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AN OVERVIEW OF REMOTE SENSING

CHAPTER TWO

LITERATURE REVIEW

2.0: INTRODUCTION

Most major metropolitan areas face the growing problems of urban sprawl, loss of natural vegetation and open space, and a general decline in the extent and connectivity of wetlands and wildlife habitat (U.S Geological Survey, 1999). Almost everyone has seen these changes taking place in their local environment but without a clear understanding of neither the causes of these changes or their impacts. Most of the land-use changes occur without a clear and logical planning with any intention to their environmental impact (Ahadnejad, 2002). Land use change is influenced by temporal and spatial factors that interact

This chapter will review all available literature relating to this project within the available time to give insight to what land use and land cover are, changes in land use and land cover, the various causes of land-use and land-cover change, effects of land-use and land-cover change on environmental variables and verse visa, the effects of land-use and land-cover on social variables and verse visa, the application of GIS/Remote Sensing in studying land-use and land-cover change, the limitation and some past works done on the topic.

2.1: LAND USE AND LAND COVER

A modern nation, as a modern business, must have adequate information on many complex interrelated aspects of its activities in order to make decisions (Anderson et al., 1976). Land use is only one such aspect, but knowledge about land use and land cover has become increasingly important as the Nation plans to overcome the problems of haphazard, uncontrolled development, deteriorating environmental quality, loss of prime agricultural lands, destruction of important wetlands, and loss of fish and wildlife habitat (Anderson et al., 1976). Land use data are needed in the analysis of environmental processes and problems that must be understood if living conditions and standards are to be improved or maintained at current levels (Anderson et al., 1976).

2.0.0 AN OVERVIEW OF REMOTE SENSING

Remote Sensing is the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object area or phenomenon under investigation (Lillesand and Keifer, 2004). There are wide range of applications of Remote Sensing including Meteorology, Engineering, Geomorphology, Climatology, Geology, Land Use and Land Cover classification, mapping and mapping, Agriculture, oceanography, Urban and Regional Planning, Environmental Planning and Health. This thesis seeks to research and explain the application of Remote Sensing in Land Use and Land Cover classification, mapping and change.  Information transfer in the field of Remote Sensing is always accomplished by the use of electromagnetic radiation measured at different wavelengths which will be discussed later in the course of this research.

2.0.1 TYPES OF REMOTE SENSING

The types of Remote Sensing could be grouped based on either the energy source or in respect to the wavelength regions (Richards and Jia, 2006). Based on source of energy, Remote Sensing Systems that make use of sensors that detect the reflected or emitted electro-magnetic radiation from the naturally available energy from the either the sun or the earth itself are called Passive Remote Sensing while Remote Sensing Systems that make use of sensors that provide their own source of energy for illumination are known as Active Remote Sensing (Lillesand and Kiefer, 2004).

The wavelengths at which sensors measures the spectral reflectance of object ranges from the Gamma Rays to the Radio Radio Waves. But with respect with wavelength region, the ranges applied in Remote Sensing include:

Optical Remote Sensing devices which operates in the visible, near infrared, middle infrared and short wave infrared portions of the electromagnetic spectrum sensitive to wavelengths ranging from 300 nm to 3000 nm.

Thermal Remote Sensing Sensors which operates in the thermal range of the electromagnetic spectrum and records the energy emitted from the earth features in the wavelength range of 3000 nm to 5000 nm and 8000 nm to 14000 nm with the previous range related to high temperature phenomenon like forest fire, and later with the general earth features having lower temperature.

Microwave Remote Sensing Devices which records the backscattered microwaves in the wavelength range of 1 mm to 1 m of the electromagnetic spectrum. Most of these sensors have their own source of energy (active) which has given them edge over other types of sensors because of their independence to weather and solar radiation.

2.0.2 ELECTRO MAGNETIC RADIATION (EMR)

According to Lillesand and Kiefer, (2004), Electromagnetic radiation often abbreviated E-M or EMR is a form of energy that reveals its presence by the observable effects it produces when it strikes the matter. Since energy is involved, it could further be explained as the energy propagated through space in the form of tiny energy packets called a proton that exhibits both wave-like and particle-like properties. This form of energy transport differs from other modes of energy transport such as conduction and convection in that electromagnetic radiation takes the form of self-propagating waves in a vacuum. There are several types and classes of electromagnetic radiation according to the frequency of the wave which includes radio waves, microwaves, terahertz radiation, infrared radiation, visible light, ultraviolet radiation, X-rays and gamma rays in order of increasing frequency and decreasing wavelength. For a variety of reasons, there are some wavelengths of electromagnetic radiation that are more commonly used in Remote Sensing than other wavelengths (Robert, et al., 2005). Remote Sensing Technology makes use of the wide range Electromagnetic Spectrum from a very short wave 'Gamma Ray' to a very long 'Radio Wave'.

Electromagnetic Spectrum

Source: Education.co.uk

Sensors on board Remote Sensing Platforms are used to record electromagnetic radiation. As stated earlier, Remotes Sensing could be active or passive based on the energy source. Focusing on passive Remote Sensing, extreme temperature and nuclear activity on the surface of the sun allows the emittance of a broad and continuous range of electromagnetic radiation. This electromagnetic radiation emitted from the sun interacts with the atmosphere, and interacts with the atmosphere before being detected by a remote sensor system in the air or in orbit (Raber, et al., 2005). Some of the energy gets absorbed by target materials like water and rocks on the earth's surface and these materials get heated as a result.

The absorbed energy is then re-emitted at longer wavelength thereby causing the materials that absorbed the sun's energy to become electromagnetic radiation themselves. A passive

Sensor like Landsat ETM+ and ASTER, which are both utilised in this research, will record the electromagnetic radiation or spectral reflectance of target materials based on the spectral resolution designed on the sensor. Active sensors that emit their electromagnetic radiation are mainly two types: Radar (Radio Detection and Ranging), which harnesses microwave energy, and LIDAR (Light Detection and Ranging), which harnesses the near-infrared or visible energy (Raber, et al., 2005).

2.0.4 REFLECTANCE OF ELECTROMAGNETIC ENERGY

Based on the atomic structure of earth's objects, different objects absorb and emit electromagnetic radiation at different wavelengths of the electromagnetic spectrum (Campbell, 2003). In the visible spectrum, these differences in reflective efficiency accounts for the colour variations we see. Green plants for example appear that colour to the eye because they reflect greater amount of green light than of blue or red light. Plotting the spectral reflectance level of a given object or phenomenon by wavelength yields a spectral reflectance curve, or spectral signature which according to Raber et al. (2005) is the Remote Sensing key to distinguishing between one type of target and another.

Typical Spectral Reflectance Curves for Soil, Vegetation and Water

Source: Lillesand and Kiefer, 1994

2.2.0 CAUSES OF LAND USE AND LAND COVER CHANGE

Identifying and understanding the major causes ofland-use and land-cover changerequires a clear understanding of both how human's decision-making processes on land-use and how specific environmental and social variables interact to influence these decisions. It is also very necessary to understand that decisions on land use are made and influenced by environmental and social variables across a wide range of spatial scales, from household level decisions that influence local land use practices, to policies and economic forces that can alter land useregionallyand even globally (Eric and Helmut 2007). The Land-use and Land-cover change model is usually governed by two broad complex sets of droving forces - human needs (social-economic factors) and environmental features and processes (biophysical factors) (Lambin, 2001).

2.2.1 PROXIMATE VERSUS UNDERLYING CAUSES

According to Eric et al., (2001), the causes ofland-use and land-cover changecan be divided into two categories:Proximate(direct or local) andUnderlying(indirect or root). The proximate, direct or local causes of land-use and land-cover change explains how and why localland coverand ecosystem processes are modified directly by humans, while underlying causes explain the broader context and fundamental forces underpinning these local actions (Eric et al., 2001). Proximate causes generally operate at the local level such as individual farm land, single households or simple communities while the underlying causes of land-use and land-cover change originate from level higher than the local level including districts, provinces, or country (regional) or even global levels, though complex interplays between these levels of organization are common. As a result of these complex interplays, underlying causes also tend to be complex, formed by interactions of social, political, economic, demographic, technological, cultural, and biophysical variables (Eric et al., 2001). Some local-scale factors originate internally within the local level and are therefore endogenousto decision makers and under local control. However, underlying causes are usuallyexogenous(originate externally) to the local communities managing land and are thus uncontrollable by these communities. In general, underlying causes tend to operate more diffusely, often by altering one or more proximate causes.


1. Anderson, J. R, Hardy, E. E., Roach, J. T., and Witmer, R.E., 1976, A Land Use and Land Cover Classification System for Use with Remote Sensor Data, United States Department of the Interior, Washington, United States Government Printing Office

2. Eric F. Lambin, B. L. Turner, Helmut J. Geist, Samuel B. Agbola, Arild Angelsen, John W. Bruce, Oliver T. Coomes, Rodolfo Dirzo, Günther Fischer, Carl Folke, P. S. George, Katherine Homewood, Jacques Imbernon, Rik Leemans, Xiubin Li, Emilio F. Moran, Michael Mortimore, P. S. Ramakrishnan, John F. Richards, Helle Skånes, Will Steffen, Glenn D. Stone, Uno Svedin, Tom A. Veldkamp, Coleen Vogel and Jianchu Xu, 2001, Causes of Land-Use and Land-Cover Change: Moving Beyond the Myths, Global Environmental Change, Volume 11, Issue 4, PP 261 - 269

3. Global Land Cover Facility, 2009, Measuring Man's Impact: Global Land Cover Change, Available online http://glcf.umiacs.umd.edu/services/landcoverchange/, Last accessed 11Th December, 2009

4. Lillesand, T. M. And Kiefer, R. W., (Ed), 2004, Remote Sensing and Image Interpretation, New York, John Wiley & Sons

5. Mohsen Ahadnejad, 2002, Environmental Land Use Change Detection Assessment Using Multi-temporal Satellite Imagery, GIS Development Conference Proceedings, Map Asia, 2002

6. Raber, G., Tullis, J., Jenson, J.,(2005), Remote Sensing Data Acquisition and Initial Processing, Earth Observation Magazine, July 2005 issue

7. Richards. J. A., and Jia, X., 2006, Remote Sensing Digital Image Analysis, Springer Verlag Berlin Heideelberg, Germany

8. USGS, 1999, Analysing Land Use Change in Urban Environment, USGS Fact Sheet188-99


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