Chapter 2. Literature Survey

2.1 Background of landusellandcover studies and pioneering works

Historically, human was dependant on surrounding for food, cloth or shelter. He

would hunt or look for fruits available around him when he would be hungry. He

was using leaves for covering body and caves for shelter. The very idea of

reproduction of seeds leads to the agriculture on land, which may be the primitive

use of land. The initial record of landuse in recent history in the form of land

record is available for agriculture land around the Nile River. As the floods would

ruin their crops, they put boundaries around the fields to prevent the flood and

assess individual loss (Anonymous). Colonies and settlements were established

mainly on the riverbank or on the coast as it provides them their basic needs for

food and shelter. The 'colony' concept provides a kind of protection also. This

plays an important role in the history of landuse. Human uses land as an eco­

system (Vink, 1975). As the population keep on increasing, land availability

becomes important issue. Major threats in coastal area are listed and very well

addressed by Clark in the Manual of Coastal Zone Management (Clark,

1992, 1996).

In India, basically kings levied land-taxes, but there were no land records.

Earliest recorded efforts of preparing sketches, compilation and codification of

laws and rules were carried out during the Mauryas (321 - 184 B. C.) and

Harsha (606- 647 A. D.). Systematic land- tax rules were introduced by Sher

Shah (1540- 1545 A. D.). Raja Todar mal, architect of land settlement pattern,

first initiated his work in 1573 in Gujarat, started first land record system with land

ownership pattern. The prime interest of these exercises was to collect revenue

(Singh, 1989). Most of the countries use aerial photographs for survey purpose.

In India, the SurvEi~ of India started using aerial photographs around 1950.

15

Initial space missions conducted by USSR and US provided initial photographs of

the earth and it opened a new dimension to the study of earth resources (Colwell,

R. N., 1983). With the availability of the initial LANDSAT (ERTS-1) images,

Anderson proposed the land use and landcover classification system (Anderson

et al., 1976). Researchers used remote sensing satellite data more for landuse

/landcover studies than any other discipline (Cihlar, 2000). In India, initially

Gautam (1989) carried out landuse/landcover studies at National remote Sensing

Agency (NRSA). Prior to that, the All India Soil and Landuse Survey (AIS&LUS)

were conducting landuse survey using conventional methods.

For coastal landuse/landcover study, Klemas (1975) has done initial work and

proposed a classification of various coastal features. In India, initially coastal

landuse/landcover study carried out at the Space Applications Centre (SAC)

(Nayak et al. 1984, Nayak et al. 1985). Nationwide database using various

coastal themes has been prepared at SAC (Anonymus, 1992).

2.2 Landuse models

A model can be defined as "a simplified representation of an object of

investigation for purpose of description, explanation, forecasting or planning" in

'Spatial model and GIS' (Camara, 1996). According to him, spatial model has two

dimensions space and attributes where as spatia-temporal model has space,

time and attributes. Various classification of spatial model are based on their

degree of formation, scale, conceptual and mathematical models (Steyaert,

1993). Other classification of spatial model based on how they deal with the

phenomenon (Berry, 1995). It can be classified based on their static ness or

dynamism. It also can be classified as per their space and time resolution. In

addition to this, spatial models can be classified based on their structure;

comprehensiveness, theoretical foundation or the modelling technique applied. . ...

16

Skidmore (2002) explained taxonomy of environmental models available from

GIS and environment literature and classify them as 'models of logic' and 'model

based on processing method'. Logical methods can be inductive or deductive

type; where as processing method model can be deterministic or stochastic type.

The deterministic can be subdivided into empirical, process-based and

knowledge-based model. The complex model may be a combination of methods.

In such case, one should be carefully identify components of the models to hold

the taxonomy of the model. As per the Michael Wagener (Camara, 1996) the

scale of the spatial models ranges from sub-molecular to astronomical scale.

Example includes from weather forecasting models, climate models, air and

liquid dispersion models, chemical reaction models, rainfall-runoff models,

ground water models, soil erosion models, biological ecosystem models, energy

system models, noise propagation model·and landuse/landcover models.

Jakeman and his co-authors (Jakeman et al, 1993) in their book ' Modelling

change in environmental systems' defines the procedure and method of the

constructing and evaluating mathematical models of the behavior of

environmental systems. According to them, the purpose for which model is to be

used will influence the form of model and its way of development. They divide

procedure of the development of model in two broad categories. Analyst with his

knowledge and imagination and without any in-situ field data can develop it. This

is called synthesis, having steps of a) conceptulisation, b) computational

. representation, usually in the different equation form or as linguistic rules or as

the rule of cellular automata c) numerical solution algorithms of differential

equations. The other model development part, called as analysis. This involves

evaluating the model against in-situ field data, and having steps, d) evaluation of

hypothesis and model structure identification, e) Parameter estimation and

analysis of the identifiably of the model, f) statistical checks and g) validation and

forecasting.

17

Though model in one form or other, is used to explain scientific phenomenon,

evolution of models goes in hand in hand with development of mathematics.

Differential equations and statistics have long historical association with model

development. Development of computers eases the limitation of human

computation power and with advancement in hardware and software help in

modelling complex phenomenon and interactions. Linguistic rules of the

conditions (IF -THEN) are part of our logical thinking and it can be realised and

manipulated through the programming language of artificial intelligence and

expert systems.

The Geographic Information System (GIS) also boost the modelling capabilities.

GIS can handle input, store, manipulate and provide output with overlaying and

for varying conditions. Thus its data manipulation and visualisation capabilities

can be used in model building and/or model evaluation. Camara (Camara, 1996)

discussed modelling using GIS and reported that spatial statistics and models to

analyse spatial data make up an area covering models for spatial point

processes, image analysis and gee-statistic methods. Though GIS helped to

boost the modelling, basically it is static system having rich database. Camara

classify three separate categories of combining dynamic models with GIS. They

are a) dynamic models are used spatially aggregated variables but their result

may be modified, b) active area dynamic and c) classical transport model. Most

of these models are governed by equations of Physics. The forth category

according to Camara, based on Object oriented representation, for natural

systems perceived as a set of interacting entities and not as a set of processes

representing theoretical principles (Tofoli and Mgrgdus, 1987, 1984).

2.3 Global landuse models

Cihlar discussed the status and research priorities in his article for landuse/

landcover studies (Cihlar, 2000). According to him, studying landcover is

important for understanding the climatic changes and for policy purposes. It is

18

important factor in deciding the landuse and other value of the land to society.

Land cover varies at a spatial rate from local to global. Locally it is required for

micro-level planning and field implementation. While at regional level, it is

required for the modelling the policy scenario and to forecast the environmental

impact of policies. At regional and national level, it helped in integrated and

sustainable management. At global level, it is required for global change

research, modelling the global studies on environment and framing and

implementing the international polices (McConnell and Moran, 2002). It varies

from days (in case of forest fire, tidal variations) to millennia (green house effect).

For studying (observations and monitoring) the large area at regional to global

level, remote sensing with its synoptic and repetitive capabilities is a logical

solution. Any remote sensing product in picture form is basically first hand land

use landcover information. Land cover and land use studies using aerial

photographs have a long history and well described in the Manual for

Photographic Interpretation (Colwell, 1960). Most of studies using satellite data

were carried out with moderate spatial resolution ranging 30 - 80 m (Cihlar,

2000). These studies were at local to regional level. Land use I land cover

mapping over a large area at national or global scale were not attempted

because of high cost of data, requirement of user community, technical

limitations like resolution, swath and other parameters, for global level analysis,

and availability of landusellandcover data sets compiled from ground survey and

national sources (Mathews et al. 1983). Ground based system has its own

limitations, due to number of sources of error, consistent definition of land cover

type and data with variable reliability and national policies of landuse/landcover

map availability (De Fries, 1994, 2000, Townshend et al 1991 ). The importance of

role of land use/ landcover in regulating climate, illustrated by studies of land

cover change with general circulation models (Shukla et al. 1990, Henderson -

seller, 1993). Satellite data because of consistent and repetitive nature, provides

a good source of landcover information. In additio-.to this, there are many other

factors which are discussed in detail by De Fries (2000), boost the new interest in

the landuse/landcover studies. These factors are mainly

10

1. Recognisation that accurate landusellandcover information is an essential

requisite for science and policy applications:

As discussed previously, accurate landcover information is very essential in

climate models at regional and global level. In addition to this, landcover

change information is included in international agreements such as Kyoto

protocol to the United Nations framework convention on climate change

(IGBP 1998).

Following are the important articles of the Kyoto Protocol.

i) Article 3: Change in carbon stocks resulting from human

induced landuse changes and forestry activities.

ii) Article 12: Monitoring human induced landuse changes

and forecasting activities under the clean development

mechanism.

iii) Article 6 &7: Monitoring of the transformation of emission

reduction limits resulting from projects, which enhances

anthropogenic removal by sink.

iv) Article 10: systematic observation and the development of

data archives to reduce uncertainties related to climate

system.

2. Improved computing capabilities and analysis techniques:

Large. storage and computational complexity were the limiting factor in the

past for the satellite data analysis. The development in computer field made it

possible now to compute the complex problem on single PC based software.

In addition to these new technologies like GIS, Neural network, fussy logic,

end-member analysis, etc. are making best out of the satellite data.

3. Availability of processed data set:

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AVHRR data with 1km resolution onboard NOAA satellite became the most

reliable source for global database (IGBP, 1992). Processed dataset at

global and regional level are available and well discussed by Skidmore

(Skidmore, 2002). A list of the data product is available from IJRS ( DeFries

and Belward, 2000)). Additional landuse/landcover studies are compiled in

special issue of IJRS vol. 21,No. 6&7, 2000, pp. 1083, 1089, 1093, 1115,

1121,1159,1313,1433.

Landuse/landcover studies assume more importance in the coastal area for

following reasons.

a. Limited availability of the land, as we have seen World's

coastline is approximately 4,40,000 km long, but more

than half the population stay in the coastal zone

(lindbhom, 2002).

b. Multiple use of land ranging from resource exploitation,

industry, habitation, recreational activities, pollution,

port development, fisheries, etc.

c. Increase in the world trade through sea route.

d. Exploitation and depletion of natural resources.

e. Developmental activities at the natural buffer zone (like

in mud-flat) make them vulnerable to natural hazards

and calamities and perturbing the natural coastal eco­

systems.

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f. Limited studies has been carried out for coast

compared to other land based studies. Despite having

very important source for natural resources, shelter

place, basic route for international trade, coastal area

has attracted very few scientific researches. Thus,

reliable databases of coastal resources and landuse

land cover inventories, landuse/landcover changes,

processes which produce changes and effects of these

changes on environment are not widely known and

available. Because of lack of this information, framing

polices, having coastal zone management in integrated

manner is not possible.

An International Geosphere Biosphere Programme (IGBP) report (IGBP, 1992)

put the stress on requirement of land data for many IGBP projects. This data is to

be used as baseline data, monitoring and for numerical modelling, which

represent complex interaction in ecosystem of the earth (Hall et al 1995). To

prepare the reliable global level model, scientific data are required. Remote

sensing with various spatial, spectral and temporal resolutions and because of its

repetitive and synoptic nature facilitate this need. In IGBP projects, for global

scale modelling, most models require data covering large area. AVHRR data has

been used since last two decades for various land - atmosphere interaction

models, ecosystem processing models and hydrological models. G!obal

databases are mainly available for various disciplines like vegetation, hydrology

and soil, snow and ice, ocean, radiation and clouds for modelling. The

encouraging results from the AVHRR study in the field of landcover (Loveland et

al, 2000, Mucher et al, 2000, Hansen et al.2000) and the derivation of biophysical

parameter form landcover further facilitate improved large area sensors, such as

SPOT4, Vegetation and MODIS (Muchoney et al. 2000, Zhan et al. 2000) etc.

Skidmore described the exhaustive details of models and data set available at

global level (Skidmore, 2002).

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Thus, global models provide the vital inputs to understand the global processes

and environmental studies but they have their own limitations. The courser

spatial resolution and availability and accuracy of region specific aspatial data

made the global model fail to explain regional processes. For modelling regional

processes basic requirement is high-resolution remote sensing data, detailed in­

situ data and constant monitoring to understand the interconnectivity with other

ecosystems. Thus, regional models can be compliment and supplement both to

the global models to improve the accuracy of model and better understanding of

the processes.

2.4 Modelling in coastal zone

Hsu and Silvester (1996) has defined Coastal Zone (as per the Carter, 1988), as

an area, resulting from the interaction between different physical, ecological and

cultural components. He has given the overview of different type of models

resulting from the beach processes. They have broadly classified them in four

topics of shoreline changes, beach profile variation, dune erosion and

topographic changes. They have not touched other coastal and ecological

issues, such as near shore current circulation, storm surge, coastal flooding,

waste disposal, etc.

According them, physical models have been used by coastal scientist for the

study of wave propagation, wave force on maritime structure, pollutant dispersion

and sediment transport. For problem involving sediment movement, location of

harbour entrance, and beach erosion and accretion, moveable bed scale model

have been utilized. Mathematical models mainly with deterministic approach, with

conservation of land momentum are applied. Models with the equations in the

form of Laplace or Navier-Stokes with continuity equations are set up for the

prediction of wave motions, density or transport of pollutants and near-shore

23

current velocity. Beach profile study equations and Littoral drift equations are

discussed in detail.

Lakhan & Trenhaile (1989) cited the Miller for describing the characteristics of a

system. Based on that, he has identified coast as a system that "a set of

interacting units with relationship (both in term of structure and processes)

among them. The state of each unit is constrained by or dependent on other

state of other units." The coastal system can be seen as complex, dynamic,

large-scale system with an integrated arrangement of separate units or

components, which vary in morphological form, pattern and configuration. The

structures of a system deal with the spatial and temporal arrangement of its sub­

systems and components, whereas processes concerned with change in matter,

energy and functioning of a system.

Lakhan & Trenhaile are defining the coastal system as a complex, de-compos

able, large-scale system. It is a composition of interacting component system and

associated sub-systems. The coast, with its component systems, will display vast

differences in morphology, physical states, and also various type of equilibrium.

In modelling the coastal system these characteristics of coast should be kept in

mind during demarcation and specifications of the boundary conditions.

According to them, it is very difficult to understand the complex, inter-dependent

and large-scale system using limited time studies. As it has interrelated

parameters, varying in time and space, the best way to study it using models and

sub-models. There are various kinds of models and different class of models as

described previously. These models can be classified in variety of manner

(Skidmore 2002, Fasol & Jorgl 1980, Fox 1985). Physical and mathematical

models are most successful in study of the natural system.

2.4.1 Physical models

4

A model said to be physical when the representation is physical and tangible and

model elements are made up of materials and hardware. It is suitable in coastal

24

studies and description can be found in text edited by Dalrymple (1985).

Svendsen (1985) describe the objectives for model to be considered as physical

model.

a) To seek quantitative insights in to a phenomenon not yet described.

b) To obtain measurements to verify the theoretical results.

Though, physical models are useful for understanding the interactions in coastal

systems, they do not describe hydrodynamics and sedimentary processes in

coastal system. In coastal system the processes, which are uncontrolled and

unpredictable in time and magnitude, cannot be explained fully by physical

models. So, results from physical models should be validated properly. (Rekhow

and Chapra, 1983).

2.4.2 Mathematical models

According to Hsu and Silvester (1996) the first mathematical model for coastal

sedimentation theory for shoreline change was given by Pelnard-Considere in

1956. This was basic concept has been used by many coastal engineers with

improvement to use the predicting the long-term evolution of a beach in the

vicinity of man made structures (Komar 1973, Rea and Komar 1975, Dean 1991).

Komar was first to give Drift equations (Komar, 1991 ).

The mathematical models are general and flexible in nature. It can be used for

very simple system to complex systems. In literature various types of

mathematical models have been described (Jacoby et al 1980, Blackwell, 1968).

Assumptions and facts are sharply stated and can be properly manipulated. They

provide formulation of hypothesis and provide guideline for the design of

experiments.

25

deterministic or stochastic.

Static models are time independent. Dynamic models are time dependent and

phenomenon with temporal variations can be studied using dynamic models.

Models can be discrete or continuous representation of system depending on

how time is treated in the model. Analytical and numerical models can be

discriminated based on the technique used to solve the model. Analytical model

has limited values for coastal system modelling as many linear and non-linear

equations need to be solved. Analytical models can be successfully developed

for the system with linear characteristics. Numerical models can be solved both

linear and non-linear problems. To solve the equations of the model, numerical

methods involving computational procedures has to be used. Numerical

methods can be used successfully to study various aspects of the coastal system

as they allows both linear and non-linear type complex equations. In deterministic

models, output is determined totally in term of the input. These models are

therefore based on notion of exactly predictable relationship between

independent and dependent variables. These models contain no random variable

and use only expected value for all parameters and variables. They are not

suitable for exploring behavior of coastal systems, which are governed by several

random processes. Stochastic model have one or more random variables that it

takes on value in accordance with a probability distribution. The probability

distribution may either vary or remain constant with time (Franta, 1977).

Stochastic models deals with systems, which allow statistical laws for

formulations. It can be applied to study the coastal system where coastal

processes are having random components. Coastal systems have large number

of interacting components that can not be described individually and in detail.

Coastal systems those governed by external forcing conditions can not be

defined except in probabilistic terms.

26

- -- .- J

for accuracy. Data collection is difficult in the coastal system. So, large numbers

of data are not available, Moreover, coastal systems are dynamic in nature. For

example, In littoral drift computations the wave conditions change hourly at any

location. So, for long-term study you have to take average only. Also, the mass .. movement of the suspended material also varies in very short time. The energy

varies with the depth.

2.4.3 Statistical and probabilistic models

Deterministic models, which characterise fixed input and output does not work for

coastal processes and landuse modelling. If actual development takes place in

mode other than predicted, it can lead to a wrong output. If we took probabilistic

approach, we can give more or various options to our model to give our model

more acceptability. In statistical methods, physical laws have been overlooked

sometime. So, we have to apply trial and error method before we reach to a

suitable goal.

2.4.4 Numerical models

Coastal processes are complex in nature and a number of parameters are acting

on it. So, when we select the differential equations for numerical models, success

depend upon the number of elements being considered.

2.4.5 Cellular Automata

The rules of cellular automata give another alternative form of conceptulisation.

Its widespread applications has until recently been constrained by the

construction of a computer designed specifically for their manipulations. It has

been claimed to be more appropriate to represent the fundamental laws of

Physics then the classical terms of differential calculus (Toffoli, 1984). Cellular

27

automata models can be used both for process view model and entity view

model. Phipps (1992) suggested testing these cellular automata models

concurrently with well-known models.

Feoli and Giacomich (2003) has shown an application of a simulation model for

land cover changes based on cellular automata model for predicting landcover

changes due to tourism in Goa, suggested by llachiniski ( 2001) and combined

cellular automata with Markov model and MCE (Multicriteria evaluation) as

suggested by Eastman (2001 ).

2.5 Coastal studies in India

Noronha (2003) identified and addressing stakeholder concern and include

various groups to develop future scenario for tourism at Goa. According to her,

associating stakeholder in identifying future is reduced the interest conflict and

allow better management of coastal resources.

Sonak (2003) developed a framework, called DPSIR (Driver-Pressure-State­

Impact-Response) framework. It connects driving forces to various coastal

ecosystems and resources trough pressure and pathways. He developed three

multi-domain (social, ecological, administrative) indicators to study the tourism

impact for monitor and managing sustainable use of coast. Indicators help to

capture the dynamics of ecosystem by communicating information about

conditions, change and trends over time. Mehra et al. (2003) developed a model

to delineate the linkage between socio-economic drivers and their impact on the

coastal ecosystems for tourism activities.

COSTED and NRSA has made an attempt in preparing meta-data directory for 4

coastal work in India. It was complied by Raghavswamy, (1999) who developed a

comprehensive database of thematic information prepared using remote sensing

28

data and many socio-economic data available at discrete places. For preparing

models to understand process that governs landuse/landcover changes and the

impact of landuse/landcover changes on climate, locally and globally.

Raghavswamy has given case studies of landuse change dynamics. He has

given abstracts of the important work done and also given a list of similar studies

being carried out in the country on Indian coastal zone.

Sunder (2004) has explained the process of erosion of a coast as " a coast is

said to be eroding when the loss of material due to various reason exceeds the

material supplied to it." He has discussed various natural and man-made

problems causing coastal erosion. In natural processes he emphasised the steep

storm waves as a main reason and explained that the long shore currents are

mainly responsible for the transport of sediment along the shore and it is called

sediment transport. The wave crest reaching the shore are generally not parallel

to coast in many cases and making some oblique angle when reaches to the

coast. This effect cause two components of third velocity, of which, one along the

direction parallel to the coast is called long shore current. Any man-made

structure to prevent the coastal erosion or for other purpose, if not properly

designed, disturb the existing equilibrium of the coast and further aggravate the

situation of erosion. Thus, he discussed merits and demerits of various shore

protection measures like sea walls, groins, revetment and designing of jetties. He

also discussed artificial nourishment and offshore breakwaters with examples in

the Indian coastal region.

Chandrashekhar lyer (2004) has given the status of coastal erosion and

protection and discussed the issues state wise and for the country. In Gujarat, he

pointed out that the coastal erosion problem is experienced mainly in the district

of Valsad, Surat and Bharuch.

Jan Van de Graff (2001) explained the coastal erosion, possible causes of

coastal erosion and protection measures to prevent this erosion. He explained

29

~~-------

that how breakwater or jetties interrupt the longshore sediment transport and

accretion occurs on the up drift side whereas severe erosion on the lee ward

side. In this article he stressed the importance of strong coastal zone

management with legal backing. Also, he emphasized coastal zone manager has

to see judicious and long term integrated planning to avoid these type of

vulnerability of the coast.

Sa nil Kumar et al (2001) have measured nearshore processes like wave

breaking, longshore and onshore - offshore currents, littoral sediment transport,

accretion of beach sediments and found the annual gross transport ranging from

0.201 x 106 m3/year to 0.078 x 106 m3/year for their study area at the Karnataka

coast. They observed that general pattern of net sediment transport is toward the

south.

Dange and Ghose (2001) measured the longshore current (velocity along the

west coast of India, at Mangalore port, Mirya bay and Muldwarka. They have

measured longshore current based on method given by Shore Protection Manual

(Shore Protection Manual) and calculated velocity ranging 0.11 to 0.61 m/ sec.

2.6 Scope of the research

Thus as we see the literature, globally and locally, regarding landuse modelling it

comprises global models based on NOAA AVHRR data. These studies and other

works mainly carried out with objective of studying global climate and land use

changes in agriculture and forestry. As we have seen, to further improve the

accuracy of these models, local or regional studies with accurate and scientific

data with additional local component are needed. This can be stand-alone study

describing and addressing local ecological and processes related problems with

detail field data, spatial and non-spatial database, and, if required, it can be

complimented with existing global models. Ocean and land interaction plays an

important role in influencing the global climate, various man-made activities and

30

other reasons cited above coastal zone assumes great importance. But, scientific

research in the coastal zone mainly confined with the studying the coastal

processes and impact of man-made structures on the coastal zone regarding the

erosion and depositional activities. Various anthropogenic activities influence the

coastal ecosystems and it assumes great importance to understand the effects of

these activities on the coastal land use and coastal processes for sustainable

development. Thus, present study is an attempt to study the effect of landuse/

landcover changes on the various coastal ecosystems and coastal processes

using remote sensing data. Non-spatial data have been integrated using GIS

and model has been developed which can be useful to the planner for developing

coastal zone in integrated sustainable manner.

31