A study of quantity control over hillside development in Taipei County area

Transcription

1 A study of quantity control over hillside development in Taipei County area T.-Y Hsiao &Y-H.YU Graduate Institute of Environmental Engineering, National Taiwan University, Taipei Taiwan. Abstract Hillsides with varying slopes account for about 88% of the total area of Taipei county. In order to reasonably control land resources, this paper presents a socalled indicator control system using the Delphi method which is still theoretical and in need of long-term, continued development. These indicators are produced by many representative and development quantities, and each indicator is weighted. However, further developing this indicator system, and applying it to regional development control in Taipei County will require many preparatory operations and follow-up items. This study, therefore, provides simplified "transient-type" development quantity control criteria. The production and major objectives of the said criteria are to facilitate related environmental protection administration operation in Taipei County, and to serve as a reference basis for the county government in managing development behavior among various towns with hillside areas. Introduction For several decades, Taipei County, by means of the advantage of encircling Taipei City, an important urban center in north Taiwan as shown in Figure, has maintained high growth of its population and industrial development. It encompasses 2,053 square kilometers with hillsides making up about 88%. The ratio of hillsides is the largest of all counties in Taiwan. Hillsides pose unique problems for the construction and maintenance of human activities. They are prone to natural hazards, and they topographically constrain the design of developments. Hillside development requires special land-use planning considerations because of their inclined slopes and often being environmentally sensitive areas. A variety of considerations of aesthetics, public safety, and environmental quality are addressed concerning hillside development. Olshansky

2 232 The Sustainable City reviewed different views among the design disciplines and illustrated common disagreements regarding hillside development planning. There were hillsides plans and ordinances collected from 90 local governments throughout the United States in that research. The earliest forms of hillside regulation consist of grading ordinances, pioneered in the City and County of Los Angeles in the United States in the 950s. These ordinances were initiated as a response to numerous damaging landslides, caused by poorly placed fills, during heavy rains in the winter. As environmental concerns began to be integrated into comprehensive plans in the 960s and 970s, many plans addressed hillsides as valued components of the landscape []. In the past, the quantity control concept was mostly applied to river-content capacity and air pollution management in Taiwan. However, the planning of development quantity control proposed in this paper is an important means to guide local development toward a more commendable approach, with so-called commendable development referring to the prime premise of development which does not sacrifice environmental quality. In any event, it is intended to further engage in detailed quantitative planning of development quantity control criteria, which prerequisites require assessing the impacts caused by natural environmental conditions and human factors in terms of each different total quantity subject. Figure : The position of Taiwan in East Asia and the location of Taipei County in Taiwan. 2 Methodology The Delphi method was used to collect expert opinions through a structured, well-designed questionnaire in this research. The Delphi method was developed in the 960s as one of many techniques used in decision analysis, probability estimates, and long-range forecasts [2]. In brief, this technique uses a questionnaire, which is circulated among a panel of experts, who are unaware of the identity of fellow members of the panel, because the Delphi method aims to

3 The Sustainable City 233 encourage independent and unbiased assessments from each individual. The method has been widely used for environmental assessment and for monitoring programs [3]. The success of this and other techniques for decision analysis is very dependent on the design of the questionnaire and the selection of panel members. A flow chart for the method is shown in figure 2. Figure 2: Indicator data analysis flow chart 2. Initial Screening of Control Indicator System The establishment of an indicator system is based on existing statistical data of higher operation property available in Taipei County serving as the selection basis, and with reference to listed items in related domestic hillside development, legal requirements are used as indicator selection [4]. First for the expert questionnaire, the Delphi method was applied to elicit expert opinions concerning the appropriateness of each indicator and its weighting. After more than two investigations and a through concurrent inspection, the investigation was then terminated. Table indicates the classification about human factors of the selected indicators in the preliminary research phase, and the integral flow through statistical inspection for screening. 2.2 Selection of Indicator Items The content of the initial investigation questionnaire was based on fulfilling the indicator system structure of the human factors on a preliminary basis, while experts only evaluated scores for a total of 27 indicators. Concerning the selection of these indicators, since the present Taiwan Provincial statistical data mainly deal with counties and cities as one unit, data collection could only be aided by local government sectors. Other reference resources also included one volume of an annual Statistics Guideline published once by the Taipei County government [5], which includes population structure, industrial structure, education, etc., as the richest data resource; the other resource is environmental

4 234 The Sustainable City information for Taipei County consigned by the Department of Environmental Protection of the Taipei County government to the Department of Botany of National Taiwan University for study [6]. Table : Human factors indicator system of hillside development in Taipei County Area Scope of unit Indicator Population density Residence density Factory density Business density Agriculture density Husbandry density Life, industry, and activities Aquaculture density Road use Traffic flow quantity Public facilities on ground surface Drinking water Sewage ditches Human Factors Related environmental damage and pollution aspect 2.3 Design of the Expert Questionnaire Cemeteries Refuse Tourism treatment sites Hillside disaster (including soil/stone drains) Dwelling place destruction Landscape destruction Floods Water pollution Air pollution Solid waste pollution Harmful industrial waste pollution Soil pollution Noise pollution Heat pollution In order to further demonstrate the difference of importance levels between indicators and to avoid the scoring from being influenced by the existing text, the attitude quantification chart used a decimal numerical system, only specifying the indicator deemed extremely unimportant to be scored as, and the one deemed extremely important to be scored as 00. The experts were also requested, either by mail or fax, to evaluate whether the indicators of the two fields directly respond to their importance. In addition, open questions were presented to request the interviewed experts to provide any omitted important indicators in the system and to recommend other representative indicators, as well as furnishing comments on the defects of the preliminary system. 2.4 Organization of an Expert Task Force The interviewed parties are quiet important to the research. In the event the specialization of an interviewed person is not related to the investigation content or the interviewed party is not familiar with the investigation content, then this will certainly cause errors in the investigation results. Therefore, while selecting

5 The Sustainable City 235 an interviewed expert, his (her) personal major and specialization must be considered. For this research, 4 experts in the fields of engineering and sanitation, etc., jointly comprised the expert task force. 2.5 Recovery of the First-time Questionnaire and the Investigation Questionnaire of the Second Go-round During arrangement of the related recommendations provided in the first-time questionnaire, some experts recommended that related legal requirements concerning development be incorporated, yet under the consideration of being unable to quantify legal requirements, this item can only be incorporated as an "ideal" or a "theoretical" indicator. The results of the expert opinions of the first interview are arranged into an evaluation scoring table, to be incorporated into the first-time questionnaire, for the above-mentioned expert task force to engage in the second scoring evaluation for various indicators under the two fields of natural environmental conditions and human factors, with results serving as the basis for conducting the analysis. 2.6 Concurrent Inspection Calculated values were transformed into probability ratios (P value). A P value larger than the statistically significant level of 0.05 indicates that the scoring difference of two times in statistical inspection is not significant; the closer the P value is to indicates the statistical scorings of both times are more concurrent. Therefore, in view of cost performance, we were not required to engage in another interview, and the data obtained in the second interview may serve as a reference for deciding important indicators. This paper attempts to obtain Chisquare statistical quantities converted to P values [7], with the focus on whether the statistics for the scoring of experts (continuous-type probability variable) and expert fields (scattered-type probability variable) are independent, i.e., whether these two variables are connected. 2.7 Non-Hierarchical Cluster Analysis A non-hierarchical cluster analysis method normally provides a certain standard first, then compares if the formed clusters are proper. These are calculated repeatedly to attain the cluster division best satisfying the said basis, and then all divisions are compared one by one with the said basis, to ultimately find out which kind of division can attain the best satisfaction. The research mainly applies the K-mean method (as shown infigure3). 2.8 Long- and Short-term Concept Classification Requirement To respond to the above-mentioned long-term concept and short-term concept requirements, the following chapter is classified into two parts. The first part deals with the establishment of an indicator control system framework, which is rather theoretical and in need of long-term continued development; the second

6 236 The Sustainable City part provides a response to immediate requirements and objectives, supplying a simplified method of quantity control criteria able to be practiced as a basis for the current stage. Figure 3: Calculation flow chart of the KL-mean method 3 Establishment of Quantity Control Indicator System 3. Preliminary Analysis of the Questionnaire Results of Two Times Before engaging in concurrent inspection, the average score and variable data of the scoring results of the two times were initially compared. From table 2, the number of indicators with an increased score the second time over the first time and the number of indicators with a decreased score can be determined; this provides an indication of upgraded indicator importance and difference in expert opinion with recession tendency, and afterward the concurrent inspection was conducted to judge if the investigation could be suspended. Table 2: Comparison table of the 2-time expert questionnaire index importance level scoring average value and variable difference in human factors Scope Indicator mean variance mean variance of unit x«-x,. s^/s,., Life, in dustry, and activities Population density Residence density Factory density Business density Agriculture density Related Refuse treatment sites environmental damage and pollution aspect Hillside disaster (including soil/stone drains) Dwelling place destruction Landscape destruction Floods Water pollution Heat pollution

7 The Sustainable City Concurrent Inspection Results and Chi-square Result of Cross-analysis As shown in table 3, almost all P values of all indicators were larger than the statistically significant level, indicating the scoring difference between two measurements was not significant. Therefore, the second scoring result shall serve as the basis for the non-hierarchical cluster analysis. It can be seen that P values are all larger than the significance level. Therefore, the assumption that the expert scoring and expert field are independent can be accepted. Table 3: P values of concurrence inspection and the statistical quantity E value of Chi-square of cross analysis in human factors Scope of unit order Indicator concurrent chi-square inspection inspection Life, industry, and activities Population density Residence density Factory density Business density Agriculture density Refuse treatment sites Related environmental dam; ige and pollution aspect Hillside disaster (including soil/stone drains) 2 Dwelling place destruction 3 Landscape destruction 4 Floods 5 Water pollution Heat pollution Result of Non-hierarchical Cluster Analysis The indicators are divided into scoring importance and scoring non-importance as shown in table 4. Table 4: The second expert importance scoring statistical table and cluster analysis result in human factors Scope of Indicator mean V ariable Ratio % of two groups unit Sj,,j Group ( important ) Life, industiry, and activities 8.23 Population density 8.07 Residence density Factory density 7.43 : Business density Agriculture density Group 2 ( non important ) Related en\ ironmental damage and pollution aspect ( 00 Hillside disaster (including soil/stone drains) ( Dwelling place destruction Landscape destruction ( Floods Water pollution

8 238 The Sustainable City 3.4 System Confirmation After the second scoring result was arranged and calculated, the relative weighting in two fields under human factors and its indicators were obtained. The total weighting of the integral human factors were counted as 00, then in both fields under human factors, the weighting of "life, industry, and activities" was 47, and that of "related environmental damage and pollution aspect" was 53; the size of the weighting indicates that the experts considered the importance of both fields to be extremely close. The weightings of each indicator are shown in table 5, in which it can be seen that in the field of "life, industry, and activities", the weighting of traffic flow quantity is the highest; and in the other field, the weighting of hillside disaster is higher. After the indicator number was confirmed, the indicators with high average scores were selected, with scores through non-hierarchical cluster analysis falling in the important cluster ratio being obviously high and able to be reasonably accepted, and which serve as the confirmation principle of the last indicators. This research ultimately choose 9 indicators for the human factor indicator system of the development quantity control in local development of Taipei County. Table 5: Indicator weightings of the human factors Scope of unit Human (weigh-ti ng 00) Life, industry, and activities (weighting 47) (No. of items, 9) Related environmental damage and pollution aspect (weighting 53) (No. of items, 0) Indicator Traffic flow quantity (weighting 4) Factory density (weighting 3) Population density (weighting 2) Road use (weighting ) Residence density (weighting ) Refuse treatment sites (weighting ) Sewerage ditch (weighting 0) Public facilities on ground surface (weighting 0) Drinking water (weighting 9) Hillside disaster(including soil/stone drains) (weighting 3) Dwelling place destruction (weighting ) Landscape destruction (weighting ) Floods (weighting ) Water pollution (weighting 0) Harmful industrial waste pollution (weighting 0) Solid waste pollution (weighting 9) Air pollution (weighting 9) Soil pollution ( weighting 8 ) Noise pollution ( weighting 8 ) 4 Simplification of Development Quantity Control Criteria The proposition of this simplification criteria is to facilitate the related environmental protection administrative operation, to enable the county government to have management references available concerning the development behaviors of various towns and cities with hillsides which may occur in the future. On the other hand, this simplification criteria shall also be provided to the public and private sectors in charge of development behaviors concerning environmental influence aspects. Particular attention will be paid to such behaviors, with the so-called major instructions, to facilitate them to be free

9 The Sustainable City 239 from being misused in performing environmental influence evaluation operation on one hand, and also be free from any impractical anticipation concerning the evaluation review result. 4. Content of Development Behavior Restriction Factors and Study on Importance Priority In view of the current development situation of Taipei County, through many site investigations for this research, the detrimental environmental side effects caused by various development behaviors can generally be divided into two major categories: () The first category concerns towns with high hillside content and high population density, in which the majority of "non-environmental improvement type" development behaviors almost always cause additional deterioration of the existing environmental quality, increase in various pollution items, and decreasing hillside safety. Next, these development behaviors also produce a load to the circulation ratio of the peripheral traffic situation of their localities, no matter during the construction schedule or commissioning schedule; in addition, because of the accumulation of each development case, inevitable regional accumulated defects appear. (2) The second category is comprised of towns with lower population density, in which the current dilemma of pollution, hillside safety, and transportation will similarly worsen due to the process of development behaviors, yet among the numerous existing environmental destruction items, land destruction, forestry variation, and dwelling place destruction, etc. are the most prominent and regretful ones. In other words, handling any new development behaviors arising from now on, the research first classifies the population density and existing hillside situation of the locality, and then the pollution and destruction items to be caused by a development behavior are divided mainly in accordance with behavioral content. With these major points provided as the operation items reference basis, an evaluation of the environmental influence of the development party is performed. Finally, for a development plan and all cases intended to be engaged in at the same period and in the same town scope, the so-called quantity control mode of thinking about traffic flow quantity influence must be applied. If accordance with the above site inspection and evaluation experience, in order to develop the development quantity control effect in the short term, we may perform a layout and arrangement concerning the restriction factor groups of development behavior and restriction priority as shown follows: () First priority: Under specification of existing legal requirements, attributed to water resource, water quality, water quantity preservation area, natural preservation area, relic protection area, hillside slope over 40%, sensitive area of soil/stone drainage and traffic jam area etc.. The party responsible for the development behavior shall first check if the development location belongs to the first category area. If so, it is recommended that the party responsible for development not make an application for an environmental impact assessment (EIA), because the chance of approval is extremely low.

10 240 The Sustainable City (2) Second priority: Connection of the development behavior locality town with its existing population/hillside ratio, and connection of the development behavior locality town with its existing pollution items. This category of restriction factor cluster attempts to inform the party responsible for the development behavior and environmental protection administrative sector where the key points of environmental impact of the related development behavior are in advance, to facilitate their conducting EIA and EIA operations. (3) Third priority: Existing situation of the peripheral traffic flow quantity, empty housing ratio, factory density, etc. of the development behavior locality; to be determined by the content of the development behavior. This category of restriction factor cluster attempts to, in accordance with the different contents of development behavior (such as a community, industrial and commercial areas, factory and refuse sites, etc.), further inform the party responsible for the development behavior and environmental protection administrative sector where the key points of environmental impact of the related development behavior are in advance, to facilitate their conducting EIA and EIA operations. 5 Conclusions The research proposes a transient-type control method for the hillside development in Taipei County. () For the time being: 9 relatively most important indicators with different weights among numerous representative items and the human factor influence items have been selected and calculated. They have pointed out guidelines of the restrictions for future hillside development in Taipei County. (2) Follow-up studies: For the construction of a long-term indicator system are yet to be promoted, so that the county government can use a more comprehensive indicator system to help protect the hillside environment. 6 References [] Robert B. Olshansky, Regulation of Hillside Development in the United State, Environmental Management Vol. 22, No. 3, pp , 998. [2] Linstone, H.A. & Turoff, M, The Delphi Method: Techniques and Applications, 975. [3] Rogers, P.P. & Murray, F.E.S., Environmental Indices as Policy Tools, Symposium on the Development of the Environmental Monitoring Program and Index System, pp (May 3-June 4, 994) Taipei, Taiwan. [4] Taipei County Government, Statistical List of Taipei County VoL46, 996. [5] Taipei County Government, Annual Statistical Guidelines, 997 [6] Department of Environmental Protection of the Taipei County Government & Department of Botany National Taiwan University, Environmental Information reports of Taipei County, 995. [7] C.T. Chen, Statistical Analysis: SPSS for Windows Introduction and Application, Zu-Lin Publisher, Taipei, 996.