Improving the continuous photogrammetric monitoring system

Abstract. The basalt wall next to the Fluvià river, where Castellfollit de la Roca (Girona) is located, is known for its high frequency of rockfalls, which can affect existing buildings. To monitor it, a continuous photogrammetry system developed by the UPC's geomatics engineering group and the ICGC was installed in 2021. This system, consisting of three cameras, has since captured images that are sent to the server located at the UPC, where they are processed to detect movements in the rock massif over time. If a rockfall is detected, a three-dimensional model is generated to estimate the volume of rock mobilised.This massif is characterised by the presence of changing vegetation and a high frequency of rainy and foggy days. These changes in the appearance of the rockfall decrease the sensitivity of the photographic system to the detection of premonitory movements or low-volume rockfalls. To mitigate these effects, improvements have been made to the matching algorithms. These improvements include the implementation of different procedures such as the automatic selection of the best quality daily image, radiance balancing techniques and the creation of dynamic masks adapted to vegetation changes.

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Publication Details

Journal
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Published
2025-06-16
DOI
https://doi.org/10.5194/isprs-archives-xlviii-1-w4-2025-89-2025
Primary Topic
Advanced Measurement and Detection Methods
Type
article
Field-Weighted Citation Impact
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article

Improving the continuous photogrammetric monitoring system

Albert Prades, María Amparo Núñez Andrés
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Advanced Measurement and Detection Methods
article

Improving the continuous photogrammetric monitoring system

Albert Prades, María Amparo Núñez Andrés
article en

Abstract

Abstract. The basalt wall next to the Fluvià river, where Castellfollit de la Roca (Girona) is located, is known for its high frequency of rockfalls, which can affect existing buildings. To monitor it, a continuous photogrammetry system developed by the UPC's geomatics engineering group and the ICGC was installed in 2021. This system, consisting of three cameras, has since captured images that are sent to the server located at the UPC, where they are processed to detect movements in the rock massif over time. If a rockfall is detected, a three-dimensional model is generated to estimate the volume of rock mobilised.This massif is characterised by the presence of changing vegetation and a high frequency of rainy and foggy days. These changes in the appearance of the rockfall decrease the sensitivity of the photographic system to the detection of premonitory movements or low-volume rockfalls. To mitigate these effects, improvements have been made to the matching algorithms. These improvements include the implementation of different procedures such as the automatic selection of the best quality daily image, radiance balancing techniques and the creation of dynamic masks adapted to vegetation changes.

˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesVol. XLVIII-1/W4-2025
Universitat Politècnica de Catalunya (ES)
Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación
Openalex Percentile: Top 88%
Advanced Measurement and Detection Methods
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Improving the continuous photogrammetric monitoring system — Albert Prades, María Amparo Núñez Andrés · ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences (2025) | TGRS Research Map | TGRS