Journal of Geography, Environment and Earth Science International

Tropical land systems are exposed to an unusually dense combination of hazards, including cyclones, extreme rainfall, riverine and coastal flooding, prolonged dry spells, wildfire, mass movement, salinisation and land subsidence. These hazards rarely act in isolation, and their combined imprint on soils, vegetation and hydrology is frequently interpreted as land degradation. Geospatial techniques based on satellite time series, active microwave sensing, cloud computing and machine learning now supply most of the evidence used to identify and report such degradation, yet the interpretive foundations of that evidence remain contested. This critical narrative review examines how geospatial methods identify land degradation attributable to climate change-induced multi-hazards in tropical settings, and evaluates the strength, consistency and limitations of the supporting literature published between January 2000 and 8 July 2026. Literature was identified through Crossref, the Directory of Open Access Journals, Semantic Scholar and Google Scholar, supplemented by citation chaining and searches of authoritative institutional sources. The synthesis identifies four persistent problems. First, definitional plurality means that measured quantities differ across studies that report the same nominal phenomenon, and global degradation hotspots diverge substantially according to the indicator selected. Second, the dominant trend-based and residual-trend methods have limited statistical power for gradual change, and are structurally poor at separating climate-driven variability from persistent capacity loss, which matters acutely where hazards recur. Third, persistent cloud cover in humid tropical regions displaces monitoring towards active microwave and fused data streams, whose degradation-relevant interpretation is less mature than that of optical vegetation indices. Fourth, multi-hazard and multi-risk frameworks and land degradation monitoring have developed largely in parallel, so the cumulative and cascading pathways through which sequential hazards deplete land capacity are seldom represented explicitly. Evidence is strongest for detecting abrupt, spatially extensive disturbance and weakest for attributing chronic degradation to specific hazard sequences. Priorities include hazard-conditioned baselines, sequence-aware detection, probability-based validation adequate to hazard footprints, and greater representation of small tropical states in the evidence base.