Geomorphometric analysis of urban fluvial terraces using UAV LiDAR: A case study from the La Silla River, Mexico

Abstract. This study presents a high-resolution geomorphological analysis of river terraces along the urban corridor of the La Silla River (Monterrey Metropolitan Area, Mexico) using UAV-based LiDAR and photogrammetry, with a DJI Matrice 350 RTK equipped with a Zenmuse L2 sensor, generating dense point clouds, Digital Elevation Models (DEMs), and orthomosaics. These products allowed for the precise identification of three terrace levels (T1-T3), their geomorphometric attributes, and their lithological composition. The results reveal contrasting degrees of anthropogenic modification: while terrace 1 retains its natural morphology, terraces 2 and 3 show substantial alterations due to residential expansion, public infrastructure, and road construction, which alter the original geomorphological surfaces. Temporal satellite images also show the sensitivity of terrace geomorphology to extreme hydrometeorological phenomena, with cyclones such as Hanna (2020) and Alberto (2024) causing vegetation loss, surface restructuring, and local modification of terraces. Overall, UAV-LiDAR proved to be very effective for mapping terraces in restricted urban environments, providing essential details for monitoring, risk assessment, and sustainable management of urban rivers.

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Publication Details

Journal
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Published
2026-07-02
DOI
https://doi.org/10.5194/isprs-annals-xi-m-1-2026-47-2026
Primary Topic
Landslides and related hazards
Type
article
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article

Geomorphometric analysis of urban fluvial terraces using UAV LiDAR: A case study from the La Silla River, Mexico

Mariana Pérez-Martínez, Kevin D. Rodríguez González, Víctor H. Guerra-Cobián, Yadira Z. Antonio-Durán et al.
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Landslides and related hazards
article

Geomorphometric analysis of urban fluvial terraces using UAV LiDAR: A case study from the La Silla River, Mexico

Mariana Pérez-Martínez, Kevin D. Rodríguez González, Víctor H. Guerra-Cobián, Yadira Z. Antonio-Durán, Fabiola D. Yépez-Rincón, Luis E. Arista Cázares, Héctor de León Gómez, Adrián L. Ferriño-Fierro
article en

Abstract

Abstract. This study presents a high-resolution geomorphological analysis of river terraces along the urban corridor of the La Silla River (Monterrey Metropolitan Area, Mexico) using UAV-based LiDAR and photogrammetry, with a DJI Matrice 350 RTK equipped with a Zenmuse L2 sensor, generating dense point clouds, Digital Elevation Models (DEMs), and orthomosaics. These products allowed for the precise identification of three terrace levels (T1-T3), their geomorphometric attributes, and their lithological composition. The results reveal contrasting degrees of anthropogenic modification: while terrace 1 retains its natural morphology, terraces 2 and 3 show substantial alterations due to residential expansion, public infrastructure, and road construction, which alter the original geomorphological surfaces. Temporal satellite images also show the sensitivity of terrace geomorphology to extreme hydrometeorological phenomena, with cyclones such as Hanna (2020) and Alberto (2024) causing vegetation loss, surface restructuring, and local modification of terraces. Overall, UAV-LiDAR proved to be very effective for mapping terraces in restricted urban environments, providing essential details for monitoring, risk assessment, and sustainable management of urban rivers.

ISPRS annals of the photogrammetry, remote sensing and spatial information sciencesVol. XI-M-1-2026
Universidad Autónoma de Nuevo León (MX)
Sustainable cities and communities
Openalex Percentile: Top 5%
Landslides and related hazards
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Geomorphometric analysis of urban fluvial terraces using UAV LiDAR: A case study from the La Silla River, Mexico — Mariana Pérez-Martínez, Kevin D. Rodríguez González, et al. · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences (2026) | TGRS Research Map | TGRS