EventsInternational Conference on Advanced Remote Sensing (ICARS 2025)
Published
This submission belongs to the session S1. Hyperspectral Remote Sensing and Imaging Spectroscopy of the event International Conference on Advanced Remote Sensing (ICARS 2025)
Published date
25 Mar, 2025
Academic Editor
author-avatarFabio Tosti
Citation
Megan Seeley, From Spectra to Solutions: Leveraging Imaging Spectroscopy for Forest Conservation in Hawaiʻi, in Proceedings of International Conference on Advanced Remote Sensing (ICARS 2025), Barcelona, 26 March–28 March 2025, MDPI: Basel, Switzerland
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From Spectra to Solutions: Leveraging Imaging Spectroscopy for Forest Conservation in Hawaiʻi

image
1. Arizona State University, USA
Abstract

Remote sensing has been instrumental in advancing forest conservation and guiding efforts to sustain ecosystem services. Imaging spectroscopy—with its ability to capture canopy traits, accurately classify vegetation species, and estimate biodiversity—has enhanced these efforts by providing detailed insights into forest composition and health. This study presents a case study of imaging spectroscopy applications in native forest conservation.

Hawaiʻi has long served as a model system for ecological studies and a testing ground for advanced remote sensing technologies. With the emergence of Rapid ʻŌhiʻa Death (ROD), a novel disease complex first observed around 2010, Hawaiʻi offers a crucial opportunity to integrate remote sensing into the management of native forest ecosystems. ROD has caused millions of ʻōhiʻa lehua (Metrosideros polymorpha) mortalities across Hawaiʻi Island and Kauaʻi. Accounting for approximately 80% of native Hawaiian forests, ʻōhiʻa forests are the ecological foundation for diverse endemic avifauna and understory communities, and provide critical ecosystem services such as watershed protection.

We used Global Airborne Observatory airborne imaging spectroscopy and coaligned LiDAR data to classify ʻōhiʻa in 28,000 km2 of area at a 2m x 2m spatial resolution. The ability to map species distributions has far-reaching conservation implications, yet few studies have used imaging spectroscopy, which yields higher classification accuracies than multispectral datasets, to classify tree species across ecosystems. As ʻōhiʻa is characterized by a high degree of intraspecific variation, we explored how its spectral variation challenged species classifications, especially across biomes, and whether this species follows the leaf economic spectrum.

Building on these results, we are collaborating with local management agencies to integrate this dataset into ROD and native forest management strategies. These data will inform efforts to control non-native biological agents spreading ROD and support scalable conservation solutions to safeguard Hawaiʻi’s forests and their vital ecosystem services.

Keywords
forest
conservation
Hawaiʻi
imaging spectroscopy
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