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In this commentary we reflect on the potential and power of geographical analysis, as a set of methods, theoretical approaches, and perspectives, to increase our understanding of how space and place matter for all. We emphasize key aspects of the field, including accessibility, urban change, and spatial interaction and behavior, providing a high‐level research agenda that indicates a variety of gaps and routes for future research that will not only lead to more equitable and aware solutions to local and global challenges, but also innovative and novel research methods, concepts, and data. We close with a set of representation and inclusion challenges to our discipline, researchers, and publication outlets. [ABSTRACT FROM AUTHOR]

Distance is an important and basic concept in geography. Many theories, methods, and applications involve distance explicitly or implicitly. While measuring the distance between two locations is a straightforward task, many geographical processes involve areal units, where the distance measurement can be complicated. This research investigates distance measurement between a location (point) and an area (polygon). We find that traditional polygon‐to‐point distance measurements, which involve abstracting a polygon into a central or representative point, could be problematic and may lead to biased estimates in regression analysis. To solve this issue, we propose a new polygon‐to‐point distance metric along with two algorithms to compute the new distance metric. Simulation analysis shows the effectiveness of the new distance metric in providing unbiased estimates in linear regression. [ABSTRACT FROM AUTHOR]

The fundamental basis for territorial political representation is the presumption that people share greater common interests with others in closer geographic proximity than with people farther away. This principle is found in U.S. legal requirements that districts for the House of Representatives and state legislatures should not needlessly divide "communities of interest" and should be "reasonably compact." We propose a new objective standard to evaluate spatial fairness of redistricting plans: the extent to which a delineation minimizes total distance between all pairs of people assigned to the same district. To date, the legal standard of compactness has primarily been thought of in terms of the shapes of political districts, but boundary shape may have little correspondence with how populations are actually clustered and dispersed. Inter‐person separation, by contrast, provides a direct, intuitive metric for evaluating the congruence of districting plans with the territorial basis of political representation. To operationalize an inter‐person separation standard, we propose a model and present a heuristic method for delineating comparator districting schemes. We apply the standard to the current U.S. Congressional Districts in the states of Arizona and North Carolina to demonstrate how inter‐person separation could be used to develop and vet future redistricting plans. [ABSTRACT FROM AUTHOR]

Traffic congestion represents an ongoing serious issue in many large cities. Many public facilities, such as hospitals, tend to be centrally located to ensure they are most accessible to local residents; as a result, they may contribute significantly to a city's traffic congestion. In this study, a multi‐objective spatial optimization model was provided to help formulate hospital relocation plans, taking into account both traffic congestion and hospital accessibility. Using intra‐urban movement data, we proposed a method to estimate the area‐wide traffic congestion caused by hospital visits and to identify potential hospitals to be relocated. An NSGA‐II (Non‐dominated Sorting Genetic Algorithm II) algorithm was applied to solve the hospital relocation optimization problem; we applied our model to study optimal hospital relocation plans in Beijing. Analysis results provide a tradeoff between traffic congestion relief and hospital accessibility. We discussed plans that significantly reduce traffic congestion while maintaining a high level of hospital accessibility. Our study has significant policy implications and provides insights for future facility planning and transportation planning. [ABSTRACT FROM AUTHOR]

Abstract: The p‐median problem (PMP) is one of the most applied location problems in urban and regional planning. As an NP‐hard problem, the PMP remains challenging to solve optimally, especially for large‐sized problems. A number of heuristics have been developed to obtain PMP solutions in a fast manner. Among the heuristics, the Teitz and Bart (TB) algorithm has been found effective for finding high‐quality solutions. In this article, we present a spatial‐knowledge‐enhanced Teitz and Bart (STB) heuristic method for solving PMPs. The STB heuristic prioritizes candidate facility sites to be examined in the solution set based on the spatial distribution of demand and service provision. Tests based on a range of PMPs demonstrate the effectiveness of the STB heuristic. This new algorithm can be incorporated into current commercial GIS packages to solve a wide range of location‐allocation problems. [ABSTRACT FROM AUTHOR]

Analysis results are often found to vary with the way we abstract geographical space. When continuous geographic phenomena are abstracted, processed, and stored in a digital environment, some level of discretization is often employed. Information loss in a discretization process brings about uncertainty/error, and as a result research findings may be highly dependent on the particular discretization method used. This article examines one spatial problem concerning how to achieve the maximal regional coverage given a limited number of service facilities. Two widely used geographical space abstraction approaches are examined, the point-based representation and the area-based representation, and issues associated with each representation scheme are analyzed. To accommodate the limitations of the existing representation schemes, a mixed representation strategy is proposed along with a new maximal covering model. Experiments are conducted to site warning sirens in Dublin, Ohio. Results demonstrate the effectiveness of the mixed representation scheme in finding high-quality solutions when the regional coverage level is medium or high. [ABSTRACT FROM AUTHOR]

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This article introduces measures to quantify spatial autocorrelation for vectors. In contrast to scalar variables, spatial autocorrelation for vectors involves an assessment of both direction and magnitude in space. Extending conventional approaches, measures of global and local spatial associations for vectors are proposed, and the associated statistical properties and significance testing are discussed. The new measures are applied to study the spatial association of taxi movements in the city of Shanghai. Complications due to the edge effect are also examined. [ABSTRACT FROM AUTHOR]

The current method for delineating U. S. metropolitan and micropolitan statistical areas (collectively referred to as core-based statistical areas- CBSAs) is to cluster counties based on the strength of commuting interactions between outlying areas and urban cores. The social and economic integration of a metropolitan or a micropolitan statistical area is operationalized using what we believe is an outdated, monocentric perspective on functional spatial structure: one that fixates solely on inward and reverse commuting. We propose a new spatial optimization model for delineating CBSAs that can better account for polycentric urban structure by considering all intercounty commuting linkages. Our model seeks to find the boundaries that maximize the containment of entire webs of intra- CBSA intercounty commuting. We apply the proposed method to delineate alternative sets of metropolitan and micropolitan statistical areas for comparison with the federal government's currently defined (2010 Office of Management and Budget [ OMB] standards) official CBSAs. El método actual para delimitar áreas estadísticas micropolitanas y metropolitana en los Estados Unidos (denomidado genéricamente áreas estadísticos nucleares o core-statistical areas- CBSA) consiste en agrupar condados en base a la fuerza de las interacciones de los desplazamientos residencia-trabajo entre las zonas periféricas y los núcleos urbanos. La integración social y económica de un área estadística metro y micro politana se pone en operación usando un enfoque funcional que los autores consideran obsoleto que se basa en una estructura espacial urbana monocéntrica. Dicho enfoque se limita únicamente a los desplazamientos hacia el interior y de vuelta. Los autores proponen un nuevo modelo de optimización espacial para delinear CBSAs que respresenta mejor una estructura urbana policéntrica que considera todos los desplazamientos entre condados. El modelo busca encontrar los límites que maximizan la inclusión de redes enteras de desplazamientos intra CBSA y entre condados. El método propuesto es aplicado para delinear conjuntos alternativos de áreas estadísticas metropolitanas y micropolitanas y es comparado con los límites oficiales actuales de CBSA proporcionados por gobierno federal (de acuerdo a los lineamientos de la Oficina de Administración y Presupuesto u Office of Management Budget-OMB) en 2010). 目前用于描述美国大都市区与居住区统计区域（共同地被称为基于核心的统计区域-CBSAs）的方法，主要是基于边远地区和城市核心区间的相互作用强度对郡县进行聚类。大都市区或居住区统计区域社会与经济一体化的运作方式，采用的是一种功能空间结构上落伍的单中心视角，即仅关注内部交换或反向交换。本文提出了一种新的空间优化模型用于描述CBSAs，将所有内部通勤联系考虑在内，能更好地解释多中心城市结构。该模型力图发现能最大化包含内部CBSA通勤联系网的边界。最后，将该模型应用于大都市区和居住区的统计区域描述，并与联邦政府目前定义的官方CBSAs（管理与预算 [OMB]标准2010办公室）进行了对比研究。 [ABSTRACT FROM AUTHOR]

Achieving the greatest coverage using limited resources has long been a concern for regional planners. Since the 1970s, a variety of models have been studied and relied upon. Finding ways to best represent geographical space remains a challenge to many researchers. Solutions suggested by models vary greatly with different space representation schemes. For example, in the past, points have been widely adopted to represent spatial demand for coverage. However, this simple abstraction of geographical space could bring about inaccuracies and uncertainties, and often compromises its solution quality. Considering that demand can be area based, which is beyond points, objects of different shapes have been proposed as an alternative for representation. With advances in geographic information systems ( GISs), the new representation scheme using objects has recently received much attention. Compared with the straightforward point-based abstraction, spatial object representation poses considerable challenges to both model formulation and computation capability. This article revisits model development for the problem of regional coverage maximization and proposes a new formulation where coverage of spatial demand is implicitly modeled. Model testing is conducted through an application to warning siren siting in Dublin, Ohio, which has been studied by other researchers. Results demonstrate the effectiveness of the new model when compared with the existing models. Uno de los objetivos comunes en la planificación regional es lograr la máxima cobertura de un servicio con recursos limitados. Desde la década de los 70s se vienen utilizado una serie de modelos conocidos. Sin embargo, la representación adecuada del espacio geográfico de dichos modelos sigue siendo un problemática para muchos investigadores. Las soluciones derivadas de los modelos varían considerablemente de acuerdo a los diferentes esquemas de representación utilizados. El uso de puntos por ejemplo, ha sido ampliamente utilizado en el pasado como esquema de representación espacial de la demanda a ser cubierta por el servicio. Sin embargo, esta simple abstracción del espacio geográfico puede provocar imprecisiones e incertidumbres que a menudo afectan la calidad de la solución matemática del modelo. En contraste, si la demanda se define como un área que abarca una extensión que va más allá de los puntos es posible proponer-como lo han hecho varios recientemente- el uso de objetos espaciales (de formas variadas) como una alternativa sensata de representación. Con los avances en los sistemas de información geográfica (SIG), este nuevo esquema de representación -que usa objetos especiales- han recibido considerable atención. En contraste con esquemas sencillos como el basado en puntos, la representación de objetos espaciales presenta varios desafíos en cuanto a la formulación y computación del modelo. El presente artículo reseña el desarrollo del modelamiento del problema de máxima cobertura regional ( problem of regional coverage maximization) y propone una nueva formulación en la cual la cobertura de la demanda en el espacio es modelada de manera implícita. La evaluación del modelo se realiza a través de una aplicación que usa datos de la ubicación sirenas de alarma en Dublín, Ohio. Los resultados demuestran la eficacia del nuevo modelo en comparación con los modelos existentes. 利用有限资源实现最大覆盖一直广受区域规划者关注。自20世纪70年代以来，发展了大量针对这一问题的模型研究。寻找最佳的地理空间表达方式仍是研究者面临的一大挑战。不同模型对于不同的空间表达模式变化很大。比如过去空间覆盖需求多采用点集表达。然而，这种简单的地理空间抽象方法可能会引起不精确性和不确定性，通常也会导致解决方案质量下降。考虑到需求可能是基于区域而非基于点，不同形状的对象已经被当作空间表达可替代的方式。随着GIS技术的进步，基于对象空间表达的新方案近来备受关注。较之于直接基于点的空间抽象，空间对象表达在模型的形式化表达和计算性能上均面临相当大的挑战。本文回顾了区域最大覆盖问题模型研究的发展历程，提出了一个新的蕴含空间覆盖建模需求的模型。以曾被诸多学者研究过的俄亥俄州都柏林的报警器选址问题为例对模型进行检验，结果显示新模型较现有模型更为有效。 [ABSTRACT FROM AUTHOR]

The Prairie Pothole Region in the United States contains millions of seasonal, semi-permanent, or permanent lakes and wetlands that typically range in size from 0.1 to 10 ha. These lakes and wetlands are vulnerable to climate change, especially in our study area in South Dakota, in which a period of deluge following a sharp drought considerably expanded the areal extent of prairie pothole lakes during the last decade of the twentieth century. Preliminary estimates of lake areas, determined using LANDSAT 5 and 7 images, had appreciable errors especially for the smallest of these lakes. This article describes a new sub-pixel approach integrated with a CART (Classification and Regression Tree) model using a GIS (Geographical Information System) to quantify mixed water pixels along lake boundaries to improve area estimations for pothole lakes. Errors in estimated area were typically 10% or less for lakes greater than 1 ha in size. An analysis of lakes in our study area demonstrates how lake area changed with the transition from drought to deluge. Small lakes exhibited a distinct seasonal variation in contrast to large lakes that tended to follow precipitation trends more broadly. The total water area of lakes is consistent with broad variation in rainfall. [ABSTRACT FROM AUTHOR]

How to represent geographic space has long been an issue in location modelling. Facilities, demand and/or the region of interest are often abstracted using aggregated points. However, substantial errors can be introduced, and obtained solutions could be dependent on the degree of aggregation. To address this, geographic representation of space is undergoing renewed research interest in spatial analysis and modelling. In this article the maximal coverage problem is studied, with a particular focus on demand coverage representation. Due to the limitations of existing modelling approaches for examining the coverage of space, there exist significant discrepancies between what is modelled and actual geographic coverage. In order to accurately reflect the mechanism of maximal coverage for spatial objects (points, lines or polygons), we introduce a new model explicitly accounting for joint service provided by multiple facilities. The new model can be viewed as an extension of existing approaches, but also a generalisation. An application to warning siren siting is carried out to demonstrate the merits of this new approach. [ABSTRACT FROM AUTHOR]