scholarly journals UAV-Derived Himalayan Topography: Hazard Assessments and Comparison with Global DEM Products

Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 18 ◽  
Author(s):  
C. Watson ◽  
Jeffrey Kargel ◽  
Babulal Tiruwa
Keyword(s):  
Mass Movement ◽  
High Mountain ◽  
Lake Area ◽  
Digital Elevation ◽  
2015 Gorkha Earthquake ◽  
Order Of Magnitude ◽  
Hazard Assessments ◽  
Elevation Model ◽  
Terrain Elevation ◽  
Fine Resolution

Topography derived using human-portable unmanned aerial vehicles (UAVs) and structure from motion photogrammetry offers an order of magnitude improvement in spatial resolution and uncertainty over small survey extents, compared to global digital elevation model (DEM) products, which are often the only available choice of DEMs in the high-mountain Himalaya. Access to fine-resolution topography in the high mountain Himalaya is essential to assess where flood and landslide events present a risk to populations and infrastructure. In this study, we compare the topography of UAV-derived DEMs, three open-access global DEM products, and the 8 m High Mountain Asia (HMA) DEMs (released in December 2017) and assess their suitability for landslide- and flood-related hazard assessments. We observed close similarity between UAV and HMA DEMs when comparing terrain elevation, river channel delineation, landside volume, and landslide-dammed lake area and volume. We demonstrate the use of fine-resolution topography in a flood-modelling scenario relating to landslide-dammed lakes that formed on the Marsyangdi River following the 2015 Gorkha earthquake. We outline a workflow for using UAVs in hazard assessments and disaster situations to generate fine-resolution topography and facilitate real-time decision-making capabilities, such as assessing landslide-dammed lakes, mass movement volumes, and flood risk.

scholarly journals Avalanche situation in Turkey and back calculation of selected events

2014 ◽  
Vol 14 (5) ◽  
pp. 1145-1154 ◽  
Author(s):  
A. Aydin ◽  
Y. Bühler ◽  
M. Christen ◽  
I. Gürer
Keyword(s):  
Simulation Software ◽  
High Mountain ◽  
Identification Algorithm ◽  
Black Sea Region ◽  
Mountain Ranges ◽  
Digital Elevation ◽  
Back Calculation ◽  
Elevation Model ◽  
Very High ◽  
Rapid Mass

Abstract. In Turkey, an average of 24 people die in snow avalanches every year, mainly in the eastern part of Anatolia and in the eastern Black Sea region, where high-mountain ranges are close to the sea. The proportion of people killed in buildings is very high (87%), especially in comparison to other European countries and North America. In this paper we discuss avalanche occurrence, the climatic situation and historical avalanche events in Turkey; in addition, we identify bottlenecks and suggest solutions to tackle avalanche problems. Furthermore, we have applied the numerical avalanche simulation software RAMMS (rapid mass movements simulation) combined with a (digital elevation model) DEM-based potential release zone identification algorithm to analyze the catastrophic avalanche events in the villages of Üzengili (Bayburt province) in 1993 and Yaylaönü (Trabzon province) in 1981. The results demonstrate the value of such an approach for regions with poor avalanche databases, enabling the calculation of different scenarios and the estimation of run-out distances, impact pressure and flow height.

scholarly journals Morpho–Sedimentary Monitoring in a Coastal Area, from 1D to 2.5D, Using Airborne Drone Imagery

Drones ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 62 ◽  
Author(s):  
Antoine Mury ◽  
Antoine Collin ◽  
Dorothée James
Keyword(s):  
Coastal Areas ◽  
Global Changes ◽  
Sea Levels ◽  
Digital Elevation ◽  
Reduced Costs ◽  
Rising Sea Levels ◽  
Elevation Model ◽  
Fine Resolution ◽  
State Of The Science ◽  
Very High

Coastal areas are among the most endangered places in the world, due to their exposure to both marine and terrestrial hazards. Coastal areas host more than two-thirds of the world’s population, and will become increasingly affected by global changes, in particular, rising sea levels. Monitoring and protecting the coastlines have impelled scientists to develop adequate tools and methods to spatially monitor morpho-sedimentary coastal areas. This paper presents the capabilities of the aerial drone, as an “all-in-one” technology, to drive accurate morpho-sedimentary investigations in 1D, 2D and 2.5D at very high resolution. Our results show that drone-related fine-resolution, high accuracies and point density outperform the state-of-the-science manned airborne passive and active methods for shoreline position tracking, digital elevation model as well as point cloud creation. We further discuss the reduced costs per acquisition campaign, the increased spatial and temporal resolution, and demonstrate the potentialities to carry out diachronic and volumetric analyses, bringing new perspectives for coastal scientists and managers.

scholarly journals Flood depth estimation by means of high-resolution SAR images and LiDAR data

2018 ◽  
Author(s):  
Fabio Cian ◽  
Mattia Marconcini ◽  
Pietro Ceccato ◽  
Carlo Giupponi
Keyword(s):  
High Resolution ◽  
Urban Areas ◽  
Depth Estimation ◽  
Flood Depth ◽  
Inundation Depth ◽  
Detection Approach ◽  
Digital Elevation ◽  
Radar Imagery ◽  
Elevation Model ◽  
Terrain Elevation

Abstract. When floods hit inhabited areas, great losses are usually registered both in terms of impacts on people (i.e., fatalities and injuries) as well as economic impacts on urban areas, commercial and productive sites, infrastructures and agriculture. To properly assess these, several parameters are needed among which flood depth is one of the most important as it governs the models used to compute damages in economic terms. This paper presents a simple yet effective semi-automatic approach for deriving very precise inundation depth. First, precise flood extent is derived employing a change detection approach based on the Normalized Difference Flood Index computed from high resolution Synthetic Aperture Radar imagery. Second, by means of a high-resolution Light Detection And Ranging Digital Elevation Model, water surface elevation is estimated through a statistical analysis of terrain elevation along the boundary lines of the identified flooded areas. Experimental results and quality assessment are given for the flood occurred in the Veneto region, North-Eastern Italy, in 2010. In particular, the method proved fast and robust and, compared to hydrodynamic models, it requires sensibly less input information.

scholarly journals A Semiautomatic Pixel-Object Method for Detecting Landslides Using Multitemporal ALOS-2 Intensity Images

2020 ◽  
Vol 12 (3) ◽  
pp. 561 ◽  
Author(s):  
Bruno Adriano ◽  
Naoto Yokoya ◽  
Hiroyuki Miura ◽  
Masashi Matsuoka ◽  
Shunichi Koshimura
Keyword(s):  
Disaster Response ◽  
Large Scale ◽  
Reference Data ◽  
Mass Movement ◽  
Recovery Planning ◽  
Additional Information ◽  
Digital Elevation ◽  
Before And After ◽  
Intensity Images ◽  
Elevation Model

The rapid and accurate mapping of large-scale landslides and other mass movement disasters is crucial for prompt disaster response efforts and immediate recovery planning. As such, remote sensing information, especially from synthetic aperture radar (SAR) sensors, has significant advantages over cloud-covered optical imagery and conventional field survey campaigns. In this work, we introduced an integrated pixel-object image analysis framework for landslide recognition using SAR data. The robustness of our proposed methodology was demonstrated by mapping two different source-induced landslide events, namely, the debris flows following the torrential rainfall that fell over Hiroshima, Japan, in early July 2018 and the coseismic landslide that followed the 2018 Mw6.7 Hokkaido earthquake. For both events, only a pair of SAR images acquired before and after each disaster by the Advanced Land Observing Satellite-2 (ALOS-2) was used. Additional information, such as digital elevation model (DEM) and land cover information, was employed only to constrain the damage detected in the affected areas. We verified the accuracy of our method by comparing it with the available reference data. The detection results showed an acceptable correlation with the reference data in terms of the locations of damage. Numerical evaluations indicated that our methodology could detect landslides with an accuracy exceeding 80%. In addition, the kappa coefficients for the Hiroshima and Hokkaido events were 0.30 and 0.47, respectively.

scholarly journals Distinguishing Glaciers between Surging and Advancing by Remote Sensing: A Case Study in the Eastern Karakoram

2020 ◽  
Vol 12 (14) ◽  
pp. 2297 ◽  
Author(s):  
Mingyang Lv ◽  
Huadong Guo ◽  
Jin Yan ◽  
Kunpeng Wu ◽  
Guang Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Google Earth ◽  
High Mountain ◽  
Glacier Mass Balance ◽  
Visual Interpretation ◽  
Stable Mode ◽  
Optical Images ◽  
Digital Elevation ◽  
Glacier Surges ◽  
Elevation Model

The Karakoram has had an overall slight positive glacier mass balance since the end of 20th century, which is anomalous given that most other regions in High Mountain Asia have had negative changes. A large number of advancing, retreating, and surging glaciers are heterogeneously mixed in the Karakoram increasing the difficulties and inaccuracies to identify glacier surges. We found two adjacent glaciers in the eastern Karakoram behaving differently from 1995 to 2019: one was surging and the other was advancing. In order to figure out the differences existing between them and the potential controls on surges in this region, we collected satellite images from Landsat series, ASTER, and Google Earth, along with two sets of digital elevation model. Utilizing visual interpretation, feature tracking of optical images, and differencing between digital elevation models, three major differences were observed: (1) the evolution profiles of the terminus positions occupied different change patterns; (2) the surging glacier experienced a dramatic fluctuation in the surface velocities during and after the event, while the advancing glacier flowed in a stable mode; and (3) surface elevation of the surging glacier decreased in the reservoir and increased in the receiving zone. However, the advancing glacier only had an obvious elevation increase over its terminus part. These differences can be regarded as standards for surge identification in mountain ranges. After combining the differences with regional meteorological conditions, we suggested that changes of thermal and hydrological conditions could play a role in the surge occurrence, in addition, geomorphological characteristics and increasing warming climate might also be part of it. This research strongly contributes to the literatures of glacial motion and glacier mass change in the eastern Karakoram through remote sensing.

scholarly journals Numerical Modelling Based on Digital Elevation Model (DEM) Analysis of Debris Flow at Rinjani Volcano, West Nusa Tenggara, Indonesia

2021 ◽  
Vol 7 (3) ◽  
pp. 279
Author(s):  
Muhammad Fatih Qodri ◽  
Noviardi Noviardi ◽  
Al Hussein Flowers Rizqi ◽  
Lindung Zalbuin Mase
Keyword(s):  
Debris Flow ◽  
Digital Elevation Model ◽  
High Speed ◽  
Human Life ◽  
Mass Movement ◽  
High Viscosity ◽  
Particle Flows ◽  
Digital Elevation ◽  
Dem Analysis ◽  
Elevation Model

Debris flow is a disaster occurring in cases where a sediment particle flows at high speed, down to the slope, and usually with high viscosity and speed. This disaster is very destructive and human life-threatening, especially in mountainous areas. As one of the world’s active volcanoes in the world, Rinjani had the capacity to produce over 3 million m3 volume material in the 2015 eruption alone. Therefore, this study proposes a numerical model analysis to predict the debris flow release area (erosion) and deposition, as well as the discharge, flow height, and velocity. The Digital Elevation Model (DEM) was analyzed in ArcGIS, to acquire the Cartesian coordinates and “hillshade” form. This was also used as a method to produce vulnerable areas in the Jangkok watershed. Meanwhile, the Rapid Mass Movement Simulation (RAMSS) numerical modeling was simulated using certain parameters including volume, friction, and density, derived from the DEM analysis results and assumptions from similar historical events considered as the best-fit rheology. In this study, the release volume was varied at 1,000,000 m3, 2,000,000 m3, and 3,000,000 m3, while the simulation results show movement, erosion, and debris flow deposition in Jangkok watershed. This study is bound to be very useful in mitigating debris flow as disaster anticipation and is also expected to increase community awareness, as well as provide a reference for structural requirements, as a debris flow prevention.

scholarly journals Lake Onego development in the late glacial assessed with the use of GIS technologies

2019 ◽  
pp. 83-90 ◽  
Author(s):  
D. A. Subetto ◽  
M. S. Potakhin ◽  
M. B. Zobkov ◽  
A. Yu. Tarasov ◽  
T. S. Shelekhova ◽  
...  
Keyword(s):  
Drainage Basin ◽  
Sediment Cores ◽  
Late Glacial ◽  
Lake Basin ◽  
Lake Area ◽  
Digital Maps ◽  
Digital Elevation ◽  
Spatial Parameters ◽  
Elevation Model ◽  
Maximum Development

The GIS-based reconstructions of Lake Onego development in the Late Glacial (14500–12300 yrs ago) were performed. Reconstructions have been based on the deglaciation model of the Lake Onego depression, digital elevation model of the lake depression, SRTM model of its drainage basin and on the data obtained from the palaeolimnological studies of numerous lake sediment cores. This allowed us to distinguish six main stages of the lake development for which a series of detailed schemes were produced. 1. Formation of the ice-dammed lake as a result of the ice sheet retreating (14.5 cal ka BP). 2. Emerging of the southern and central parts of the lake basin from the ice cover (14.0 cal ka BP). 3. The maximum development of the proglacial lake (13.3 cal ka BP). The lake area in this period was around 33 000 km2. 4. The first regression (13.2 ka BP). 5. The second regression (12.4 ka BP). 6. The third regression (12.3 ka BP), when the area of the lake dropped to 18 000 km2. We created detailed digital maps of the main stages of Lake Onego development during the Late Glacial and calculated the spatial parameters of the lake. The quantitative data obtained in this study would be used in estimation of the volumes of the lake and outflow discharges in the past. Maps are available in electronic form.

scholarly journals A GIS-Based Water Balance Approach Using a LiDAR-Derived DEM Captures Fine-Scale Vegetation Patterns

2019 ◽  
Vol 11 (20) ◽  
pp. 2385 ◽  
Author(s):  
James M. Dyer
Keyword(s):  
Water Balance ◽  
Vegetation Patterns ◽  
Fine Scale ◽  
Individual Tree ◽  
Annual Variations ◽  
Digital Elevation ◽  
Climatic Water Deficit ◽  
Elevation Model ◽  
Fine Resolution ◽  
Strong Control

Topography exerts strong control on microclimate, resulting in distinctive vegetation patterns in areas of moderate to high relief. Using the Thornthwaite approach to account for hydrologic cycle components, a GIS-based Water Balance Toolset is presented as a means to address fine-scale species–site relationships. For each pixel within a study area, the toolset assesses inter-annual variations in moisture demand (governed by temperature and radiation) and availability (precipitation, soil storage). These in turn enable computation of climatic water deficit, the amount by which available moisture fails to meet demand. Summer deficit computed by the model correlates highly with the Standardized Precipitation–Evapotranspiration Index (SPEI) for drought at several sites across the eastern U.S. Yet the strength of the approach is its ability to model fine-scale patterns. For a 25-ha study site in central Indiana, individual tree locations were linked to summer deficit under different historical conditions: using average monthly climatic variables for 1998–2017, and for the drought year of 2012. In addition, future baseline and drought-year projections were modeled based on downscaled GCM data for 2071–2100. Although small deficits are observed under average conditions (historical or future), strong patterns linked to topography emerge during drought years. The modeled moisture patterns capture vegetation distributions described for the region, with beech and maple preferentially occurring in low-deficit settings, and oak and hickory dominating more xeric positions. End-of-century projections suggest severe deficit, which should favor oak and hickory over more mesic species. Pockets of smaller deficit persist on the landscape, but only when a fine-resolution Light Detection and Ranging (LiDAR)-derived Digital Elevation Model (DEM) is used; a coarse-resolution DEM masks fine-scale variability and compresses the range of observed values. Identification of mesic habitat microrefugia has important implications for retreating species under altered climate. Using readily available data to evaluate fine-scale patterns of moisture demand and availability, the Water Balance Toolset provides a useful approach to explore species–environment linkages.

scholarly journals Geomorphological and Climatic Drivers of Thermokarst Lake Area Increase Trend (1999–2018) in the Kolyma Lowland Yedoma Region, North-Eastern Siberia

2021 ◽  
Vol 13 (2) ◽  
pp. 178
Author(s):  
Alexandra Veremeeva ◽  
Ingmar Nitze ◽  
Frank Günther ◽  
Guido Grosse ◽  
Elizaveta Rivkina
Keyword(s):  
Landsat Imagery ◽  
Lake Basin ◽  
Lake Area ◽  
The Holocene ◽  
Thermokarst Lake ◽  
Digital Elevation ◽  
Area Increase ◽  
High Precipitation ◽  
Elevation Model ◽  
Map Data

Thermokarst lakes are widespread in Arctic lowlands. Under a warming climate, landscapes with highly ice-rich Yedoma Ice Complex (IC) deposits are particularly vulnerable, and thermokarst lake area dynamics serve as an indicator for their response to climate change. We conducted lake change trend analysis for a 44,500 km2 region of the Kolyma Lowland using Landsat imagery in conjunction with TanDEM-X digital elevation model and Quaternary Geology map data. We delineated yedoma–alas relief types with different yedoma fractions, serving as a base for geospatial analysis of lake area dynamics. We quantified lake changes over the 1999–2018 period using machine-learning-based classification of robust trends of multi-spectral indices of Landsat data and object-based long-term lake detection. We analyzed the lake area dynamics separately for 1999–2013 and 1999–2018 periods, including the most recent five years that were characterized by very high precipitation. Comparison of drained lake basin area with thermokarst lake extents reveal the overall limnicity decrease by 80% during the Holocene. Current climate warming and wetting in the region led to a lake area increase by 0.89% for the 1999–2013 period and an increase by 4.15% for the 1999–2018 period. We analyzed geomorphological factors impacting modern lake area changes for both periods such as lake size, elevation, and yedoma–alas relief type. We detected a lake area expansion trend in high yedoma fraction areas indicating ongoing Yedoma IC degradation by lake thermokarst. Our concept of differentiating yedoma–alas relief types helps to characterize landscape-scale lake area changes and could potentially be applied for refined assessments of greenhouse gas emissions in Yedoma regions. Comprehensive geomorphological inventories of Yedoma regions using geospatial data provide a better understanding of the extent of thermokarst processes during the Holocene and the pre-conditioning of modern thermokarst lake area dynamics.

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