Validating the use of object-based image analysis to map commonly recognized landform features in the United States

ABSTRACT

The U.S. Geological Survey (USGS) National Geospatial Program (NGP) seeks to i) create semantically accessible terrain features from the pixel-based 3D Elevation Program (3DEP) data, and ii) enhance the usability of the USGS Geographic Names Information System (GNIS) by associating boundaries with GNIS features whose spatial representation is currently limited to 2D point locations. Geographic object-based image analysis (GEOBIA) was determined to be a promising method to approach both goals. An existing GEOBIA workflow was modified and the resulting segmented objects and terrain categories tested for a strategically chosen physiographic province in the mid-western US, the Ozark Plateaus. The chi-squared test of independence confirmed that there is significant overall spatial association between terrain categories of the GEOBIA and GNIS feature classes. Contingency table analysis also suggests strong category-specific associations between select GNIS and GEOBIA classes. However, 3D visual analysis revealed that GEOBIA objects resembled segmented regions more than they did individual landform objects, with their boundaries often failing to correspond to match what people would likely perceive as landforms. Still, objects derived through GEOBIA can provide initial baseline landscape divisions that can improve the efficiency of more specialized feature extraction methods.     

Gathering Places for America's Dead: How Many,Where, and Why?

Recent availability of a place-specific roster of 99,625 named cemeteries appearing on USGS quadrangles renders possible for the first time the study of such places at more than the state or localized scale. County-level plotting of named sites for the eastern United States yields two unexpected results: a band of exceptionally high densities of named cemeteries traversing much of the Upper South and a parallel tract of low densities dominating the South Atlantic States. Region-specific cultural processes could apply since population density, physical geography, longevity of settlement, social diversity, and land costs, factors operating moderately well elsewhere, work poorly here to explain the pattern, as does diffusion.     

Establishing Classification and Hierarchy in Populated Place Labeling for Multiscale Mapping for The National Map

Current standards for federal mapping call for use of the Geographic Names Information System (GNIS) point layer for placement of United States populated place labels. However, this point layer contains limited classification information and hierarchy information, resulting in problems of map quality for database-driven, multi-scale, reference mapping, such as maps served by The National Map Viewer from USGS. Database-driven mapping often relies simply on what labels fit best in the map frame. Our research investigates alternative sources for labeling populated places, including polygons defined by the U.S. Census Bureau, such as incorporated place, census designated place (CDP), and economic place. Within each of these polygon layers we investigate relevant attributes from the decennial and economic censuses, such as population for incorporated places and CDPs, and the number of employees for economic places. The data selected are available for the entire country to serve national mapping requirements. This combination of data allows a more refined classification of populated places on maps that better represents relative importance. Visual importance on maps through scale should derive from more than simply residential population, but also economic importance, though comparison is made to this simpler case. We differentiate a fourth category of GNIS populated place points, essentially “neighborhoods” and related features—which are not incorporated places, CDPs, nor economic places. Populated places in this fourth class do not have federally defined boundaries, necessitating an alternative method for determining hierarchy in label presentation through scale.