Evidence map›Paper›PMID 42884294›Full record

ArticleSensors (Basel, Switzerland)2026

Applicability of L-Band and C-Band InSAR for Detecting Slow-Moving Landslides in Vegetated Tropical Andes.

Emanuel Castillo-Cardona, Stefania Valencia-Herrera, Exneyder A Montoya-Araque, Marco F Gamboa-Ramirez, Adriana I Osorio-Mosquera, Daniel F Ruiz, Alejandro Marulanda-Tobon

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Emanuel Castillo-CardonaProyecto Sistema de Alerta y Monitoreo de Antioquia (SAMA), Universidad EAFIT, Carrera 49 N° 7 Sur-50, Medellín 050022, Colombia.ORCID 0009-0003-2391-1237
Stefania Valencia-HerreraProyecto Sistema de Alerta y Monitoreo de Antioquia (SAMA), Universidad EAFIT, Carrera 49 N° 7 Sur-50, Medellín 050022, Colombia.ORCID 0009-0002-2880-9795
Exneyder A Montoya-AraqueProyecto Sistema de Alerta y Monitoreo de Antioquia (SAMA), Universidad EAFIT, Carrera 49 N° 7 Sur-50, Medellín 050022, Colombia.ORCID 0000-0002-6566-4962
Marco F Gamboa-RamirezProyecto Sistema de Alerta y Monitoreo de Antioquia (SAMA), Universidad EAFIT, Carrera 49 N° 7 Sur-50, Medellín 050022, Colombia.
Adriana I Osorio-MosqueraSchool of Applied Sciences and Engineering, Universidad EAFIT, Carrera 49 N° 7 Sur-50, Medellín 050022, Colombia.
Daniel F RuizSchool of Applied Sciences and Engineering, Universidad EAFIT, Carrera 49 N° 7 Sur-50, Medellín 050022, Colombia.ORCID 0009-0009-0452-9394
Alejandro Marulanda-TobonSchool of Applied Sciences and Engineering, Universidad EAFIT, Carrera 49 N° 7 Sur-50, Medellín 050022, Colombia.ORCID 0000-0001-7327-9231

Funding

Gobernación de Antioquia, SAMA program 25CT424C2101
6 · The paper itself

Abstract

Interferometric Synthetic Aperture Radar (InSAR) enables the measurement of ground deformation with high spatial coverage and frequent temporal sampling, making it a valuable tool for landslide monitoring in remote mountainous regions. However, in tropical mountainous environments, dense vegetation, steep topography, and rapid surface changes often reduce interferometric coherence, limiting the reliability of C-band observations. This study evaluates the applicability of C-band and L-band spaceborne InSAR data for detecting slow-moving landslides in the northern tropical Andes. The analysis focuses on two case studies in the northern Colombian Andes, where slow-moving landslides have affected two municipalities. Time-series deformation and velocity analysis were derived using a Small Baseline Subset (SBAS) approach applied to Sentinel-1 (C-band) and SAOCOM-1 (L-band) SAR datasets. The detected deformation patterns were compared with independent field evidence reported in previous geotechnical investigations of the study area. Results show that both sensors successfully identified the spatial extent of the slow-moving landslide. However, L-band data exhibited higher coherence and reduced noise levels in densely vegetated zones. These differences highlight the improved performance of L-band observations under tropical vegetation conditions, while C-band data remain effective for detecting moderate surface displacements where coherence is preserved. The findings provide guidance for selecting appropriate SAR wavelengths for landslide detection in tropical mountainous regions and support the integration of multi-frequency InSAR for operational hazard assessment.

Indexed as

landslideremote sensingtime-series InSARtropical region

Identifiers

PMID42884294
PMCPMC13667631

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.