Enrika Hlavacek
Provides GIS support for the Geospatial Sciences & Technologies Branch, including spatial analysis of biological resources data. Manages various geospatial tasks and provides project management in support of UMESC science.
Biography
Eduation:
- B.S. Geography, GIS Concentration - Univ. of Wisconsin - La Crosse, La Crosse, WI, 2011
- M.S. Geographic Information Systems - Univ. of Redlands, Redlands, CA, 2014
Research Interests:
- GIS data visualization
- Cartographic design
- Remote sensing applications, including light detection and ranging (lidar)
- Geoprocessing desktop and online tool development utilizing Python
- Open source GIS software
Current Projects:
- Deep learning for automated detection and classification of waterfowl, seabirds, and other marine wildlife from digital aerial imagery
- Database, visualization, and decision support tool development for UMESC eDNA monitoring and Asian carp projects
- Digital conversion, orthorectification, and archiving of historial aerial imagery datasets
Science and Products
Develop Orthophotos and Mosaics from systemic color infrared aerial photography of the Upper Mississippi River System from 1975, 1989, 1994, and 2000
The U.S. Army Corps of Engineers’ Upper Mississippi River Restoration (UMRR) Program Long Term Resource Monitoring (LTRM) element is implemented by the U.S. Geological Survey, Upper Midwest Environmental Sciences Center (UMESC), in cooperation with the five Upper Mississippi River System (UMRS) states of Illinois, Iowa, Minnesota, Missouri, and Wisconsin. Color infrared aerial photography was...
Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery
In collaboration with the Bureau of Ocean Energy Management, U.S. Fish and Wildlife Service, and the Vision Group at the International Computer Science Institute at the University of California - Berkeley, the U.S. Geological Survey Upper Midwest Environmental Sciences Center is developing deep learning algorithms and tools for the automatic detection, enumeration, classification, and...
Decision Support Systems
A Decision Support System (DSS) can be defined in many ways. The working definition the Upper Midwest Environmental Sciences Center (UMESC) uses is, "A spatially based computer application or data that assists a researcher or manager in making decisions." This is quite a broad definition and it needs...
Preliminary analysis to estimate the spatial distribution of benefits of P load reduction: Identifying the spatial influence of phosphorus loading from the Maumee River (USA) in western Lake Erie
Since the early 2000s, Lake Erie has been experiencing annual cyanobacterial blooms that often cover large portions of the western basin and even reach into the central basin. These blooms have affected several ecosystem services provided by Lake Erie to surrounding communities (notably drinking water quality). Several modeling efforts have...
Larson, James H.; Hlavacek, Enrika; De Jager, Nathan R.; Evans, Mary Anne; Wynne, Timothy National Park Service Vegetation Mapping Inventory Program: Jean Lafitte National Historical Park and Preserve Vegetation Mapping Project
The National Park Service, Natural Resource Stewardship and Science office in Fort Collins, Colorado, publishes a range of reports that address natural resource topics. These reports are of interest and applicability to a broad audience in the National Park Service and others in natural resource management, including scientists, conservation and...
Hop, Kevin D.; Strassman, Andrew C.; Sattler, Stephanie; Pyne, Milo; Teague, Judy; White, Rickie; Ruhser, Janis; Hlavacek, Enrika; Dieck, Jennifer National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project
The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program classifies, describes, and maps existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural...
Hop, Kevin D.; Strassman, Andrew C.; Hall, Mark; Menard, Shannon; Largay, Ery; Sattler, Stephanie; Hoy, Erin E.; Ruhser, Janis; Hlavacek, Enrika; Dieck, Jennifer Automated lidar-derived canopy height estimates for the Upper Mississippi River System
Land cover/land use (LCU) classifications serve as important decision support products for researchers and land managers. The LCU classifications produced by the U.S. Geological Survey’s Upper Midwest Environmental Sciences Center (UMESC) include canopy height estimates that are assigned through manual aerial photography interpretation techniques...
Hlavacek, Enrika