New Drone Survey Reveals Structural Secrets of Sagrada Familia’s Unfinished Towers
BARCELONA, 25 October 2023 (Reuters) – A groundbreaking aerial drone survey, conducted by the Sagrada Familia Foundation and the Polytechnic University of Catalonia, has unveiled new structural complexities within the iconic basilica’s as-yet-unfinished central towers. The survey, completed on Tuesday, utilized high-resolution LiDAR and thermal imaging to map previously inaccessible sections of the structure, including the 170-meter-high Jesus Christ Tower.
WHAT: A comprehensive drone-based inspection of the Sagrada Familia’s structural integrity and historical construction techniques. The assessment revealed that certain internal stone joints and load-bearing pillars, originally designed by architect Antoni Gaudi, have shifted over 130 years of construction due to environmental factors.
WHEN: The data was collected over three days last week. Preliminary results were released to the public on October 24, coinciding with the 100th anniversary of Gaudi’s appointment as building director.
WHERE: The basilica of Sagrada Familia, a UNESCO World Heritage Site in Barcelona, Spain. The survey specifically focused on the tallest towers, which remain under construction and are projected for completion by 2026.
WHO: The project is a collaboration between the Sagrada Familia Foundation, which manages the site, and engineering experts from the Polytechnic University of Catalonia. Drone operators were supervised by structural engineer Dr. Maria Ester Vidal.
WHY: Officials stated that the survey was essential to verify the long-term stability of the towers amid ongoing construction and to validate Gaudi’s original mathematical models. The Foundation aims to finalize the church’s liturgical furnishings by the 2026 target.
Effects and Future Steps: Engineers confirmed the shifts are minor and do not pose immediate safety risks. However, the findings will force a recalibration of the 3D-printed architectural models used for the final stonework. The drone data