File size: 4,131 Bytes
70f7df8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 | ---
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
---
## 🛰 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.
---
|