The objective of this Topic Area was to demonstrate and validate advanced and emerging monitoring methods and remote sensing technologies on DoD lands to improve the efficiency, scale, and accuracy of: population and habitat assessments for threatened, endangered and at-risk species; ecosystem health; resilience and trends monitoring; assessing fire risk and documenting fire effects; watershed health assessments; invasive species detection; species migrations; and carbon sequestration estimates.
Proposals focused on:
Advanced remote sensing technologies that have shown the ability to identify and evaluate habitat, ecosystems, native plant communities, diversity indicators, and their change over time with increased spatial scale or sampling efficiency over current methods;
New or emerging machine learning or advanced algorithms for detecting or mapping natural resources from lidar (light detection and ranging), satellite imagery, or other remote sensing sources;
Automated data processing or analysis to decrease the time between data acquisition and analysis to address management needs of DoD natural resource managers;
The application of emerging technology or novel instrumentation on unmanned aerial systems (UAS) to increase the efficiency of traditional survey techniques to identify and/or evaluate the changing quality of threatened or endangered species habitat, spread of invasive species, carbon accounting, wildland fire activities, vegetative species composition and changes, or watershed assessments;
Improved analysis of acoustic, telemetry, or camera data via artificial intelligence and machine learning;
Advances in the application of virtual reality or augmented reality for monitoring application and decision support systems;
Implementation of new and emerging sampling designs or procedures to more effectively adapt ecosystem monitoring programs to mitigate the effects of climate change.
Proposals considered tools or technology that addresses natural resources management needs relevant to DoD installations.
The proposed research work will benefit the DoD’s natural resources management by providing improved tools and procedures for monitoring trends, assessing biodiversity and ecosystem health, evaluating ecosystem change, and improving resilience of natural resources in support of mission activities. The tools and technology demonstrated will ultimately be used for the development of improved and more cost-effective ecological monitoring of status and trends, more efficient analysis, or more timely notifications to managers of key system changes. The Department’s natural resources are part of the nations’ assets, and the Department holds these resources in trust for future generations. Properly managed, natural resources are mission-enhancing assets that sustain test and training through ecosystem services, recovery from disturbances, and resilience to climate change and extreme events. These projects should provide installation leaders with the ability to make informed decisions about natural resources to best fulfill installation needs.
Monitoring the status and trends of species habitat, vegetation communities, watersheds, and invasive species is a critical component of natural resource compliance requirements, ecosystem management principles, Integrated Natural Resource Management Plans, Wildland Fire Management Plans, carbon accounting and climate resilience strategies on DoD lands and waters. Despite its critical importance, ecological monitoring programs are often challenged by lack of funding, inconsistent data acquisition over time, the complexity of data analysis, and the requirement for specialized skills.
Recent advances of remote sensing technology and analytical algorithms have revolutionized the ability to identify and map natural resources at landscape scales. Machine learning and artificial intelligence are a key part of scaling observations from lidar, commercial satellites, and sensors affixed to UAS. Increasing the pace and efficacy of natural resource surveys and site mapping is a priority for DoD natural resource managers and installation environmental staff.