Статья

GIS and remote sensing in soil erosion studies: a systematic bibliometric review (2000–2024) and implications for Central Asia

Shakhnoza BakhronovaCentral Asian University of Environmental and Climate Change Studies (Green University), UzbekistanSayidjakhon KhasanovCentral Asian University of Environmental and Climate Change Studies (Green University), UzbekistanQiuying ZhangChinese Research Academy of Environmental SciencesPeifang LengShandong Yucheng Agro-ecosystem National Observation and Research Station, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesHongguang LiuCollege of Resources and Environment, University of Chinese Academy of SciencesPing GongCollege of Resources and Environment, University of Chinese Academy of SciencesGang ChenDepartment of Civil and Environmental Engineering, College of Engineering, Florida A&M University-Florida State UniversityRashid KulmatovNational University of UzbekistanLuqmon SamievResearch Institute of Environment and Nature Conservation TechnologiesFadong LiCollege of Resources and Environment, University of Chinese Academy of Sciences

2026en

ABI

Аннотация

Soil erosion and associated land degradation threaten agricultural sustainability in arid and semi-arid regions, yet evidence remains uneven across geographies. This review synthesizes global progress in GIS and remote sensing applications for soil erosion assessment from 2000 to 2024 and highlights implications for Central Asia, with a particular focus on Uzbekistan. Following the PRISMA procedures, 383 Scopus-indexed studies were analyzed using Bibliometrix and VOSviewer. Publication activity increased markedly after 2019, paralleling expanded access to Sentinel and Landsat archives, cloud-based geospatial processing, and machine-learning approaches. The analysis showed that recent soil erosion research was increasingly driven by GIS- and remote-sensing-based workflows, with vegetation indices, DEM-derived terrain variables, and rainfall-related factors emerging as the most frequently applied inputs in spatial assessment and hotspot identification. Across the reviewed studies, vegetation cover and management, DEM-derived topography, rainfall-runoff processes, and soil erodibility were the dominant modelling inputs, while NDVI and land-use dynamics increasingly supported multi-temporal monitoring. However, Central Asia remains underrepresented and is constrained by limited field validation, inconsistent soil databases, and weak integration of remote-sensing indicators with measured soil properties and irrigation-driven salinity and groundwater dynamics. This review identifies key priorities for the region, including standardized workflows, long-term monitoring sites, and locally calibrated models to support targeted conservation planning and policy interventions.

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Идентификаторы

DOI: 10.1080/10106049.2026.2695486

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