scholarly journals Present extent, features and regional distribution of Italian glaciers

2019 ◽  
pp. 159-175 ◽  
Author(s):  
Guglielmina Adele Diolaiuti ◽  
Roberto Sergio Azzoni ◽  
Carlo D'Agata ◽  
Davide Maragno ◽  
Davide Fugazza ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Regional Scale ◽  
Regional Distribution ◽  
Alpine Region ◽  
Glacier Area ◽  
Glacier Inventory ◽  
Mountain Glaciers ◽  
Multi Temporal ◽  
Comprehensive Study

Remote sensing investigations permit to map and describe at a regional scale and with a multi-temporal approach mountain glaciers. In this work, we present some results from the New Italian Glacier Inventory which we developed by analyzing high-resolution color orthophotos acquired in the timeframe 2005–2011. In particular, in this paper we focused on each Italian Alpine Region, describing in detail glacier extent and features of each mountain group. Although Italian glaciologists were the first to produce glacier inventories (developing a glacier database as early as the beginning of the 20th century), during the last three decades only regional and local glacier lists have been developed. Therefore, a comprehensive study describing the actual whole Italian glaciation has been lacking. The New Italian Glacier Inventory describes 903 glaciers covering altogether an area of 368.10 km2 ± 2%. We found that about 84% of the total number of ice bodies is composed of glaciers smaller than 0.5 km2 covering only 21% of the total area, indicating that the Italian glacier resource is spread into several small ice bodies with only few larger glaciers. A comparison between the total glacier area of the new inventory and the glacier coverage value from the CGI Inventory (1959–1962) suggests a reduction of the glacier extent of about 30%.

scholarly journals A new glacier inventory of Iran

2009 ◽  
Vol 50 (53) ◽  
pp. 93-103 ◽  
Author(s):  
M.S. Moussavi ◽  
M.J. Valadan Zoej ◽  
F. Vaziri ◽  
M.R. Sahebi ◽  
Y. Rezaei
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Maximum Height ◽  
Mountain Range ◽  
Glacier Inventory ◽  
Mountain Glaciers ◽  
Alborz Mountain ◽  
Gis Environment ◽  
Mountain Chain ◽  
Comprehensive Study

AbstractA new glacier inventory of Iran, compiled according to GLIMS guidelines through the use of photogrammetry and remote sensing supported by fieldwork, provides the first comprehensive study of its mountain glaciers. The glaciers are found in five main areas: two in the higher elevations of the Alborz mountain range (Damavand and Takhte–Soleiman regions), two on the Zardkuh and Oshtorankuh mountain chain in the Zagros mountain range and one in the Sabalan Mountains in northwest Iran. Several important glacier attributes, including minimum and maximum height of ice, area and maximum length and width, together with glacier extent, were successfully extracted using aerial and satellite imagery. Thereafter a comprehensive glacier database was established in a GIS environment.

scholarly journals Inventory of Glaciers in the Shaksgam Valley of the Chinese Karakoram Mountains, 1970–2014

2018 ◽  
Vol 10 (8) ◽  
pp. 1166 ◽  
Author(s):  
Haireti Alifu ◽  
Yukiko Hirabayashi ◽  
Brian Johnson ◽  
Jean-Francois Vuillaume ◽  
Akihiko Kondoh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Thematic Mapper ◽  
Western China ◽  
Glacier Area ◽  
Glacier Inventory ◽  
Local Climate ◽  
Glacier Terminus ◽  
Glacier Changes ◽  
Multi Temporal ◽  
Karakoram Mountains

The Shaksgam Valley, located on the north side of the Karakoram Mountains of western China, is situated in the transition zone between the Indian monsoon system and dry arid climate zones. Previous studies have reported abnormal behaviors of the glaciers in this region compared to the global trend of glacier retreat, so the region is of special interest for glacier-climatological studies. For this purpose, long-term monitoring of glaciers in this region is necessary to obtain a better understanding of the relationships between glacier changes and local climate variations. However, accurate historical and up-to-date glacier inventory data for the region are currently unavailable. For this reason, this study conducted glacier inventories for the years 1970, 1980, 1990, 2000 and 2014 (i.e., a ~10-year interval) using multi-temporal remote sensing imagery. The remote sensing data used included Corona KH-4A/B (1965–1971), Hexagon KH-9 (1980), Landsat Thematic Mapper (TM) (1990/1993), Landsat Enhanced Thematic Mapper Plus (ETM+) (2000/2001), and Landsat Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) (2014/2015) multispectral satellite images, as well as digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM), DEMs generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images (2005–2014), and Advanced Land Observing Satellite (ALOS) World 3D 30 m mesh (AW3D30). In the year 2014, a total of 173 glaciers (including 121 debris-free glaciers) (>0.5 km2), covering an area of 1478 ± 34 km2 (area of debris-free glaciers: 295 ± 7 km2) were mapped. The multi-temporal glacier inventory results indicated that total glacier area change between 1970–2014 was not significant. However, individual glacier changes showed significant variability. Comparisons of the changes in glacier terminus position indicated that 55 (32 debris-covered) glaciers experienced significant advances (~40–1400 m) between 1970–2014, and 74 (32 debris-covered) glaciers experienced significant advances (~40–1400 m) during the most recent period (2000–2014). Notably, small glaciers showed higher sensitivity to climate changes, and the glaciers located in the western part of the study site were exhibiting glacier area expansion compared to other parts of the Shaksgam Valley. Finally, regression analyses indicated that topographic parameters were not the main driver of glacier changes. On the contrary, local climate variability could explain the complex behavior of glaciers in this region.

scholarly journals On the potential of very high-resolution repeat DEMs in glacial and periglacial environments

2010 ◽  
Vol 4 (1) ◽  
pp. 53-65 ◽  
Author(s):  
J. Abermann ◽  
A. Fischer ◽  
A. Lambrecht ◽  
T. Geist
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Airborne Lidar ◽  
Primary Data ◽  
Glacier Area ◽  
Airborne Laser ◽  
Multi Temporal ◽  
Rock Glaciers ◽  
Data Source ◽  
Very High

Abstract. The potential of high-resolution repeat DEMs was investigated for glaciological applications including periglacial features (e.g. rock glaciers). It was shown that glacier boundaries can be delineated using airborne LIDAR-DEMs as a primary data source and that information on debris cover extent could be extracted using multi-temporal DEMs. Problems and limitations are discussed, and accuracies quantified. Absolute deviations of airborne laser scanning (ALS) derived glacier boundaries from ground-truthed ones were below 4 m for 80% of the ground-truthed values. Overall, we estimated an accuracy of +/−1.5% of the glacier area for glaciers larger than 1 km2. The errors in the case of smaller glaciers did not exceed +/−5% of the glacier area. The use of repeat DEMs in order to obtain information on the extent, characteristics and activity of rock glaciers was investigated and discussed based on examples.

scholarly journals Compiling a new glacier inventory for southeastern Qinghai–Tibet Plateau from Landsat and PALSAR data

2016 ◽  
Vol 62 (233) ◽  
pp. 579-592 ◽  
Author(s):  
LINGHONG KE ◽  
XIAOLI DING ◽  
LEI ZHANG ◽  
JUN HU ◽  
C. K. SHUM ◽  
...  
Keyword(s):  
Shuttle Radar Topography Mission ◽  
Tibet Plateau ◽  
Landsat 8 ◽  
Glacier Change ◽  
Glacier Area ◽  
Glacier Inventory ◽  
Radar Images ◽  
Water Classification ◽  
Multi Temporal ◽  
Classification Information

ABSTRACTGlacier change has been recognized as an important climate variable due to its sensitive response to climate change. Although there are a large number of glaciers distributed over the southeastern Qinghai–Tibetan Plateau, the region is poorly represented in glacier databases due to seasonal snow cover and frequent cloud cover. Here, we present an improved glacier inventory for this region by combining Landsat observations acquired over 2011–13 (Landsat 8/OLI and Landsat TM/ETM+), coherence images from Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar images and the Shuttle Radar Topography Mission (SRTM) DEM. We present a semi-automated scheme for integrating observations from multi-temporal Landsat scenes to mitigate cloud obscuration. Further, the clean-ice observations, together with coherence information, slope constraints, vegetation cover and water classification information extracted from the Landsat scenes, are integrated to determine the debris-covered glacier area. After manual editing, we derive a new glacier inventory containing 6892 glaciers >0.02 km2, covering a total area of 6566 ± 197 km2. This new glacier inventory indicates gross overestimation in glacier area (over 30%) in previously published glacier inventories, and reveals various spatial characteristics of glaciers in the region. Our inventory can be used as a baseline dataset for future studies including glacier change assessment.

Multi-scale analysis of landslide occurrence and evolution using optical and radar time series

2020 ◽  
Author(s):  
Sigrid Roessner ◽  
Robert Behling ◽  
Mahdi Motagh ◽  
Hans Ulrich-wetzel
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
High Resolution ◽  
Intense Rainfall ◽  
Large Area ◽  
Landslide Occurrence ◽  
Multi Scale ◽  
Multi Temporal ◽  
Hazard And Risk

<p>Landslides represent a worldwide natural hazard and often occur as cascading effects related to triggering events, such as earthquakes and hydrometeorological extremes. Recent examples are the Kaikoura earthquake in New Zealand (November 2016), the Gorkha earthquake in Nepal (April/May 2015), and the Typhoon Morakot in Taiwan (August 2009) as well as less intense rainfall events persisting over unusually long periods of time as observed for Central Asia (spring 2017) and Iran (spring 2019). Each of these events has caused thousands of landslides that account substantially to the primary disaster’s impact. Moreover, their initial failure usually represents the onset of long-term progressing slope destabilization leading to multiple reactivations and thus to long-term increased hazard and risk. Therefore, regular systematic high-resolution monitoring of landslide prone regions is of key importance for characterization, understanding and modelling of spatiotemporal landslide evolution in the context of different triggering and predisposing settings. Because of the large extent of the affected areas of up to several ten thousands km<sup>2</sup>, the use of multi-temporal and multi-scale remote sensing methods is of key importance for large area process analysis. In this context, new opportunities have opened up with the increasing availability of satellite remote sensing data of suitable spatial and temporal resolution (Sentinels, Planet) as well as the advances in UAV based very high resolution monitoring and mapping.</p><p>During the last decade, we have been pursuing extensive methodological developments in remote sensing based time series analysis including optical and radar observations with the goal of performing large area and at the same time detailed spatiotemporal analysis of landslide prone regions. These developments include automated post-failure landslide detection and mapping as well as assessment of the kinematics of pre- and post-failure slope evolution.  Our combined optical and radar remote sensing approaches aim at an improved understanding of spatiotemporal dynamics and complexities related to evolution of landslide prone slopes at different spatial and temporal scales.  In this context, we additionally integrate UAV-based observation for deriving volumetric changes also related to globally available DEM products, such as SRTM and ALOS.  </p><p>We present results for selected settings comprising large area co-seismic landslide occurrence related to the Kaikoura 2016 and the Nepal 2015 earthquakes. For the latter one we also analyzed annual pre- and post-seismic monsoon related landslide activity contributing to a better understanding of the interplay between these main triggering factors. Moreover, we report on ten years of large area systematic landslide monitoring in Southern Kyrgyzstan resulting in a multi-temporal regional landslide inventory of so far unprecedented spatiotemporal detail and completeness forming the basis for further analysis of the obtained landslide concentration patterns. We also present first results of our analysis of landslides triggered by intense rainfall and flood events in spring of 2019 in the North of Iran. We conclude that in all cases, the obtained results are crucial for improved landslide prediction and reduction of future landslide impact. Thus, our methodological developments represent an important contribution towards improved hazard and risk assessment as well as rapid mapping and early warning</p>

scholarly journals Decadal changes from a multi-temporal glacier inventory of Svalbard

2013 ◽  
Vol 7 (5) ◽  
pp. 1603-1621 ◽  
Author(s):  
C. Nuth ◽  
J. Kohler ◽  
M. König ◽  
A. von Deschwanden ◽  
J. O. Hagen ◽  
...  
Keyword(s):  
Dynamic Response ◽  
Response Times ◽  
Glacier Area ◽  
Land Area ◽  
Glacier Inventory ◽  
Tidewater Glaciers ◽  
The Past ◽  
Multi Temporal ◽  
Recent Epoch ◽  
Lateral Area

Abstract. We present a multi-temporal digital inventory of Svalbard glaciers with the most recent from the late 2000s containing 33 775 km2 of glaciers covering 57% of the total land area of the archipelago. At present, 68% of the glacierized area of Svalbard drains through tidewater glaciers that have a total terminus width of ~ 740 km. The glacierized area over the entire archipelago has decreased by an average of 80 km2 a−1 over the past ~ 30 yr, representing a reduction of 7%. For a sample of ~ 400 glaciers (10 000 km2) in the south and west of Spitsbergen, three digital inventories are available from the 1930/60s, 1990 and 2007 from which we calculate average changes during 2 epochs. In the more recent epoch, the terminus retreat was larger than in the earlier epoch, while area shrinkage was smaller. The contrasting pattern may be explained by the decreased lateral wastage of the glacier tongues. Retreat rates for individual glaciers show a mix of accelerating and decelerating trends, reflecting the large spatial variability of glacier types and climatic/dynamic response times in Svalbard. Lastly, retreat rates estimated by dividing glacier area changes by the tongue width are larger than centerline retreat due to a more encompassing frontal change estimate with inclusion of lateral area loss.

scholarly journals Bridge monitoring and deformation time-series analysis by high-resolution Multi-Temporal SAR Interferometry (MT-InSAR) 

2021 ◽  
Author(s):  
Valerio Gagliardi ◽  
Luca Bianchini Ciampoli ◽  
Amir Alani ◽  
Fabio Tosti ◽  
Andrea Benedetto
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
High Resolution ◽  
Health Monitoring ◽  
Interferometric Synthetic Aperture Radar ◽  
Space Agency ◽  
Multi Temporal ◽  
Italian Space Agency ◽  
Remote Sensing Techniques ◽  
Non Destructive

<p>Multi-temporal Interferometric Synthetic Aperture Radar (InSAR) is a space-borne monitoring technique capable of detecting cumulative surface displacements with millimeter accuracy in the Line of Sight (LOS) of the radar sensor [1-3]. Several developments in the processing methods and the increasing availability of SAR datasets from different satellite missions, have proven the viability of this technique in the near-real-time assessment of bridges and the health monitoring of transport infrastructures [2-4].</p><p>This research aims to demonstrate the potential of satellite-based remote sensing techniques as an innovative health-monitoring method for structural assessment of bridges and the prevention of damages by structural subsidence, using high-resolution SAR datasets integrated with complementary Ground-Based (GB) Non-Destructive Testing (NDT) techniques. To this purpose, high-resolution COSMO‐SkyMed (CSK) products provided by the Italian Space Agency (ASI) were acquired and processed.</p><p>In particular, a multi-temporal InSAR analysis was developed to identify and monitor the structural displacements of the Rochester Bridge, located in Rochester, Kent, UK. To this extent, a clustering operation is realised to collect the identified Persistent Scatterers (PSs) over the structural elements of the bridge (i.e., bridge piers and arcs). Furthermore, several sub-clusters with a comparable deformation trend were identified and located over the bridge elements. This operation paves the way for an automatisation of the process through a Machine Learning (ML) clustering algorithms to assign each PS data-point to specific groups, based on the structural element type and the trend of seasonal deformation time-series.</p><p>The outcomes of this study demonstrate how multi-temporal InSAR remote sensing techniques can be synergistically applied to complement non-destructive ground-based analyses, paving the way for future integrated methodologies in the monitoring of infrastructure assets.</p><p><strong>Acknowledgments: </strong>The authors want to acknowledge the Italian Space Agency (ASI) for providing the COSMO-SkyMed Products® (©ASI, 2017-2019),  in the framework of the ASI-Open Call Project “MoTIB, ID 742” accepted by ASI. In addition, the authors would like to acknowledge the Rochester Bridge Trust for facilitating and supporting this research. This research is supported by the Italian Ministry of Education, University and Research under the National Project “EXTRA TN”, PRIN 2017, Prot. 20179BP4SM.</p><p><strong>References</strong></p><p>[1] Alani A. M., Tosti F., Bianchini Ciampoli L., Gagliardi V., Benedetto A., Integration of GPR and InSAR methods for the health monitoring of masonry arch bridges. NDT&E International. (2020)</p><p>[2] Gagliardi V., Bianchini Ciampoli L., D'Amico F., Alani A. M., Tosti F., Battagliere M. L., Benedetto A., Bridge monitoring and assessment by high-resolution satellite remote sensing technologies, Proc. SPIE 11525, SPIE Future Sensing Technologies. 2020. doi: 10.1117/12.2579700</p><p>[3] Selvakumaran, S., Plank, S., Geiß, C., Rossi, C., Middleton, C. (2018). Remote monitoring to predict bridge scour failure using Interferometric Synthetic Aperture Radar (InSAR) stacking techniques, Int. J. .Appl. Earth Obs. and Geoinf. 73, 463-470.</p><p>[4] Qin X, Liao M., Zhang L., & Yang M., Structural Health and Stability Assessment of High-Speed Railways via Thermal Dilation Mapping with Time-Series InSAR Analysis. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing</p>

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