inie2003's picture
Updated README.md with andrei fixes
31be0cd verified
|
raw
history blame
4.99 kB
---
task_categories:
- zero-shot-classification
language:
- en
---
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
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) |
<!-- Provide a longer summary of what this dataset is. -->
**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
<!-- Address questions around how the dataset is intended to be used. -->
# 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
<!--direct use have to think still with de code snippet -->
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
**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. |