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A framework for detecting conifer mortality across an ecoregion using high spatial resolution spaceborne imaging spectroscopy

Tane, Zachary, Roberts, Dar, Koltunov, Alexander, Sweeney, Stuart, Ramirez, Carlos
Remote sensing of environment 2018 v.209 pp. 195-210
Dendroctonus, Landsat, algorithms, bark beetles, canopy, conifers, data collection, drought, ecoregions, ecosystems, image analysis, monitoring, mortality, mountains, multispectral imagery, remote sensing, spectrometers, spectroscopy, summer, surveys, California
Between 2013 and 2015, during a time of severe drought and elevated bark beetle (Dendroctonus spp.) activity in California, the amount of conifer mortality in the Southern Sierra Nevada increased greatly. Remote sensing is a critical means of providing up-to-date information on the location, magnitude, and extent of mortality across a broad geographic area. We used eleven Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) flight lines, resampled to 30 by 30 m pixel size and acquired on six separate dates as part of the HyspIRI Preparatory Campaign to simulate spaceborne imaging spectroscopy. We also spectrally degraded the AVIRIS images to simulate Landsat-8 data. We tested the ability of single-date and multi-temporal remote sensing to identify red stage conifer mortality, healthy conifer, and non-conifer dominated pixels using a random forest algorithm. Accuracy was assessed with an independent validation dataset acquired via WorldView imagery in areas spatially separate from where training data were collected, as well as through comparison with aerial detection survey and canopy water loss data, with generally good agreement. We found that classifications based on imaging spectroscopy significantly outperformed broadband multispectral feature sets (with a highest overall accuracy of 85.1% obtained by imaging spectroscopy and 80.2% obtained by the simulated multispectral images). We also found that classifications based on multi-temporal imaging spectroscopy were more accurate than single-date imaging spectroscopy (the highest overall accuracy obtained for single-date imaging spectroscopy was 83.4%). Imaging spectroscopy that included interseasonal data from the end of the drought outperformed all other datasets, including interannual data that included only images collected in the summer. Multi-date analysis also improved accuracy using broad band systems. Although current spaceborne assets are adequate for monitoring bark beetle mortality in a heterogeneous ecosystem, a spaceborne imaging spectrometer would further improve operational accuracy.