Maldives - Spatial Planning Strategy - 12-20-2010

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• published: 20 Dec 2010
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Maldives - Spatial Planning Strategy With over 1000 islands containing an average land area of only 0.3 km2, the Maldives is a geographic anomaly. Access to basic services is a foremost challenge for its dispersed population, particularly as climate change and increasing fuel costs will necessitate changes in transportation planning. Evolutionary Allocation - Part 1: On Demand Services (Hospitals) This study examines land use planning for a network of on-demand services, such as emergency care. Due to their unpredictability, it is assumed that on-demand services cannot rely on scheduled transportation routes and must therefore be situated to minimize the population-weighted distance to all islands in their service area. We begin with an allocation (aka voronoi, postal) map to establish the nearest service point for each inhabited island. The magenta cells indicate zones in which all inhabited islands point to a single service point, and those trajectories are indicated in dark green. We then test a random set of potential sites to see what would happen if we added service points at each location. The rearrangement of the voronoi diagram reflects the changes in service areas. Each island that finds itself in a new cell does so only because it has found a closer service point. If we multiply the reduction in travel distance by the population (assuming that more populous islands would have greater need for such services) then we can establish an index of improved accessibility for that island, as indicated by the light green trajectories. By adding the indexes for all such islands nationwide (or regionally), we can establish a nationwide (or regional) index of improved accessibility. With the appropriate usage statistics for each service, this number can be expressed either as a reduction in carbon footprint or as a cost savings. Using the accessibility index as a performance metric, we continue to test the impact of other combinations of potential sites, much as one would attempt to establish a network of cellular phone towers. Rather than test all possible combinations of N potential sites (~1000^N), we employ an evolutionary solver, which quickly establishes effective combinations of sites. Within the limited scope of this test, we have established that the islands of Biyadhoo, Ihavandhoo, Kaashidhoo, Lankanfushi, and Aluvifushi would provide excellent locations for future hospital development, insofar as each site would offer substantial improvement in accessibility for inhabitants in its service area. Naturally, this study does yet not account for other considerations, such as island area, environmental suitability, existing usage, and access to routine transportation - all features which would doubtless influence the decision to develop and which may readily be incorporated into the evolutionary solver to extend this study. Even in its initial state, however, this study already offers insight into alternative island clusters. Evolutionary Allocation - Part 2 - Routine Services (Postal) The second phase of this research examines the potential to apply graph theory based optimization techniques to study the efficiencies of transit networks as they relate to routine services. Because routine services do not require a direct connection between each populated island and a service point, they offer the potential to daisy-chain islands in a single network, much like a public transit map, and thereby make much more efficient use of shared capacities. While cyclical routing problems such as the hermitian traveling salesman problem (TSP) provide the most meaningful translation to the problem of supplying routine services to a dispersed community, the acylclic spanning problem know as the minimal spanning tree offers much less cumbersome algorithms which ensure (at the very least) an upper bound on the more relevant cyclical problem. By introducing additional service points, we can effectively negotiate the range to which each service cluster must extend in order to connect to its entire user-base. The reduction of total distance traveled on these routine routes offers analogous carbon savings to the on-demand service example. The study demonstrates that Machchafushi, Gulhi, Vihamaafushi, Kihaadhuffaru, and Kudafulhudhoo would provide excellent locations for new post offices, all else being equal. Population Potential - Part 3 Due to the wide possibilities offered by the 700+ uninhabited islands of the Maldives, it is critical to provide a graphic means of organizing the layers of information that relate to each island's suitability for future development. By graphing land area against proximity to existing services we can establish a measure of latent population potential. Other quantifiable measures, such as land-cover and ecosystem resilience may be accounted for as an additional dimension or graphic style. -Plan B

Maldives - Spatial Planning Strategy - 12-20-2010

• Report rights infringement
• published: 20 Dec 2010
• views: 819

Maldives - Spatial Planning Strategy With over 1000 islands containing an average land area of only 0.3 km2, the Maldives is a geographic anomaly. Access to basic services is a foremost challenge for its dispersed population, particularly as climate change and increasing fuel costs will necessitate changes in transportation planning. Evolutionary Allocation - Part 1: On Demand Services (Hospitals) This study examines land use planning for a network of on-demand services, such as emergency care. Due to their unpredictability, it is assumed that on-demand services cannot rely on scheduled transportation routes and must therefore be situated to minimize the population-weighted distance to all islands in their service area. We begin with an allocation (aka voronoi, postal) map to establish the nearest service point for each inhabited island. The magenta cells indicate zones in which all inhabited islands point to a single service point, and those trajectories are indicated in dark green. We then test a random set of potential sites to see what would happen if we added service points at each location. The rearrangement of the voronoi diagram reflects the changes in service areas. Each island that finds itself in a new cell does so only because it has found a closer service point. If we multiply the reduction in travel distance by the population (assuming that more populous islands would have greater need for such services) then we can establish an index of improved accessibility for that island, as indicated by the light green trajectories. By adding the indexes for all such islands nationwide (or regionally), we can establish a nationwide (or regional) index of improved accessibility. With the appropriate usage statistics for each service, this number can be expressed either as a reduction in carbon footprint or as a cost savings. Using the accessibility index as a performance metric, we continue to test the impact of other combinations of potential sites, much as one would attempt to establish a network of cellular phone towers. Rather than test all possible combinations of N potential sites (~1000^N), we employ an evolutionary solver, which quickly establishes effective combinations of sites. Within the limited scope of this test, we have established that the islands of Biyadhoo, Ihavandhoo, Kaashidhoo, Lankanfushi, and Aluvifushi would provide excellent locations for future hospital development, insofar as each site would offer substantial improvement in accessibility for inhabitants in its service area. Naturally, this study does yet not account for other considerations, such as island area, environmental suitability, existing usage, and access to routine transportation - all features which would doubtless influence the decision to develop and which may readily be incorporated into the evolutionary solver to extend this study. Even in its initial state, however, this study already offers insight into alternative island clusters. Evolutionary Allocation - Part 2 - Routine Services (Postal) The second phase of this research examines the potential to apply graph theory based optimization techniques to study the efficiencies of transit networks as they relate to routine services. Because routine services do not require a direct connection between each populated island and a service point, they offer the potential to daisy-chain islands in a single network, much like a public transit map, and thereby make much more efficient use of shared capacities. While cyclical routing problems such as the hermitian traveling salesman problem (TSP) provide the most meaningful translation to the problem of supplying routine services to a dispersed community, the acylclic spanning problem know as the minimal spanning tree offers much less cumbersome algorithms which ensure (at the very least) an upper bound on the more relevant cyclical problem. By introducing additional service points, we can effectively negotiate the range to which each service cluster must extend in order to connect to its entire user-base. The reduction of total distance traveled on these routine routes offers analogous carbon savings to the on-demand service example. The study demonstrates that Machchafushi, Gulhi, Vihamaafushi, Kihaadhuffaru, and Kudafulhudhoo would provide excellent locations for new post offices, all else being equal. Population Potential - Part 3 Due to the wide possibilities offered by the 700+ uninhabited islands of the Maldives, it is critical to provide a graphic means of organizing the layers of information that relate to each island's suitability for future development. By graphing land area against proximity to existing services we can establish a measure of latent population potential. Other quantifiable measures, such as land-cover and ecosystem resilience may be accounted for as an additional dimension or graphic style. -Plan B