Add CityLine temporal aerial sample dataset

README.md

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+---
+tags:
+  - aerial
+  - temporal
+  - time-series
+  - construction
+  - multiview
+  - change-detection
+  - world-model
+  - urban
+task_categories:
+  - video-prediction
+  - 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 orbital 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 Hugging Face dataset is a **limited 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 versions available commercially) |
+| Coverage period (full set) | 2017 → 2025 (approx.) |
+| Temporal cadence | ~monthly (full set) |
+| Viewpoints per capture | Multiple oblique angles (sample: up to 8 per date) |
+| Coordinates | 37.374751, -122.032811 |
+
+---
+
+## 🎯 Machine Learning Use Cases
+
+| Area | Tasks Enabled |
+|------|---------------|
+| **Temporal Vision** | Change detection, temporal consistency, world models |
+| **3D / Multiview** | Structure-from-motion, NeRF, multi-view reconstruction |
+| **Autonomous Systems** | Aerial mapping, localization, planning context |
+| **AEC / Construction Analytics** | Progress estimation, site monitoring, digital twins |
+| **Earth Observation** | Building footprint evolution, urban growth analysis |
+
+---
+
+## 📁 Dataset Contents (Sample)
+
+Folder structure:
+
+```text
+images/
+  2017-12/
+    171229258.jpg
+    ...
+  2019-01/
+    ...
+  2020-06/
+    ...
+  2021-09/
+    ...
+  2023-06/
+    ...
+  2025-01/
+    ...
+metadata.csv
+```
+
+### `metadata.csv` Schema
+
+| Column | Description |
+|--------|-------------|
+| project_id | Numeric ID for the project |
+| project_name | "CityLine" |
+| filename | Image filename |
+| date | Capture date parsed from filename |
+| year_month | Temporal grouping |
+| image_seq | Sequence index from filename |
+| orbit_index | Orbit grouping (sample = 1) |
+| orbit_frame | Ordered view index (1…N) |
+| latitude | Project latitude |
+| longitude | Project longitude |
+| notes | Optional free-text annotation |
+
+---
+
+## 🔧 Example Code: Loading Metadata & Images
+
+```python
+import pandas as pd
+from pathlib import Path
+from PIL import Image
+
+meta = pd.read_csv("metadata.csv")
+root = Path("images")
+
+for _, row in meta.iterrows():
+    img_path = root / row["year_month"] / row["filename"]
+    img = Image.open(img_path).convert("RGB")
+    # do something with img
+```
+
+---
+
+## 📬 Full Dataset Access & Licensing
+
+This sample is provided for **evaluation only**.
+
+The complete CityLine sequence (836 images) and a library of **270+ full commercial construction projects** are available for enterprise licensing, including:
+
+- RAW imagery  
+- Full monthly coverage start → completion  
+- Stadiums, hospitals, towers, interchanges, etc.
+
+**Contact for access:**  
+📧 gene@sharpshotsaerial.com
+
+---
+
+## 🛰 About SharpShots Aerial
+
+SharpShots Aerial provides unique temporal helicopter-based datasets for AI, construction analytics, and mapping workflows.
+
+---