NASA_NEO_Dataset
Collection
This collection has the following maps from the NASA NEO dataset: MODAL2_D_CLD_WP,MOD_LSTD_D/E/M
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4 items
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Updated
Datasets:
Tasks:
Image-to-Image
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
Tags:
climate
License:
image
imagewidth (px) 3.6k
3.6k
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Space Climate Dataset
Overview
The Space Climate Dataset provides a collection of satellite-generated images displaying surface temperature and climate patterns across different regions of Earth. These visualizations, such as the one included in the dataset, represent variations in land surface temperature (LST) and other atmospheric conditions captured via satellite. The dataset primarily serves researchers, data scientists, and climate analysts aiming to study Earth’s climate patterns, surface temperatures, and environmental changes over time.
Dataset Structure
- Images: Each image in the dataset represents Earth’s climate state on specific dates. The imagery focuses on parameters such as land surface temperature (LST), which is represented by a color scale from cooler (blue) to hotter (red/orange).
- Image Format: All images are in .png format.
Data Source
The dataset is derived from Earth-observing satellite missions, specifically those under NASA's MODIS (Moderate Resolution Imaging Spectroradiometer) program, which captures climate data from space at multiple intervals. The satellite data is processed and visualized to highlight global land surface temperatures, atmospheric conditions, and changes over time.
Key Features of the Dataset
Satellite imagery of Earth’s climate conditions. Color-coded data visualization: Blue to cyan shades represent cooler temperatures, while orange to red indicates higher temperatures. Time-series data: The dataset allows users to analyze and track changes in temperature patterns over specific time periods.
Applications
This dataset can be used for various purposes, including but not limited to:
- Climate change research: Study global warming and temperature variation patterns.
- Environmental analysis: Assess regional and seasonal changes in land surface temperatures.
- Machine Learning Models: Train machine learning models on spatial climate data for predictive analysis.
- Education: Use the images for educational purposes, particularly in Earth sciences and remote sensing.
File Naming Convention
- MOD_LSTD: Stands for MODIS Land Surface Temperature Data.
- D: Indicates that the image represents global Earth data daily.
- YYYY-MM-DD: The date when the satellite image was captured.
Example: MOD_LSTD_D_YYYY-MM-DD.png
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