Great Thinkers, Great Minds (Vol. 1) (Preview)

Sunway University Professorial Lecture Series Edited by Peter J Heard

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Sunway University Professorial Lecture Series

Edited by Peter J Heard

Volume 1

Copyright © 2018 by Sunway University Sdn Bhd Published by Sunway University Press An imprint of Sunway University Sdn Bhd

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No. 5, Jalan Universiti Sunway City 47500 Selangor Darul Ehsan Malaysia

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press.sunway.edu.my

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All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, now known or hereafter invented, without permission in writing from the publisher.

Cataloguing-in-Publication Data

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Perpustakaan Negara Malaysia

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GREAT THINKERS GREAT MINDS. Volume 1/EDITED BY PETER J. HEARD (SUNWAY UNIVERSITY PROFESSORIAL LECTURE SERIES) ISBN 978-967-13697-4-6 1. Education. Higher--Research. 2. Universities and colleges--Research.

I. Heard, Peter J. II. Series.

378.12072

Printed by Vivar Printing Sdn Bhd, Selangor

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Contents

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A Note on the Order of Papers Preface Foreword Introduction

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Satellite Earth Observation and Geospatial Analytics in the Sustainable Management of Planet Earth Graeme Wilkinson 28th May 2014

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Development of Antivirals and Vaccines against Enterovirus 71 (EV-A71) Poh Chit Laa 23rd July 2014

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Plurilingual Positioning and Its Effectiveness in Classroom Interaction and Teacher Education Stephen J Hall 24th September 2014 The Expansion of Higher Education and Student Diversity Glenda Crosling 26th November 2014

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Contents

Molecules in a State of Flux Peter J Heard 27th May 2015

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The Rise of Japan and China: A Historical Perspective Goh Cheng Teik 30th September 2015

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Searching for Factors Controlling Cloning of Plants Pua Eng Chong 27th January 2016

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Adventures in Crystal Engineering Edward RT Tiekink 26th May 2016

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War on Terror Cells Naveed Ahmed Khan 5th October 2016

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Acknowledgements

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Index

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Digital Transformations of the Cultural Imaginary Harold Thwaites 28th July 2016

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A Note on the Order of Papers

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The papers in this volume are arranged according to the dates of the Sunway University Professorial Lecture Series presentations held from 2014 to 2016.

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Preface

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Great Thinkers, Great Minds: Sunway University Professorial Lecture Series seeks to highlight and celebrate the expertise of Sunway University’s own preeminent professors and their broad research efforts. The term “professor” in Latin means one who “professes to be an expert in some art or science; [a] teacher of highest rank”.

The title of “professor” is conferred on members of academic staff who not only excel in research but whose research has also gained at least national, if not international, recognition. Alongside the normal academic duties of professors, there is an onus on professors to share their knowledge and expertise more widely and, increasingly important, in ways which an educated lay person may readily understand. It is to this latter end that Sunway University runs a regular series of open lectures — the Professorial Lecture Series — whereby the university’s respected professors present their research work to a broad audience of both fellow academics and members of the public. Following the lectures, speakers are invited to write their lecture presentations into short papers to be added to the general body of knowledge emanating from the university.

This book — the first of what shall become a series of books covering the Professorial Lecture Series — is a compilation of selected papers from some of the most senior professors of Sunway University during the 2014–2016 Professorial Lecture Series presentations. In ideating and nurturing novel research ideas, as well as disseminating their results and findings, professors are not only able to make strides in being the pioneering vanguards of their fields but also enhance the

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research profile of the institutions that they belong to. The value of research in higher education is therefore critical in catapulting a young and modern university to greater heights in terms of world-class academic repute, credibility and excellence. This is the conviction that Sunway University adheres to and one that inspires its commitment to publishing its first book with Sunway University Press. While the endeavour of transforming lectures into book chapters may be challenging, the essence of each lecture is preserved and even augmented to further engage readers.

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Foreword

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The sun has existed for billions of years, giving light and energy for the sustenance of life in our solar system as part of the universe’s spectacular grand design. It fits perfectly into the complex web of extreme creation and brilliance that has existed in delicate balance, giving light and hope that all life depends upon.

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The above opening words also accurately describe the organic growth and evolution of a young, dynamic educational institution in the heart of a magnificent, vibrant premier Malaysian township known as Sunway City. The inspiration and birth of this young but rapidly growing academic institution came from the finest, inspirational corporate mind of its founder, and subsequently refined by a stream of business and academic leaders. From its humble beginnings, initially as Sunway College and then rightfully upgraded to Sunway University, its growth has been charted out along its own carefully chosen path. This stunning progress can be best described by its own unique name, which is the amalgamation of the words ‘Sun’ and ‘Way’, providing illumination and guidance to all those along the Way of the Sun. At this very young age of its history, Sunway University has set very high aspirations to grow into one of the best and finest global academic institutions in the rank of Cambridge and Harvard. The institution is fully aware of the requirements needed to become a top university, where above other strategic priorities, it has to quickly achieve success and recognition as an institution of leading, cutting-

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edge research and impactful publications. Leading academics in several key areas spanning the sciences, arts and humanities have been recruited, joining a team of already talented academic staff, to form a critical academic workforce to push the achievement bar upwards. This is a truly daunting task but one which Sunway is entirely confident it will achieve in the years to come.

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This publication is part of an all-embracing coordinated effort, not only to promote its achievements to the general academic community, but also to establish the dynamic culture of quality research and publications along the practices of top leading universities. In this first issue of its kind, a good spread of papers covering topics in science, medicine, economics, education, IT, engineering and social science are documented, representing a sampling of the latest work of leading professors within the system. These are papers that have been presented in the Professorial Lecture Series of the university and it is hoped that these papers will provide readers with a flavour of some of the university’s current research activities. This practice of sharing its research with a wider audience is crucial at this stage, as universities must prove their relevance to society and engender a culture of impactful and beneficial research that contributes not only to economic prosperity, but also to the greater good of humanity in Malaysia and beyond.

Professor Tan Sri Dr Ghauth Jasmon Sunway University Board Member, November 2017

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Introduction

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Cynics may argue that universities have changed little since they were first established around 900 years ago. Still others have argued that the massification and marketisation of higher education — definitely something of a major change in recent years — have led to the loss of much of what was precious, perhaps even quintessential, about universities. These are polar views that both capture something of the truth. While in some ways universities may appear to have changed little over time — the design of the programmes of study, and the way in which students are taught and assessed are oft-cited examples of what has not (but many argue surely must be) changed — in many aspects, universities are now radically different places from what they were when most of today’s academics were undergraduate students, with much of that change seen as a detriment to the primary mission of universities: the betterment of human experience.

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The emergence of research assessment exercises, such as the REF in the UK and MyRA in Malaysia, and the emergence of league tables which place such a high weightage on research excellence, are key criteria on which universities are now judged. Consequently, any university aspiring to be regarded as among the best in the world must focus a significant amount of its energies on developing its research profile.

This fact is not fundamentally all bad, as the competition that it has created has undoubtedly led to highly beneficial developments that may otherwise have taken many more years to achieve, and it has increased the importance of the sharing of research findings among a wider audience that is beyond the so-called ivory towers of the

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universities themselves. It is part of Sunway University’s key missions to share the knowledge created within its walls, and in universities elsewhere, to the benefit of as wide an audience as possible that it established a series of open lectures by its professors called the Professorial Lecture Series.

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The Professorial Lecture Series was established to provide a platform for the university’s most senior academic staff to share their knowledge and expertise, and this book was conceived as a by-product of those lectures to try to reach beyond just those able to attend the lectures themselves. While the lectures in this book mainly cover the areas of the sciences, such as biology, chemistry and physics, they also include notable contributions in the arts, education and global politics.

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In the subject of biology, Professor Pua Eng Chong — who is the Deputy Vice-Chancellor of Sunway University — examines the factors that regulate the growth of young plant shoots in his paper.

This work is of tremendous importance, given the ever-increasing pressures on food supply and the need to produce crops more efficiently, albeit with minimal wider environmental impact. From plants, we move on to human health. Professors Poh Chit Laa and Naveed Ahmed Khan are focusing their efforts on some of the world’s most pressing human health issues. Professor Poh has a lifelong ambition to find a vaccine for hand, foot and mouth disease and is working on the development of antivirals against Enterovirus 71, which is one of the leading pathogens of the disease. Professor Poh is now also applying the knowledge and understanding she has gained in this work to help find a vaccine for Dengue, a major disease problem in Malaysia and elsewhere. In contrast, Professor Khan’s work focuses not on viruses, but on finding new drugs that are effective against drug-resistant bacteria. Professor Khan’s hypothesis is a very simple

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one: animals that live in highly polluted environments must have evolved mechanisms for fighting microbial infections. As he explains in his paper, Professor Khan has found that animals, such as humble cockroaches, have indeed developed natural defences which he is now looking to exploit in the development of new drugs.

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Crystal engineering is a new and rapidly expanding area of research at Sunway University. In his paper on the subject, Professor Edward RT Tiekink examines the various intermolecular forces that help to hold molecules together in a crystal. Armed with this knowledge, Professor Tiekink hopes that it will be possible to design crystal architectures to confer particular properties on the crystal.

Underlying this work is his desire to find new and improved drugs for treating infections and diseases, such as drug-resistant cancers.

My own work, described in the chapter Molecules in a State of Flux, explores the dynamic world at a molecular level. All molecules are in constant motion and I set out to show how the careful design of molecules can help provide an insight into a variety of different dynamic — or so-called fluxional — processes.

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The university’s Vice-Chancellor, Professor Graeme Wilkinson, reviews 50 years of remote (satellite) sensing in his chapter and discusses the role of satellite data in the sustainable management of our environment. He looks forward to how recent developments in the field, coupled with geographic and other data, are opening up exciting prospects for a better understanding of the world and our impact on it.

From the sciences, we move — perhaps more smoothly than you might imagine — to the arts, and in particular, to the preservation of cultural heritage. Professor Harold Thwaites, the Dean of the School of Arts, has a passion for exploring how technology can enhance xv

Introduction

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our cultural lives. In his paper entitled Digital Transformations of the Cultural Imaginary, Professor Thwaites shows how modern digital technologies can be applied to the capture and (re)presentation of our cultural heritage, using the example of the Hainan boatbuilders of Pangkor Island. From the boatbuilders, we move on to examining how the expansion of higher education, particularly in more recent years, is impacting on the very nature of higher education itself. This is a highly important topic for academics and policymakers to get to grips with if higher education is to make a positive impact on the lives of future generations — an influence that those of us who work in higher education believe can and must happen. In her paper exploring how teaching and learning are evolving, Professor Glenda Crosling argues for the need to embrace student diversity and harness the talents of all if we are to be able to face future global challenges with confidence of success. As a native of the UK and having now moved to live and work in Malaysia, I find myself wondering what it means “to speak English”. In his paper on “plurilingualism”, Professor Stephen J Hall considers how the learning of a second (or third, or fourth!) language can be enhanced and nurtured in multilingual environments, such as Malaysia.

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In a chapter contributed by Professor Goh Cheng Teik — one of Malaysia’s best known scholars and a member of the Board of Directors of Sunway University — an overview of the history of East Asia and international relations from the Opium Wars to today is given. Professor Goh examines the factors leading up to World War II and touches on the rise of China to becoming one of — if not the — economic superpowers of the world today.

Professor Peter J Heard Sunway University, November 2017 xvi

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Satellite Earth Observation and Geospatial Analytics in the Sustainable Management of Planet Earth

Abstract

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Graeme Wilkinson

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This paper considers the development of and future prospects for the field of satellite remote sensing as a tool for monitoring and

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managing the Earth’s environment. This is now a key technology in sustainability planning. The development of satellite imaging sensor systems is reviewed, leading up to the contemporary hyperspectral

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high-resolution sensors and multi-polarisation synthetic aperture radar systems. The paper also considers the complexity of the data analysis required for useful environmental applications, along with the issue of handling the data volumes involved, particularly arising from multi-sensor approaches. The use of artificial intelligence to analyse complex satellite data is discussed, such as the use of neural networks to yield useful maps for environmental scientists and policymakers.

While technological advances in satellite hardware and software algorithms to analyse data have been impressive, a number of complex issues remain in the exploitation of satellite data for environmental monitoring, especially when it comes to changes in land cover. These

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difficulties arise from the difficulty of defining meaningful land cover labels and from the mathematical properties of natural phenomena, such as the fractal aspects of forest patterns. This paper also considers the prospects for the use of geospatial analytics. Data analytics can now be used to extract valuable environmental information from massively rich data sets comprising complex satellite data plus a wide

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variety of ancillary geographical data for an increasingly exciting range of applications. Â

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The sustainable management of our planet’s environment is now one of the most important challenges facing mankind. The Earth’s land, atmosphere and oceans are constantly undergoing changes as a result of human activities. Many of those changes are damaging, longlasting and likely to impact significantly on the ultimate survivability of the human race. Although the threat to the quality of human life and human existence is real, we do at least have the tools to monitor the changes that are taking place and analyse the results of any action to mitigate environmental damage.

Most of us are probably unaware that there are now dozens of satellites in orbit around the Earth gathering highly complex environmental information on a continuous basis, mostly in the form of images. The scale of satellite imaging operations is rarely appreciated by users of Google Earth who may understand that image collection has been taking place but may not understand the complexity of it. These satellites have been put into orbit mainly by national and international space agencies, and increasingly by commercial companies in recent years, to improve our stewardship

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of the planet. The field of satellite remote sensing is now almost half a century old and, as the technology of satellite sensors has improved, the environmental problems requiring increased monitoring have become steadily more serious.

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Notable successes have been achieved, such as the reduction in the use of chlorofluorocarbons as refrigerants which were found in the 1980s to be destroying the Earth’s ozone layer. The ozone layer has provided protection against excessive ultraviolet radiation from the Sun for millions of years, protecting the ability of many species of flora and fauna to survive. But when it came under threat from human activity, it was only through the use of satellite remote sensing that mankind was able to appreciate the scale of the problem and then introduce an international policy to control it (in this case, the 1987 Montreal Protocol).

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This paper shall examine some of the developments in satellite remote sensing technology that have taken place over the last five decades to help monitor planet Earth, as well as in the computational approaches for extracting useful information from the many terabytes of environmental data collected by satellites each day.

Developments in Satellite Sensor Systems The science of Earth observation, or satellite remote sensing, even at half a century, is still relatively young. It is in many respects an interdisciplinary science, drawing on technical developments in physics, computer science, engineering, information systems, space science, environmental science and geography. This gives it an appeal to many scientists who come from different backgrounds. Satellite remote sensing effectively began in the 1960s, when the first satellites

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were developed with primitive television and infrared cameras to observe weather patterns. Indeed, meteorology became the first and only real civil application of satellite remote sensing for almost 10 years. The first satellites designed to provide information about land surface were launched in the early 1970s. The first Earth Resources Technology Satellite, which later became known as Landsat-1, was launched in 1972. Carrying a simple visual imaging system, Landsat-1 began to provide multispectral computerised images of the Earth, which gave an entirely new perspective on examining the state of our planet. The Landsat satellite series has continued ever since with each one providing improved imaging capability. The latest, Landsat-8, launched in 2013, is providing detailed multispectral images which can be compared to ones of 42 years earlier to detect changes in the landscape, such as through desertification or deforestation. The long-term continuity of the Landsat mission series, despite some setbacks along the way, has been one of the greatest achievements of the remote sensing community and its supporters.

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The next landmark in the evolution of satellite remote sensing, after the development of land observing satellites using multispectral visual and digital imaging systems, was the development of radar satellites in the 1980s. Imaging radar systems, known as Synthetic Aperture Radar (SAR), were developed and deployed on the European ERS-1 satellite in 1984 and subsequent satellites, e.g.

Sentinel 1, launched in 2014 (Figure 1). SAR systems can provide a detailed view of the Earth’s surface, both land and sea, at radar frequencies similar to those of a domestic microwave and they can, moreover, “see� through clouds day and night.

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Impression of Sentinel 1 radar remote sensing satellite in orbit (Source: European Space Agency; CC BY-SA 3.0 IGO)

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Figure 1

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The SAR technique relies on a complex mathematical approach to analysing radar signals transmitted from the satellite and bounced back from the ground. The technique enables the sensor system to behave as though it has a giant antenna much larger than it really does (hence the name “synthetic aperture�) and, by so doing, focus in on sufficiently small details on the landscape to be able to generate an image that looks, to all intents and purposes, exactly like a detailed photograph. The key difference, however, is that such a radar image shows not the visible appearance of the landscape as would be seen by the human eye but the appearance to a radar beam. The bright parts of an image would be those which reflect radar waves strongly and the dark parts would be those which do not. As the extent to which

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Figure 2 Radar image of the city of Lisbon and the estuary of the River Tagus, Portugal. The colours indicate variations in the radar reflection properties of the land surface, signifying different types of land use and crops. The city centre appears bright where the buildings strongly reflect the radar beam. (Source: NASA; Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar Image)

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the land surface reflects radar waves can depend on its roughness and moisture content, the patterns seen in radar images (Figure 2) can be used to infer soil moisture content, the density of vegetation, the state of health of trees, etc. Over the seas, radar images can reveal the patterns of ocean currents and the presence and density of ice floes, etc., all of which are extremely important to shipping and also relevant in the context of global change monitoring. Recent radar images have indeed revealed loss of huge quantities of ice from the Antarctic coast, indicative of global warming.

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Continuing with the history of satellite remote sensing, the 1990’s became the decade in which, for the first time, imagery became available of such fine detail that even human beings could just be seen — a remarkable feat considering that the satellites providing the imagery orbit at an altitude of around 700 kilometres. The first satellites providing very high-resolution imagery, such as Ikonos and Quickbird, were essentially a spin-off from military surveillance technology. The same technology used by the military for surveillance effectively entered the civilian domain to provide imagery which almost anyone in the world could buy with sufficient funds. Very high-resolution images show such detail that they can be used to create or update maps. New roads, for example, are clearly visible.

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The dawn of the 21st century brought yet another evolution in Earth observation. Concerns about the state of the planet led to the development of advanced satellites, such as the American Terra satellite and the European Envisat satellite, which were essentially large space platforms carrying many sensor systems designed to observe the atmosphere, land and oceans in different ways. Such satellites were truly large-scale orbiting platforms, providing rich combinations of imagery and measurements that were unprecedented in terms of their information content. Envisat, for example, could capture multispectral images with one sensor in up to 36 wavelengths of light or infrared, and highly complex radar images at multiple frequencies and with multiple polarisations with another sensor. Terra also had imaging systems to take views of the Earth at different angles, i.e. not simply a straight-down view but also an oblique view of the same spot on the ground.

In combination, all this information is extremely valuable and a

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considerable amount of research has been devoted over the years to the mathematical approaches for integrating such data, through techniques of “data fusion”.

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Essentially, all remote sensing satellites now provide “photos” of the ground as digital multispectral images. Such images can be stored and processed in a computer in much the same way as images from a digital camera, although the multispectral aspect creates many more opportunities for useful information extraction by a range of techniques. Indeed, there are many similarities between domestic digital cameras and satellite imaging sensors, except the technical specifications are several orders of magnitude apart, as shown in Table 1.

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Table 1 Comparison between a domestic digital camera (e.g. smartphone) and a satellite imaging sensor system

Domestic Digital Camera

Satellite Imaging Sensor Can exceed 100 megapixels per view

Single spectral image (visible)

Multiple spectral images, even over 200 of them

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~12 megapixels per view

Can resolve ~1 mm of detail at a 10 m range

Visible, infrared and radar parts of the electromagnetic spectrum Can resolve ~0.5 m of detail (sufficient to see human beings) from an altitude of around 700 km

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The images are normally captured by the satellite sensor system as a continuous stream of rows of pixels which the satellite views as it flies around in its orbit. The digital pixel data are transmitted to ground receiving stations where they can be corrected for any distortion and then archived. The pixel data can then be sliced up into image frames, like photographs, and distributed to users who themselves may apply a considerable amount of computer analysis to them to extract information of interest.

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It is interesting to note that in order to see the land or ocean surface, a satellite imaging system has to work at a wavelength at which the Earth’s atmosphere is transparent. This applies in the visible part of the spectrum and at some infrared wavelengths. The fact that the atmosphere is transparent at visible wavelengths is well demonstrated by the fact that we humans, who have eyes that are sensitive to visible light, can see through the atmosphere and see the moon, stars and planets. At some wavelengths, the atmosphere is not transparent at all. The Eumetsat operational weather satellites, for example, have an imaging sensor that records images at a wavelength where water vapour in the atmosphere strongly absorbs infrared radiation. The images from such a sensor simply show strange murky patterns as though looking into a dense fog or liquid. While it is impossible to see the ground in such images, they are still extremely useful as they show the patterns of water vapour and the flow of the weather systems in the middle of the troposphere. To the uninitiated, such images look as though they are from another planet, such as one of the so-called “gas giants�, Jupiter or Saturn. Essentially, our view of our own planet and of others is strongly influenced by the types of sensors used to observe them. Likewise, although radar can penetrate

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the atmosphere and see to the ground, the images from radar sensors can be significantly different to those obtained over the same piece of landscape from a visible or infrared camera. It is this possibility of viewing our terrestrial environment in so many different ways that is a real advantage of satellite remote sensing.

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One of the characteristics of satellite sensors that differentiates them one from another is the “spatial resolution”. This is the size of each pixel as measured on the ground and indicates the amount of detail in an image. Weather satellites produce images with pixel sizes of several kilometres. A typical image of several thousand pixels square can thus cover an area equivalent to a whole country or continent. This “synoptic” view is essential to viewing the general weather patterns and their movements. Sensors on environmental monitoring satellites, whether optical, infrared, or radar, tend to have spatial resolutions of a few tens of metres, or sometimes up to one kilometre. This means typical images of several thousand pixels square will cover an area ranging from a county to a whole country in which the general patterns of land cover, such as natural land, agricultural plantations, forests, industrial areas, ice sheets, urban areas, etc., are clearly visible. Such images can reveal subtle changes in landscapes that are not easily assimilated on the ground and help in the monitoring of global change such as glacier retreat.

Finally, at the top end, sensors operating at very high spatial resolutions have pixel sizes in the range of 0.5–10 metres. Such pixels are sufficiently small to be able to identify buildings and vehicles, etc.

Humans can just be seen, though not explicitly identified. Images a few thousand pixels square with such resolutions cover a few square kilometres and are optimal for detailed mapping purposes. The quantity of data now generated by remote sensing satellites through

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such sensor developments is indeed growing rapidly. Many terabytes of data are generated every day and the quantity of data now archived is of the order of many petabytes. This archive is being added to on a continual basis, providing a rich source of data for analysing trends in ecosystems, environmental changes and human uses of the planet’s resources.

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Developments in Data Analysis Techniques — From Photo Interpretation to Artificial Intelligence Based Image Understanding

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Having explored some of the history of Earth monitoring satellites and some of their characteristics, it is now appropriate to consider the applications of the satellites and the means by which it is possible to derive useful quantitative information about our planet from their images. At a simple level, the images themselves provide dramatic, colourful views of our planet and reveal significant changes to the landscape. For example, satellite images of South America reveal bright rectangular areas of soil and cultivation against a background of dark, dense tropical rainforest. These are the areas of deforestation where farmers have destroyed natural habitats for economic gain.

While such changes to the landscape can be readily identified visually, many other changes are subtle and require computer analysis of the images, exploiting the spectral, spatial and contextual nature of the digital pixels.

One of the most common procedures adopted in the exploitation of satellite images is “classification”. In the scientific sense, this is essentially a mathematical pattern recognition technique, the aim of which is to assign individual pixels in an image to a land cover “class”, such as “forest”, “bare soil”, “vine plantation” and

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Figure 3 Principle of multispectral imaging and analysis. Multiple views of the Earth from the sensor at different wavelengths create a data stack.

This can be augmented by data from different types of sensor and on different dates, as well as with ancillary data from geographical databases, giving highly rich data sets for analysis and interpretation.

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“urban area”, which can then be shown on a thematic map. This process can also be described as pixel labelling and its purpose is to transform a stack of satellite images into a useful map that can be used in environmental studies (Figure 3). Interestingly, classification or labelling is not restricted to the analysis of satellite images.

Classification in a non-scientific sense is actually an inherent part of human everyday experience. It can be argued that humans are almost obsessed with classification and labelling, both of which are activities that are undertaken daily. Classification and labelling are all about making sense of the world. We attach labels to objects, both animate and inanimate, in our daily lives and put objects into classes. We categorise and label people, for example, as “upper class”, “middle class” or “working class”; we say they are of one type of ethnicity or

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another. At work, time is spent categorising and filing documents in files with labels attached to them, either physically in filing cabinets or virtually in computers. Labelling is a fundamental aspect of being human. It is an integral part of language and communication. Even the first humans to walk on the planet had to learn to distinguish between “safe” and “unsafe” plants and animals, and to label them as such and use such labels in their interpersonal communications — mistakes could have been costly.

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Classification of satellite imagery is also concerned with communication. It is concerned with labelling image pixels so that their meaning or interpretation can be communicated. By mathematically classifying pixels, labels are assigned to them that can then be represented as a map. The classification process effectively transforms an image consisting of pixels with multiple spectral measurements into a map of labelled squares showing what is on the landscape. Such maps are usually known as categorical maps or thematic maps. In many respects, the classification of satellite images is directly analogous to human visual perception. Humans have eyes (sensors) that observe objects and produce electrical signals (data) that are interpreted (classified) in the brain to produce an understanding of the scene as labels, e.g. I can see a “chair”, “table”, etc. The cognitive human process and the machine process have much in common, except we do not fully understand how the brain comprehends objects, while we can describe with great precision, mathematically, how an image classification algorithm performs.

The computational classification of satellite imagery is a significant challenge firstly because of the large number of pixels in a typical image, and secondly because each pixel may have a large number of spectral measurements associated with it. These

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separate measurements can be regarded as different mathematical dimensions. The task of classifying pixels in a multispectral image of N spectral bands actually amounts to determining which regions of an N-dimensional space should be labelled as particular land cover types. This can be done in a variety of ways; some statistical and some non-statistical. Statistical approaches are the most conventional and have been used for many years. The statistics of the pixels have to be derived mathematically and are then used in a “maximum likelihood� process to determine the optimum labelling, i.e. to determine the class label with the highest probability of being associated with that pixel.

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Such conventional classification techniques have also been supplemented by approaches based on artificial intelligence and, in particular, the use of artificial neural networks. Such techniques, which are at the forefront of computing research, demonstrate the truly multidisciplinary aspect of satellite monitoring. Artificial neural network software programmes simulate groups of simple interconnected processing units which, in a very crude sense, are modelled on neurons in the human brain (Figure 4). However, there is a large difference; most artificial neural network programmes simulate typically 10–100 neurons, whereas the human brain has of the order of 10,000,000,000,000 neurons. The aim of artificial neural network programmes is to mathematically transform pixel data into labels, just as the human brain transforms visual stimuli into a description of a visual scene using language. Following over two decades of research in this area, neural network programmes are now routinely used alongside other mathematical approaches for satellite image classification and, in some cases, among whole ensembles of classifier algorithms with the aim of producing an

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Output = landscape classes (e.g. forest, grassland,...)

Output layer

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Mathematical “weights” of connections between artificial neurons must be adapted to do the mapping job accurately – a “learning” process

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“Hidden” layer

Input layer

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Input = satellite image data (pixel intensities)

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Figure 4 Multi-layer artificial neural network approach to satellite image analysis. The multi-layer software system learns how to recognise patterns in satellite data and transform images into useful environmental maps.

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optimum labelled map of a landscape as viewed from space. The use of artificial neural networks applied to satellite imagery (a satelliteneuro-classification process) can be analogous to the human visual cognition process.

Although most neural networks are simulations of neural behaviour in software, there have been some attempts to construct computer hardware which contains special microchips designed to mimic simple neuronal processing. Some of these machines have been used in experimental classification of satellite imagery. Although such machines are extremely powerful and interesting from a scientific point of view, there is little market demand for them, and they have tended to remain as prototypes in research institutions and have not become commercially available on a wide scale. Interestingly,

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