Publications
Filter Total Items: 103
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 map-type cla
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
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 hydrologic modeli
Authors
Ethan J. Shavers, Larry V. Stanislawski
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. Geographic obj
Authors
Samantha Arundel, Gaurav Sinha
Automated road breaching to enhance extraction of natural drainage networks from elevation models through deep learning
High-resolution (HR) digital elevation models (DEMs), such as those at resolutions of 1 and 3 meters, have increasingly become more widely available, along with lidar point cloud data. In a natural environment, a detailed surface water drainage network can be extracted from a HR DEM using flow-direction and flow-accumulation modeling. However, elevation details captured in HR DEMs, such as roads a
Authors
Larry Stanislawski, Tyler Brockmeyer, Ethan J. Shavers
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 distinctio
Authors
Barry J. Kronenfeld, Larry V. Stanislawski, Tyler Brockmeyer, Barbara P. Buttenfield
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 need updates
Authors
Larry V. Stanislawski, Jeffrey Wendel, Ethan J. Shavers, Ting Li
Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks
Automated generalization software must accommodate multi-scale representations of hydrographic networks across a variety of geographic landscapes, because scale-related hydrography differences are known to vary in different physical conditions. While generalization algorithms have been tailored to specific regions and landscape conditions by several researchers in recent years, the selection and c
Authors
Larry V. Stanislawski, Michael P. Finn, Barbara P. Buttenfield
Generalizing linear stream features to preserve sinuosity for analysis and display: A pilot study in multi-scale data science
Cartographic generalization can impact geometric properties of geospatial data and subsequent analyses. This study evaluates simplification methods with the goal of preserving geometric details, such as sinuosity. We evaluate two recently developed line simplification algorithms that introduce Steiner points: Raposo’s Spatial Means, and Kronenfeld’s new area-preserving segment collapse algorithm,
Authors
Larry V. Stanislawski, Barry J. Kronenfeld, Barbara P. Buttenfield, Tyler (Contractor) Brockmeyer
Modeling and simulation of emergent behavior in transportation infrastructure restoration
The objective of this chapter is to create a methodology to model the emergent behavior during a disruption in the transportation system and that calculates economic losses due to such a disruption, and to understand how an extreme event affects the road transportation network. The chapter discusses a system dynamics approach which is used to model the transportation road infrastructure system to
Authors
Akhilesh Ojha, Steven Corns, Thomas G. Shoberg, Ruwen Qin, Suzanna K. Long
An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions
This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell
Authors
Larry V. Stanislawski, Kornelijus Survila, Jeffrey Wendel, Yan Liu, Barbara P. Buttenfield
A linked GeoData map for enabling information access
OverviewThe Geospatial Semantic Web (GSW) is an emerging technology that uses the Internet for more effective knowledge engineering and information extraction. Among the aims of the GSW are to structure the semantic specifications of data to reduce ambiguity and to link those data more efficiently. The data are stored as triples, the basic data unit in graph databases, which are similar to the vec
Authors
Logan J. Powell, Dalia E. Varanka
Mapping interactive geospatial linked data
No abstract available.
Authors
William (Contractor) Baumer, Logan J. Powell, Dalia E. Varanka