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This raster stack contains 15 probability layers representing the pixel-level predicted probability of membership in each species-specific vegetation class from 0 to 1. These probability layers can be used to generate class membership uncertainty maps or probabilistic class cover maps from the model outputs. They provide additional information beyond the discrete categorial land cover assignments.
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This dataset comprises high-resolution geotif files representing various aspects of the ʻākohekohe (Palmeria dolei) potential habitat on the Island of Hawaiʻi. It includes a habitat suitability map showing average suitability scores, a map of homogenous forested areas (HFAs) depicting clusters with consistent suitability scores, and a map of pixel-wise standard deviation across habitat suitability models. These maps were generated through a comprehensive analysis using lidar-based metrics, offering detailed insights into the habitat preferences of ʻākohekohe.


    map background search result map search result map High-Resolution Land Cover Maps of Lāna‘i, Hawai‘i, 2020 - Class Probability Stack Island of Hawaiʻi lidar-based habitat suitability for ʻākohekohe (Palmeria dolei) conservation introductions, 2023 High-Resolution Land Cover Maps of Lāna‘i, Hawai‘i, 2020 - Class Probability Stack Island of Hawaiʻi lidar-based habitat suitability for ʻākohekohe (Palmeria dolei) conservation introductions, 2023