Application of Multi-Temporal LiDAR for Gully Erosion Monitoring in Mediterranean Intensive Olive Groves

Monitoring the dynamics of gullies in Mediterranean agrosystems is critical but severely limited by agricultural practices that generate continuous machinery compaction and tillage of the soil, camouflaging topographic features and disturbing erosion analyses. This study discusses strategies to quantify erosion by distinguishing natural erosion from agricultural disturbance, integrating multitemporal LiDAR data (2014, 2020, 2024) with gully inventories using orthophoto maps (2011–2022). The volumetric changes were assessed using DoD for the periods 2014–2020 and 2020–2024, and the morphometric performance of the TNO index was further validated using ROC curves in R. Both approaches performed consistently higher in detecting permanent gullies. The TNO index has proven its usefulness for semi-automated delimitation in large or low-data areas. By intersecting DoD surfaces with the gully inventory, localized erosion processes were successfully isolated from the surrounding agricultural landscape matrix. The quantified rate of erosion in the gullies refers strictly to their internal dynamics, which have been close to the natural threshold for soil formation, indicating a risk of soil degradation.

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Publication Details

Journal
Remote Sensing
Published
2026-10-22
DOI
https://doi.org/10.3390/rs18213632
Primary Topic
Soil erosion and sediment transport
Type
article
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article

Application of Multi-Temporal LiDAR for Gully Erosion Monitoring in Mediterranean Intensive Olive Groves

Susana Pereira, Sara L. Teixeira
Remote Sensing
Soil erosion and sediment transport
article

Application of Multi-Temporal LiDAR for Gully Erosion Monitoring in Mediterranean Intensive Olive Groves

Susana Pereira, Sara L. Teixeira
article en

Abstract

Monitoring the dynamics of gullies in Mediterranean agrosystems is critical but severely limited by agricultural practices that generate continuous machinery compaction and tillage of the soil, camouflaging topographic features and disturbing erosion analyses. This study discusses strategies to quantify erosion by distinguishing natural erosion from agricultural disturbance, integrating multitemporal LiDAR data (2014, 2020, 2024) with gully inventories using orthophoto maps (2011–2022). The volumetric changes were assessed using DoD for the periods 2014–2020 and 2020–2024, and the morphometric performance of the TNO index was further validated using ROC curves in R. Both approaches performed consistently higher in detecting permanent gullies. The TNO index has proven its usefulness for semi-automated delimitation in large or low-data areas. By intersecting DoD surfaces with the gully inventory, localized erosion processes were successfully isolated from the surrounding agricultural landscape matrix. The quantified rate of erosion in the gullies refers strictly to their internal dynamics, which have been close to the natural threshold for soil formation, indicating a risk of soil degradation.

Remote SensingVol. 18(21)
Centro de Estudos em Geografia e Ordenamento do Territorio (PT)
Openalex Percentile: Top 14%
Soil erosion and sediment transport
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