THE IMEDEA M&CGIS: A GIS BASED INTERDISCIPLINARY TOOL FOR SCIENTIFIC MANAGEMENT OF THE COASTAL ZONE
A. Fornés,
G. Basterretxea, A. Orfila, T. Jordi, F.
Moral, A. Álvarez, G. Vizoso, B. Casas,
C. Duarte, J. Tintoré
Grupo de Oceanografía Interdisciplinar, IMEDEA (CSIC-UIB), Esporles (ES)
Abstract
The high economical and environmental value of the marine and coastal areas,
compel to act with the basic principle of knowledge. In this sense, the Cross-Disciplinary
Oceanographic Group (GOI) of the Mediterranean Institute for Advanced Studies
(IMEDEA) is joining efforts to achieve the integration of the physical, chemical
and biological processes of the marine and coastal environment. New information
systems, data acquisition techniques and communication technologies are, at
these moments, essential for marine and coastal studies using up-to-date scientific
technologies and global perspectives. This aim can be pursued with the construction
of a Marine and Coastal Geographic Information System (M&CGIS) that integrates
environmental data and governmental regulations allowing to consider the complexity
of all the coastal system. The M&CGIS allows environmental managers, legislators,
scientists and other potential users access to maps and geographic data so
that adequate management decisions can be made taking into account the complexity
of the coastal system.
Herein we present an overview of the particularities and difficulties of the marine and coastal data model due to its interdisciplinary interest, its wide range of methods, instruments, time scales, periodicity, precision and accuracy of data collection, and also due to the inherently fuzzy and indeterminate nature of so many coastal entities and phenomena. We present the IMEDEA M&CGIS, where its capacity of capture, management, manipulation, analysis and display of data has proven to be useful and valuable in a great number of applications exposing here a specific study case at Santa Ponça bay (Calvià - Mallorca).
Introduction
Marine research in coastal waters often requires the integration of physical,
chemical, geological and biological aspects of the environment. The interdisciplinary
nature is an aim often pursued by marine research institutions since is the
way of understanding some aspects of an inherently complex world such as the
marine environment. The use of the new information and communication technologies
are a powerful to integrate data from these fields in a way that new perspectives
can achieved. Geographic Information Systems (GIS) with its integration capacity
allow exploring the complexity of the coastal system in a comprehensive manner
and promote synergies between different types of data that provide more information
than that obtained by considering data from each field separately.
The advantages of applying GIS to the coast and marine environment include: (1) the ability to handle large databases and to integrate and synthesize data from a wide range of sources, (2) the encouragement for the development and use of standards for coastal data definition, collection an storage, (3) the use of shared database, especially if access is provided via a data network, facilitating the updating of records and the provision of a common set of data and (4) the ability to model, test and compare alternative management scenarios, before a proposed strategy is imposed on the real world (Bartlett, 2000).
The IMEDEA M&CGIS development and implementation
The development of the IMEDEA Marine and Coastal Geographic Information System
(IMEDEA M&CGIS) follows different stages up to its full implementation
(Figure 1).
Figure1. Phases in a Geographical Information System development
In a first stage, the real world is simplified
according to application requirements resulting a data dictionary describing
spatial and attribute data to be included in the GIS. When the focus of study
is the marine and coastal environment, this simplicity of the reality is made
particularly difficult due to their interdisciplinary interest and also due
to the inherently fuzzy and indeterminate nature of so many coastal entities
and phenomena. Nevertheless, a list of priority variables to incorporate in
the GIS was made to drive data collection and development efforts.
In a second stage (conceptual design), spatial data are simplified as discrete
objects or as continuous surfaces as a function as the geographic reality
is understood. Data in the coastal and marine environment are collected through
a wide range of methods, instruments, time scales, periodicity, precision
and accuracy. Thus, marine and coastal GIS applications are particularly complex
since a wide array of sampling media and time varying data types ought to
be integrated. Indeed, the majority of marine and coastal data are four dimensional,
showing variation in location, depth and changes through time. Moreover, when
compared with land-base systems, marine systems tend to be sampled more sparsely
and infrequently. Furthermore, since the ocean is a dynamic environment, it
can experience significant changes over a wide range of timescales (seconds
to decades). Figure 2 displays an example of data types that can be observed
in the coastal and marine environment. Data type will determinate how data
will be imported in the GIS.
The third stage consists in the planning and design of the database based
on the conceptual model. Afterwards, it is proceeded to the construction of
the database, where the data structure, that is the manner of organize spatial
data for their use by computer systems, is implemented. In this phase, functions
and capabilities of the hardware and software have to be considered for actual
implementation of the model. Based on the common marine and coastal data types
and in the variables to incorporate in the GIS, an hybrid raster-vector GIS
system was selected to implement the IMEDEA M&CGIS. The comprehensive
GIS commercial software ArcInfo and ArcView were selected for data development
and as final software that will serve the scientific community.
Figure 2. Common Coastal and Marine Data Types. Modified from Breman et al., 2002.
The following stage of the project was focused on the development of specific applications to address more significant management issues that scientific members had identified. The final technological issue to be addressed was how to best serve the data to the user community. Thus, all data incorporated in the M&CGIS is accessible and distributed in the World Wide Web. Researchers can download and examine the data using their own platforms (GIS or other types) for their specific analytical research or for data integration. In the future the project will be delivered entirely on-line by an interactive GIS with different functions of displaying and analysis.
Applications of the IMEDEA M&CGIS. A case
study: Santa Ponça Bay (Balearic Islands)
As populations and economic activities increase in coastal zones, coastline
erosion and coastline change detection become critical to coastal resource
management, coastal environmental protection, and sustainable coastal development
and planning. An investigation into interrelationships among various causes
and impacts of coastline changes is necessary before any objectives and scientific
decisions related to coastal zone policies, engineering projects, and coastal
management can be made.
The aim of the on going work at Santa Ponça bay is to obtain reliable indicators and thresholds of the seasonal beach variation and coastal ocean dynamics that allow decision making based on scientific knowledge. The study area, Santa Ponça bay, is located in the west coast of Mallorca, Balearic Islands (Figure 3).
Figure 3. Location of the study area: Santa Ponça Bay (Balearic Islands, Spain).
A) Data incorporated in the GIS
Several sources of data are used in the research at Santa Ponça bay.
This alone demonstrates one of the well recognized reasons for using GIS,
the integration of disparate data sets. Following we describe briefly the
data acquired for the study and their incorporation in the GIS.
- Nautical chart. The nautical chart for the area on 1:10.000
scale was scanned to a resolution of 400 dots-per-inch (dpi) and georeferenced
with the ArcInfo software. The bathymetric points of the georeferenced nautical
chart were digitalized with the ArcView software to incorporate in the GIS
and to derivate the Digital Bathymetric Model (DBM) in the Triangulated
Irregular Network (TIN) data structure. The TIN method constructs adjacent,
non overlapping triangles by connecting the nearest sample points with lines
and it is a suitable method for sparsing sampling data sets.
- Base Cartography. Not all data sets are used for data analysis,
some of them are for meeting the requirements of cartographic designs and
map presentation. This is the case of the governmental digital cartography
on a 1:5000 scale existing for the study area. However some information
of this cartography, in particular the topographic level lines were used
to calculate the Digital Elevation Model (DEM) for the area describing the
land terrain relief. In the GIS the Digital Bathymetric Model and the Digital
Elevation Model were integrated generating a Topo-Bathy Model.
- Aerial photography. Aerial photographs are nowadays one
of the main sources of information. An aerial photo taken on July 1956 and
other one taken on March 2001 on 1:20.000 scale were acquired for the study
with a resolution of 300 dpi and 1270 dpi, respectively. The aerial photos
were georeferenced with the ER-MAPPER software using the digital elevation
model and digital cartography as reference. By means of photointerpretation
techniques the upper limit of Posidonia oceanica meadows was digitalized.
Comparing the feature lines, the regression of the Posidonia oceanica was
identified.
- Acoustical Sampling for a detailed bathymetry. Acoustic
data obtained with a shipmounted echosounder were incorporated in the database.
A detailed Digital Bathymetric Model was generated from acoustical data
applying a Kriging interpolation with the linear model and 32 points, since
the TIN method is not suitable for interpolating data based on widely separated
transects, specifically when the distance between transects lines is much
greater than the distance between sampling points along a transect, seeing
that the TIN constructs very thin and long triangles causing erroneous spikes
perpendicular to the transect lines (Guan et al., 1999).
- Topographical Survey: Coastline and cross-shore beach profiles. To characterize the beach of Santa Ponça, topographical surveys of the coastline and beach profiles were carried out periodically. The sampled points with the x, y coordinates and the z elevation values, were imported and mapped in the GIS (Figure 4).
Figure 4. Coastline and beach profiles
points resulting from a topographical survey.
- Sediment samples: Mineralogical analysis, grain size and
organic matter. To sediment characterization, various samples were collected
at different topographic levels along two profiles. Grain size, mineralogical
composition and the organic matter content were calculated for each sediment
sample. All three data types were incorporated in the GIS as tables associated
to the location point where the samples were taken.
- CTD casts. CTD data are integrated into the GIS in three
dimensions utilizing some functions of the Oceanographic Analyst Extension
(Hooge and Hooge, 2000).
- Continuous records of underwater temperature. Recorded data
were incorporated in the GIS as tables associated to the location point
of the moored instruments.
- Meteorology: temperature, wind and pressure. Wind velocity,
air temperature and atmospheric pressure data recorded at 20 minute intervals
on a weather station installed in Santa Ponça port were incorporated
in the GIS as a table associated to the location of the weather station.
- Currentmeter and current numerical simulations. Time series
of Acoustic Doppler Current Profiler (ADCP) data are incorporated in the
GIS as tables associated to the location point of the moored instruments.
Also, spatial current vectors, with de x,y coordinates and the u,v components,
derived from hydrodynamic numerical models for different wind scenarios
are incorporated in the GIS
- Wave propagation simulations. In this case the GIS, as well as representing the output data, acts as input to the model, since the model requires a detailed bathymetry of the area under study. Data from wave propagation simulations are incorporated in the GIS as a raster layer (Figure 5).
Figure 5. Free surface variation from wave propagation analysis
B) An integrated approach
In this example at Santa Ponça bay, different types of data have been
incorporated in the GIS: instantaneous points (CTD data), times series points
(underwater temperature, meteorology), feature lines (coastline), regularly
interpolated surfaces (nautical charts, aerial photographs), irregularly interpolated
surfaces (digital bathymetric model), etc. Also, it has been possible to provide
operational communications between hydrodynamic models and the GIS either
in vector and in raster format. This is the case of the integration in the
GIS of current and wave propagation simulations. Also, the GIS allows to incorporate
other data sources as CAD files (Governmental Digital Cartography).
Integrating all this information and using the analysis GIS functions, some interesting conclusions can be drawn about issues as the regression of Posidonia oceanica meadows, changes in beach extension, beach volume estimation, sediment characteristics, water quality and accretion and erosion processes and their relation with current and wave patterns.
To sum up, the Santa Ponça GIS project has allowed: (1) to collect the data in a common repository with common formats, (2) to allow researchers to view and query data availability, then download it from the World Wide Web, (3) to overlay different layers of information and to apply analysis functions to get some environmental indicators and conclusions, and (4) to give beach management recommendations based on the scientific knowledge.
Conclusions
Despite the heterogeneity and forth dimensional character of the marine and
coastal data, Geographic Information Systems provide an essential technology
for their store, access, integrate, analysis, display, disseminate and mapping.
Also, Geographic Information Systems comprise a key piece in the integrated
coastal zones management plans, updating data, sensitizing and educating to
the population and generating indicators for the decision making. Nevertheless,
much work still has to be done to improve the linkage between different data
types representing a variety of spatial-temporal scales.
References
- Bartlett, D.J. (2000). Working on the frontiers of science: Applying GIS to the Coastal Zone. Wright, D.J., Bartlett, D.J., Marine and Coastal Geographical Information Systems. Taylor & Francis, London, pp. 11-24.
- Breman, J., Wright, D., Halpin, P. N. (2002). The inception of the ArcGis marine data model. Breman, J. Marine Geography: GIS for the oceans and seas. 224 pp.
- Guan, W., Chamberlain, R. H., Sabol, B. M., Doering, P. H. (1999). Mapping Submerged Aquatic Vegetation with GIS in the Caloosahatchee Estuary: Evaluation of different interpolation methods. Marine Geodesy, 22: 69-91.
- Hooge, P.N. and Hooge E.R. (2000). The Oceanographic
Analyst Extension to the ArcView Geographic Information System version 1.4.
U.S. Geological Survey, Alaska Science Center, Glacier Bay Field Station.