# What is Site Reconstruction?

## Module Overview

This module frames the course. You'll learn what site reconstruction is, where it sits in the wider reconstruction workflow, and — most importantly — the **two anchors** every site reconstruction depends on: a **georeferenced world** (satellite imagery at real-world scale) and a **matched camera** (a Blender camera that replicates the original photo). Everything in the course is a step toward establishing and combining those two anchors.

## Introduction

Site reconstruction is the practice of rebuilding a physical location in 3D from imagery you did not shoot yourself: satellite views, street-level photos, drone video, social media stills. In a visual investigation context, the goal is rarely "a pretty 3D model." It is a **verifiable, measurable 3D environment** that lets you answer questions like:

- Could the witness at that location have seen the event?
- How large is the compound, the container yard, the vehicle — really?
- Does this photo match this claimed location, or is something off?
- Where was this shot taken from?

The method has been developed and tested through a live 8-week curriculum (an Oxford + Dutch Police pilot). The version in this course is the generalizable core of that curriculum, built around a deliberately generic scenario: **reconstructing a house from satellite imagery and multiple photos**. The house is not the point — the pipeline is.

## The Two Anchors

Every site reconstruction stands on two things. If either one is missing or weak, everything built on top of it is suspect.

### Anchor 1: A Georeferenced World

Satellite imagery gives you the site at **real-world scale and position**. In Blender, that means a scene where 1 unit = 1 meter, the origin sits at the site's real coordinates, and the ground truth of "what is where" is fixed before you model anything.

This anchor is established in [Module 02](../02-satellite-baseline/lesson.md) using tools like [BlenderGIS](../../../addons/blendergis.mdx) and [QGIS](../../../tools/QGIS/index.md).

### Anchor 2: A Matched Camera

OSINT photos give you the **viewpoint**: the exact position, orientation, and focal length of the camera that captured them. Camera matching (a.k.a. perspective solving, the "fSpy process") recovers those camera parameters from a single photo using the vanishing points of parallel lines in the image.

This anchor is established in [Module 03](../03-camera-matching/lesson.md).

### Why Both?

- A georeferenced world without a matched camera gives you a site you can measure but **cannot prove your source photo came from**.
- A matched camera without a georeferenced world gives you a photo-accurate scene in **arbitrary, unscaled units** — impressive, but unverifiable.

Together they let you say: *"This is the site at real-world scale, and this is the exact camera from which the evidence photo was taken — here is what that camera can and cannot see."*

## Why This Matters for Visual Investigation

### The Opportunity

OSINT imagery is abundant and often geolocatable. Site reconstruction turns flat images into a measurable, explorable environment — the difference between *looking at* evidence and *interrogating* it.

### The Caveat

Reconstruction is **interpretation, not recording**. A reconstructed site is a model of a site, built from assumptions (imagery resolution, matching accuracy, what you chose to model). It must be documented and presented with its uncertainties — which is exactly what [Module 06](../06-investigation-context/lesson.md) covers.

### Where It Fits in the Workflow

Site reconstruction is one branch of **geometric reconstruction**. The KB's [geometric reconstruction playbook](../../../techniques/geometric-reconstruction.md) distinguishes between object-level, site-level (this course), and environmental reconstruction. The [camera matching technique page](../../../techniques/1-foundation-preparation/camera-matching.md) is the core skill this course operationalizes.

## Key Concepts at a Glance

| Concept | Definition |
|---------|------------|
| **Georeferenced baseline** | A Blender scene aligned to real-world coordinates at 1:1 scale, built from satellite imagery |
| **1:1 scale** | The convention that 1 Blender unit = 1 meter, so all measurements are in real-world units |
| **Vanishing point** | The point where parallel lines (not parallel to the image plane) converge in a perspective image |
| **Perspective solving (camera matching)** | Recovering camera position, orientation, and focal length from vanishing points in a single image |
| **Photomatch** | The verification step: comparing a render from your matched camera against the original photo |
| **Scale hierarchy** | The ranked source-reliability system for scale references (detailed in [Scale Estimation](../../../techniques/1-foundation-preparation/scale-estimation.md)) |

## Knowledge Check

1. What are the two anchors of a site reconstruction, and what does each one give you?
2. Why is a matched camera useless for measurement unless the scene is at 1:1 scale?
3. Name one question an investigation can answer with a reconstructed site that it cannot answer from the flat photo alone.

### Check your answers

1. The **georeferenced world** (real scale + position from satellite imagery) and the **matched camera** (the exact viewpoint of the source photo). One gives you measurability, the other gives you provenance of the viewpoint.
2. Camera matching recovers relative geometry, not absolute scale — the recovered camera is only in scene units. Without a 1:1 georeferenced scene, those units are arbitrary, so any distance you measure is meaningless.
3. Examples: line-of-sight from a specific spot, the true size of a structure, the camera height at capture, whether an object was present in a scene reconstructed from another angle.

## Exercise: When to Reconstruct a Site

For each scenario, answer:

1. **Is site reconstruction the right tool here?** (Yes / No / Only partially)
2. **Which anchor do you establish first** — the georeferenced world, or the matched camera? Why?
3. **What is your first concrete step** in Blender or a GIS tool?

### Scenario A

You have a drone video orbiting a two-story house and its compound, suspected of being used as a weapons cache. You want to measure the compound, test sightlines from neighboring buildings, and later show where a specific van was positioned.

### Scenario B

A single street-level photo shows a suspect's car parked in front of a building. You want to determine whether a witness standing 200 m away could have read the license plate.

### Scenario C

A social media post claims to show a building destroyed by a strike in a named city district. You want to check whether the visible skyline and street layout actually match that district.

*There are no single "correct" answers — this is a judgment exercise. Compare your reasoning against the Camera Matching reference module (in the sidebar) and the [Analyzing Footage](../../../techniques/1-foundation-preparation/analyzing-footage.md) page. You'll put these judgments into practice in the [Final Project](../07-final-project/lesson.md).*

## Summary

Site reconstruction rebuilds a location in 3D from satellite and OSINT imagery. It stands on two anchors: a georeferenced 1:1 world (satellite baseline) and a matched camera (perspective solving of the source photo). The course proceeds from anchor to anchor to model: baseline → camera → model → verify → document.

## Resources

### Knowledge Base Pages

- [Camera Matching](../../../techniques/1-foundation-preparation/camera-matching.md) — the core technique this course operationalizes
- [Camera and Perspective](../../../techniques/1-foundation-preparation/camera-and-perspective.md) — the foundational perspective concepts
- [Geometric Reconstruction](../../../techniques/geometric-reconstruction.md) — the playbook: three scopes and the full phase flow
- [Measurements, Scale & Dimension](../../../techniques/1-foundation-preparation/measurements.md) — the scale hierarchy you'll lean on constantly

### Add-ons

- [fSpy](../../../addons/fspy.mdx) — vanishing-point camera estimation, imported into Blender
- [Perspective Plotter](../../../addons/perspective-plotter.mdx) — real-time camera matching inside Blender

### Upcoming Videos in This Course

| Module | Video |
|--------|-------|
| 02 | *Establishing a Measurement Baseline from Satellite Imagery* |
| 03 | *Applied Camera Matching from Photos* |
| 04 | *Modeling from Matched Photos* |

### Up Next

[Module 02: Establishing the Satellite Baseline →](../02-satellite-baseline/lesson.md)