Urban Vulnerabilities in the Kathmandu Valley, Nepal: Visualizations of Human/hazard Interactions

Bhattarai, Keshav, Conway, Dennis, Journal of Geographic Information System

1. Introduction

Urban vulnerability analysis using spatio-temporal information is increasingly used by urban planners and policy makers to anticipate and prevent catastrophic human disasters. Throughout the world, urban centers are becoming environmentally complex; home to over half of the world's population, these centers provide employment and commerce opportunities as well as administrative services to residents. Even in smaller urban centers many complex infrastructures have been developed to provide essential amenities to their overcrowded urban populations. At the same time, organic (haphazard/unplanned) developments often lead to increased vulnerability, and in many cases a variety of urban vulnerabilities, that taken together, make public solutions difficult if not impossible to anticipate, ameliorate or address adequately. The identification of such "mixes of vulnerabilities" requires sophisticated spatial analysis to understand the interactions among biophysical and economic factors that bring about such heightened vulnerabilities.

Over the past two and half decades, the integrated use of geographic information systems (GIS), global positioning systems (GPS), and remote sensing has become instrumental in addressing urban vulnerabilities at the local, national, and international levels [1-4]. Using these tools to analyze the landscape, researchers have identified numerous urban vulnerabilities resulting from a lack of emergency vehicular accesses and open spaces, uncontrolled solid waste management, and related unhygienic conditions, to name a few. To date, methodological approaches to identify and monitor urban vulnerabilities are limited and inconsistent due to an absence of uniform concepts, rules, and principles among academics and practitioners. To help remedy this situation, this paper analyzes spatial arrangements and housing types, population densities, road networks, vehicular densities, garbage problems, available open spaces and possible seismic vulnerabilities using 3D visualization techniques for the Kathmandu Valley of Nepal. One goal is to identify gaps within the extant of urban literature. A secondary goal is to explain how urban density-intensification not only results in declining rates of economic returns per land area unit [3,5], but also how such density-intensification hinders accessibility in cases of natural disasters such as Haiti's 2010 earthquakes, negatively impacts hygienic conditions, and threatens the public's health.

Urban vulnerabilities are the result of the complex interaction of biophysical and economic factors. The identification of such intertwined complex interactions requires three-dimensional (3D) x, y, and z information, due to the fact that two-dimensional (2D), x and y, information produces incomplete and therefore, inadequate scenarios for analyzing future urban landscape trajectories. We take a 3D visualization approach and use combinations of different datasets, such as GIS layers of multi-layer building morphologies, satellite images, and high resolution digital elevation data models (DEM) to assess vulnerabilities. More specifically, these visualizations evaluate: a) man-made hazards in congested urban areas; b) access to roads and bridges by emergency vehicles; and c) highlight the importance of such infrastructure patterns in politics, culture, economy and finance. Similar purposeful, three-dimensional visualizations will make it easier to implement settlement planning in locations such as the Kathmandu Valley, considering the challenges routinely faced by national and regional planners in Third World urban centers. In addition to regularly addressing the problems of slums, squatters, inadequate low-income housing and overburdened infrastructure systems, urban planners of the Third World may also have to work within a corrupt political system and with an equally inefficient governmental bureaucracy [5]. Planners and policy makers should find 3D data valuable not only to present long-term urban trajectories, but also to overcome undue pressures from politicians who routinely get their votes from the slums and squatter dwellers and who generally look for immediate problem-solving approaches in an organic fashion [5]. Instead, 3D presentations can illuminate planned outlays to promote sustainable solutions based on scientific, methodological analysis.

Using spatial information within an urban theoretical framework, we analyze urban vulnerabilities of the Kathmandu Valley (Figure 1). To address urban vulnerability issues, this paper is structured as follows: 1) research questions; 2) literature review; 3) brief description of the study area; 4) data and methodology; 5) causes of urban vulnerabilities; 6) remediation procedures to alleviate congestion problems, and 7) conclusion.

2. Research Questions

1) What determines urban vulnerabilities, and what factors make some urban areas more vulnerable than others?

2) Is it possible to identify repeated patterns of urban vulnerabilities and if so, how might such vulnerabilities be ameliorated?

3. Review of Literature

Research has identified a mix of urban vulnerabilities [6-9]. As a spatial science, geography concerns itself with the behavior and distribution of: 1) urban objects, such as residential and commercial buildings, pedestrians, and vehicles; 2) urban features, such as land parcels, shops, roads, sidewalks; and 3) natural features, such as green/ open spaces, rivers, and the seismic vulnerability of places. Spatial science considers these dynamic factors as "urban ensembles," which vary at different locations and scales [10]. Some researchers have used simulation methods to view the roles of these ensembles in urban amenities Torrens [11] while Blaikie et al. [12] have taken a theoretical approach and defined vulnerability as being prone to, or susceptible to, damage or injury due to biophysical factors. Rasheed and Week [13] relate urban vulnerabilities to natural hazards such as earthquakes, and to human behavioral adaptations; and argue that urban vulnerabilities become intertwined with socioeconomic systems. The World Vulnerability Report (2003) presented 50 different indicators of urban vulnerabilities by analyzing "urban ensembles" at various scales.

Urban ensembles such as buildings, streets, bridges, public and industrial areas, roofs, facades, open and green spaces, are obviously highly interrelated, but they can be visualized using design plans, drawings, and video data records [14]. Various layers such as houses, critical facilities, industrial sectors, and others can be overlaid together for visualization and subsequent spatial analysis. Researchers often apply spatial, multi-criteria approaches using spatial objects to examine the quality of life, urban conditions and aesthetic structures, because these "urban ensembles" represent dynamic phenomena involving people not only as users but also as victims, contributors, and modifiers [15-21]. Remote sensing and GIS technologies have proved to be especially-helpful tools to identify vulnerable and/or non-vulnerable ensembles across urban landscapes.

Alexander [6] used GIS to locate areas within seismic zones and analyzed the degrees of urban vulnerability they posed. Webster [22] used GIS at three levels of analysis: describing, predicting, and prescribing the growth and associated problems within an urban area. Cutter [23] used GIS to develop weighted social and biophysical indicators associated with urban vulnerability. Wu and Webster [3] hypothesized an artificial city and created a multi-dimensional matrix model as P grids each consisting of n x n cells to demonstrate the power of GIS as an integrative exploratory tool within the geographical, complex systems and economic theories. They argued that a city constantly shifts spatially achieving fraction of the cells, starting with pre-existing residential and industrial uses, initializing the majority of cells as vacant and then presented several possible scenarios of urban morphologies. Further, they analyzed the agglomeration effect in a city through a moving kernel, which returns a parameter that is a function of the number of built-up activities in the immediate neighborhood. They argue households in a community are assumed to place a measurable value on such development, which may add to both urban amenities and vulnerabilities due to their causal linkages. Madhavan et al. [24] used remote sensing to explain how land use and land cover changes are associated with urban vulnerabilities in the Metropolitan area of Bangkok, Thailand. Rashed and Weeks [2] explained how a society might be subjected to various hazards because of its own actions, such as construction of unaesthetic and congested structures such as substandard buildings and narrow roads.

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Bhaskaran et al. [25] analyzed vulnerability due to hail damage in urban areas of Sydney, Australia, using remote sensing techniques. They determined the need for a higher concentration of post-disaster emergency operations in areas with less resistant roofing materials. Bottari et al. [26] identified seismic urban vulnerabilities citing examples from Sicily using GIS techniques. Li et al. (2006) used quantitative models using GIS and remote sensing and analyzed urban vulnerabilities associated with environment conditions in the upper reaches of the Minjiang River, China. Zamoranoa et al. [27] used GIS techniques to develop indices to determine appropriate locations for waste disposal. Kamozawa et al. [28] studied vulner abilities associated with bed rock movements during earthquakes using 3D features.

Researchers have found the 3D visualization technique useful in examining the effects of adjacency (what is next to what), containment (what is enclosed by what), proximity (how close one geographic object is to another), accessibility (how an object can be reached from a certain road), and visibility (how far certain objects are visible from certain locations) [29]. However, as in simple two-dimensional features, it is essential in 3D features to either associate the distance and direction with the object as an attribute to the housing unit, or to compute the distance and direction between the roads and houses along with the height or depth of individual objects. This requires the storage of extra attribute information, i.e. latitude, longitude, height or depth, (and/or time). In earlier times, 3D visualizations were possible only in computer-aided design (CAD) [30,31] and cadastral mapping [32]. Today, ArcGIS 9.4 beta version incorporates 3D functions in its Network Analyst [33], making it accessible and functionally more useful to planners and researchers alike in the accessibility analyses [34].

Urban vulnerability analysts have found 3D models very efficient for correlating societal and biophysical factors while working in unfamiliar locations [2,35]. Others have used 3D visualization to display remotely sensed images and to analyze ozone and nitrous oxide concentration and dispersal patterns [36]. The use of 3D is also increasing in transportation planning with the use of a lane-oriented, 3D road-network model [37], though very little research has been done in this area to date. Since 2D road network data does not have sufficient accuracy for lane-oriented micro-scale, the recent development of sensor technology has been recommended for the development of road layers with higher positional accuracy that use differential GPS, often termed as DGPS receivers. Moreover, the rapid …

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Publication information: Article title: Urban Vulnerabilities in the Kathmandu Valley, Nepal: Visualizations of Human/hazard Interactions. Contributors: Bhattarai, Keshav - Author, Conway, Dennis - Author. Journal title: Journal of Geographic Information System. Volume: 2. Issue: 2 Publication date: April 2010. Page number: 63+. © 2010 Scientific Research Publishing, Inc. COPYRIGHT 2010 Gale Group.

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