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Landslides, resulting from disturbances in slope equilibrium, pose a significant threat to landscapes, infrastructure, and human life. Triggered by factors such as intense precipitation, seismic activities, or volcanic eruptions, these events can cause extensive damage and endanger nearby communities. A comprehensive understanding of landslide characteristics, including spatio-temporal patterns, dimensions, and morphology, is vital for effective landslide disaster management. Existing remote sensing approaches mostly use either optical or synthetic aperture radar sensors. Integrating information from both these types of sensors promises greater accuracy for identifying and locating landslides. This study proposes a novel approach, the ML-LaDeCORsat (Machine Learning-based coseismic Landslide Detection using Combined Optical and Radar Satellite Imagery), that integrates freely available Sentinel-1, Palsar-2, and Sentinel-2 imagery data in Google Earth Engine (GEE). The approach also integrates relevant spectral indices and suitable bands used in a machine learning-based classification of coseismic landslides. The approach includes a robust and reproducible training and validation strategy and allows one to choose between five classifiers (CART, Random Forest, GTB, SVM, and Naive Bayes). Using landslides from four different earthquake case studies, we demonstrate the superiority of our approach over existing solutions in coseismic landslide identification and localization, providing a GTB-based detection accuracy of 87–92%. ML-LaDeCORsat can be adapted to other landslide events (GEE script is provided). Transfer learning experiments proved that our model can be applied to other coseismic landslide events without the need for additional training data. Our novel approach therefore facilitates quick and reliable identification of coseismic landslides, highlighting its potential to contribute towards more effective disaster management. [ABSTRACT FROM AUTHOR]

A disjunct population of red stringybark (Eucalyptus macrorhyncha) trees in South Australia is experiencing increasing amounts of dieback. Because the population is considered vulnerable to extinction, we investigated spatiotemporal vegetation changes, quantified the extent of dieback, and determined how topography influences dieback using aerial and satellite imagery. Classification of vegetation health status using hyperspectral aerial imagery indicated that 37% (accuracy = 0.87 Kappa) of the population was unhealthy and potentially experiencing dieback. When correlating this classification with a digital terrain model (DTM), the aspect and amount of solar radiation had the strongest relationship with the presence of unhealthy vegetation. PlanetScope satellite-derived, and spectral index-based analysis indicated that 7% of the red stringybark population experienced negative vegetation health changes during a five-year period (2017–2022), with positive vegetation health changes (9.5%) noted on pole-facing slopes. Therefore, our integrated remote sensing approach documented the extent and spatiotemporal dynamics of dieback, suggesting it could be applied in other studies. Topographical aspects exposed to high-solar radiation were particularly vulnerable to dieback, and pole-facing aspects demonstrated some recovery between droughts. The influence of topography and maps of vegetation health can be used to guide future management and restoration of the population. [ABSTRACT FROM AUTHOR]

Charles Darwin proposed his 'principle of divergence' to account for changes in traits that could promote speciation and coexistence of diverse forms through occupation of different niches to reduce interspecific competition. We explore interspecific foraging behaviour overlap in Fiji's forest birds, and address two main questions: (1) Is there vertical stratification of foraging behavior? and (2) Is there evidence of interspecific competition driving the differences in foraging behaviour? We explore these questions across three foraging guilds, nectarivores (three species), insectivores (two species), and omnivores (two species), and find vertical portioning of foraging in each group. To investigate the effect of interspecific competition, we compared foraging heights of the Orange-breasted Myzomela (Myzomela jugularis) honeyeater on Viti Levu Island (where it coexists with two other honeyeater species) and Leleuvia Island (no other honeyeater species). On the main island Viti Levu, we found evidence for vertical niche partitioning within each foraging guild. On Leleuvia, with the 'one-species only foraging guild', Orange-breasted Myzomela occupied broader vertical foraging niche than on Viti Levu with two other competitor honeyeater species. This result supports the idea that vertical foraging height can be shaped by interspecific competition. The findings of this study support Darwin's principle of divergence in Fiji's forest birds for every foraging guild measured and adds to our understanding of the significance of interspecific competition and niche divergence for patterns of ecological speciation on islands. [ABSTRACT FROM AUTHOR]