2020 - (Vol. 07, Issue 01)http://dl.lib.uom.lk/handle/123/186772024-03-29T08:04:23Z2024-03-29T08:04:23ZFinding The Logic Of Location: An Analysis Of The Distribution Pattern Of Urban Activities In The City Of Colombo With Space SyntaxMunaisnghe, JNBandara, Ahttp://dl.lib.uom.lk/handle/123/189362022-10-12T03:30:24Z2020-11-01T00:00:00ZFinding The Logic Of Location: An Analysis Of The Distribution Pattern Of Urban Activities In The City Of Colombo With Space Syntax
Munaisnghe, JN; Bandara, A
The self-organized order of the types, scales, and locations of different activities in urban areas has throughout been a matter of concern for planning. In order to regulate ‘unplanned’ distribution of activities in urban areas, planning authorities used different tools, of which zoning is still the most popular. However, except under heavily regimented conditions, zoning has continuously failed to withstand the forces that empowered urban activities to find their preferred locations in an urban area. Hence, planners need more strategic approaches than conventional methods in order to deal with the location dynamics of urban activities. In this regard, a comprehensive understanding on space appropriation by urban activities and the methods in which such understanding can be effectively integrated into planning strategies, are essential in planners. In a context where the available theories were limited in serving for this purpose, the Space Syntax method provides planners with a more convincing method to analyze and simulate spatial dynamics of urban areas, relating to ‘spatial integration’, which is an attribute that emerges from the overall configuration of the physical environment. Using this method, this study explored the potential relationship between the location choices of different urban activity types, and the level of spatial integration of their current locations within the core area of the city of Colombo.
2020-11-01T00:00:00ZA Machine Learning Approach Towards Determining The Openness Of Urban PlazaAlam, MDSImam, CAhttp://dl.lib.uom.lk/handle/123/189312022-10-12T03:30:26Z2020-11-01T00:00:00ZA Machine Learning Approach Towards Determining The Openness Of Urban Plaza
Alam, MDS; Imam, CA
The design of urban plaza is guided by the principle of D/H ratio where D denotes distance and H denotes building façade height which provides a quantitative measure of the enclosure. Plaza has been considered as an outdoor room and the buildings are the walls. But these urban walls are not continuous. Connecting roads, voids between buildings, the variation of building heights, and the omission of building on any side of the plaza affect openness. So, maintaining the same D/H ratio the sense of enclosure can be varied. This paper aims at determining the inter-relation of openness with distance and height for better understanding the idea of enclosure of urban plaza using machine learning algorithms. Machine learning can be used to determine the non-linear relationship between multiple variables. The variables D and H are set by the author where the perforation of the surrounding elevation varied, then respondents were asked to rate the degree of openness of the plazas based on their virtual journey using a head-mounted Virtual Reality (VR) display. Utilizing their responses an inter-relation among the parameters is determined by training up an artificial Neural Network (ANN) to predict the openness of any plaza. This can be used as a process of analyzing user experience of urban plazas.
2020-11-01T00:00:00ZA Gis-Based Simulation Application To Model Surface Runoff Level In Urban Blocks.Wijayawardana, PNPAbenayake, CCayasinghe, ABKalpana, LDCHNDias, NAmaratunga, DHaigh, Rhttp://dl.lib.uom.lk/handle/123/189252022-10-12T03:30:30Z2020-11-01T00:00:00ZA Gis-Based Simulation Application To Model Surface Runoff Level In Urban Blocks.
Wijayawardana, PNP; Abenayake, CC; ayasinghe, AB; Kalpana, LDCHN; Dias, N; Amaratunga, D; Haigh, R
Simulation of flood inundation in urban areas longer important, given the magnitude of potential loss and disruption associated with non-river based, urban flooding. The complexity of the urban environment and lack of high-resolution topographic and hydrologic data compromise the development and implementation of models. Low impact development (LID) is technical know-how on a collection of sustainable practices that mimic natural hydrological functions including infiltration, evapotranspiration or use of surface runoff. Several studies have been carried out to discuss the impact of urbanization scenarios in reducing the urban flood risk in watershed scale in Sri Lanka. Yet, there is a gap remains in simulating the effectiveness of LID-based planning practices to reduce flood risk with the complex built form scenarios. In such a situation, this study attempts to make a significant contribution to simulate the variations of flood regulation functions under different high-intensive urban development scenarios, particularly focusing on the urban metropolitan regions. The analyses were carried out utilizing SWMM (Storm Water Management Model) which is open-source flood inundation simulation approach with the help of GIS in a more qualitative manner. The simulation results indicate that expanding built form scenarios increase the flood venerability for city functions, increasing inundation duration and LID scenarios able to reduce the surface runoff to reduce flood vulnerability at a significant level. The simulation results had been verified with the real ground situation (mean percentage change < 15.5%) which able to capture the thresholds of built form variation, as well as dynamic land uses and infrastructure supply which can be used as a tool for future planning practices and decision-making.
2020-11-01T00:00:00ZAn Alternative Approach to Assess The Residential Population Resilience to Urban FloodingKalpana, LDCHNJayasinghe, ABAbenayake, CCWijayawardana, PNPhttp://dl.lib.uom.lk/handle/123/189222022-10-12T03:30:36Z2020-11-01T00:00:00ZAn Alternative Approach to Assess The Residential Population Resilience to Urban Flooding
Kalpana, LDCHN; Jayasinghe, AB; Abenayake, CC; Wijayawardana, PNP
Community resilience assessments and minimizing the anticipated disruptions to vulnerable communities, is a broad topic in disaster studies. In common practice, most of the indicator-based resilience assessment studies rely on statistical aggregation methods of tabular data collected for macro administrative units, as it is readily available in most of the countries. However, this method confronts severe drawbacks in converting such data into micro-scale geospatial units. To address those issues, this study proposes to utilize the Dasymetric Mapping Technique in the geospatial population resilience assessments, as it is capable of identifying the micro level impact to the population distribution as a pixel representation. In order to geospatially demonstrate the population exposure, the study has selected three major flooding events occurred in Colombo, Sri Lanka. The results revealed a great applicability of the proposed method as a statistical approach which estimates the exposed population by over 90% accuracy. Therefore, the proposed method is recommended to be utilized as an efficient tool of community resilience assessment as it is highly accurate in downscaling the spatial distribution of population data.
2020-11-01T00:00:00Z