---
tags:
  - aerial
  - temporal
  - time-series
  - construction
  - multiview
  - change-detection
  - world-model
  - urban
task_categories:
  - video-classification
  - image-classification
  - image-segmentation
  - object-detection
size_categories:
  - small
license: other
---

# CityLine — Temporal Aerial Construction Dataset (Sample)

**Temporal Aerial Vision · Construction Progress · Multiview Geometry · San Jose, CA**

CityLine is a multi-year aerial imagery sequence captured from a helicopter during the construction of a major mixed-use development in **San Jose, California**.  
This sample highlights multiple construction phases over time, with several oblique views per capture date.

The full (commercial) dataset contains **hundreds of high-resolution images** with monthly coverage across several years — suitable for **world models, 3D reconstruction, change detection, construction analytics, and urban growth modeling**.

This dataset is a **limited preview sample** intended for evaluation and experimentation.

---

## 📍 Project Overview

| Property | Value |
|---------|------|
| Project name | CityLine |
| Location | San Jose, California, USA |
| Capture type | Helicopter-based oblique aerial imagery |
| Resolution | 12MP JPEG (RAW available commercially) |
| Coverage period (full set) | 2017 → 2025 (approx.) |
| Temporal cadence | ~monthly |
| Viewpoints per capture | Multiple oblique angles |
| Coordinates | 37.374751, -122.032811 |

---

## 🎯 Machine Learning Use Cases

| Category | Tasks Enabled |
|---------|---------------|
| **Temporal Vision** | World models, change detection, temporal consistency |
| **Multiview Geometry** | Structure-from-motion, NeRF, depth from motion |
| **Autonomy + Robotics** | Mapping, localization, spatial reasoning |
| **Construction Analytics** | Progress estimation, digital twins, safety monitoring |
| **Earth Observation** | Urban growth, infrastructure evolution |

---

## 📁 Dataset Contents (Sample)

Folder structure:

```text
preview/              # resized JPEG previews for fast HF browsing
images/               # full-resolution JPEGs grouped by month
  2017-12/
  2019-01/
  2020-06/
  2021-09/
  2023-06/
  2025-01/
metadata.csv
```

➡ Preview images are **2048px max dimension**, ideal for Hugging Face’s viewer  
➡ Full-resolution files contain the highest-quality data for research/licensing

---

### `metadata.csv` Schema

| Column | Description |
|--------|-------------|
| `project_id` | Numeric ID for the project |
| `project_name` | "CityLine" |
| `filename` | Full-resolution image filename |
| `preview_filename` | Lower-resolution preview filename |
| `date` | Capture date parsed from filename |
| `year_month` | Monthly grouping |
| `image_seq` | Sequence index derived from filename |
| `orbit_index` | Orbit grouping (sample = 1) |
| `orbit_frame` | Ordered view index (1…N) |
| `latitude` | Project latitude |
| `longitude` | Project longitude |
| `notes` | Optional annotation |

---

## 🔧 Quick Usage Example

```python
import pandas as pd
from pathlib import Path
from PIL import Image

meta = pd.read_csv("metadata.csv")

# Load preview image first (fast)
preview_path = Path("preview") / meta['preview_filename'][0]
img_preview = Image.open(preview_path).convert("RGB")
img_preview.show()

# Load matching full-resolution image when needed
full_path = Path("images") / meta['year_month'][0] / meta['filename'][0]
img_full = Image.open(full_path).convert("RGB")
img_full.show()
```

---

## 🔐 Full Dataset Access & Licensing

This sample is provided for **evaluation purposes only**.

The complete CityLine dataset (836 images) and a library of **270+** full-lifecycle construction projects are available under commercial license:

- Towers
- Hospitals
- Stadiums
- Highways & interchanges
- Commercial sites

**Contact for full access:**  
📧 gene@sharpshotsaerial.com

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## 🛰 About SharpShots Aerial

SharpShots Aerial specializes in long-term helicopter-based imaging of major construction and urban projects, enabling advanced mapping and AI research applications.

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