README.md

---
license: mit
pretty_name: FARM Aerial Radio Map Dataset
task_categories:
  - image-to-image
  - feature-extraction
tags:
  - radio-map
  - aerial-networking
  - wireless-communication
  - low-altitude-networking
  - foundation-model
  - simulation
size_categories:
  - 10M<n<100M
---

# FARM Aerial Radio Map (ARM) Dataset

## Paper:

- FARM: Foundational Aerial Radio Map for Intelligent Low-Altitude Networking (https://arxiv.org/abs/2604.17362)

## Overview

This repository releases the constructed ARM datasets based on ARM-Omni for FARM training, in-domain evaluation (`D1-D10`), and zero-shot evaluation (`P1`, `F1`, and `A1`). The dataset coverage is summarized below:


| Dataset | Frequencies (GHz) | Max Rx Height (m) | Beamwidths | Map Grid Size | Volume |
| --- | --- | ---: | --- | --- | ---: |
| D1 | 2.1, 3.3, 5.9 | 120 | 30°, 120°, Iso | 512 × 512 | 15000 |
| D2 | 3.5, 4.9, 5.9 | 130 | 30°, 120°, Iso | 512 × 512 | 15000 |
| D3 | 2.1, 4.9, 5.9 | 110 | 30°, 120° | 512 × 512 | 15000 |
| D4 | 3.3, 3.5, 4.9 | 110 | 30°, 120°, Iso | 512 × 512 | 15000 |
| D5 | 3.3, 4.9, 5.9 | 120 | 30°, 120°, Iso | 512 × 512 | 15000 |
| D6 | 2.1, 3.3, 3.5 | 130 | 30°, 120° | 512 × 512 | 15000 |
| D7 | 2.1, 3.3, 3.5, 5.9 | 130 | 30°, Iso | 512 × 512 | 15000 |
| D8 | 2.1, 3.5, 4.9, 5.9 | 100 | 120°, Iso | 512 × 512 | 15000 |
| D9 | 2.1, 3.3, 3.5, 4.9 | 120 | 30°, 120° | 512 × 512 | 15000 |
| D10 | 2.1, 3.3, 3.5, 4.9, 5.9 | 130 | 30°, 120°, Iso | 512 × 512 | 15000 |
| P1 | 2.1, 3.3, 3.5, 4.9, 5.9 | 150 | 30°, 120°, Iso | 256 × 256 | 15000 |
| F1 | 2.6, 7.1 | 120 | 30°, 120°, Iso | 512 × 512 | 15000 |
| A1 | 2.1, 3.3, 3.5, 4.9, 5.9 | 120 | 60° | 512 × 512 | 15000 |

A fuller ARM-Omni release is planned for a future update.

## Repository Layout

Each scene is stored as a compressed archive on the Hub:

```text
<dataset>/scene_<scene_id>.tar.gz
```

After extraction, the scene contains .npy ARM tensors organized as:

```text
<dataset>/<scene_id>/<frequency>/<antenna_pattern>/tx<ID>_yaw<VALUE>.npy
```

Example:

```text
D1/7/freq59/iso/tx45_yaw0.npy
```

Scene IDs are not globally continuous across dataset groups. Users should rely on the extracted folder names as the authoritative scene IDs.

## Data Format

Each released raw `.npy` file stores an ARM volume with shape:

```text
1 × 30 × 512 × 512
```

The dimensions correspond to one radio-map channel, 30 height layers, and a `512 × 512` spatial grid. During data loading, different input sizes can be obtained by selecting a subset of height layers and applying a spatial crop centered on the transmitter pixel. For example, this procedure is used to obtain the `256 × 256` crop for `P1`.

## Signal Encoding and Scene Metadata

- The no-signal truncation threshold is `-120 dB`. In the encoded `uint8` representation, this threshold corresponds to pixel value `130`.
- Building occupancy is embedded in the released ARM tensors; in each height-layer radio map, pixels with value `0` correspond to building-occupied regions.
- The transmitter location metadata is stored in the scene-level CSV file:

```text
<dataset>/<scene_id>/tx_positions_512.csv
```

````md
## Citation

If you use this dataset, please cite our paper:

```text
S. Gao, J. Liang, Y. Yuan, W. Lu, G. Shen, and L. Yang, "FARM: Foundational Aerial Radio Map for Intelligent Low-Altitude Networking," arXiv preprint arXiv:2604.17362, 2026.

@article{gao2026farm,
  author  = {Gao, Shijian and Liang, Jiahui and Yuan, Yifeng and Lu, Wenlihan and Shen, Guobin and Yang, Liuqing},
  title   = {{FARM}: Foundational Aerial Radio Map for Intelligent Low-Altitude Networking},
  journal = {arXiv preprint arXiv:2604.17362},
  year    = {2026}
}