Editorial: Remote sensing applications in mountainous regions

Mountainous regions cover approximately 24%–27% of the total land surface of Earth and host critical water resources, biodiversity hotspots and are among the most climate-sensitive landforms. The complex and challenging topography of high mountain catchments and significant climate variability contribute to formidable challenges in conventional ground data collection. Subsequently, remote sensing has historically offered significant means to process, analyse and retrieve critical multi-faceted information in these regions.

This Research Topic on “Remote Sensing Applications in Mountainous Regions” was motivated by the challenges in remotely sensed observations of mountain systems and hydro-climatological processes and was conceived to showcase the contributions in aligned areas. The collection highlights multi-disciplinary research in hydrological modelling, extreme event characterisation, and environmental risk mapping in varied mountain catchments, leveraging multi-sensor datasets and geospatial analysis.

The contributions assembled in this Research Topic illustrate the breadth of remote sensing applications in mountainous regions. For example, a key insight is developed on the propagation of uncertainties in hydrological modelling corresponding to the spatial resolution of precipitation products. In their study, “Assessing Temporal Sampling Uncertainty in Hydrological Modelling Using Multi-Sensor Observations from GPM and TROPICS Constellations”, Sharma et al. delineated critical insights on the impact of temporal sampling uncertainty in precipitation products on modelled runoff simulation in data-scarce hydrological extreme-prone watersheds through multi-sensor observations of the Global Precipitation Measuring Mission (GPM) and Time Resolved Observations of Precipitation Structure and Storm Intensity with a Constellation of Smallsats (TROPICS) constellations. The study deemed that in such watersheds, for a reliable rainfall runoff simulation and effective hydrological assessment, a minimum of three high-frequency CubeSats is likely to be necessary to achieve sufficiently short revisit intervals for analysis of extreme events resulting in potential flash-floods. Further, the significance of high-resolution weather radar in investigations of intra-event extreme precipitation dynamics was emphasized by Urgilés et al. in their study, “Intra-event extreme rainfall characterization in the tropical Andes: a high-resolution weather radar approach”. Their study highlighted hotspots across 67 critical events in the tropical Andes by employing high-resolution X-band weather radar to characterise extreme rain events (EREs) based on parameters such as peak intensity, spatial area, and core cell cohesion, providing critical insights for improving localized flood forecasting.

The other two contributions assembled in this Research Topic focused on the diverse mountain regions of India from the Teesta catchment of the Sikkim Himalayas to the Western Ghats of Kerala. Mukherjee and Krishna in their study, “Temperature-index routing approach based Snowmelt–Runoff modelling in Lachen basin of upper Teesta catchment, Sikkim (India)”, investigated the performance of a coupled temperature-index based snowmelt runoff model in the largely ungauged Lachen Basin of the Upper Teesta basin of Sikkim. They coupled the traditional temperature-index routing with a linear reservoir routing scheme to model the discharge using remote sensing and gridded datasets and demonstrated that this approach led to improved water resource forecasts in a data-scarce Himalayan basin. In the other study, “Integrated Eco-Environmental Risk Mapping in the Mountainous Tropical Landscapes of Western Ghats of Kerala”, by Drisiya and Singh, illustrated the value of multi-source remote sensing in assessing the cumulative pressures on tropical mountainous landscapes of the Iduki district in Kerala, India. They observed a significant overlap of extreme precipitation events with landslide affected areas comprising high-risk zones in the region with risk heightened by increasing development corresponding to higher tourism and corresponding forest alteration in steep topography. The findings delineate a stark reminder on how increased human activities and development pressures in natural mountainous landscapes are transforming the land-use in the region and increasing the environmental sensitivity.

Despite advances in multi-sensor remote sensing and greater availability of open-source remote sensing data, significant challenges and constraints are observed in various applications across steep mountainous regions. The studies are often predominantly constrained by inadequate representation of topography by open-source Digital Elevation Models (DEM), and imprecise modelling of snow-glacier land-cover in hydro-fluvial and geomorphological models. Moreover, validation is a key challenge in these data-sparse regions where accessibility is a critical issue, resulting in further constraints on integrated development and application of machine learning based frameworks and physical process based models with remote sensing data. Moreover, in the mountain catchments, another critical constraint that inhibits the broader application of these models is the spatio-temporal resolution of the remote sensing data.

Subsequently, looking ahead, several opportunities stand out. The next-generation of satellite missions is expected to offer higher spatial and temporal resolution, enhanced spectral coverage, and significant innovation in sensing modalities, thereby expanding the observational envelope. Moreover, closer coupling of remote sensing data with in-situ and crowd sourced information is expected to improve the Earth observation and bio-physical products in the mountainous regions. This Research Topic contributed to the growing body of evidence for remote sensing as a foundational element of mountain science and sustainability through documented methodologies and multifaceted practical applications across diverse mountain systems. We thank the authors and the reviewers for their contributions to this Research Topic and encourage the broader scientific community to continue advancing the science and application of remote sensing in mountainous environments.

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Footnotes

Edited and reviewed by: Frédéric Frappart, INRAE Nouvelle-Aquitaine Bordeaux, France