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--- |
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license: cc0-1.0 |
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task_categories: |
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- depth-estimation |
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- image-to-image |
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language: |
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- en |
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pretty_name: MCTED |
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size_categories: |
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- 10K<n<100K |
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tags: |
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- Mars |
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- remote-sensing |
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- image |
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- depth-estimation |
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- DEM |
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--- |
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# MCTED - Mars CTX Terrain-Elevation Dataset |
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[**Dataset repository**](https://github.com/ESA/MCTED) | [**arXiv article**](https://arxiv.org/abs/2509.08027) |
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<img src="./.images/dataset_samples.png" alt="Dataset samples" style="width:100%;"/> |
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## Overview |
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**MCTED** is a machine-learning-ready dataset of optical images of the surface of Mars, paired with their corresponding digital elevation models. |
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It was created using an extensive repository of orthoimage-DEM pairs with the NASA Ames Stereo Pipeline using the Mars Reconneissance Orbiter's CTX instrument imagery by |
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[Day et al. 2023](https://github.com/GALE-Lab/Mars_DEMs). We process the samples from the repository using a developed pipeline aimed at eliminating elevation artifacts, |
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imputing missing data points and sample selection. The dataset is provided in the form of 518x518 patches. |
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This dataset is fully open-source, with all data and code used for it's generation available publicly. |
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## Dataset contents |
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The dataset contains in total **80,898** samples, divided into two splits: |
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|Training|Validation| |
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|---|---| |
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|65,090|15,808| |
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Each sample consists of 4 different files: |
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|Type|Description| |
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|---|---| |
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|***optical.png***|The monochromatic optical image patch. Despite being monochromatic, the image still has 3 channels, with all channels being the same| |
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|***elevation.tiff***|The elevation data patch in meters w.r.t. the Martian datum| |
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|***deviation_mask.png***|Binary mask with locations that were identified as elevation artifacts during dataset generation and were replaced with interpolated values| |
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|***initial_nan_mask.png***|Binary mask with locations that contained missing values in the Day et al. data samples and were imputed during processing| |
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### Sample naming |
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Each sample follows the following naming convention: |
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<img src="./.images/sample_naming.png" alt="Naming convention of each sample" style="border-radius:15px; width: 70%;"> |
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## Data source |
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The dataset has been generated using a orthoimage-DEM pair repository generated from MROs CTX imagery using the [NASA Ames Stereo Pipeline](https://github.com/NeoGeographyToolkit/StereoPipeline) |
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by [Day et al. 2023](https://faculty.epss.ucla.edu/~mday/index.php/mars-dems/). We pass the samples through an extensive processing and selection pipeline, using approximately **47%** of the available data. |
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<img src="./.images/sankey_processing.png" alt="Sankey diagram of processed samples" style="width:50%;"/> |
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## Typical usage |
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The simplest way to use MCTED is by using the `load_dataset` function from HuggingFace's `datasets` python package: |
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```python |
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from datasets import load_dataset |
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# Download and load the dataset |
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mcted = load_dataset("ESA-Datalabs/MCTED", num_proc=8) |
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``` |
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## Example of accessing sample data |
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```python |
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from datasets import load_dataset |
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import matplotlib.pyplot as plt |
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import numpy as np |
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mcted = load_dataset("ESA-Datalabs/MCTED", num_proc=8) |
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# Load one sample from the validation split |
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sample = mcted["validation"][0] |
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plt.figure(figsize=(15, 5)) |
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plt.subplot(1, 4, 1) |
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plt.imshow(sample["optical.png"]) |
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plt.title("Optical image") |
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plt.subplot(1, 4, 2) |
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plt.imshow(np.array(sample["elevation.tif"]), cmap="terrain") |
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plt.title("DEM") |
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plt.subplot(1, 4, 3) |
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plt.imshow(sample["deviation_mask.png"], cmap="gray") |
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plt.title("Elevation outlier mask") |
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plt.subplot(1, 4, 4) |
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plt.imshow(sample["initial_nan_mask.png"], cmap="gray") |
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plt.title("Initial invalid values mask") |
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``` |
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## Citation |
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```bibtex |
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@misc{osadnik2025, |
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title={MCTED: A Machine-Learning-Ready Dataset for Digital Elevation Model Generation From Mars Imagery}, |
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author={Rafał Osadnik and Pablo Gómez and Eleni Bohacek and Rickbir Bahia}, |
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year={2025}, |
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eprint={2509.08027}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2509.08027}, |
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} |
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``` |
