2026-10-08T05:26:55Z https://api.figshare.com/v2/oai

oai:figshare.com:article/32040951 2026-09-23T05:22:49Z category_26899 category_26872 category_25765 category_25942 item_type_3 month_year_09_2026

Fusing spectral and structural imagery detects escalating canopy dieback in a vulnerable eucalyptus population Donna Fitzgerald (19228720) Landscape ecology Ecological impacts of climate change and ecological adaptation Climate change science not elsewhere classified Other earth sciences not elsewhere classified Fusion hyperspectral LiDAR dieback eucalyptus <p dir="ltr">Climate‑driven forest dieback is emerging as a major threat to biodiversity, yet early detection of canopy decline remains challenging with single‑sensor remote‑sensing approaches. We present a canopy-focused data fusion method that combines high-resolution aerial hyperspectral imagery with LiDAR-derived structural data to detect subtle changes in canopy condition class that neither dataset can capture independently. We integrated hyperspectral and LiDAR variables into a single raster stack, including a 3 m LiDAR-derived canopy mask that removed understorey vegetation and improved classification accuracy compared with hyperspectral-only approaches. We applied this framework to a vulnerable <i>Eucalyptus macrorhyncha</i> population in South Australia, using two aerial surveys from 2022 and 2025 that span a shift from post-drought recovery to renewed severe drought stress. Pixel‑based classification of canopy condition into healthy, moderately stressed, and stressed categories achieved high accuracy (Kappa = 0.81) across both surveys. Results showed a decline of over 50% in the healthy canopy class. Overall, 25.95% of the canopy displayed a positive change and 17.71% a negative change between the two surveys. Structural and spectral indicators indicated different patterns. Normalised LiDAR return density increased, while NDVI decreased in previously healthy sites and increased in unhealthy sites. This pattern likely reflects resprouting of drought-stressed trees and proliferation of understorey vegetation during wetter years, while NDVI decreases in previously healthy sites likely reflect canopy browning under drought, suggesting growing vulnerability for the study population under a warming, drying climate. More broadly, our study highlights the value of integrating spectral and structural data to detect, monitor, and understand the intricacies of changes in canopy health. Hence, integrated spectral and structural data may allow determination of vegetation change and landscape vulnerability under climate change at large scales. Identifying these changes and vulnerabilities is increasingly important, as the speed and extent of climate change impacts make field-based detection increasingly challenging.</p> 2026-04-22T05:25:45Z Dataset Dataset 10.6084/m9.figshare.32040951.v2 https://figshare.com/articles/dataset/Fusing_spectral_and_structural_airborne_imagery_data_to_detect_escalating_canopy_dieback_in_a_vulnerable_eucalyptus_population/32040951 CC BY 4.0