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Research Scientist

Employer
ASRC Federal Holding Company
Location
Sioux Falls, South Dakota, US
Salary
Competitive
Closing date
May 30, 2022

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Sector
Academic / Research
Field
Informatics / GIS
Discipline
Land Management
Salary Type
Salary
Employment Type
Full time
ASRC Federal Data Solutions (AFDS), LLC invites applications for a Research Scientist position for fire science. The successful candidate will work among hundreds of scientists and engineers at the USGS Earth Resources Observation and Science (EROS) Center ( in Sioux Falls, South Dakota participating on teams conducting various projects and studies addressing land resources management challenges. EROS is a national center of earth science research for developing land use and land cover change products, operating the Landsat satellite program with NASA, and maintaining the largest civilian collection of aerial and satellite images of the Earth's land surface. Scientists working at EROS collaborate and coordinate with multiple Federal and International agencies on a broad scope of global, national, and regional earth science projects. Will provide support to the EROS in the areas of fire science research and related change detection activities. LANDFIRE is a shared program between the wildland fire management programs of the U.S. Department of Agriculture (USDA) Forest Service and the U.S. Department of the Interior. Through LANDFIRE project, the USGS EROS provides nationally consistent collection of geospatial layers such as vegetation, fuel, disturbance, etc. These information help land management agencies in land monitoring and stewardship decisions, especially for wildland fire management. As a participant in an AFDS and USGS interdisciplinary team of scientists, the Research Scientist will: Advance the understanding and the applications of remote sensing capabilities for characterizing the ecological impacts of fire on various landscapes Develop LANDFIRE remote sensing capabilities to ingest data from Sentinel Red edge bands, ECOSTRESS, and lidar sensors to further enhance disturbance mapping efforts Explore seasonal and red edge spectral signatures to further enhance vegetation lifeform and species detection Develop Landsat/Sentinel image segmentation techniques to improve vegetation and disturbance modeling and subsequent mapping Apply more advanced AI methods like CNN or DNN to LANDFIRE research and development support integration of generic remote sensing-based disturbance assimilation and error reduction methodologies into LANDFIRE's disturbance mapping production system Explore ways to incorporate the best aspects of Continuous Change Detection and Classification (CCDC) algorithms into LANDFIRE to enhance its mapping capabilities Write research proposal for funding opportunities related to fire science research Contribute to development of new fire science research ideas Participate in change detection activities to develop a change detection algorithm that leverages a multi-sensor, multi-tiered approach to expedite vegetation change detection in an operational setting Prepare periodic progress reports, publish peer-review journal articles, and provide oral presentations to internal and external researchers Requirements: Experience with geospatial dataset generation and modeling using programming languages/software Demonstrated experience with applications of optical remotely sensed imagery from Landsat, MODIS, VIIRS, Sentinel etc. Familiarity with wildland fire, shrubland, and forest ecosystems Knowledge of data analysis and statistical analysis methods Experience with common commercial and/or open source image processing and GIS software packages Strong background in characterizing vegetation, surface, and/or canopy fuels at regional scales Experience with advanced computing and automation processes using AI/ML Proficiency in writing scripts in Python, IDL, R or other language appropriate for processing and analyzing raster and other types of geospatial data Excellent written English and oral communication skills Self-motivated and able to work collaboratively and independently Education: Masters or PhD in geography, natural sciences, Engineering or a closely related discipline with experience in research and application of remote sensing methods for assessment of fire effects, landscape characterization, and change detection/characterization.
Associated topics: earthquake, environmental, geodynamic, geology, geophysics, geoscience, hydrologist, oil, petroleum, petrophysicist

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