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  6. High-Resolution Land Cover Maps of Lāna‘i, Hawai‘i, 2020 - Class Probability Stack

High-Resolution Land Cover Maps of Lāna‘i, Hawai‘i, 2020 - Class Probability Stack

Dates

Publication Date
Time Period
2022-06-10

Citation

Berio Fortini, L., 2023, High-Resolution Land Cover Maps of Lāna‘i, Hawai‘i, 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P94TS6W6.

Summary

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.

Contacts

Point of Contact :
Lucas Berio Fortini, U.S. Geological Survey
Originator :
Lucas Berio Fortini
Metadata Contact :
U.S. Geological Survey, pierc-datasteward
Distributor :
U.S. Geological Survey - ScienceBase

Attached Files

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Extension: lanai_class_probability_stack_v1.zip
lanai_class_probability_stack_v1.tif 436.55 MB
lanai_class_probability_stack_v1.tif-ColorRamp.SLD 2.07 KB
lanai_class_probability_stack_v1.tif.xml
Original FGDC Metadata
View 		27.69 KB

Purpose

This land cover dataset enables highly detailed vegetation mapping to track the spread of invasive species, guide conservation actions, assess ungulate damage, and monitor ecosystem changes over time on Lāna‘i. The fine-scale maps can also inform erosion control, carbon inventory, and climate change planning. Their accuracy and resolution surpass existing products to aid research and management across taxa in this topographically complex island ecosystem.

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Communities

  • Pacific Island Ecosystems Research Center

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Additional Information

Raster Extension

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