A new algorithm based on Region Partitioning for Filtering candidate viewpoints of a multiple viewshed

Selecting the set of candidate viewpoints (CVs) is one of the most important procedures in multiple viewshed analysis. However, the quantity of CVs remains excessive even when only terrain feature points are selected. Here we propose the Region Partitioning for Filtering (RPF) algorithm, which uses a region partitioning method to filter CVs of a multiple viewshed. The region partitioning method is used to decompose an entire area into several regions. The quality of CVs can be evaluated by summarizing the viewshed area of each CV in each region. First, the RPF algorithm apportions each CV to a region wherein the CV has a larger viewshed than that in other regions. Then, CVs with relatively small viewshed areas are removed from their original regions or reassigned to another region in each iterative step. In this way, a set of high-quality CVs can be preserved, and the size of the preserved CVs can be controlled by the RPF algorithm. To evaluate the computational efficiency of the RPF algorithm, its performance was compared with simple random (SR), simulated annealing (SA), and ant colony optimization (ACO) algorithms. Experimental results indicate that the RPF algorithm provides more than a 20% improvement over the SR algorithm, and that, on average, the computation time of the RPF algorithm is 63% that of the ACO algorithm.     

An IO-efficient parallel implementation of an R2 viewshed algorithm for large terrain maps on a CUDA GPU

A rapid and flexible parallel approach for viewshed computation on large digital elevation models is presented. Our work is focused on the implementation of a derivate of the R2 viewshed algorithm. Emphasis has been placed on input/output (IO) efficiency that can be achieved by memory segmentation and coalesced memory access. An implementation of the parallel viewshed algorithm on the Compute Unified Device Architecture (CUDA), which exploits the high parallelism of the graphics processing unit, is presented. This version is referred to as r.cuda.visibility. The accuracy of our algorithm is compared to the r.los R3 algorithm (integrated into the open-source Geographic Resources Analysis Support System geographic information system environment) and other IO-efficient algorithms. Our results demonstrate that the proposed implementation of the R2 algorithm is faster and more IO efficient than previously presented IO-efficient algorithms, and that it achieves moderate calculation precision compared to the R3 algorithm. Thus, to the best of our knowledge, the algorithm presented here is the most efficient viewshed approach, in terms of computational speed, for large data sets.     

Appreciating migration flows for health/social services planning: A case study of older adults leaving from New York to Florida

This paper utilizes the 2009/2010/2011 American Community Survey to examine spatial patterns of later-life relocation from the state of New York into Florida. Given that the first-wave of the Baby Boom generation reached the retirement age of 65 years in January 2011 and many more will continue to do so, examining the mobility/subsequent residential choices of this group is a worthwhile undertaking. This research paper is also a noteworthy contribution because it offers an interdisciplinary study of spatial statistics and population geography. Exploratory spatial analysis and multinomial regressions suggest older adults from New York leave select origins, such as Capital District, Mid-Hudson, and Lower Hudson. In addition, these older adults select preferred destinations in Florida, such as Fort Myers, Fort Pierce–Stuart, and West Palm Beach. This finding can inform planners, policy analysts, and social workers about how to best address issues related to health and community services since not all older adult migrants seeking coastal and recreational areas in Florida maintain greater wealth and better health.