Environmental Science Division (EVS)a Division of Argonne National Laboratory

Providing Monitoring Support through Remote Sensing and Use of Small Unmanned Aircraft Systems

Argonne is an FAA-approved center for use of small unmanned aircraft systems (sUASs), allowing EVS remote sensing staff to support sUAS data collection design and analysis work.

EVS is responsible for supporting integrated assessment, environmental management, natural and cultural resource analyses, and basic science programs. The division has in-depth disciplinary strength in ecology, geology, hydrology, atmospheric science, spatial analysis, computer science, geography, social and cultural sciences, environmental engineering, and ecological and human health risk assessment. EVS staff have conducted remote sensing work using very high-resolution images to support long-term monitoring of the Riverside East solar energy zone in California, a priority area for utility scale solar energy development identified by the Bureau of Land Management in October 2012. This work has supported identification of vegetation density, desert pavement, and erosion-sensitive areas. Additionally, Argonne is an FAA-approved center for use of small unmanned aircraft systems (sUASs), allowing EVS remote sensing staff to support sUAS data collection design and analysis work.

EVS Remote Sensing and sUAS Capabilities

Land Resource Assessment and Monitoring

Collection of high-resolution images and development of algorithms for image processing and interpretation to assist natural and cultural resource monitoring and management.

  • Assess and monitor changes in individual plants and vegetation communities by customizing image processing algorithms; extract and map detailed ephemeral stream networks using image transformations; map land surface stability or the risk of erosion; monitor invasive plant species; model seasonal habitat suitability over large areas.
  • Package remote sensing methodologies for cost-effective, multi-scale ecological and environmental monitoring to make ecosystems in arid and semiarid lands more sustainable.
  • Supplement archaeological field surveys with aerial assessment and mapping of cultural features and monitoring land surface changes over time for assessing impacts on cultural sites.

Predictive Modeling

Formulation of predictive models to provide managers tools for informing field survey planning, testing scenarios, and analyzing future states.

  • Develop predictive models for plant productivity to facilitate landscape design; species occurrences; and greater sage-grouse population trend analysis using individual-based modeling and geospatial layers.

River Applications

Development of methods to obtain difficult-to-collect measurements across extensive water bodies.

  • Estimate water depth of critical backwater habitats along a turbid river by applying optical remote sensing in conjunction with advanced statistical modeling.

Vegetation Health and Carbon Cycling

Development of methods to obtain measurements that indicate the integrity or health of vegetated lands.

  • Estimate carbon exchange between the atmosphere and land surfaces using hyperspectral remote sensing, statistical modeling, and machine learning.

Data Collection with sUASs

Timely and cost-effective collection of very detailed imagery to acquire highly customized images to meet specific project needs.

  • Collect multi-temporal images with high spatial alignment to accurately detect and monitor land surface changes to assess impacts and monitor mitigation effectiveness.
  • Collect high-resolution thermal infrared imagery to examine the integrity of infrastructure.
[Source: Argonne National Laboratory]

Related Research Areas

See the Research Highlights Index for a complete list of EVS Research Areas.

photo of Yuki Hamada
Assistant Biophysical Scientist/Remote Sensing
Capabilities: Applications of optical and infrared remote sensing and geospatial modeling approaches for analyzing and monitoring terrestrial ecosystem functions and processes; application of plant spectroscopy to hyperspectral image analysis for terrestrial ecosystem research; development of novel image processing algorithms to extract and characterize land surface and aquatic features and properties; use of geospatial information technologies in development of a framework for data interpolation, extrapolation, and scaling from fine-resolution local scale to coarse-resolution regional scale.
photo of Heidi Hartmann
Program Manager, Land Resources and Energy Policy
Capabilities: Project management; environmental impact analysis, risk assessment for environmental contaminants; health and safety assessments for workers and the general public.