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Remote Sensing, Geospatial Technologies and Coastal Ecosystems

Remote Sensing, Geospatial Technologies and Coastal Ecosystems

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X. Yang



applications (Yang et al. 1999, Yang 2005a,b). But the coastal environment, because

of its complex and dynamic landscapes, challenges the applicability and robustness

of remote sensing and geospatial technologies. Encouragingly, recent innovations in

data, technologies, and theories in the wider arena of remote sensing and geospatial

technologies have permitted scientists with invaluable opportunities to advance the

studies on the coastal environment.

Within the above context, a book on coastal ecosystems is timely. Designed for

both the academic and business sectors, this book is dedicated to the development

of remote sensing and related geospatial technologies for monitoring, synthesis, and

modeling in the coastal environment. Specifically, this book concentrates on the

following aspects:

• Reviews the principles and methods of remote sensing and geospatial technologies as applied in the coastal environment;

• Examines some latest development in the use of remote sensing and geospatial

technologies for coastal ecosystem assessment with emphasis on coastal waters,

submerged aquatic vegetation, benthic habitats, shorelines, coastal wetlands and

watersheds; and

• Highlights a watershed-wide synthetic approach that links upstream stressors

with downstream responses for integrated coastal ecosystem assessment.

In addition to scientific research, the book has incorporated a management component that can be found in some major chapters. Cutting-edge research based on

remote sensing and geospatial technologies helps improve our understanding of the

status, trends and threats in coastal ecosystems; such knowledge is critical for formulating effective strategies in future management and sustainable coastal ecosystem planning.

Unlike most edited books that are largely based on paper presentations at a specific theme conference, this book features the research conducted by a selected

group of interdisciplinary scholars:

• Researchers affiliated with the Estuarine and Great Lakes (EaGle) research program (http://es.epa.gov/ncer/centers/eagles/) that was established by US Environmental Protection Agency (EPA) partnered with National Aeronautics &

Space Administration (NASA);

• Researchers who present a scholarly paper in a special paper session on estuarine and coastal ecosystem analysis we organized at the Annual Meetings of

Association of American Geographers (AAG) since 2003;

• Some active researchers largely identified from their presentations at several

other premier conferences (e.g. annual meetings of American Geophysical UnionAGU or American Society for Photogrammetry and Remote Sensing-ASPRS) in

recent years; and

• A small number of other world-level scholars in remote sensing, GIS, and coastal

science.

A total of 44 authors from USA, Canada, UK, Holland, Russia, Argentina, and

Barbados contribute to this book. Although most of the chapters are authored by US



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scholars and with a clear focus on a study site in USA, the knowledge gained from

this region can be applied to other coastal ecosystems globally.



1.2 Major Types of Coastal Ecosystems

There is no single definition on the coastal zone. Here we consider the coastal zone

as a physical region extending from the edge of the continental shelf to the intertidal

and near-shore terrestrial area. Globally, this physical region includes a wide array

of near-shore terrestrial, intertidal, benthic and pelagic marine ecosystems (Burke

et al. 2001). More comprehensive discussions on these ecosystem types are given

elsewhere (e.g. Mann 2000, Beatley et al. 2002). Our current discussion limits to

several coastal ecosystems including estuaries, coastal marshes, mangroves, seagrass systems and benthic systems because they are among the major chapter subjects in this book. Note that these ecosystems are largely recognized according to

the main primary producer with the exception of estuaries; as a rather large ecosystem, estuaries can include the other four as subsystems but the latter may also occur

outside an estuary.

Estuaries are a partially enclosed body of coastal waters typically found where

freshwater from rivers meet with saltwater from the ocean. As the tidal mouths of

rivers, estuaries and the surrounding lands are places of transition from land to sea.

They are often known as bays, lagoons, harbors, inlets, sounds, or fjord. Estuaries are important ecosystems, providing goods and services that are ecologically,

economically, and culturally indispensible. Ecologically, estuaries are not only the

‘nurseries of the sea,’ providing habitats for many marine organisms, such as fish,

mammals, birds, and other wildlife, but also serve as a natural buffer that filters

out much of the sediments and pollutants carried in by terrestrial runoff, creating

cleaner water that eventually benefits both human and marine life. Economically,

estuaries support significant fisheries, tourism, and other commercial activities and

the development of important public infrastructure, such as harbors and ports vital

for shipping, transportation, and industry. Culturally, estuaries are often the focal

points for recreation, commerce, scientific research and education, and aesthetic enjoyment. The major threats to estuaries are from human activities as more than two

thirds of the global large cities are based on estuaries (Ross 1995). Stresses caused

by excessive use of the natural resources and unchecked watershed land use practices have resulted in water quality degradation, harmful algal blooms, unproductive

fisheries, loss of biodiversity, and many other human health and natural resource

problems.

Coastal marshes are a sensitive, dynamic, and productive ecosystem. They are

predominately grasslands that are periodically flooded by tides in the intertidal regions. The salinity from salt or brackish tidal waters creates a salt-stressed aquatic

environment where halophytic plants thrive. Coastal marshes may be classified as

salt marshes, brackish marshes and freshwater tidal marshes. They may be associated with estuaries, and are also along waterways between coastal barrier islands



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and the inner coast. Coastal marshes are of great ecological values because they

serve as the nursery grounds for fish, habitats for a wide variety of wildlife, and the

buffer zones to protect water quality. The major disturbances and threats to coastal

marshes largely come from human activities, such as draining, filling, ditching, and

waste dumping, although natural processes like sea-level changes can also affect the

areal distribution of coastal marshes.

The mangrove ecosystem is commonly found in tropical and subtropical tidelands throughout the world. The mangrove family of plants dominates this coastal

wetland ecosystem due to their ability to thrive in the saline coastal environment.

The three mangrove species grown in the United States are red, black, and white

mangroves. The term mangroves can narrowly refer to these species but most commonly refers to the habitat and entire plant assemblages, for which the term mangrove swamp or mangrove forest is often used. Because mangroves are constantly

replenished with nutrients, they sustain a huge population of organisms that in turn

feed fish and shrimp, which support a variety of wildlife; their physical stability help

prevent shoreline erosion, shielding inland areas from damage during severe storms

and waves. The major threats to mangroves are mostly related to human impacts

from dredging, filling and diking, oil spills, herbicide and urban waster runoff.

Seagrasses are aquatic flowering plants that live fully submerged in the saline

coastal environment, and are also called ‘submerged aquatic vegetation.’ Seagrasses

can form extensive beds or meadows, dominated by one or more species. They are

distributed worldwide in soft sediments from mean low tide level to the depth limit

determined by the penetration of light that permits seagrass plants to photosynthesize. Seagrass beds are a highly diverse and productive ecosystem, and they almost always support more invertebrates and fish than the adjacent areas lacking

seagrasses (Mann 2000). Seagrass beds provide coastal zones with a number of

ecosystem goods and services, such as fishing grounds, wave protection, oxygen

production and protection against coastal erosion. Disturbances and threats to seagrasses include natural processes, such as grazing, storms, ice-scouring and desiccation; but human activities, such as entrophication due to excessive nutrient inputs,

mechanical destruction of habitat, and overfishing, are considered to be the major

stressors.

The benthic system is the community of organisms living on the bottom of oceans

in areas not colonized by macrophytes (Mann 2000). Benthic habitats are virtually

bottom environments with distinct physical, chemical, and biological characteristics. They vary widely depending upon their location, depth, salinity, and sediment.

Benthic habitats in areas with depth of larger than 200 m have been much less commonly observed and mapped. Estuarine and nearshore benthic habitats can be highly

diverse, including submerged mudflats, rippled sandflats, rocky hard-bottom habitats, shellfish beds, and coral reefs. Note that seagrass beds can be described as a

benthic system but they are treated separately (see the above paragraph). In terms

of ecological functioning, the benthic system serves as the site of nutrient regeneration and the site of considerable secondary production that is utilized by important

predators, such as bottom-feeding fish and crustaceans (Mann 2000). The major disturbances and threats to the benthic system are similar to those listed for seagrasses.



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1.3 Remote Sensing and Geospatial Technologies

Remote sensing is the science and art of acquiring information by a recording device

that is not in physical contact with the object under investigation. The technology

of modern remote sensing began with the invention of camera more than 150 years

ago, and by now many different remote sensing systems have been developed to

detect and measure energy patterns from different portions of the electromagnetic

spectrum. Remote sensing and related geospatial technologies can help improve

our understanding of the coastal ecosystems in several ways, although the realistic

potential for making these improvements are often challenged by the complexity in

the coastal environment.

Remote sensing and related geospatial technologies (such as geographic information system and spatial analysis) provide at least five major benefits for coastal

studies. Firstly, perhaps the largest benefit of remote sensing is its capability of acquiring photos or images that cover a large area, providing a synoptic view that

allows us to identify objects, patterns, and human-land interactions. This unique

perspective is highly relevant to the ecosystem approach we advocate to study the

coastal environment in this book since many coastal processes are operating over

a rather large area; failure in observing the entire mosaic of a coastal phenomenon

may hinder our ability to understand the potential processes behind the observed

patterns.

Secondly, remote sensing provides additional measures for coastal studies.

Coastal researchers frequently use data collected from field surveys and measurements. This way of data collection is considered to be accurate but can introduce

potential errors due to the bias in sampling design (Jensen 2007). Field measurements can become prohibitively expensive over a large area. Remote sensing can

collect data in an unbiased and cost-effectiveness fashion. Moreover, remote sensors

can measure energy at wavelengths which are beyond the range of human vision;

remote sensor data collected from the ultra-violet, infrared, microwave portions of

the electromagnetic spectrum can help obtain knowledge beyond our human visual

perception. Data fusion from different sensors can improve coastal mapping and

analysis.

Thirdly, remote sensing allows retrospective viewing of the Earth surface, and

time-series of remote sensor data can be quite useful to develop a historical perspective of a coastal phenomenon or process, which can help examine significant human

or natural processes that act over a long time period. Examples in this book include

time-series data on chlorophyll (chl-1) and primary productivity that helped examine climate contribution in spatio-temporal dynamics of phytoplankton in Chesapeake Bay (Chap. 6); declining of submerged aquatic vegetation that was linked

with increased nutrient and sediment discharges into Chesapeake Bay (Chap. 10);

and marshland conversion into other habitat types driven by hydrological modifications and off-farm sedimentation (Chap. 21).

Fourthly, remote sensing can help make connections across levels of analysis

for coastal studies. Coastal science disciplines and subdisciplines have their own

preferred levels of analysis and normally do not communicate across these levels.



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For example, coastal biologists tend to work with individual organisms and populations; oceanographers and coastal ecologists tend to work at higher levels defined by

oceanographical features or ecological units; while geographers and coastal planers

tend to work at community and ecosystem levels. On the other hand, the temporal

scales used by these different coastal researchers vary greatly, from hourly, daily,

weekly, monthly, seasonally, to annual or decadal basis. Remote sensing provides

essentially global coverage of data with individual pixels ranging from sub-meters to

a few kilometers and with varying temporal resolution; such data can be combined

to allow work at any scales or levels of analysis, appropriate to the coastal process

or phenomenon being examined (Millennium Ecosystem Assessment 2003). Therefore, remote sensing offers the potential for promoting coastal researchers to think

across levels of analysis and to develop theories and models to link these levels.

Lastly, remote sensing integrated with other relevant geospatial technologies,

such as geographic information systems, spatial analysis and modeling, offers an

indispensible framework of monitoring, synthesis and modeling for the coastal environment. Such frameworks support the development of a spatio-temporal perspective of coastal processes or phenomena across different scales and the extension of

historical and current observations into the future. They can also be used to relate

different human and natural variables for developing an understanding of the indirect and direct drivers of changes in ecological services and the potential feedbacks

of such changes on the drivers of changes in the coastal environment.

On the other hand, coastal environments are characterized by erratic climate conditions and complex ecosystem types, challenging the applicability and robustness

of remote sensing and geospatial technologies. The high humidity in coastal areas makes difficult to obtain cloud-free images. The complex optical properties in

coastal waters dilute the effectiveness of many algorithms for retrieving water quality parameters that were originally developed for open-ocean waters. The complex

spectral signatures in coastal aquatic systems make difficult to map and classify benthic habitats. The presence of complex urban impervious materials and croplands,

along with a variety of wetlands and vegetation cover, causes substantial inter-pixel

and intra-pixel scenic changes, thus complicating the classification and characterization of coastal landscape types. Moreover, it is always difficult to organize field

campaigns in coastal areas to acquire sufficient ground-truth data for model development and verification.



1.4 Overview of the Book

With a total of 22 chapters, this book is divided into three major sections (Fig. 1.1).

The first section includes the first five chapters that examine a set of core conceptual and technical issues. The second section consists of 15 chapters that showcase

some latest development in remote sensing of the coastal ecosystems with emphasis on coastal waters, submerged aquatic vegetation populations, benthic habitats,

shorelines, coastal wetlands and watersheds. The last major section comprises the



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Fig. 1.1 A graphical overview of the book structure



two remaining chapters highlighting a watershed-wide synthetic approach that links

upstream stressors with downstream responses for integrated coastal ecosystem assessment and management.

In terms of the writing style and contents, this book contains at least three types

of chapters. The first type is predominately an overview on one or more major

conceptual or technical issues. There are three chapters falling into this category:

a generic discussion on the rationale behind the development of remote sensing

and related geospatial technologies for coastal ecosystem research and management (Chap. 1), a review on the advances in sensor design and related field observation techniques that are relevant to coastal studies (Chap. 2), and a review on

the utilities of geographic information systems and spatial analysis as applied in

the coastal environment (Chap. 3). The second type of chapters examines a significant coastal research topic, such as fuzzy approach for integrated coastal zone

management (Chap. 4), coastal spatial data infrastructure (Chap. 5), airborne remote sensing of chlorophyll (ch-a) in Chesapeake Bay (Chap. 6), remote sensing

of bio-optical properties of Chesapeake Bay waters (Chap. 7), remote sensing of

submerged aquatic vegetation (SAV) populations in Chesapeake Bay (Chap. 10),

shoreline mapping and change analysis (Chap. 13), remote sensing of tidal wetland vegetation (Chap. 15), LIDAR remote sensing of coastal-plant communities

(Chap. 16), and remote sensing and spatial analysis of watershed and estuarine

processes in Elkhorn Slough (Chap. 21). The last type of chapters discusses a

specific research or application: coral reefs and associated benthic habitat mapping (Chap. 8), benthic habitat mapping (Chap. 9), submerged aquatic vegetation

mapping and change analysis (Chap. 11), marine macrophyte mapping (Chap. 12),

coastal mangrove species discrimination (Chap. 14), barrier island marshes mapping and change analysis (Chap. 17), reed mudflat characterization (Chap. 19),



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coastal landscape pattern characterization (Chap. 20), and land use and water quality

(Chap. 22). The following paragraphs provide a chapter-by-chapter overview.

As an introduction to the entire book, Chap. 1 discusses the rationale and motivation leading to the development of remote sensing and related geospatial technologies for coastal ecosystem assessment and management. It reviews the major types

of global coastal ecosystems, discusses the major benefits and possible challenges

of using remote sensing and geospatial technologies for coastal ecosystem research

and management, and previews the book structure with a chapter-by-chapter outline.

The chapter concludes by highlighting some areas that deserve further research.

Chapter 2 reviews the advances in remote sensor design and related field observation techniques that are appropriate for coastal ecosystem research and management.

It covers a variety of remote sensors, such as multispectral and hyperspectral imagers, thermal infrared scanners, radar imagers, scatterometers, altimeters, and

LIDAR. The discussion on the sensor development is closely tied with specific

coastal and marine applications that characterize the physical and chemical properties of coastal waters, bathymetry or coastal land cover. It emphasizes not only the

integration of data acquired from both satellite and airborne platforms to provide

sufficient spatial, spectral, radiometric and temporal resolutions but also the incorporation of a reliable field data collection approach to acquire sufficient in situ measurements that are used to calibrate and validate the remotely sensed information.

Chapter 3 provides an overview on the utilities of geographic information systems

(GIS) and spatial analysis techniques in the context of coastal and marine applications. It reviews several GIS data models that can be used to represent spatiotemporal information in digital environment and the four major groups of spatial

analysis techniques, namely, basic spatial analysis, spatial pattern analysis, statistical spatial analysis and spatial modeling. These techniques are especially suitable

for characterizing patterns, relationships, and trends in geographically referenced

data that can help improve our understanding of the natural and social processes at

work and make better decisions for coastal ecosystem planning and management.

The chapter concludes by emphasizing technology integration that is needed to deal

with the complex and dynamic coastal environment.

Uncertainties exist among almost all the activities in integrated coastal zone management (ICZM), from problem formulation, data collection, analysis and modeling, to decision making and implementation. Chapter 4 details a fuzzy approach to

integrated coastal zone management by using the isle of Ameland in the Netherlands

as a case study. It discusses the indeterminate nature of coastal landscape units and

how they can be represented as fuzzy spatial objects in GIS. It further identifies the

dynamic processes and investigates the changes of these fuzzy objects and uncertainties. It finally applies this fuzzy approach to characterize the dynamic changes

of sediments along the Dutch coast.

Building a spatial data infrastructure (SDN) for coastal ecosystem assessment

and management is critical yet quite challenging. Chapter 5 discusses use of the

‘data portal’ as the primary means for search, discovery and download of spatial

data, one of the most important and intuitive aspects of an SDN. It discusses some

of the most pressing challenges to effective implementation of portals within a broad



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context of an SDI and explores the potential solutions by using two major case studies that demonstrate innovation, implementation, and practice. At the end, the chapter highlights the importance of partnerships behind the portals with a consideration

of virtual communities as an emerging necessity.

Chapter 6 describes airborne remote sensing of phytoplankton dynamics in

Chesapeake Bay, the largest estuary in the USA. The high-resolution data obtained

in more than 400 flights are synthesized to document the strong role of climate

in driving spatial and temporal variability of chlorophyll (chl-a) and primary productivity (PP) in the Bay. The climate-induced change is further separated from

secular change due to nutrient overenrichment. The chapter further discusses the

development of water quality ‘criteria’, including chl-a as an indicator of ecosystem responses to nutrient loading, which requires to consider climatic forcing of

phytoplankton dynamics.

Remote sensing of water quality and biogeochemical processes largely depends

on the accuracy and consistency of the in-situ data used in the calibration and validation of satellite signals and in algorithm development. Chapter 7 discusses how

remote sensing of water quality in optically complex environments can be improved

by integrating optical measurements and radiative-transfer model calculations. The

approach is illustrated with recent findings on the bio-optical characteristics of

Chesapeake Bay waters, including measurements of the magnitude and spectral

characteristics of particulate backscattering. It then discusses progress on optical

closure studies in coastal regions and proposes bio-optical relations for remote sensing retrieval of water quality indicators in the Chesapeake Bay ecosystem.

Remote sensing of benthic habitats is challenged by the confounding influence

water column attenuation on substrate reflectance. Chapter 8 reports a research effort that aims to resolve this confounding influence. High-resolution multispectral

satellite imagery and airborne hyperspectral imagery are used as inputs in semianalytical models to derive water depth and water column optical parameters which

are further used in various bio-optical algorithms to deduce bottom albedo and to

map benthic habitats along the north shore of Roatan Island, Honduras. The hyperspectral data are found to consistently outperform the high spatial-resolution multispectral imagery in terms of classification accuracy but both show similar accuracies at the coarse classification level. This study suggests the need of data fusion from high spectral and spatial resolution sensors for accurate benthic habitat

mapping.

Chapter 9 describes an effort to map benthic habitats within the Kaloko- Honokohau National Historic Park, Hawaii, USA, by combining color aerial photography,

high-resolution bathymetrical data, and georeferenced underwater video and still

photography. Individual habitat polygons are classified and several derivative data

concerning seafloor morphology are also generated. It is found that benthic habitat

and seafloor morphology vary greatly throughout the study area and the underlying

geologic framework and morphology of the submerged volcanic flows provide the

primary control on benthic habitats within the park. The habitat maps and associated data can be used as a stand-alone product or in a GIS to provide useful baseline

information to coastal scientists and managers.



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Chapter 10 reports airborne remote sensing of submerged aquatic vegetation

(SAV) populations in Chesapeake Bay. The aerial mapping program began in 1978

and has continued on an annual basis since 1984; currently173 flight lines are photographed and mapped for SAV each year. Aerial mosaics are produced and the SAV

beds are delineated in a GIS environment. The SAV photo-interpretation results are

further verified by using extensive ground survey data. A composite historical SAV

coverage is also developed by using archival aerial photographs that date back to the

1930s. Comparisons of current SAV populations with historical restoration targets

are used annually to provide important indexes of bay condition and trends that are

further used to assess the effectiveness of nutrient and sediment reduction strategies

for the Bay and its associated watershed.

Chapter 11 discusses the spatio-temporal change of SAV populations in the

Hudson River estuary, New York, USA, by using remote sensing, GIS and statistical analysis. The SAV populations show obvious change but are always present

in some areas; these persistent SAV beds serve as indicators of overall estuarine

health and provide clues to the driving forces responsible for the observed changes

in the Estuary. The tidal fresh and oligohaline zones support the greatest abundance

of SAV per unit area while the mesohaline zone supports the least. Salinity, light

availability, and turbidity are found to affect the SAV distribution. At the end, the

chapter discusses how the SAV mapping and change detection information has been

used to better protect SAV habitats in the Hudson River estuary.

In many coastal areas, rich marine macrophytes grow to form subaquatic ‘forests’

that are of great industrial values. Chapter 12 describes an effort aiming to map the

marine macrophytes along the intertidal zones in the eastern coast of Tierra del

Fuego, Argentina, by using satellite imagery from Landsat, SAC-C, Aster, Radarsat

and QuickBird, as well as aerial photographs and maps. These data layers are coregistered before actual mapping the algae distribution. The final maps illustrate

the algae distribution and temporal change, which can be useful for improving the

management of coastal environment and resources in the study area.

Chapter 13 discusses algorithms and methods for shoreline extraction from remote sensor imagery and LIDAR elevation data. The shoreline extraction method

from remote sensor data consists of preprocessing, segmentation and classification,

and post-processing. Two methods are used for automated shoreline delineation

from LIDAR data. The first method consists of contouring, line selection with a

length threshold, and line smoothing and generalization; and the second one is based

on LIDAR DEM segmentation. These methods are used to process multi-temporal

digital orthorectified aerial photographs, Landsat imagery, and airborne LIDAR data

in the upper Texas Gulf coast. The shorelines delineated from a time series of remote sensor images and LIDAR DEMs are further compared in GIS environment

for coastal change analysis.

Mangroves are of great ecological and economic values and mangrove mapping

can help derive vital information for developing a mangrove management plan.

Chapter 14 discusses remote sensing based methods for mangrove species discrimination. Two IKONOS scenes acquired during dry and wet seasons are used to map

mangrove species through a Clustering-Based Neural Network (CBNN) classifier.



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CBNN is found to outperform two other conventional classifiers, namely, BackPropagation Neural Networks classifier (BPNN) and Maximum Likelihood Classifier (MLC), when using textural information; rainy season is better than dry season

for mangrove species classification. This chapter also examines the capability of

hyperspectral data for distinguishing mangrove species.

Chapter 15 reviews the spatial and temporal patterns of tidal wetland vegetation and the ecosystem services these systems provide and examines how remote

sensing has been used to map and monitor tidal wetlands. This is accompanied by

examples from the authors’ actual research and from the published literature. At

the end, the chapter discusses some of the remaining technical challenges facing

wetland managers and scientists who wish to study tidal marshes by remote sensing. The discussion is grounded in recent work in the San Francisco Bay area, but

lessons learned can be applied to other estuarine systems globally.

Chapter 16 reviews airborne LIDAR technology and assesses the capabilities and

limitations of LIDAR instruments available from research and commercial sources.

The focus is on the extraction of canopy height of short shrubs, marsh, grass, and

other vegetation found in the littoral zone. The accuracy in determining the height of

low vegetation is considerably improved when using a small-footprint, waveformresolving LIDAR system. The integration of spectral imagery and LIDAR has

the potential of significantly improving the classification and structural mapping

of coastal-plant communities. This chapter also identifies several technical challenges in LIDAR remote sensing. Overall, the chapter demonstrates that LIDAR

remote sensing is a cost-effective and reliable tool for the quantitative assessment of vegetation habitats on barrier islands, wetlands, and other coastal-plant

communities.

Chapter 17 reports a change analysis of back-barrier land cover types at Topsail

Island in southeastern North Carolina, USA, by using historical aerial photography

and GIS. Spatial analysis of land cover types indicates that when upland gains, it

replaces marsh; when upland loses, marsh replaces it; when marsh gains, it replaces

upland; when water loses, marsh replaces it; and there was no clear pattern for what

transitions when marsh is lost. A series of tests are conducted to verify the accuracy

of aerial photo rectification, digitizing and change detection. In addition, a fuzziness

test is used to identify true changes in the marsh habitats versus positional changes

(or sliver polygons). Results indicate that rectification, interpretation and digitizing

of historical aerial photography can be done with reasonable accuracy that warrants

meaningful change analysis of back-barrier land cover types.

Chapter 18 focuses on the development of remote sensing methods to detect,

inventory and monitor burnt marshes. Two very different coastal marshes in terms

of seasonal biomass turnover pattern are monitored with aerospace remote sensing

and ground measurement of canopy structure and optical reflectance. The seasonal

maidencane marsh produces a very different temporal response to burning than the

non-seasonal black needlerush saline marsh does. A vegetation indicator derived

from optical data is used to monitor the black needlerush marsh burn, and the use of

SAR data further extends the time-since-burn to approximately 900 days. Multi-date

TM data in combination with ground measurements are used to monitor the full burn



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history of the maidencane marsh. This study indicates that it is possible to monitor

marsh recovery history and predict burn history by using optical and radar data.

Chapter 19 examines the response of the Kalmykian coastal zone and the Ural

River delta to sea level fluctuations by using a time series of optical and radar images. Photo-interpretation of optical data and digital analysis of radar images indicate that the reed mudflats have played a very important role in the coastal zone

dynamics. When the Caspian Sea level rose, the shoreline began to change not from

the front reed-belt bound but from the rear bound; when the sea level declined, the

rear bound moved seaward faster than the front bound. The ecological niche for reed

growth is further determined by constructing a series of profiles along the Ural River

delta. Overall, this study shows the usefulness of satellite imagery for the study of

coastal zone dynamics in the context of global changes.

Chapter 20 illustrates the utilities of integrating remote sensing and geospatial

technologies for coastal landscape pattern characterization. Central to this study

is the two satellite images that have been used to extract land cover information

through hierarchic classification and spatial reclassification techniques. To suppress

the information redundancy and improve the manageability, the initial landscape

metrics derived from the land cover information are then reduced to a core set by

using landscape ecology principles and multivariate statistical techniques, which

are further used to examine the spatio-temporal pattern of landscape. This research

demonstrates the integration of remote sensing and other geospatial technologies

(such as GIS, landscape metrics and multivariate statistical analysis) has mutually

reinforced their utilities effective for coastal landscape pattern characterization.

Chapter 21 discusses the roles of remote sensing and spatial analysis of watershed and estuarine processes for conservation planning in Elkhorn Slough, a coastal

watershed in central California. The use of archival aerial photographs helps identify significant trends of marshland conversion to other habitat types, mainly due

to hydrological modifications and off-farm sedimentation. Remote sensing research

addressing nutrient and sediment runoff demonstrate the potential to correlate estuarine disturbance and response to watershed inputs or properties. Despite some challenges, remote sensing and spatial analysis, especially when applied for salt marsh

vegetation change detection and bathymetric change detection, help identify areas

for conservation; GIS-based watershed management continues to improve estuarine

conditions, as restoration and erosion control are underway to reduce nutrient and

sediment discharge.

Chapter 22 examines the impacts of land use upon surface water and seawater quality for a coastal watershed draining into the Holetown Lagoon, Barbados.

Surface water quality was poorer in the sub-basin with the highest proportion of developed land; nutrient concentrations at the watershed outlet were quite high, suggesting overfertilization of agricultural lands and nutrient enrichment from urban

impervious surfaces. Runoff discharge into the nearshore zone causes plumes with

excessive turbidity and nutrients dispersing towards the Bellairs Reef, contributing to the chronic effects of eutrophication and sedimentation. It further recommends several remedy strategies, including improved farming practices for reducing the use of fertilizer quantities, enlargement of sewerage treatment facilities for



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