Yang X, Damen MCJ, Van Zuidam RA. Use of thematic mapper imagery with geographic information

system for geomorphologic mapping in a large deltaic lowland environment. International Journal of

Remote Sensing 1999;20:659–81.

[9] Singhroy V. Interpretation of SAR images for coastal zone mapping in Guyana. Canadian Journal of

Remote Sensing 1996;22:317–28.

[10] Rudant JP, Baltzer F, Deroin JP, Lointier M, Maitre H, et al. Apport des images radar satellitaires ERS-1

et JERS-1 dans le domaine de la cartographie generale et thematique en contexte tropical humide: exemples

en Guyane franc-aise et regions limitrophes. Societe Franc-aise de Photogrammetrie et Teledetection

1996;142:15–33.

[11] Kushwaha SPS, Dwivedi RS, Rao BRM. Evaluating of various digital image processing techniques for

detection of coastal wetlands using ERS-1 SAR data. International Journal of Remote Sensing

2000;21:565–79.

[12] Proisy C, Mougin E, Fromard F, Karam MA. Interpretation of polarimetric radar signatures of mangrove

forests. Remote Sensing of Environment 2000;71:56–66.

[13] Souza Filho PWM, Paradella WR. Recognition of the main geobotanical features along the Braganc-a

mangrove coast (Brazilian Amazon Region) from Landsat TM and RADARSAT-1 data. Wetlands Ecology

and Management 2002;10:123–32.

[14] Souza Filho PWM, Paradella WR. Use of Synthetic Aperture Radar for Recognition of Coastal

Geomorphological Features, Land-Use Assessment and Shoreline Changes in Braganc-a coast, Para,

Northern Brazil. Annals of the Brazilian Academy of Science 2003;75:341–56.

[15] Berger AR. The geoindicators concept and its application: an introduction. In: Berger AR, Iams WJ, editors.

Geoindicators: assessing rapid environmental changes in Earth systems. Rotterdam: Balkema; 1996. p. 1–14.

[16] Woodroffe C. Mangrove sediments and morphology. In: Robertson AI, Alongi DM, editors. Tropical

mangrove ecosystems. Washington: American Geophysical Union; 1992. p. 7–41.

[17] Morais BC, Costa JMN, Costa ACL. Variac- ao espacial e temporal da precipitac- ao no estado do Para. Acta

Amazonica 2005;35:207–14.

[18] DHN. Tabuas de Mares para 2000: Costa do Brasil e alguns portos estrangeiros. Rio de Janeiro: DHN; 2000.

p. 9–11.

[19] Souza Filho PWM, El-Robrini M. Coastal zone geomorphology of the Braganc-a area, Northeast of Amazon

region, Brazil. Revista Brasileira de Geociencias 2000;30:518–22.

[20] PCI Geomatic 9.0 User’s Manual, version 6.3. Ontario: PCI Enterprises; 1999, 282pp.

[21] Paradella WR, Santos AR, Dall‘Agnol R, Pietsch RW, Sant‘Anna MV. A geological investigation based on

airborne (SAREX) and spaceborne (RADARSAT-1) SAR integrated Products in the central Serra dos

Carajas granite area, Brazil. Canadian Journal of Remote Sensing 1998;21:376–92.

[22] Paradella WR, Santos AR, Veneziani P, Morais MC. Synthetic aperture radar for geological applications in

the moist tropics: experiences from the Brazilian Amazon region. Revista Brasileira de Geociencias

2000;30:538–42.

ARTICLE IN PRESSP.W.M. Souza Filho et al. / Ocean & Coastal Management 49 (2006) 462–475 475

[23] Toutin T. Multisource data integration with an integrated and unified geometric modeling. In: Askne

J, editor. Sensors and environmental applications of remote sensing. Rotterdam: Balkema; 1995. p. 163–74.

[24] Lopes A, Touzi R, Nezry E. Adaptive speckle filters and scene heterogeneity. IEEE Transaction on

Geoscience and Remote Sensing 1990;28:992–1000.

[25] Chavez PS. An improved dark-object subtraction technique for atmospheric scattering correction of

multispectral data. Remote Sensing of Environment 1988;24:450–79.

[26] Forber DL, Livernam DGE. Geological indicators in the coastal zone. In: Berger AR, Iams WJ, editors.

Geoindicators: assessing rapid environmental changes in Earth systems. Rotterdam: Balkema; 1996.

p. 175–92.

[27] Souza Filho PWM, Paradella WR. Use of RADARSAT-1 Fine and Landsat-5 TM selective principal

component analysis for geomorphological mapping in a macrotidal mangrove coast, Amazon region.

Canadian Journal of Remote Sensing 2005;31:214–24.

[28] Krause G, Glaser M. Co-evolving geomorphical and socio-economic dynamics in a coastal fishing village of

the Braganc-a region (Para, North Brazil). Ocean & Coastal Management 2003;46:859–74.

[29] Souza Filho PWM, Tozzi HAM, El-Robrini M. Geomorphology, land use and environmental hazard in

Ajuruteua macrotidal sandy beach, northeastern, Para, Brazil. Journal of Coastal Research 2003;35:580–9.

[30] Cohen MCL, Souza Filho PWM, Lara RJ, Behling H, Angulo RJ. A model of Holocene mangrove

development and relative sea-level changes on the Braganca Peninsula (Northern Brazil). Wetlands Ecology

and Management 2005;13:433–43.

[31] Souza Filho PWM, Cohen MCL, Lara RJ, Lessa GC, Koch B, Behling H. Holocene coastal evolution and

facies model of the Braganc-a macrotidal flat on the Amazon mangrove coast, Northern Brazil. Journal of

Coastal Research 2006;SI39:306–10.

[32] Cohen MCL, Behling H, Lara RJ. Amazonian mangrove dynamics during the last millennium: the relative

sea-level and the Little Ice Age. Review of Paleobotany and Palynology 2005;136:93–108.

[33] Young RS, Bush DM, Pilkey OH. Evaluating shoreline change and associated risk on coastal hazards: an

inexpensive qualitative approach. In: Berger AR, Iams WJ, editors. Geoindicators: assessing rapid

environmental changes in Earth systems. Rotterdam: Balkema; 1996. p. 193–206.

[34] Kjerfve B, Macintosh DJ. The impact of climatic change on mangrove ecosystems. In: Kjerfve B, Lacerda

LD, Diop EHS, editors. Mangrove ecosystem studies in Latin America and Africa. Paris: UNESCO; 1997.

p. 1–7.

[35] Schaeffer-Novelli Y, Citron-Molero G. Brazilian mangroves: a historical ecology. Ciencia e Cultura Journal

1999;51:274–86.

[36] Dahdouh-Guebas F. The use of remote sensing and GIS in the sustainable management of tropical coastal

ecosystems. Environment, Development and Sustainability 2002;4:93–112.

[37] Green EP, Clark CD, Mumby PJ, Edwards AJ, Ellis A. Remote sensing techniques for mangrove mapping.

International Journal of Remote Sensing 1998;19:935–56.

[38] Malthus TJ, Mumby PJ. Remote sensing of the coastal zone: an overview and priorities for future research.

International Journal of Remote Sensing 2003;24:2805–15.

[39] Lewis AJ, Henderson FM, Holcomb DW. Radar fundamentals: the geoscience perspective. In: Henderson

FM, Lewis AJ, editors. Principles and applications of imaging radar. Manual of remote sensing. 3rd ed.

New York: Wiley; 1998. p. 131–80.

[40] Souza Filho PWM, Paradella WR, Silveira OFM. Synthetic aperture radar for recognition of coastal features

in the wet tropics: Applications in the Brazilian Amazon coast. Boletim do Museu Paraense Emılio Goeldi

2005;1:149–54.

[41] Mumby PJ, Green EP, Edwards AJ, Clark CD. The cost-effectiveness of remote sensing for tropical coastal

resources assessment and management. Journal of Environmental Management 1999;55:157–66.

[42] Gornitz V. Global coastal hazards from future sea level rise. Palaeogeography, Paleaoclimatology,

Palaeoecology 1991;89:379–98.