NASA
Datasets
All datasets matching “NASA”WxC-Bench
Dataset Card for WxC-Bench
WxC-Bench primary goal is to provide a standardized benchmark for evaluating the performance of AI models in Atmospheric and Earth Sciences across various tasks.
Dataset Details
WxC-Bench contains datasets for six key tasks:
Nonlocal Parameterization of Gravity Wave Momentum Flux
Prediction of Aviation Turbulence
Identifying Weather Analogs
Generation of Natural Language Weather Forecasts
Long-Term Precipitation Forecasting
Hurricane Track and… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/WxC-Bench.legacy-satvision-sr-pretrain-small
Satvision Pretraining Dataset - Small
Developed by: NASA GSFC CISTO Data Science Group
Model type: Pre-trained visual transformer model
License: Apache license 2.0
This dataset repository houses the pretraining data for the Satvision pretrained transformers.
This dataset was constructed using webdatasets to
limit the number of inodes used in HPC systems with limited shared storage. Each file has 100000
tiles, with pairs of image input and annotation. The data has been further… See the full description on the dataset page: https://huggingface.co/datasets/nasa-cisto-data-science-group/legacy-satvision-sr-pretrain-small.Landslide4sense
Landslide4Sense
Dataset Description
This dataset is originally introduced in GitHub repo Landslide4Sense-2022.
The Landslide4Sense dataset has three splits, training/validation/test, consisting of 3799, 245, and 800 image patches, respectively. Each image patch is a composite of 14 bands that include:
Multispectral data from Sentinel-2: B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12.
Slope data from ALOS PALSAR: B13.
Digital elevation model (DEM) from ALOS… See the full description on the dataset page: https://huggingface.co/datasets/ibm-nasa-geospatial/Landslide4sense.hls_burn_scarsThis dataset contains Harmonized Landsat and Sentinel-2 imagery of burn scars and the associated masks for the years 2018-2021 over the contiguous United States. There are 804 512x512 scenes. Its primary purpose is for training geospatial machine learning models.NASA-Power-Daily-Weather
NASA Power Weather Data over North, Central, and South America from 1984 to 2022
This dataset contains daily solar and meteorological data downloaded from the NASA Power API
Overview
The dataset includes solar and meteorological variables collected from January 1st, 1984, to December 31st, 2022.
We downloaded 28 variables directly and estimated an additional 3 from the collected data. The data spans a 5 x 8 grid covering
the United States, Central America, and South… See the full description on the dataset page: https://huggingface.co/datasets/notadib/NASA-Power-Daily-Weather.core-sdo
ML-Ready Multi-Modal Image Dataset from SDO
Overview
This dataset provides machine learning (ML)-ready solar data curated from NASA’s Solar Dynamics Observatory (SDO), covering observations from May 13, 2010, to Dec 31, 2024. It includes Level-1.5 processed data from: Atmospheric Imaging Assembly (AIA)
and Helioseismic and Magnetic Imager (HMI).
The dataset is designed to facilitate large-scale learning applications in heliophysics, such as space weather forecasting… See the full description on the dataset page: https://huggingface.co/datasets/nasa-ibm-ai4science/core-sdo.