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Filter Total Items: 116
A spatio-contextual probabilistic model for extracting linear features in hilly terrain from high-resolution DEM data A spatio-contextual probabilistic model for extracting linear features in hilly terrain from high-resolution DEM data
This paper introduces our research in developing a probabilistic model to extract linear terrain features from high resolution DEM (Digital Elevation Model) data. The proposed model takes full advantage of spatio-contextual information to characterize terrain changes. It first derives a quantifiable measure of spatio-contextual patterns of linear terrain feature, such as ridgelines...
Authors
Xiran Zhou, Wenwen Li, Samantha Arundel
The effect of resolution on terrain feature extraction The effect of resolution on terrain feature extraction
Recent increase in the production of high-resolution digital elevation models (DEMs) from lidar data has led to interest in their use for terrain mapping. Although the impact of different resolutions has been studied relative to terrain characteristics like roughness, slope and curvature, its relationship to the extraction of terrain features remains unclear. To address this question...
Authors
Samantha Arundel, Wenwen Li, Xiran Zhou
Analysis for agreement of the Northern Gulf of Mexico topobathymetric digital elevation model with 3-Dimensional Elevation Program 1/3 arc-second digital elevation models Analysis for agreement of the Northern Gulf of Mexico topobathymetric digital elevation model with 3-Dimensional Elevation Program 1/3 arc-second digital elevation models
Topographical differencing and edge-matching analyses were used to evaluate agreement of the Coastal National Elevation Database Applications Project’s Northern Gulf of Mexico topobathymetric digital elevation model (TBDEM) with The National Map 3-Dimensional Elevation Program (3DEP) 1/3 arc-second digital elevation models (DEMs). In addition to topographic map products provided through...
Authors
Cynthia Miller-Corbett
Topographic mapping evolution: From field and photogrammetric data collection to GIS production and Linked Open Data Topographic mapping evolution: From field and photogrammetric data collection to GIS production and Linked Open Data
Whither the topographic map? Topographic mapping historically has been approached as a map factory operation through the period 1879-1990. During this time, data were field and photogrammetrically collected; cartographically verified and annotated creating a compilation manuscript; further edited, generalized, symbolized, and produced as a graphic output product using lithography, or...
Authors
E. Lynn Usery, Dalia Varanka, Larry Davis
US Topo Product Standard US Topo Product Standard
This document defines a U.S. Geological Survey (USGS) digital topographic map. This map product series, named “US Topo,” is modeled on the now historical USGS 7.5-minute (1:24,000 scale) topographic map series produced and printed by the USGS from 1947 to 2006. US Topo maps have the same extent, scale, and general layout as the historical topographic maps. US Topo maps incorporate an
Authors
Larry Davis, Kristin Fishburn, Helmut Lestinsky, Laurence Moore, Jennifer Walter
Generalization in practice within national mapping agencies Generalization in practice within national mapping agencies
National Mapping Agencies (NMAs) are still among the main end users of research into automated generalisation, which is transferred into their produc- tion lines via various means. This chapter includes contributions from seven NMAs, illustrating how automated generalisation is used in practice within their partly or fully automated databases and maps production lines, what results are...
Authors
Cecile Duchene, Blanca Baella, Cynthia Brewer, Dirk Burghardt, Barbara P. Buttenfield, Julien Gaffuri, Dominik Kauferle, Francois Lecordix, Emmanuel Maugeais, Ron Nijhuis, Maria Pla, Marc Post, Nicolas Regnauld, Larry Stanislawski, Jantien Stoter, Katalin Toth, Sabine Urbanke, Vincent van Altena, Antje Wiedemann
Deep convolutional neural networks for map-type classification Deep convolutional neural networks for map-type classification
Maps are an important medium that enable people to comprehensively understand the configuration of cultural activities and natural elements over different times and places. Although a massive number of maps are available in the digital era, how to effectively and accurately locate and access the desired map on the Internet remains a challenge today. Previous works partially related to...
Authors
Xiran Zhou, Wenwen Li, Samantha Arundel, Jun Liu
Streams do work: Measuring the work of low-order streams on the landscape using point clouds Streams do work: Measuring the work of low-order streams on the landscape using point clouds
The mutable nature of low-order streams makes regular updating of surface water maps necessary for accurate representation. Low-order streams make up roughly half the streams in the conterminous United States by length, and small inaccuracies in stream head location can result in significant error in stream reach, order, and density. Reliable maps of stream features are vital for...
Authors
Ethan Shavers, Larry Stanislawski
Validating the use of object-based image analysis to map commonly-recognized landform features in the United States Validating the use of object-based image analysis to map commonly-recognized landform features in the United States
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...
Authors
Samantha Arundel, Gaurav Sinha
Area-preserving simplification of polygon features Area-preserving simplification of polygon features
Developing simplified representations of a two-dimensional polyline is an important problem in cartographic data analytics where datasets must be integrated across spatial resolutions. This problem is generally referred to as line simplification, and is increasingly driven by preservation of specific analytic properties such as positional accuracy and high-frequency detail. However, the
Authors
Barry Kronenfeld, Larry Stanislawski, Tyler Brockmeyer, Barbara Buttenfield
Similarity assessment of linear hydrographic features using high performance computing Similarity assessment of linear hydrographic features using high performance computing
This work discusses a current open source implementation of a line similarity assessment workflow to compare elevation-derived drainage lines with the high-resolution National Hydrography Dataset (NHD) surface-water flow network. The process identifies matching and mismatching lines in each dataset to help focus subsequent validation procedures to areas of the NHD that more critically...
Authors
Larry Stanislawski, Jeffrey Wendel, Ethan Shavers, Ting Li
A comparison of synthetic flowpaths derived from light detection and ranging topobathymetric data and National Hydrography Dataset High Resolution Flowlines A comparison of synthetic flowpaths derived from light detection and ranging topobathymetric data and National Hydrography Dataset High Resolution Flowlines
Bathymetric and topobathymetric light detection and ranging (lidar) digital elevation models created for the Delaware River were provided to the National Geospatial Program and used to evaluate synthetic flowpath extraction from bathymetric/topobathymetric lidar survey data as a data source for improving the density, distribution, and connectivity of the National Hydrography Dataset High
Authors
Cynthia Miller-Corbett