How Do Homeowners Associations Regulate Residential Landscapes?

Abstract

Problem, research strategy, and findings: Residential landscapes are homogenizing the ecology of cities, and decisions about yard structure and management practices are the result of a complex mix of actors and institutions operating at multiple scales. In this study we examine how one such institution, the homeowners association (HOA), homogenizes yard ecology at the neighborhood scale through formal institutional rules. We examine a random sample of publicly recorded covenants, codes, and restrictions (CCRs) documents and a nonrandom sample of private architecture and landscaping guidelines for HOAs in Maricopa County (AZ). We find landscaping rules in CCRs have increased over time but are relatively small in number and generic in content, sometimes repeated municipal rules, and increasingly outsourced rules to architectural and landscaping guidelines. Rules about yard aesthetics or maintenance were required, whereas rules relating to environmentally sensitive landscaping were encouraged. We propose HOAs facilitate ecological homogenization by aggregating heterogeneous rule types to formulate a club good.

Takeaway for practice: Our findings suggest planners can enact ordinances that influence residential landscape ecology in HOAs via statutory mandates because CCRs reinforce existing rules at the neighborhood scale. However, HOAs potentially inhibit adoption of voluntary programs directly or indirectly via approvals and restrictions. Moreover, the finding that HOAs are increasingly shifting regulations from publicly recorded CCRs to private documents reveals a challenge for planners because private contract law allows land use provisions in HOAs to remain “hidden” from the public domain.     

A filter-and-fan approach with adaptive neighborhood switching for resource-constrained project scheduling

This paper presents an effective heuristic algorithm based on the framework of the filter-and-fan (F&F) procedure for solving the resource-constrained project scheduling problem (RCPSP). The proposed solution methodology, called the filter-and-fan approach with adaptive neighborhood switching (FFANS), operates on four different neighborhood structures and incorporates improved local search, F&F search with multiple neighborhoods and an adaptive neighborhood switching procedure. The improved local search, in which a new insert-based move strategy and new time compression measurement of schedules having the same makespan are embedded, is utilized to identify a local optimum and a basic move list. The F&F search, aimed to further improve the local optimum, applies multi-neighborhood filter and fan strategies to generate compound moves and a neighborhood-switch list in a tree search fashion. When the current neighborhood cannot further improve the local optimum, the adaptive neighborhood switching procedure picks the most potential neighborhood for the next run of the local search procedure. The entire solution procedure is autonomous and adaptive due to its variable search range depending on the project sizes and characteristics. Computational results and comparisons with some state-of-the-art algorithms indicate the effectiveness and competence of the proposed FFANS.     

Root neighborhoods, generalized lemniscates, and robust stability of dynamic systems

A root neighborhood (or pseudozero set) of a degree-n polynomial p(z) is the set of all complex numbers that are the roots of polynomials whose coefficients differ from those of p(z), under a specified norm in , by no more than a fixed amount . Root neighborhoods corresponding to commonly used norms are bounded by higher-order algebraic curves called generalized lemniscates. Although it may be neither convenient nor useful to derive their implicit equations, such curves are amenable to graphical analysis by means of simple contouring algorithms. Root neighborhood methods offer advantages over alternative approaches (the Kharitonov theorems and their generalizations) for investigating the robust stability of dynamic systems with uncertain parameters, since they offer valuable insight concerning which roots of the characteristic polynomial will become unstable first, and the relative importance of parameter variations on the root locations—and hence speed and damping of the system response. We derive a generalization of root neighborhoods to the case of polynomial coefficients having an affine linear dependence on a set of complex uncertainty parameters, bounded under a general weighted norm, and we discuss their applications to robust stability problems. The methods are illustrated by several computed examples.     

Two very large-scale neighborhoods for single machine scheduling

In this paper, the problem of minimizing the total completion time on a single machine with the presence of release dates is studied. We introduce two different approaches leading to very large-scale neighborhoods in which the best improving neighbor can be determined in polynomial time. Furthermore, computational results are presented to get insight in the performance of the developed neighborhoods.     

Strength and adaptability of problem-space based neighborhoods for resource-constrained scheduling

In this paper, Resource Constrained Scheduling (RCS) consists of scheduling activities on scarce resources, each activity may require more than one resource at a time, and each resource is available in the same quantity throughout the planning period. This paper described a methodology for RCS that can be easily adapted to consider different regular measures of performance. The solution approach is local search using a recent development published in the literature; namely, problem-space based neighborhoods. Computational results are encouraging when searching these spaces using simple local search techniques. Further improvements are explored through the use of a genetic algorithm. In both cases, close-to-optimal solutions are found for standard problems from the literature. The adaptability of the methodology is demonstrated using makespan and mean tardiness as performance measures.     

Neighborhood Social Disorder as a Determinant of Drug Injection Behaviors: A Structural Equation Modeling Approach.

Neighborhood environments are increasingly recognized as a contextual determinant of health, behaviors, and disease; however, the pathways through which neighborhood characteristics impact health behaviors are poorly understood. This article examines pathways to elucidate how neighborhood social disorder may lead to HIV transmission. Data are from a baseline survey of 701 injection drug users from the Self-Help in Eliminating Lethal Diseases Study, an HIV prevention intervention in Baltimore. Structural equation modeling was used to examine the pathways among social disorder, psychological distress, and drug injection behaviors. The relationship between disorder and injection behaviors in the models tested suggests that psychological distress is higher in more socially disordered neighborhoods, that distress leads to greater injection frequency and equipment sharing, and that injection frequency predicts equipment sharing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Prejudice and discontent.

"Two groups of parents, living in adjacent neighborhoods characterized by markedly different physical features, made approximately equal mean scores on a questionnaire designed to measure prejudice toward Negroes. An analysis of these mean scores, utilizing categories related to liking or disliking the neighborhood, and, for men, liking or disliking their job, showed considerable differences among the respondents in each neighborhood and between the respondents in the two neighborhoods." (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

细胞自动机及其在模拟城市时空演化过程中的应用

对城市发展与演化过程的模拟和预测 ,需要地理信息系统 (GIS)等相关技术的支撑 .但目前的商用GIS不能完整地表达地理实体的时态信息和时空关系 ,缺乏时空分析和动态模拟的能力 .细胞自动机 (CellularAutomata ,简称CA)是一种“自下而上”的动态模拟建模框架 ,具有模拟地理复杂系统时空演化过程的能力 .文章从细胞自动机的原理和特征入手 ,介绍了CA模型的构造方法 ,对CA模型应用于城市时空演化过程的模拟及预测的可行性和可操作性进行了探讨 .     

基于8邻域编码逐像素跟踪法的指纹细节特征提取算法

研究并实现基于8邻域编码逐像素跟踪法的细节特征提取算法。该算法能有效提取细化后指纹图像中的端点和分叉点,通过回朔跟踪法,能有效去除图像中的伪特征点。实验结果表明该算法较大幅度提高了特征提取的速度,并能够较准确的滤除伪特征点,缩短了图像后处理时间,可以满足实际应用的需要。