The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia

Cascading hazard processes refer to a primary trigger such as heavy rainfall, seismic activity, or snow melt, followed by a chain or web of consequences that can cause subsequent hazards influenced by a complex array of preconditions and vulnerabilities. These interact in multiple ways and can have tremendous impacts on populations proximate to or downstream of these initial triggers. High Mountain Asia (HMA) is extremely vulnerable to cascading hazard processes given the tectonic, geomorphologic, and climatic setting of the region, particularly as it relates to glacial lakes. Given the limitations of in situ surveys in steep and often inaccessible terrain, remote sensing data are a valuable resource for better understanding and quantifying these processes. The present work provides a survey of cascading hazard processes impacting HMA and how these can be characterized using remote sensing sources. We discuss how remote sensing products can be used to address these process chains, citing several examples of cascading hazard scenarios across HMA. This work also provides a perspective on the current gaps and challenges, community needs, and view forward toward improved characterization of evolving hazards and risk across HMA

Advances in Remote Sensing-based Disaster Monitoring and Assessment

Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones

Sensing Mountains

Sensing mountains by close-range and remote techniques is a challenging task. The 4th edition of the international Innsbruck Summer School of Alpine Research 2022 – Close-range Sensing Techniques in Alpine Terrain brings together early career and experienced scientists from technical-, geo- and environmental-related research fields. The interdisciplinary setting of the summer school creates a creative space for exchanging and learning new concepts and solutions for mapping, monitoring and quantifying mountain environments under ongoing conditions of change

Landslide mapping and characterization through Infrared Thermography (IRT): Suggestions for a methodological approach from some case studies

In this paper, the potential of Infrared Thermography (IRT) as a novel operational tool for landslide surveying, mapping and characterization was tested and demonstrated in different case studies, by analyzing various types of instability processes (rock slide/fall, roto-translational slide-flow). In particular, IRT was applied, both from terrestrial and airborne platforms, in an integrated methodology with other geomatcs methods, such as terrestrial laser scanning (TLS) and global positioning systems (GPS), for the detection and mapping of landslides’ potentially hazardous structural and morphological features (structural discontinuities and open fractures, scarps, seepage and moisture zones, landslide drainage network and ponds). Depending on the study areas’ hazard context, the collected remotely sensed data were validated through field inspections, with the purpose of studying and verifying the causes of mass movements. The challenge of this work is to go beyond the current state of the art of IRT in landslide studies, with the aim of improving and extending the investigative capacity of the analyzed technique, in the framework of a growing demand for effective Civil Protection procedures in landslide geo-hydrological disaster managing activities. The proposed methodology proved to be an effective tool for landslide analysis, especially in the field of emergency management, when it is often necessary to gather all the required information in dangerous environments as fast as possible, to be used for the planning of mitigation measures and the evaluation of hazardous scenarios. Advantages and limitations of the proposed method in the field of the explored applications were evaluated, as well as general operative recommendations and future perspectives

Using a new generation of remote sensing to monitor Peru’s mountain glaciers

Remote sensing technologies are integral to monitoring mountain glaciers in a warming world. Tropical glaciers, of which around 70% are located in Peru, are particularly at risk as a result of climate warming. Satellite missions and field-based platforms have transformed understanding of the processes driving mountain glacier dynamics and the associated emergence of hazards (e.g. avalanches, floods, landslides), yet are seldom specialised to overcome the unique challenges of acquiring data in mountainous environments. A ‘new generation’ of remote sensing, marked by open access to powerful cloud computing and large datasets, high resolution satellite missions, and low-cost science-grade field sensors, looks to revolutionise the way we monitor the mountain cryosphere. In this thesis, three novel remote sensing techniques and their applicability towards monitoring the glaciers of the Peruvian Cordillera Vilcanota are examined. Using novel processing chains and image archives generated by the ASTER satellite, the first mass balance estimate of the Cordillera Vilcanota is calculated (-0.48 ± 0.07 m w.e. yr-1) and ELA change of up to 32.8 m per decade in the neighbouring Cordillera Vilcabamba is quantified. The performance of new satellite altimetry missions, Sentinel-3 and ICESat-2, are assessed, with the tracking mode of Sentinel-3 being a key limitation of the potential for its use over mountain environments. Although currently limited in its ability to extract widespread mass balance measurements over mountain glaciers, other applications for ICESat-2 in long-term monitoring of mountain glaciers include quantifying surface elevation change, identifying large accumulation events, and monitoring lake bathymetry. Finally, a novel low-cost method of performing timelapse photogrammetry using Raspberry Pi camera sensors is created and compared to 3D models generated by a UAV. Mean difference between the Raspberry Pi and UAV sensors is 0.31 ± 0.74 m, giving promise to the use of these sensors for long-term monitoring of recession and short-term warning of hazards at glacier calving fronts. Together, this ‘new generation’ of remote sensing looks to provide new glaciological insights and opportunities for regular monitoring of data-scarce mountainous regions. The techniques discussed in this thesis could benefit communities and societal programmes in rapidly deglaciating environments, including across the Cordillera Vilcanota

Investigation of Coastal Vegetation Dynamics and Persistence in Response to Hydrologic and Climatic Events Using Remote Sensing

Coastal Wetlands (CW) provide numerous imperative functions and provide an economic base for human societies. Therefore, it is imperative to track and quantify both short and long-term changes in these systems. In this dissertation, CW dynamics related to hydro-meteorological signals were investigated using a series of LANDSAT-derived normalized difference vegetation index (NDVI) data and hydro-meteorological time-series data in Apalachicola Bay, Florida, from 1984 to 2015. NDVI in forested wetlands exhibited more persistence compared to that for scrub and emergent wetlands. NDVI fluctuations generally lagged temperature by approximately three months, and water level by approximately two months. This analysis provided insight into long-term CW dynamics in the Northern Gulf of Mexico. Long-term studies like this are dependent on optical remote sensing data such as Landsat which is frequently partially obscured due to clouds and this can that makes the time-series sparse and unusable during meteorologically active seasons. Therefore, a multi-sensor, virtual constellation method is proposed and demonstrated to recover the information lost due to cloud cover. This method, named Tri-Sensor Fusion (TSF), produces a simulated constellation for NDVI by integrating data from three compatible satellite sensors. The visible and near-infrared (VNIR) bands of Landsat-8 (L8), Sentinel-2, and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were utilized to map NDVI and to compensate each satellite sensor\u27s shortcomings in visible coverage area. The quantitative comparison results showed a Root Mean Squared Error (RMSE) and Coefficient of Determination (R2) of 0.0020 sr-1 and 0.88, respectively between true observed and fused L8 NDVI. Statistical test results and qualitative performance evaluation suggest that TSF was able to synthesize the missing pixels accurately in terms of the absolute magnitude of NDVI. The fusion improved the spatial coverage of CWs reasonably well and ultimately increases the continuity of NDVI data for long term studies

Review article: The use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

The number of scientific studies that consider possible applications of remotely piloted aircraft systems (RPASs) for the management of natural hazards effects and the identification of occurred damages strongly increased in the last decade. Nowadays, in the scientific community, the use of these systems is not a novelty, but a deeper analysis of the literature shows a lack of codified complex methodologies that can be used not only for scientific experiments but also for normal codified emergency operations. RPASs can acquire on-demand ultra-high-resolution images that can be used for the identification of active processes such as landslides or volcanic activities but can also define the effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologies developed for the study and monitoring of natural hazard

Gazing at the Solar System: Capturing the Evolution of Dunes, Faults, Volcanoes, and Ice from Space

Gazing imaging holds promise for improved understanding of surface characteristics and processes of Earth and solar system bodies. Evolution of earthquake fault zones, migration of sand dunes, and retreat of ice masses can be understood by observing changing features over time. To gaze or stare means to look steadily, intently, and with fixed attention, offering the ability to probe the characteristics of a target deeply, allowing retrieval of 3D structure and changes on fine and coarse scales. Observing surface reflectance and 3D structure from multiple perspectives allows for a more complete view of a surface than conventional remote imaging. A gaze from low Earth orbit (LEO) could last several minutes allowing for video capture of dynamic processes. Repeat passes enable monitoring time scales of days to years. Numerous vantage points are available during a gaze (Figure 1). Features in the scene are projected into each image frame enabling the recovery of dense 3D structure. The recovery is robust to errors in the spacecraft position and attitude knowledge, because features are from different perspectives. The combination of a varying look angle and the solar illumination allows recovering texture and reflectance properties and permits the separation of atmospheric effects. Applications are numerous and diverse, including, for example, glacier and ice sheet flux, sand dune migration, geohazards from earthquakes, volcanoes, landslides, rivers and floods, animal migrations, ecosystem changes, geysers on Enceladus, or ice structure on Europa. The Keck Institute for Space Studies (KISS) hosted a workshop in June of 2014 to explore opportunities and challenges of gazing imaging. The goals of the workshop were to develop and discuss the broad scientific questions that can be addressed using spaceborne gazing, specific types of targets and applications, the resolution and spectral bands needed to achieve the science objectives, and possible instrument configurations for future missions. The workshop participants found that gazing imaging offers the ability to measure morphology, composition, and reflectance simultaneously and to measure their variability over time. Gazing imaging can be applied to better understand the consequences of climate change and natural hazards processes, through the study of continuous and episodic processes in both domains