Author(s)

LADY BRAVO-MONTERO, GRICELDA HERRERA-FRANCO, CRISTHIAN BRAVO-PIN, PAÚL CARRIÓN-MERO

Abstract

Monitoring fluvial systems (FS) and using remote sensing (RS) tools provide essential spatial data for assessing riverine and marine-coastal environments at global and regional scales. In areas with difficult access or limited data, knowledge gaps exist regarding RS methodologies or tools that can assist in identifying flood events or changes in flow rates, tailored to local conditions. This study aims to examine the processes involved in monitoring FS using RS tools, through a scientometric analysis and a review of the scientific literature to identify research trends and methodologies developed. The methodology was based on: (i) defining a search strategy in the Scopus and Web of Science databases for science mapping by research areas and trends, (ii) a literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method, and (iii) a matrix of FS monitoring processes and environmental assessment using RS tools. It was found that, of the 2,166 publications from 1973 to 2025, the predominant areas of research focused on: (i) remote sensing tools in spatial modelling, (ii) satellite image processing, (iii) ecological dynamics and aquatic systems, (iv) geospatial analysis applied to geomorphology, and (v) fluvial and sedimentary processes. 63.81% of the studies reviewed utilised geospatial data (Landsat and Sentinel-2) for multi-temporal analysis in integrated water resources management. The analysis matrix of the systematic review provided further insight into the main RS methodologies used (e.g., 55% machine learning, 20% deep learning). RS technologies such as: (i) LiDAR, (ii) Sentinel, (iii) Radar and (iv) synthetic aperture radar, enable high-precision multi-temporal monitoring to optimise decision-making processes aimed at the governance and sustainability of territories.

Keywords

random forest, satellite images, fluvial geomorphology, Scientometrics, PRISMA