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metadata
task_categories:
  - zero-shot-classification
language:
  - en

Dataset Card for Dataset Name

We downloaded satellite images from Major-TOM, filtered for Germany, and processed them into vector embeddings.

Datasource Details

Value
Datasource Major-TOM/Core-S2L2A
Region box(5.98865807458, 47.3024876979, 15.0169958839, 54.983104153) (Covers whole of Germany)
Date Range ('2020-01-01', '2025-01-01')
Cloud Cover (0, 10)
No Data (0.0, 0.0)

Metadata.paraquet File

This dataset shows the relationship between our embeddings/vectors and Major TOM images for fast linking to other Major TOM datasets.

Embedding.dat

This dataset has the vector embeddings calculated by us.

What we did was:

a) to vectorise the entire Major-TOM image data for Germany;

b) used the OPENCLIP_SIGCLIP_400M on the Quasara Platform for embedding generation

c) no pre-training, no labelling happened in the preparation of this dataset

Uses

MajorTOM-DE Dataset

The MajorTOM-DE dataset provides embeddings derived from high-resolution satellite images of the Germany region, generated using the OpenCLIP SigLIP model. These embeddings, extracted from images covering a range of geographic coordinates across Germany, provide a powerful tool for various applications.

Dataset Information

  • Coordinates Info: The embeddings cover a range of geographic coordinates across the Germany region.
  • Related Dataset: The MajorTOM-DE dataset is closely related to the original S2L2A dataset.

Features

The MajorTOM-DE dataset leverages CLIP's ability to relate textual descriptions to visual data, enabling more intuitive searches and analysis. This allows users to search among images using text-based queries effectively.

Applications

The MajorTOM-DE dataset can be utilized for various applications, including:

  • Monitoring Changes in Land Use and Land Cover:

    • Track deforestation
    • Observe urban expansion
    • Monitor water body dynamics
  • Precision Agriculture:

    • Analyze crop health
    • Predict yields
    • Plan harvests
  • Climate Research:

    • Study climate patterns
    • Monitor changes and impacts on regional and local levels

Dataset Structure

Metadata.paraquet

Column Explanation
grid_cell Coordinates in the Major TOM grid, enabling fast linking to other Major TOM datasets.
grid_row_u Row identifier in the Major TOM grid for linking purposes.
grid_row_r Another row identifier in the Major TOM grid for linking purposes.
centre_lat Latitude of the center of the image portion for which embedding has been computed.
centre_lon Longitude of the center of the image portion for which embedding has been computed.
timestamp Date and time of the original product in the %Y%m%dT%H%M%S format.
dat_row Row number in the .dat file associated with the data entry.
unique_id Unique identifier combining grid_cell, timestamp, and possibly other parameters (e.g., parquet).

Embedding.dat

Column Explanation
ID ID of the image/image part for which the embedding was calculated.
dat_row Row in the .dat file that can be used to match the embeddings to the MajorTOM datasets via metadata.paraquet dataset.
image_type Each image is split into 70 segments and vectorized.
coordinates Coordinates in the image that define the segment that was vectorized. Full images have no coordinates.
split_configs Quasara auto split configuration
embeddings Vectors calculated from the image/image segment.