The Progression of GIS in the Field of Coastal Morphology
A Literature Review

Adam T. Gustafson

GEO 4221, University of West Florida, Pensacola, Florida

Abstract

        Since its inception, in the early 1960’s, to the present geographic information systems (GIS) have revolutionized the way earth sciences have operated, especially in the field of geomorphology. This literature review will cover the progression of GIS, specifically in the field of coastal morphology, from its early predecessors of cartography and photogrammetry, to its initial development in the form of the Canada Geographic Information System (CGIS), to present applications and trends, and into the future.

Introduction

The coastal zone garners ever increasing attention from those who are involved with the collection, management, processing, and distribution of geospatial data. This can be attributed to the fact that 60 % of the world’s population lives within the coastal zone. With so much of humankind residing within the coastal zone increasing pressures are being placed on coastal resources. Resources under pressure must be carefully managed if they are to be retained for future use and development (Drummond et al. 1997). The coastal zone can be defined as the boundary between land and ocean, extending from the landward margin affected by salt water to the outer edge of the continental shelf (IGBP 1990). GIS data that can be used to measure, analyze, or classify the coastal zone can be broken down into four categories based on the way in which it depicts the real world situation. They are: in situ measurements, remotely-sensed data, secondary data and numerical simulations. In situ measurements are recorded at a single point over many layers for a period of time i.e. current meters or tidal gauges. Remotely-sensed data is grid-based and provides complete coverage over the study area i.e. satellite imaging or light detection and ranging data (LiDAR). Secondary data includes data sources that have been generated for other purposes and widely distributed i.e. atlases or climatologies and, finally numerical simulations, which are composed of predicted data in a matrix or grid format. These data are derived from the simulation of physical processes calculated from mathematic expressions or formulas i.e. shoreline detection or coastal ocean circulation models (Lucas 1996).

 The purpose of this literature review is to cover the progression of GIS in the field of coastal morphology over five distinct periods, as outlined by Waters in his paper GIS: History. The five periods consist of the pioneer period from the mid-1950s to approximately 1975, the government-supported, experimental period beginning in the mid-1970s and ending in the early 1980s, the commercial period from the early 1980s to 1989 the user dominance period starting in 1990 onwards into the mid-2000s and the current integrated GIS era from 2005 to the present. These periods are marked by their significance of conceptual developments, progress and improvements in software and hardware, and the contributions made to academia, commercial enterprises, and governments (Waters 2016).

Predecessors & the pioneer period
(pre 1950s – 1975)

The origins of GIS developed from the collaboration of individuals whose goal was to organize, visualize, and interpret spatial data and phenomena (Waters 2016). The direct predecessors of GIS, inarguably, lie in the fields of cartography and photogrammetry, respectively. Cartography refers to the science of drawing maps and photogrammetry refers to the science of making measurements from photographs, specifically aerial photography.  The earliest forms of aerial photography in the United States were mainly performed by the United States Army Air Service and the United States Navy Air Service. Aerial photographers must take into account the method of geographical analysis. A method that states phenomena have spatial relationships with each other and that the patterns, relationship or connection of one phenomenon may be deduced from the visible presence of another (Powers & Kohn 1959). Photogrammetric instruments used by military topographic units are based on the principle of projecting the images of two overlapping photographs to create a three-dimensional spatial model which reproduces the relationship between the images. These instruments came in two general types, the multiplex and the stereoplotter.  (DAF & DA 1970). Aerial photographs can generally be classified into two categories depending on whether the photograph was taken with the camera pointing vertically or obliquely downward. Technically, a photograph of the earth's surface is not a map, but when it is interpreted sufficiently it can be made into one. In interpreting aerial photographs it is imperative to know the scale, which is dependent upon the altitude at which the photo was taken, the angle of the lens, and the variation from the vertical, in order to make corrections for distortion (Lee 1922). The ability to digitize aerial photographs into computer data was possible at the time through the use of densitometers. A densitometer could measure the film densities of colored transparent photographs or black and white negatives. The film was placed on a scanning table and each time the table changed direction the film was advanced one scan width. The voltage outputs from the film densities were recorded as Y coordinates and the X coordinates were recorded from the number of scans required to digitize the photograph (Burgess & James 1970).

The advancements of photogrammetry and the demand for a more advanced and efficient geographical database directly correlated with the introduction of the first true vector based system known as the Canada Geographic Information System (CGIS). In the early 1960s Roger Tomlinson, manager of the computer mapping division at Spartan Air Services, and Lee Pratt, head of the Canada Land Inventory, collaborated to produce CGIS which led to a series of innovations such as  hardware for laser scanning of maps and software for vectorizing the resulting images and storing them. Due to Tomlinson’s contribution to the origins and development of GIS he has been recognized as the “father of GIS” (Waters 2016).

The government-funded experimental research period (1976 – 1982)

This period was primarily characterized by advancements in computing technology that led to conceptual and software developments within academia, government agencies, and industry. The transition from bulky mainframe systems to minicomputers then, eventually, to desktop microcomputers and laptops occurred during this period. This transition in computing technology was accompanied by the migration of GIS software to these new platforms (Waters 2016).

Advancements in satellite technology were also occurring during this period. In Doyle’s 1977 paper Photogrammetry: The Next Two Hundred Years he discusses how the Landsat multispectral scanner was already “producing astonishing new looks at our planet”. He also mentions that in the following year the launch of the Seasat-A satellite, carrying a radar which can resolve 25 meters on the Earth's surface from orbital altitudes, was being carried out (Doyle 1977).

The commercial period (1983 – 1989)

        During this period it was the commercial sector that saw the greatest influence over the development of GIS related applications. In 1986 Esri released PC ARC/INFO becoming the first commercially available GIS for desktop computers and by 1988 Esri had become a $40 million a year company with clients worldwide (Waters 2016). This set the stage for Esri to become the world’s leading supplier of GIS software, web GIS, and geodatabase management applications.

On the academia side of things, developments in the study of oceanography were possible through the use of satellites such as the National Oceanic and Atmospheric Administration (NOAA) series. This group of satellites utilizes an advanced very high resolution radiometer (AVHRR) that can repeatedly detect the thermal and visible emissions of any region of the Earth at least twice a day. The purpose of infrared satellite data is to measure the ocean’s surface temperature derived from equivalent blackbody emissions. Another advantage AVHRR data has is that geographic positions are incorporated into its datasets. This allowed images to be displayed in standard map projections allowing for sets of NOAA imagery to be analyzed on a spatial and temporal scale with such ease never before possible (Violette 1988).

The period of user dominance (1990 – 2004)

During this period GIS accessibility was increased exponentially by allowing users to collect data by foot, by vehicle, or by airplane via a global positioning system (GPS) receiver and inputting said data into GIS software directly. This development greatly increased the potential for GIS consumer related applications (Speed & Lang 1990). Other related instruments such as total stations also gained significant prominence in coastal research during this time, specifically the study of dune morphology. Total stations are able to measure distance by recording the time it takes for a beam to travel to a reflective target and back to the instrument. Each data point has x, y, and z values, computed from distance data and angular measurements. The survey data points are then interpolated into a gridded, continuous surface from which a raster based topographic map, called a digital elevation model (DEM), can be created using GIS software (Andrews et al 2002).  

It was during this period that the United Nations Conference on Environment and Development (UNCED) conveyed in 1992 and came to the following three prioritizations regarding integrated coastal zone management (ICZM): (1) ecological integrity, (2) economic efficiency, and (3) social intra- and intergenerational equity (Vallega 2005). A simplified framework for understanding the wide range of administrative, social, and technical instruments used in an ICZM program could be analyzed through the Pressure State Impact Response cycle (PSIR) (Kay & Alder 2000). Pressures, whether natural or anthropogenic, can cause partial or total imbalance of a coastal system. The first effects of these pressures are changes in the environmental state such as the degradation of habitats and changes in land cover and land use. This disequilibrium results in impacts that affect natural processes, use and protection of resources, and socioeconomic activities that take place in coastal areas. Once these impacts are acknowledged strategies for environmental protection and rehabilitation begin to take form as scientists and policy makers collaborate on reducing and managing the coastal systems vulnerability (Szlafsztein & Sterr 2007).  The outcomes of UNCED set the precedent for future coastal management politics, projects, and procedures.

Two separate studies that occurred during this period that embodied UNCED’s ICZM policies were Li & colleague’s 2001 study that analyzed an area of shoreline along the southern edge of Lake Eerie, Michigan in order to detect and predict shoreline erosion, and Mas’s 2004 study that examined a region of the Lagoon of Terminos, in the State of Campeche, located in the south eastern part of Mexico in order to classify coastal land types based on their spectral signatures. Li and colleague’s shoreline detection survey involved the development of a shoreline detection model that evolved over the course of the study from regular/polygonal data, to dynamic segmentation, and then to a digital shoreline detection model. This shoreline generation method was of importance for the prediction of high-water and low-water shorelines in anticipation of extreme events such as storms, severe erosion, and other natural disasters (Li et al. 2001). Mas’s study aimed at tackling a common problem encountered in land use/land classification (LULC) studies, during this time, involving spectral confusion. This issue occurs when different LULC classes share a similar spectral signature and are often misclassified. The study utilized a state of the art artificial neural network (ANN) called multiplayer perceptron (MLP). The purpose of the MLP was to model complex relationships between variables and resulted in an overall increase in classification accuracy from 67% to 82% (Mas 2004). Both of these studies utilized cutting edge GIS techniques, for their time, to better understand and manage coastal resources in their respective areas in order to reduce system vulnerability for the present and future protection of the populaces residing in them thus embodying the characteristics UNCED put forth in their ICZM policies.

Integrated GIS era (2005 – present)

        Returning to the importance of computing technology and user interaction progression in GIS, since 2005, has been focused not only on increasing computation ability but also on networking and outreach potential. Web based programs and online social networks have been hugely influential developments in the social application of computing technology. These changes have seen prominence in the rise of new web based GIS applications such as public participation GIS (PPGIS) and volunteered geographic information (VGI). PPGIS and VGI have the advantage of being inexpensive, timely, and available to all who have access to the internet (Waters 2016).

Another developing online based application that has the potential to revolutionize GIS capabilities is grid computing. Grid computing is essentially online based networking that combines computer resources spread over different geographical locations in order to achieve a common goal. In 2008 a large collaborative project utilizing grid computing for coastal modeling and prediction was carried out by the SURA Coastal Ocean Observing and Prediction (SCOOP) program in an attempt to provide improved forecasts and real-time information for severe storm events, such as tropical storms and hurricanes. By utilizing an assortment of computational models, such as Advanced Circulation (ADCIRC at University of North Carolina),  Curvilinear-grid Hydrodynamics in three dimensions (CH3D at University of Florida), 3D baroclinic circulation  (ELCIRC at Virginia Institute of Marine Sciences), and wave watch 3(WW3 at Louisiana State University), that factor in variables such as wave and atmospheric elements in a combined manner, advanced 72 hour forecasts for specific sites in the southeastern United States were created (Allen et al 2008). Another network based GIS project is the coastal observatory program established on the French controlled Mayotte Island in the Indian Ocean. The goal of the observatory is to understand the recovery potential of the sediment budget for local beaches and characterize mangrove recovery following storm damage in order to help make decisions for key stakeholders involved in the islands coastal management. The observatory monitors waves, currents, short term beach face stability, long term cycles of erosion, and mangrove surface area variations through the use of a networked array database known as Manguiers (Jeanson et al. 2014). Array databases provide a more convenient way to store and process large amounts of datasets. Some advantages that these databases have are that queries can be made quicker than traditional file based systems and they can be configured to operate in parallel with other array databases (Pourabbas 2014). Parallel computing involves the practice of splitting a large amount of work between multiple central processing units (CPUs) (Zieg J Zawada 2021). Parallel databases operate under one of the following three architectures: shared-memory architecture, where interconnected CPUs have access to a common memory region, shared-disk architecture, where CPUs have access to a common disk space but maintain their private memory, and shared-nothing architecture, where CPUs do not share any memory and communicate with each other over a network (Pourabbas 2014). The Manguiers database of the Mayotte Island observatory is an example of shared-disk architecture where access is shared but limited to local management organizations and is updatable as new data is acquired (Jeanson et al. 2014).  

Waters argues that GIS is returning to its roots regarding earlier concerns common to many geographers throughout time in regards to the human side of the discipline. He describes geographers concerns, towards map making over time, as either being nomothetic (macro-scale) or idiographic (micro-scale) approaches (Waters 2016). Some recent studies that have been conducted with a nomothetic approach include Haar and colleague’s 2019 study involving the development of a GIS tool for predicting coastal litter accumulation and Isha & Adib’s 2020 study on the potential of a shoreline analysis model in determining future changes. In Haar’s study the coastal litter accumulation model was generated using field data collected from the Lofoten archipelago in Norway. This field data was categorized and then statistically analyzed based on shore gradient obtained from GIS generated DEM’s in order to create the coastal litter accumulation model (Haar et al. 2019). In Isha & Adibs’s study they utilized a shoreline analysis tool created by the United States Geological Survey (USGS) known as Digital Shoreline Analysis System (DSAS) in order to detect erosion and accretion rates for the area of Regency Beach, Port Dickson in Malaysia (Isha & Adib 2020). While both of these studies were conducted in a particular area their techniques could be applied generally to any location in the world thus making their research nomothetic in scope and approach. On the flip side, some studies that have been conducted recently with an idiographic approach include Khan & Hasan’s 2020 study involving spatial modeling for biofuel plantation sites within the coastal city of  Karachi, Pakistan and Hakami and colleague’s 2022 study involving spatial modeling for soil sites within the coastal area of Jizan in southwestern Saudi Arabia. Karachi has an ideal environment for growing the biofuel source plant Jatropha Curcas. This plant, that was once native to only South America, is now being cultivated in similar tropical areas due to its ability to grow in former waste land and high saline environments. Khan & Hasan’s goal was to map available plantation sites for this biodiesel energy crop by using meteorological parameters and satellite imagery. Criteria that went into mapping the sites took into account land surface temperature, bareness of land, slope, surface elevation, humidity and rainfall. The result of taking all of these factors into the account was the creation of a map that shows classification suitability for Jatropha Curcas plantations in the area (Khan & Hasan 2020). Saudi Arabia contains a corrosive soil type referred to as sabkha. Sabkha is a medium-to-fine-grained saline deposit that is primarily found in coastal regions of Saudi Arabia. The high corrosivity of this soil type poses a risk to underground structures and can cause land subsidence. The main goal of Hakami’s study was to assess sabhka soil samples in the Jizan area of Saudi Arabia for their corrosivity and chemical composition in order to map spatial distribution. The spatial interpolation technique in ArcGIS was used to map the spatial distribution of the following soil corrosion parameters: pH, resistivity, chloride, and sulfates (Hakami et al. 2022). Both of these studies were restricted to the area in which they were conducted in with specific research goals in mind. The techniques and methods involving spatial interpretation applied to these studies would not be applicable in other areas thus making their research idiographic in scope and approach.

Conclusions

The progression timeline of GIS has been characterized and shaped by the unique events and developments that have taken place in each of the outlined periods. The overall trend in GIS application has been an increase in technological power and capability while being nomothetic or idiographic in approach. Coastal GIS studies have followed the same trends as general GIS studies in that they have seen expansion in ability and scope through overcoming hardware and software limitations of the past. Modern coastal GIS studies embody the ICZM principles put forth by UNCED and focus on socio-environmental interactions. Waters describes GIS as a “transformative science” due to how it has evolved and how it has impacted the field of geography as a whole. He likens the impact that GIS has had on the discipline of geography as being comparable to the impact that the telescope had on astronomy because, like the telescope, people choose what they want to see through the GIS lens (Waters 2016). In Doyle’s 1977 predictions for the future of photogrammetry he states “In order to guide the forces of technology we need a clearer understanding not only of where we are going, but why. We need to comprehend that the real objective of our work is the betterment of the condition of our fellow man.” Never more than now have these sentiments aligned more with the direction GIS is progressing.

Works Cited

Allen G, Bogden P, Creager G, Dekate C, Jesch C, Kaiser H,McLaren J, Perrie W, Stone G, Zhang X         (2008) Towards an Integrated GIS-Based Coastal Forecast Workflow. Concurrency and         Computation 20(14): 1637-51

Andrews BD, Gares PA, Colby JD (2002) Techniques for GIS Modeling of Coastal Dunes.         Geomorphology (Amsterdam) 48(1): 289-308

Burgess FJ, James WP (1970) Aerial photographic tracing of pulp mill effluent in marine         waters. United         States Federal Water Quality Administration & Oregon State University

Doyle FJ (1977) Photogrammetry: The Next Two Hundred Years. Photogrammetric
        Engineering and Remote Sensing 43: 575-577

Drummond JE, Tait DA, Zamlope Z (1997) Building a Coastal GIS Using Digital Photogrammetry.         Photogrammetric Record 15(90): 863-873

Haarr ML, Westerveld L, Fabres J, Iversen KR, Busch KET (2019) A Novel GIS-Based         Tool for         Predicting Coastal Litter Accumulation and Optimising Coastal Cleanup         Actions. Marine         Pollution Bulletin 139: 117–26

Hakami A, Ghrefat H, Elwaheidi M, Galmed M, Yahya MA (2022) Assessment of the Corrosivity of the         Southern Red Sea Coastal Sabkha Soil: An Integrated Mineralogical, Geochemical, and GIS         Approach. Environmental Earth Sciences 81(8)

The International Geosphere-Biosphere Programme (IGBP) (1990) A Study of Global Change. IGBP         Report No. 12, Chapter 4: 4.1-3

Isha IB, Adib MRM (2020) Application of Geospatial Information System (GIS) Using Digital         Shoreline Analysis System (DSAS) in Determining Shoreline Changes. IOP Conference Series.         Earth and Environmental Science 616(1): 12029–12037

Jeanson M, Dolique F, Anthony EJ (2014) GIS-Based Coastal Monitoring and Surveillance         Observatory on Tropical Islands Exposed to Climate Change and Extreme Events: The         Example of Mayotte Island, Indian Ocean. Journal of Coastal Conservation 18(5): 567–80

Kay R, Alder J (2000) Coastal planning and management. E & FN Spon, London, pp 375

Khan MJ, Hasan SA (2020) GIS- Based Screening Model of Coastal City Karachi for Plantation of         Biofuel Source. Scientific Reports 10(1): 4666–4673

Lee WT (1922) The Face of the Earth as Seen from the Air : a Study in the Application of Airplane         Photography to Geography.  American Geographical Society

Li R, Liu JK, Felus Y (2001) Spatial Modeling and Analysis for Shoreline Change Detection and Coastal         Erosion Monitoring. Marine Geodesy 24(1): 1-12

Lucas AE (1996) Data for coastal GIS: issues and implications for management. GeoJournal 39(2): 133-        142

Mas JF (2004) Mapping Land Use/cover in a Tropical Coastal Area Using Satellite Sensor Data, GIS and         Artificial Neural Networks. Estuarine, Coastal and Shelf Science 59(2): 219–30

Pourabbas E (2014) Geographical Information Systems: Trends and Technologies. Taylor & Francis         Group, Chapter 1:5-10

Powers WE, Kohn CF (1959) Aerial photo-interpretation of landforms and rural cultural features in         glaciated and coastal regions. Dept. of Geography, Northwestern University

Speed V, Lang L (1990) A New Tool for GIS. Computer Graphics World 13(10): 40–44

Szlafsztein C, Sterr H (2007) A GIS-Based Vulnerability Assessment of Coastal Natural         Hazards, State         of Pará, Brazil. Journal of Coastal Conservation 11(1): 53-66

United States Dept. of the Air Force (DAF), United States Dept. of the Army (DA) (1970) Cartographic         aerial photography. U.S. Government Printing Office, Washington, D.C

Vallega A (2005) From Rio to Johannesburg: The Role of Coastal GIS. Ocean & Coastal         Management         48(7): 588-618

Violette PE (1988) Satellite Image Analysis Techniques Applied to Oceanography. Philosophical         Transactions of the Royal Society of London, Series A: Mathematical and Physical Sciences         324(1579): 325–46

Waters N (2016) GIS: History. International Encyclopedia of Geography, John Wiley &         Sons, Ltd

Zieg J Zawada DG (2021) Improving ESRI ArcGIS Performance of Coastal and Seafloor Analyses with         the Python Multiprocessing Module. Journal of Coastal Research 37(6): 1288–1293