DISTRIBUTION AND EVOLUTION OF ICE APRONS IN A CHANGING CLIMATE IN THE MONT-BLANC MASSIF (WESTERN EUROPEAN ALPS)

Abstract. Ice Apron (IA) is a poorly studied ice feature, commonly existing in all the world’s major mountain regions. This study aims to map the locations of the IAs in the Mont Blanc massif (MBM), making use of the very high-resolution optical satellite images from 2001, 2012 and 2019. 423 IAs were identified and accurately delineated in the MBM on the images from 2019, and their topographic characteristics were studied. We generated our own Digital Elevation Model (DEM) at 4 m resolution since the freely available products predominantly suffer from significant inconsistencies, especially in steep mountain areas. Results show that most IAs exist at elevations above the regional Equilibrium Line Altitude (ELA), on steep slopes, on concave surfaces, on northern and southern aspects and on the most rugged terrains. They are also commonly associated with steep slope glaciers as 85% of them occur on these glaciers’ headwalls. A comparison between 2001 and 2019 shows that IAs have lost around 29% of their area over a period of 18 years. This is significant and the rate of area loss is very alarming in comparison with the larger glacier bodies. We also studied the effect of topographic parameters on the area loss. We found that topographic factors like slope, aspect, curvature, elevation and Terrain Ruggedness Index (TRI) strongly influence the rate of area loss of IAs.

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A new glacier inventory for the European Alps from Landsat TM scenes of 2003: challenges and results

Annals of Glaciology ◽

10.3189/172756411799096295 ◽

2011 ◽

Vol 52 (59) ◽

pp. 144-152 ◽

Cited By ~ 77

Author(s):

F. Paul ◽

H. Frey ◽

R. Le Bris

Keyword(s):

Shuttle Radar Topography Mission ◽

European Alps ◽

Glacier Inventory ◽

Area Loss ◽

Class Frequency ◽

Digital Elevation ◽

Glacier Changes ◽

Hydropower Production ◽

Current Area ◽

Elevation Model

AbstractMeltwater from glaciers in the European Alps plays an important role in hydropower production, and future glacier development is thus of economic interest. However, an up-to-date and alpine-wide inventory for accurate assessment of glacier changes or modelling of future glacier development has not hitherto been available. Here we present a new alpine-wide inventory (covering Austria, France, Italy and Switzerland) derived from ten Landsat Thematic Mapper (TM) scenes acquired within 7 weeks in 2003. Combined with the globally available digital elevation model from the Shuttle Radar Topography Mission, topographic inventory parameters were derived for each of the 3770 mapped glaciers, covering 2050 km2. The area-class frequency distribution is very similar in all countries, and a mean northerly aspect (NW, N, NE) is clearly favoured (arithmetic counting). Mean glacier elevation is ~2900 m, with a small dependence on aspect. The total area loss since the previous glacier inventory (acquired around 1970±15 years) is roughly one-third, yielding a current area loss rate of ~2%a–1. Digital overlay of the outlines from the latest Austrian glacier inventory revealed differences in the interpretation of glacier extents that prohibit change assessment. A comparison of TM-derived outlines with manually digitized extents on a high-resolution IKONOS image returned 1.5% smaller glaciers with TM.

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A New Approach to the Quality Control of Slope and Aspect Classes Derived from Digital Elevation Models

Remote Sensing ◽

10.3390/rs13112069 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2069

Author(s):

M. V. Alba-Fernández ◽

F. J. Ariza-López ◽

M. D. Jiménez-Gamero

Keyword(s):

Quality Control ◽

Hypothesis Test ◽

Simulated Data ◽

Slope Aspect ◽

New Approach ◽

Reference Set ◽

Digital Elevation ◽

Using Data ◽

Elevation Model ◽

Degree Of Similarity

The usefulness of the parameters (e.g., slope, aspect) derived from a Digital Elevation Model (DEM) is limited by its accuracy. In this paper, a thematic-like quality control (class-based) of aspect and slope classes is proposed. A product can be compared against a reference dataset, which provides the quality requirements to be achieved, by comparing the product proportions of each class with those of the reference set. If a distance between the product proportions and the reference proportions is smaller than a small enough positive tolerance, which is fixed by the user, it will be considered that the degree of similarity between the product and the reference set is acceptable, and hence that its quality meets the requirements. A formal statistical procedure, based on a hypothesis test, is developed and its performance is analyzed using simulated data. It uses the Hellinger distance between the proportions. The application to the slope and aspect is illustrated using data derived from a 2×2 m DEM (reference) and 5×5 m DEM in Allo (province of Navarra, Spain).

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Fusion Analysis of Optical Satellite Images and Digital Elevation Model for Quantifying Volume in Debris Flow Disaster

Remote Sensing ◽

10.3390/rs11091096 ◽

2019 ◽

Vol 11 (9) ◽

pp. 1096 ◽

Cited By ~ 2

Author(s):

Hiroyuki Miura

Keyword(s):

Debris Flow ◽

Digital Elevation Model ◽

Large Scale ◽

Satellite Images ◽

Erosion Depth ◽

Digital Elevation ◽

Elevation Model ◽

Fusion Analysis ◽

Optical Satellite Images ◽

Debris Flow Disaster

Rapid identification of affected areas and volumes in a large-scale debris flow disaster is important for early-stage recovery and debris management planning. This study introduces a methodology for fusion analysis of optical satellite images and digital elevation model (DEM) for simplified quantification of volumes in a debris flow event. The LiDAR data, the pre- and post-event Sentinel-2 images and the pre-event DEM in Hiroshima, Japan affected by the debris flow disaster on July 2018 are analyzed in this study. Erosion depth by the debris flows is empirically modeled from the pre- and post-event LiDAR-derived DEMs. Erosion areas are detected from the change detection of the satellite images and the DEM-based debris flow propagation analysis by providing predefined sources. The volumes and their pattern are estimated from the detected erosion areas by multiplying the empirical erosion depth. The result of the volume estimations show good agreement with the LiDAR-derived volumes.

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Mapping Post-Earthquake Landslide Susceptibility: A U-Net Like Approach

Remote Sensing ◽

10.3390/rs12172767 ◽

2020 ◽

Vol 12 (17) ◽

pp. 2767

Author(s):

Yu Chen ◽

Yongming Wei ◽

Qinjun Wang ◽

Fang Chen ◽

Chunyan Lu ◽

...

Keyword(s):

Landslide Susceptibility ◽

Environmental Influence ◽

Landslide Susceptibility Mapping ◽

Slope Aspect ◽

Support Vector ◽

Gis Technology ◽

2008 Wenchuan Earthquake ◽

Structure Information ◽

Digital Elevation ◽

Elevation Model

A serious earthquake could trigger thousands of landslides and produce some slopes more sensitive to slide in future. Landslides could threaten human’s lives and properties, and thus mapping the post-earthquake landslide susceptibility is very valuable for a rapid response to landslide disasters in terms of relief resource allocation and posterior earthquake reconstruction. Previous researchers have proposed many methods to map landslide susceptibility but seldom considered the spatial structure information of the factors that influence a slide. In this study, we first developed a U-net like model suitable for mapping post-earthquake landslide susceptibility. The post-earthquake high spatial airborne images were used for producing a landslide inventory. Pre-earthquake Landsat TM (Thematic Mapper) images and the influencing factors such as digital elevation model (DEM), slope, aspect, multi-scale topographic position index (mTPI), lithology, fault, road network, streams network, and macroseismic intensity (MI) were prepared as the input layers of the model. Application of the model to the heavy-hit area of the destructive 2008 Wenchuan earthquake resulted in a high validation accuracy (precision 0.77, recall 0.90, F1 score 0.83, and AUC 0.90). The performance of this U-net like model was also compared with those of traditional logistic regression (LR) and support vector machine (SVM) models on both the model area and independent testing area with the former being stronger than the two traditional models. The U-net like model introduced in this paper provides us the inspiration that balancing the environmental influence of a pixel itself and its surrounding pixels to perform a better landslide susceptibility mapping (LSM) task is useful and feasible when using remote sensing and GIS technology.

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Landsat TM and ETM+ derived snowline altitudes in the Cordillera Huayhuash and Cordillera Raura, Peru, 1986–2005

The Cryosphere ◽

10.5194/tc-5-419-2011 ◽

2011 ◽

Vol 5 (2) ◽

pp. 419-430 ◽

Cited By ~ 26

Author(s):

E. M. McFadden ◽

J. Ramage ◽

D. T. Rodbell

Keyword(s):

Thermal Emission ◽

Thematic Mapper ◽

Equilibrium Line Altitude ◽

Local Climate ◽

Clear Sky ◽

The Andes ◽

Time Period ◽

Digital Elevation ◽

Local Climate Change ◽

Elevation Model

Abstract. The Cordilleras Huayhuash and Raura are remote glacierized ranges in the Andes Mountains of Peru. A robust assessment of modern glacier change is important for understanding how regional change affects Andean communities, and for placing paleo-glaciers in a context relative to modern glaciation and climate. Snowline altitudes (SLAs) derived from satellite imagery are used as a proxy for modern (1986–2005) local climate change in a key transition zone in the Andes. Clear sky, dry season Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) satellite images from 1986–2005 were used to identify snowline positions, and their altitude ranges were extracted from an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model (DEM). Based on satellite records from 31 glaciers, average snowline altitudes (SLAs), an approximation for the equilibrium line altitude (ELA), for the Cordillera Huayhuash (13 glaciers) and Cordillera Raura (18 glaciers) from 1986–2005 were 5051 m a.s.l. from 1986–2005 and 5006 m a.s.l. from 1986–2002, respectively. During the same time period, the Cordillera Huayhuash SLA experienced no significant change while the Cordillera Raura SLA rose significantly from 4947 m a.s.l. to 5044 m a.s.l.

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ICESAT VALIDATION OF TANDEM-X I-DEMS OVER THE UK

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b4-129-2016 ◽

2016 ◽

Vol XLI-B4 ◽

pp. 129-136 ◽

Cited By ~ 2

Author(s):

L. Feng ◽

J.-P. Muller

Keyword(s):

Slope Aspect ◽

Surface Slope ◽

Grid Spacing ◽

Digital Elevation ◽

X Band ◽

Elevation Data ◽

Vertical Accuracy ◽

Elevation Model ◽

The Uk ◽

Interferometric Sar

From the latest TanDEM-X mission (bistatic X-Band interferometric SAR), globally consistent Digital Elevation Model (DEM) will be available from 2017, but their accuracy has not yet been fully characterised. This paper presents the methods and implementation of statistical procedures for the validation of the vertical accuracy of TanDEM-X iDEMs at grid-spacing of approximately 12.5 m, 30 m and 90 m based on processed ICESat data over the UK in order to assess their potential extrapolation across the globe. The accuracy of the TanDEM-X iDEM in UK was obtained as follows: against ICESat GLA14 elevation data, TanDEM-X iDEM has −0.028±3.654 m over England and Wales and 0.316 ± 5.286 m over Scotland for 12 m, −0.073 ± 6.575 m for 30 m, and 0.0225 ± 9.251 m at 90 m. Moreover, 90 % of all results at the three resolutions of TanDEM-X iDEM data (with a linear error at 90 % confidence level) are below 16.2 m. These validation results also indicate that derivative topographic parameters (slope, aspect and relief) have a strong effect on the vertical accuracy of the TanDEM-X iDEMs. In high-relief and large slope terrain, large errors and data voids are frequent, and their location is strongly influenced by topography, whilst in the low- to medium-relief and low slope sites, errors are smaller. ICESat derived elevations are heavily influenced by surface slope within the 70 m footprint as well as there being slope dependent errors in the TanDEM-X iDEMs.

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Monitoring Errors of Semi-Mechanized Coffee Planting by Remotely Piloted Aircraft

Agronomy ◽

10.3390/agronomy11061224 ◽

2021 ◽

Vol 11 (6) ◽

pp. 1224

Author(s):

Lucas Santos Santana ◽

Gabriel Araújo e Silva Ferraz ◽

João Paulo Barreto Cunha ◽

Mozarte Santos Santana ◽

Rafael de Oliveira Faria ◽

...

Keyword(s):

Process Control ◽

Statistical Process Control ◽

Aerial Images ◽

Statistical Process ◽

Digital Elevation ◽

Dependent Variables ◽

Remotely Piloted Aircraft ◽

Elevation Model ◽

Steep Slopes

Mechanized operations on terrain slopes can still lead to considerable errors in the alignment and distribution of plants. Knowing slope interference in semi-mechanized planting quality can contribute to precision improvement in decision making, mainly in regions with high slope. This study evaluates the quality of semi-mechanized coffee planting in different land slopes using a remotely piloted aircraft (RPA) and statistical process control (SPC). In a commercial coffee plantation, aerial images were collected by a remotely piloted aircraft (RPA) and subsequently transformed into a digital elevation model (DEM) and a slope map. Slope data were subjected to variance analysis and statistical process control (SPC). Dependent variables analyzed were variations in distance between planting lines and between plants in line. The distribution of plants on all the slopes evaluated was below expected; the most impacted was the slope between 20–25%, implementing 7.8% fewer plants than projected. Inferences about the spacing between plants in the planting row showed that in slopes between 30–40%, the spacing was 0.53 m and between 0 and 15% was 0.55 m. This denotes the compensation of the speed of the operation on different slopes. The spacing between the planting lines had unusual variations on steep slopes. The SCP quality graphics are of lower quality in operations between 30–40%, as they have an average spacing of 3.65 m and discrepant points in the graphics. Spacing variations were observed in all slopes as shown in the SCP charts, and possible causes and implications for future management were discussed, contributing to improvements in the culture installation stage.

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Assessing ice-cliff backwasting and its contribution to total ablation of debris-covered Miage glacier, Mont Blanc massif, Italy

Journal of Glaciology ◽

10.3189/2014jog13j045 ◽

2014 ◽

Vol 60 (219) ◽

pp. 3-13 ◽

Cited By ~ 67

Author(s):

T.D. Reid ◽

B.W. Brock

Keyword(s):

Field Measurements ◽

Distributed Model ◽

Short Term ◽

Model Calculations ◽

Digital Elevation ◽

Debris Cover ◽

Continuous Surface ◽

Elevation Model ◽

Miage Glacier ◽

Mont Blanc Massif

AbstractContinuous surface debris cover strongly reduces the ablation of glaciers, but high melt rates may occur at ice cliffs that are too steep to hold debris. This study assesses the contribution of ice-cliff backwasting to total ablation of Miage glacier, Mont Blanc massif, Italy, in 2010 and 2011, based on field measurements, physical melt models and mapping of ice cliffs using a high-resolution (1 m) digital elevation model (DEM). Short-term model calculations closely match the measured melt rates. A model sensitivity analysis indicates that the effects of cliff slope and albedo are more important for ablation than enhanced longwave incidence from sun-warmed debris or reduced turbulent fluxes at sheltered cliff bases. Analysis of the DEM indicates that ice cliffs account for at most 1.3% of the 1 m pixels in the glacier’s debris-covered zone, but application of a distributed model indicates that ice cliffs account for ~7.4% of total ablation. We conclude that ice cliffs make an important contribution to the ablation of debris-covered glaciers, even when their spatial extent is very small.

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A NEW METHOD TO DETECT REGIONS ENDANGERED BY HIGH WIND SPEEDS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b8-59-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 59-63

Author(s):

P. Fischer ◽

S. Ehrensperger ◽

T. Krauß

Keyword(s):

Shuttle Radar Topography Mission ◽

Boosted Regression Trees ◽

Slope Aspect ◽

Maximum Wind ◽

Wind Speeds ◽

Landform Classification ◽

Area Of Interest ◽

Land Cover Data ◽

Digital Elevation ◽

Elevation Model

In this study we evaluate whether the methodology of Boosted Regression Trees (BRT) suits for accurately predicting maximum wind speeds. As predictors a broad set of parameters derived from a Digital Elevation Model (DEM) acquired within the Shuttle Radar Topography Mission (SRTM) is used. The derived parameters describe the surface by means of quantities (e.g. slope, aspect) and quality (landform classification). Furthermore land cover data from the CORINE dataset is added. The response variable is maximum wind speed, measurements are provided by a network of weather stations. The area of interest is Switzerland, a country which suits perfectly for this study because of its highly dynamic orography and various landforms.

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