A neural network for cloud masking in WorldView satellite imagery ...

• Main Authors: Rumpca, Collin, Abolt, Charles, Atchley, Adam, Harp, Dylan
• Format: Dataset
• Language: English
• Published: Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US) 2024
• Subjects: 54 ENVIRONMENTAL SCIENCES; Cloud area; EARTH SCIENCE > SPECTRAL/ENGINEERING > VISIBLE WAVELENGTHS; EARTH SCIENCE > ATMOSPHERE > CLOUDS; EARTH SCIENCE > ATMOSPHERE; EARTH SCIENCE > SPECTRAL/ENGINEERING > VISIBLE WAVELENGTHS > VISIBLE IMAGERY; Barrow; north slope; permafrost; Tundra; Alaska
• Online Access: https://dx.doi.org/10.5440/1834771; https://www.osti.gov/servlets/purl/1834771/

This repository includes the cloud detection algorithm used in the manuscript 'Topography controls variability in circumpolar permafrost thaw pond expansion' by Abolt et al. It also includes a demonstration of the algorithm's use at a survey area in northern Alaska and a demonstration of training the algorithm. This dataset includes .pt place-text, .py python, .tif image, .ipynb Jupyter notebook, and .txt text files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost ...