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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Modern Pyromes: Biogeographical Patterns Of Fire Characteristics Across The Contiguous United States, Megan E. Cattau, Adam Mahood, Jennifer K. Balch, Carol Wessman
Modern Pyromes: Biogeographical Patterns Of Fire Characteristics Across The Contiguous United States, Megan E. Cattau, Adam Mahood, Jennifer K. Balch, Carol Wessman
Human-Environment Systems Research Center Faculty Publications and Presentations
In recent decades, wildfires in many areas of the United States (U.S.) have become larger and more frequent with increasing anthropogenic pressure, including interactions between climate, land-use change, and human ignitions. We aimed to characterize the spatiotemporal patterns of contemporary fire characteristics across the contiguous United States (CONUS). We derived fire variables based on frequency, fire radiative power (FRP), event size, burned area, and season length from satellite-derived fire products and a government records database on a 50 km grid (1984–2020). We used k-means clustering to create a hierarchical classification scheme of areas with relatively homogeneous fire characteristics, or modern …
Integrating National Ecological Observatory Network (Neon) Airborne Remote Sensing And In-Situ Data For Optimal Tree Species Classification, Victoria M. Scholl, Megan E. Cattau, Maxwell B. Joseph, Jennifer K. Balch
Integrating National Ecological Observatory Network (Neon) Airborne Remote Sensing And In-Situ Data For Optimal Tree Species Classification, Victoria M. Scholl, Megan E. Cattau, Maxwell B. Joseph, Jennifer K. Balch
Human-Environment Systems Research Center Faculty Publications and Presentations
Accurately mapping tree species composition and diversity is a critical step towards spatially explicit and species-specific ecological understanding. The National Ecological Observatory Network (NEON) is a valuable source of open ecological data across the United States. Freely available NEON data include in-situ measurements of individual trees, including stem locations, species, and crown diameter, along with the NEON Airborne Observation Platform (AOP) airborne remote sensing imagery, including hyperspectral, multispectral, and light detection and ranging (LiDAR) data products. An important aspect of predicting species using remote sensing data is creating high-quality training sets for optimal classification purposes. Ultimately, manually creating training data …