fotogrammetrii

Fotogrammetria is a scientific discipline that involves the art, science, and technology of obtaining reliable information about physical objects and environments through the process of recording, measuring, and interpreting photographic images and patterns of recorded radiant electromagnetic energy and converting this pattern into digital models. The term originates from the Greek words *phos* (light), *gramma* (drawing), and *metron* (measure), literally meaning "light drawing measurement."

The primary goal of fotogrammetria is to extract precise spatial measurements from photographs or digital images. This process can be applied in various fields, including architecture, archaeology, geodesy, remote sensing, and computer vision. Traditional fotogrammetria relies on analog photographs, while modern techniques utilize digital cameras, drones, and specialized software for data processing.

Key techniques in fotogrammetria include aerial fotogrammetria, terrestrial fotogrammetria, and close-range fotogrammetria. Aerial fotogrammetria involves capturing images from aircraft or satellites to create maps, orthophotos, and 3D models of large areas. Terrestrial fotogrammetria is used for smaller-scale applications, such as surveying buildings or infrastructure. Close-range fotogrammetria focuses on capturing detailed images of objects within a few meters, often used in forensic investigations, cultural heritage documentation, and industrial inspections.

The process typically begins with capturing multiple overlapping images of the subject from different angles. These images are then processed using specialized software to create a 3D point cloud, which can be further refined into a textured 3D model. Photogrammetric software employs algorithms to match features between images, calculate camera positions, and reconstruct the geometry of the scene.

Fotogrammetria has seen significant advancements with the rise of consumer-grade digital cameras, high-resolution sensors, and machine learning techniques, making it more accessible and accurate than ever before. Its applications continue to expand, contributing to fields such as virtual reality, autonomous vehicles, and environmental monitoring.