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The paper presents results and analysis of a methodology for automatic building extraction that integrates remote sensing sources and readily available geographic information system data (tax assessor parcel data). The methodology consists of a series of image processing and spatial analysis techniques and incorporates an initial simplification, parcel-based image partitioning procedure. The results showed great promise for such image partitioning in reducing the complexity of the building extraction procedure by localizing its search while maintaining the integrity of the structures (85 percent of buildings reside completely within parcels and the majority of the rest consists of very small portions outside the parcel boundaries). Herein, we discuss the results as they apply to three distinct building types (commercial, residential, and high-rise). The paper presents successful building extraction scenarios as well as challenges, difficulties and drawbacks of the process and identifies the underlying factors that impact the success of footprint extraction for each type of building. The results show that 83 percent of commercial buildings are successfully extracted with average footprint area discrepancy less than 10 percent, while challenges in high-rise and residential scenes are examined and further investigated. [ABSTRACT FROM AUTHOR]

Background: Although colorectal cancer death rates in the United States have declined by half since 1970, large geographic disparities persist. Spatial identification of high-risk areas can facilitate targeted screening interventions to close this gap. Methods: We used the Getis-Ord Gi* statistic within ArcGIS to identify contemporary colorectal cancer "hotspots" (spatial clusters of counties with high rates) based on county-level mortality data from the national vital statistics system. Hotspots were compared with the remaining aggregated counties (non-hotspot United States) by plotting trends from 1970 to 2011 and calculating rate ratios (RR). Trends were quantified using joinpoint regression. Results: Spatial mapping identified three distinct hotspots in the contemporary United States where colorectal cancer death rates were elevated. The highest rates were in the largest hotspot, which encompassed 94 counties in the Lower Mississippi Delta [Arkansas (17), Illinois (16), Kentucky (3), Louisiana (6), Mississippi (27), Missouri (15), and Tennessee (10)]. During 2009 to 2011, rates here were 40% higher than the non-hotspot United States [RR, 1.40; 95% confidence interval (CI), 1.34-1.46], despite being 18% lower during 1970 to 1972 (RR, 0.82; 95% CI, 0.78-0.86). The elevated risk was similar in blacks and whites. Notably, rates among black men in the Delta increased steadily by 3.5% per year from 1970 to 1990, and have since remained unchanged. Rates in hotspots in west central Appalachia and eastern Virginia/North Carolina were 18% and 9% higher, respectively, than the non-hotspot United States during 2009 to 2011. Conclusions: Advanced spatial analysis revealed large pockets of the United States with excessive colorectal cancer death rates. Impact: These well-defined areas warrant prioritized screening intervention. [ABSTRACT FROM AUTHOR]

One of the most challenging problems in digital photogrammetry todayis automatic extraction of cartographic features from large-scale aerial images. Automatic detection of such features in general, and buildings in particular, will significantly improve the map compilation process as well as other tasks, such as DEM and orthophoto generation. This paper presents a semiautomatic approach for the extraction of buildings from large-scale images. The main goal is to recover three-dimensional (3D) outlines of buildings. The extraction should be sufficiently accurate, reliable, and efficient in order to comply with the high standards set by the photogrammetric community. In order to obtain a 3D description, the approach comprises stereo analysis for extracting building heights, along with a general knowledge of building geometry and shadow information. The paper explains the approach, presents experiments, and discusses the results. [ABSTRACT FROM AUTHOR]