S5. Terrain Feature Modeling and Extraction for Mapping and Earth Resource Applications
We seek a postdoctoral fellow to study terrain processes and geomorphic development to model terrain features in support of extraction from lidar data for representation as a part of The National Map. Throughout the United States, terrain features such as mountains, hills, and valleys are sculpted by many different agents including mass wasting, wind, water, ice, and anthropogenic sources with each resulting in various processes and forms. The modeling, identification, and extraction mechanisms for these various forms are dependent on an understanding of the creation processes (Wilson and Gallant, 2000). Lidar data are being acquired as a part of the 3D Elevation Program (3DEP) and have sufficient resolution to capture the many and varied aspects of all types of terrain features (Renslow, 2012). The ability to use these data as a source for extraction of geomorphologic features that can then be used in topographic science modeling and map generation depends on a thorough understanding of the processes which formed the features (Smith and Mark, 2003, ).
A core element of the USGS mission is to provide scientific data in the form of digital terrain and map databases that support scientific investigation and public uses. This mission element is developed and managed within the Core Science Systems Mission Area of the USGS through the National Geospatial Program. The NGP conducts long term topographic research through the Center of Excellence for Geospatial Information Science (CEGIS), which is responsible for innovating and researching new technology for mapping and geospatial data generation, management, archiving, and distribution (Usery, 2013). During the past several years, CEGIS researchers have developed ontology design patterns for specific terrain and hydrologic features (Varanka, 2011; Usery and Varanka, 2012; Sinha and others, 2014a; 2014b). The extension of this work to model terrain processes will allow effective extraction of geomorphological features from lidar terrain data.
Under this Research Opportunity, the Mendenhall Fellow is expected to investigate how knowledge of process formation can support feature extraction with lidar data. Specifically, the incumbent will be expected to model glacial features such as cirques, arêtes, eskers, drumlins, and other features and determine characteristics of these features that can be explicitly determined with lidar data (Eisank, 2013). Similarly, the incumbent will be expected to model features in other types of sculpted environments, particularly, wind-blown sediments that form distinctive features such as loess hills. Water sculpted features are probably the most numerous but result in many diverse forms and these also can be modeled. Finally, structurally controlled geomorphic patterns, such as annular and parallel drainage systems, can be modeled. The results of these models must be evidenced in the lidar data.
The incumbent will be expected to develop these models and use object oriented image analysis in conjunction with the lidar data to isolate and extract these features from lidar data (Li and others, 2012). The procedures for building specific geomorphic features from process modeling and ontology design patterns will be developed as part of the research. The work will be supported by ongoing work in the ontology of terrain features that has been a research focus for CEGIS for the past 5 years.
Eisank, C., 2013. An Object-Based Workflow for Integrating Spatial Scale and Semantics to Derive Landforms from Digital Elevation Models, Unpublished Ph.D. Dissertation, University of Salzburg. 142 p.
Li, W., R. Raskin, and M.F. Goodchild, 2012. Semantic similarity measurement based
on knowledge mining: an artificial neural net approach, International Journal Of Geographical Information Science, v. 26, n. 8, p. 1415-1435.
Renslow, Michael S., (ed.), 2012. Manual of Airborne Topographic Lidar, American Society for Photogrammetry and Remote Sensing, Bethesda, MD, 528 p.
Sinha, G., D. Kolas, D. Mark, B. Romero, E.L. Usery, G. Berg-Cross, A. Padmanabhan, 2014a. Surface networked ontology design patterns for linked topographic data, Semantic Web Journal. http://www.semantic-web-journal.net/content/surface-network-ontology-design-patterns-linked-topographic-data.
Sinha, G., D. Mark, D. Kolas, D. Varanka, B. Romero, C.C. Feng, E.L. Usery, J. Lieberman, and A, Sorokine, 2014b. An ontology design pattern for surface water features, Proceedings, GIScience 2014, Salzburg, Austria.
Smith, B. and D. Mark, 2003. Do mountains exist? Towards an ontology of landforms, Environment and Planning B; Planning and Design, v. 30, p. 4111-427.
Usery, E.L., 2013, Center of Excellence for Geospatial Information Science research plan 2013–18: U.S. Geological Survey Open-File Report 2013–1189, 50 p., http://pub.usgs.gov/of/2013/1189/.
Usery, E.L. and D. Varanka, 2012. Design and development of linked data from The National Map, Semantic Web Journal, http://www.semantic-web-journal.net/content/design-and-development-linked-data-national-map.
Varanka, D., 2011. Ontology patterns for complex topographic feature types, Cartography and Geographic Information Science, v. 38, n. 2, p. 126-136.
Wilson, J. P. and J.C. Gallant, (eds.), 2000. Terrain Analysis: Principles and Applications, John Wiley and Sons, London: 520 p.
Proposed Duty Station: Rolla, MO.
Area of Ph.D., Geography, geomorphology, geographic information science, cartography, geomatics, remote sensing, computer sciences, environmental science, geology
Qualifications: Applicants must meet one of the following qualifications – Research Geographer, Research Physical Scientist, Research Cartographer
Research Advisor: E. Lynn Usery, 573-308-3837. email@example.com.
Human Resources Office Contact: Mario Jones, (303) 236-9576, firstname.lastname@example.org.
|Summary of Opportunities|