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Date: April 30, 2024 Tue
Time: 12:55 am
Time: 12:55 am
Results for residential neighborhoods
2 results foundAuthor: Smith, Laura Michelle Title: Incorporating Spatial Information into Density Estimates and Street Gang Models Summary: The spatial features within a region influence many processes in human activity. Mountains, lakes, oceans, rivers, freeways, population densities, housing densities, and road networks are examples of geographical factors that impact spatial behaviors. Separated into two parts, the work presented here incorporates this information into both density estimation methods and models of street gang rivalries and territories. Part I discusses methods for producing a probability density estimate given a set of discrete event data. Common methods of density estimation, such as Kernel Density Estimation, do not incorporate geographical information. Using these methods could result in non-negligible portions of the support of the density in unrealistic geographic locations. For example, crime density estimation models that do not take geographic information into account may predict events in unlikely places such as oceans, mountains, etc. To obtain more geographically accurate density estimates, a set of Maximum Penalized Likelihood Estimation methods based on Total Variation norm and H1 Sobolev semi-norm regularizers in conjunction with a priori high resolution spatial data is proposed. These methods are applied to a residential burglary data set of the San Fernando Valley using geographic features obtained from satellite images of the region and housing density information. Part II addresses the behaviors and rivalries of street gangs and how the spatial characteristics of the region affect the dynamics of the system. Gangs typically claim a specific territory as their own, and they tend to have a set space, a location they use as a center for their activities within the territory. The spatial distribution of gangs influences the rivalries that develop within the area. One stochastic model and one deterministic model are proposed, providing different types of outputs. Both models incorporate important geographical features from the region that would inhibit movement, such as rivers and large highways. In the stochastic method, an agent-based model simulates the creation of street gang rivalries. The movement dynamics of agents are coupled to an evolving network of gang rivalries, which is determined by previous interactions among agents in the system. Basic gang data, geographic information, and behavioral dynamics suggested by the criminology literature are integrated into the model. The deterministic method, derived from a stochastic approach, modifies a system of partial differential equations from a model for coyotes. Territorial animals and street gangs often exhibit similar behavioral characteristics. Both groups have a home base and mark their territories to distinguish claimed regions. To analyze the two methods, the Hollenbeck policing division of the Los Angeles Police Department is used as a case study. Details: Los Angeles, CA: University of Californa, Los Angeles, 2012. 144p. Source: Internet Resource: Dissertation: Accessed April 2, 2013 at: http://escholarship.org/uc/item/0z69s4gh Year: 2012 Country: United States URL: http://escholarship.org/uc/item/0z69s4gh Shelf Number: 128185 Keywords: Gangs (California)Geographic StudiesResidential NeighborhoodsSpatial Analysis |
Author: Brooks, Taggert J. Title: Strip Clubs, 'Secondary Effects', and Residential Property Prices Summary: The 'secondary effects' legal doctrine allows municipalities to zone, or otherwise regulate, sexually oriented businesses. Negative 'secondary effects' (economic externalities) justify limiting First Amendment protection of speech conducted inside strip clubs. One example of a secondary effect, cited in no fewer than four United States Supreme Court rulings, is the negative effect of strip clubs on the quality of the surrounding neighborhood. Little empirical evidence that strip clubs do, in fact, have a negative effect on the surrounding neighborhood exists. To the extent that changes in neighborhood quality are reflected by changes in property prices, property prices should decrease when a strip club opens up nearby. We estimate an augmented repeat sales regression model of housing prices to estimate the effect of strip clubs on nearby residential property prices. Using real estate transactions from King County, Washington, we test the hypothesis that strip clubs have a negative effect on surrounding residential property prices. We exploit the unique and unexpected termination of a 17 year moratorium on new strip club openings in order to generate exogenous variation in the operation of strip clubs. We find no statistical evidence that strip clubs have 'secondary effects' on nearby residential property prices. Details: Unpublished paper, 2016. 32p. Source: Internet Resource: Accessed September 19, 2017 at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2809807 Year: 2016 Country: United States URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2809807 Shelf Number: 147403 Keywords: Property Values Residential NeighborhoodsSexually Oriented Business Strip Clubs |