Using Neural Networks to Predict Subterranean Termite Hazard in Chi
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Using Neural Networks to Predict Subterranean Termite Hazard in Chi by DANIEL SCHMIDT B.Arch., Universidad Mayor, Chile, 2003 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE FACULTY OF GRADUATE STUDIES (Forestry) THE UNIVERSITY OF BRITISH COLUMBIA December 2006 © Daniel Schmidt, 2006 Abstract In this thesis a neural network is used to create a termite hazard map for China. First, a brief overview of the current situation in China regarding the efforts Canadians are making to introduce light wood frame construction and the challenges they are facing. Amongst these challenges, one of the most important is the hazard of termites in China. The most economically important termite species found in China are then described along with methods commonly used to control the spread of these pests. It serves to identify which species are of more relevance to light timber frame structures in order to concentrate the efforts only on these species in creating the hazard map.. Following this, more information on termite control is given and the issue of Persistent Organic Pollutants (POP's) and the alternative integrated pest management (IPM) system are introduced as possible solutions to deal with the termite problem and, at the same time, comply with international environmental agreements such as the Stockholm Convention. The rationale for methods used to predict the hazard of termite attack in the different geo-climatic zones of China using Neural Network technology is then presented. Existing geo-climatic information for different locations in Japan, the United States and Australia, was linked with previously developed survey-based hazard maps for the three countries. This matrix was used to train a Neural Network, to accurately predict the hazard of the two most economically important subterranean termite genera, Reticulitermes and Coptotermes. The development of a subterranean termite hazard map using verified Neural Network techniques reduces the effort of performing extensive surveys and provides important information for designers, developers and researchers. This work is the first attempt to apply Neural Networks in the forecasting of termite hazard. Further exercises could be carried out to improve the methodology used and expand its field of application. TABLE OF CONTENTS Abstract ii Table of Contents iii List of Tables v List of Figures vi List of Illustrations vii Acknowledgements viii 1. Introduction 1 1.1. Thesis objectives 5 2. Termites and their Control in China 6 2.1. Termites in China 7 2.1.1. Cryptotermes (Kalotermitidae) 8 2.1.2. Reticulitermes (Rhinotermitidae) 9 2.1.3. Coptotermes (Rhinotermitidae) 10 2.1.4. Macrotermes (Termitidae) 11 2.1.5. Odontotermes (Termitidae) 11 2.2. Comments on Termites in China 12 2.3. Termite Control in China 13 3. POP's and Integrated Pest Management (IPM) 15 3.1. Overview 15 3.2. Persistent Organic Pollutants (POPs) 15 3.3. China and the Stockholm Convention 17 3.4. Finding Alternatives to POPs 17 3.5. Integrated pest (termite) management (IPM) 19 3.6. The Australian Example 20 3.7. Facilitating the implementation of IPM 22 3.8. Comments on China, POP's and the Implementation of IPM 23 4. Developing a Termite Hazard Map 25 4.1. Background 25 4.2. Neural Networks 26 4.3. Materials 27 iii 4.4. Methodology 29 4.5. Finding samples 33 4.6. Training the Neural Network 35 4.7. Results 40 5. Conclusions 46 Bibliography 48 Appendices 52 Appendix I. Original Japan Subterranean Termite Hazard Map 52 Appendix II. Original North American Subterranean Termite Hazard Map 53 Appendix III. Original Australian Subterranean Termite Hazard Map 54 Appendix IV. List of parameters used in figures 5 & 6 55 Appendix V. Relationship between stakeholders involved in the implementation of IPM and their function 56 Appendix VI. List of Japanese cities used as data locations in Training Networks 57 Appendix Vll. List of North American cities used as data locations in Training Networks 58 Appendix VIII. List of Australian cities used as data locations in Training Networks 59 Appendix IX. List of Chinese cities used as production sample set for the final Network and their hazard classification 60 IV LIST OF TABLES Table 4.1 Parameters used in climate assessment LIST OF FIGURES Figure 2.1 Northern Limit for Termite activity in China and Population Density Figure 4.1 Japan Hazard Zones and data locations Figure 4.2 North America Hazard Zones and data locations Figure 4.3 Australia Hazard Zones and data locations Figure 4.4 Linear Correlation Coefficient (r) by exclusion.. Figure 4.5 Linear Correlation Coefficient (r) for each parameter tested individually Figure 4.6 Location of data point for China by colour according to hazard value Figure 4.7 Termite Hazard map for China Figure 4.8 China - Annual Precipitation and Termite Hazard Figure 4.9 China - Altitude and Termite Hazard LIST OF ILLUSTRATIONS Illustration 1.1 Villa in Woodland development, Shanghai 3 Illustration 1.2 Dongjiao Development under construction, Shanghai 4 Illustration 2.1 Coptotermes formosanus-eaten container in Guangdong Entomological Institute 10 Vll ACKNOWLEDGEMENTS I want to thank all people that helped putting this work together. First of all, my loving wife Sibylle, for being the best company and support, second, my advisory committee, where Dr. Frank Lam and Dr. Helmut Prion accepted me as a graduate student working under their supervision and constantly advised and guided this lost architect in learning about wood and Dr. Paul Morris, who provided with fundamental information and precious time throughout the process and company in an intense journey to China. I also want to thank Dr. Kunio Tsunoda from Kyoto University, Dr. Robert Leicester of CSIRO, Dr. Zhong Junhong of Guandong Entomological Institute, Dr. Li Xiao-ying of Wuxi Institute for Termite Control and many others that contributed with valuable information. Dr. Wang Jieying and Dr. Ge Hua, for being an amazing company and help in visiting their country. vni 1 INTRODUCTION On September 17tn 2001, China joined the World Trade Organization (WTO) after more than 15 years of negotiations (Panitchpakdi & Clifford, 2002). The most populous country in the world opened new doors for international trade and agreed to undergo a process of modernization of the government administration and legal system to comply with international standards. China has since emerged as one of the biggest traders of products in the world and in 2004 became the third largest merchandise trader (WTO, 2005). Canada, as most of the countries in the world, sees this as an opportunity to expand its trading with China. Forest products are one of Canada's most important exports, accounting for 8% of the total export in 2005 (Statistics Canada, 2006). Therefore, it is not surprising to find Canadian initiatives promoting forest products in China and trying to find opportunities to introduce these products into the huge Chinese market. The emphasis is being put into those products that are more likely to have a large scale impact and most benefit to the forestry sector. In 2004, softwood lumber and wood panels combined accounted for close to 40% of the Canadian forest product's export (CFS, 2005), proving that construction is one of the industries that consumes the largest amount of forest products. However, 80% of all Canadian forest products' export goes to the US, meaning that Canada's forest industries rely heavily on the US and urgently need to diversify its market to mitigate this dependency. China accounts nowadays for only 3% of Canadian forest products' export (Statistics Canada, 2006). The government and the industry recognize that the promotion of light wood frame houses is a key point for the market of wood products in China to grow. Initiatives like the Canada Wood Export Program, that puts together the government and the industry to promote Canadian wood products overseas, is a response to this necessity. According to a report by Canada Wood, there was an increase in the consumption of wood products in China that coincided with the 1 housing policy reform in 1998. This policy reform absolved the state from the cost of providing its people with shelters (Canada Wood, 2003) and allowed employees to buy the apartments they were living in at heavy discounts {Economist, 2000). In 2004, the cycle of privatization was completed and despite the continuous endorsement of Marxist principles among communist Party officials, a constitutional amendment that described private property rights as inviolable was issued and approved by the Chinese communist party {Economist, 2004 (a)). Additionally, a large amount of the unusually large Chinese rural population is migrating towards the cities. Many of the farmers' tiny land-plots are being merged to increase returns on agriculture and boost incomes. The surplus labor is moving into urban areas to work in the manufacturing facilities {Economist, 2003). The housing market engine in China is moving, not only because of the millions of countryside people willing to step into the city, but also because of the millions of citizens wanting to leave overcrowded family homes. This creates a demand for wood products to be used in construction. Interior decoration products, including a variety of value-added products such as furniture, moldings and decorative floor paneling, are the most sought after. Also, the demand for softwood lumber and panels has increased due to the greater number of wood-frame houses that are being built (Canada Wood, 2003). Residential areas of luxury houses commonly known as "villas" have proliferated in and around many Chinese cities. The prices of these houses, characterized by its eclectic architecture, often copying extremes of western style, can go up to US$4 million (see Illustrations 1.1 & 1.2). 2 Illustration 1.1 Villa in Woodland development, Shanghai Source: Picture taken by the author, Feb.