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 Volkanostratigrafi Inderaan Jauh Kompleks Gunungapi Gede dan Sekitarnya, Jawa Barat, Indonesia

2019 ◽  
Vol 20 (1) ◽  
pp. 9
Author(s):  
Fitriani Agustin ◽  
Sutikno Bronto
Keyword(s):  
Remote Sensing ◽  
Geological Mapping ◽  
Lava Flows ◽  
Energy Resources ◽  
Visual Interpretation ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Digital Elevation ◽  
History Of ◽  
Elevation Model

Remote sensing technology greatly helps to identify the various of volcano features, including active, old and ancient volcanoes. The aim of this  paper is intended to introduce various volcanic features in the Gede Volcano Complexs (GVC) and souronding area; compose volcanostratigraphy; and estimate the history of the volcanoes. The method used is a visual interpretation 9 meters spatial resolution of Digital Elevation Model (DEM) TerraSar-x image. Indonesian Stratigraphy Nomenclature Guide 1996 was implemented in vocanostratigraphy unit classification, involving Arc, Super Brigate, Brigate, Crown and Hummockly. Based on the interpretation the DEM image, volcanostratigraphic unit the Gede Volcano Complex consists of Bregade Masigit (Br. M.), which consists of Joklok (Gm.J.) and Gegerbentang (Gm.G.) Hummocs; Crown Lingkung (Kh.L.) consisting of Pangrango (Gm.P.), Situ Gunung (Gm Sg.), Cikahuripan (Gm.Ck.), Pasir Prahu (Gm.Ph) Hummocs; Gege Crown (Kh.G.), which is located in the east of Lingkung Crown. The Gede Crown consists of Gumuruh humock (Gm.Gh.), Gunung Gede lava flows (LG 1,2,3,4,5), and giant debrise avalances (gv-G). The geological mapping based volcanostratigraphy is very useful for exploration of mineral and energy resources, as well as geological hazards.Keywords : volcanostratigraphy, DEM TerraSar-x image, Gunung Gede Complexs.

scholarly journals Volkanostratigrafi Inderaan Jauh Kompleks Gunungapi Gede dan Sekitarnya, Jawa Barat, Indonesia

2019 ◽  
Vol 20 (1) ◽  
pp. 9
Author(s):  
Fitriani Agustin ◽  
Sutikno Bronto
Keyword(s):  
Remote Sensing ◽  
Geological Mapping ◽  
Lava Flows ◽  
Energy Resources ◽  
Visual Interpretation ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Digital Elevation ◽  
History Of ◽  
Elevation Model

Remote sensing technology greatly helps to identify the various of volcano features, including active, old and ancient volcanoes. The aim of this  paper is intended to introduce various volcanic features in the Gede Volcano Complexs (GVC) and souronding area; compose volcanostratigraphy; and estimate the history of the volcanoes. The method used is a visual interpretation 9 meters spatial resolution of Digital Elevation Model (DEM) TerraSar-x image. Indonesian Stratigraphy Nomenclature Guide 1996 was implemented in vocanostratigraphy unit classification, involving Arc, Super Brigate, Brigate, Crown and Hummockly. Based on the interpretation the DEM image, volcanostratigraphic unit the Gede Volcano Complex consists of Bregade Masigit (Br. M.), which consists of Joklok (Gm.J.) and Gegerbentang (Gm.G.) Hummocs; Crown Lingkung (Kh.L.) consisting of Pangrango (Gm.P.), Situ Gunung (Gm Sg.), Cikahuripan (Gm.Ck.), Pasir Prahu (Gm.Ph) Hummocs; Gege Crown (Kh.G.), which is located in the east of Lingkung Crown. The Gede Crown consists of Gumuruh humock (Gm.Gh.), Gunung Gede lava flows (LG 1,2,3,4,5), and giant debrise avalances (gv-G). The geological mapping based volcanostratigraphy is very useful for exploration of mineral and energy resources, as well as geological hazards.Keywords : volcanostratigraphy, DEM TerraSar-x image, Gunung Gede Complexs.DOI: 10.33332/jgsm.2019.v20.1.9-16

scholarly journals Volkanostratigrafi Inderaan Jauh Kompleks Gunungapi Gede dan Sekitarnya, Jawa Barat, Indonesia

2019 ◽  
Vol 20 (1) ◽  
pp. 9
Author(s):  
Fitriani Agustin ◽  
Sutikno Bronto
Keyword(s):  
Remote Sensing ◽  
Geological Mapping ◽  
Lava Flows ◽  
Energy Resources ◽  
Visual Interpretation ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Digital Elevation ◽  
History Of ◽  
Elevation Model

Remote sensing technology greatly helps to identify the various of volcano features, including active, old and ancient volcanoes. The aim of this  paper is intended to introduce various volcanic features in the Gede Volcano Complexs (GVC) and souronding area; compose volcanostratigraphy; and estimate the history of the volcanoes. The method used is a visual interpretation 9 meters spatial resolution of Digital Elevation Model (DEM) TerraSar-x image. Indonesian Stratigraphy Nomenclature Guide 1996 was implemented in vocanostratigraphy unit classification, involving Arc, Super Brigate, Brigate, Crown and Hummockly. Based on the interpretation the DEM image, volcanostratigraphic unit the Gede Volcano Complex consists of Bregade Masigit (Br. M.), which consists of Joklok (Gm.J.) and Gegerbentang (Gm.G.) Hummocs; Crown Lingkung (Kh.L.) consisting of Pangrango (Gm.P.), Situ Gunung (Gm Sg.), Cikahuripan (Gm.Ck.), Pasir Prahu (Gm.Ph) Hummocs; Gege Crown (Kh.G.), which is located in the east of Lingkung Crown. The Gede Crown consists of Gumuruh humock (Gm.Gh.), Gunung Gede lava flows (LG 1,2,3,4,5), and giant debrise avalances (gv-G). The geological mapping based volcanostratigraphy is very useful for exploration of mineral and energy resources, as well as geological hazards.Keywords : volcanostratigraphy, DEM TerraSar-x image, Gunung Gede Complexs.DOI: 10.33332/jgsm.2019.v20.1.9-16

scholarly journals Water Reservoir Area and Volume Determination using Geoinformation Technologies and Remote Sensing

2019 ◽  
Vol 8 (4) ◽  
pp. 5458-5461 ◽  
Keyword(s):  
Remote Sensing ◽  
Digital Elevation Model ◽  
Water Reservoir ◽  
Google Earth ◽  
Volume Determination ◽  
Reservoir Area ◽  
Geoinformation Technologies ◽  
Digital Elevation ◽  
Elevation Model ◽  
Area And Volume

This article presents the method for calculating the area and volume of the water reservoir using Remote Sensing and Geoinformation Technologies. All calculations were performed for the Tashtepa water reservoir which recommended for construction in the Tashkent region. The territory of Tashtepa water reservoir was explored using the Google Earth program, was identified the alignment for the construction of dams, and the file was saved as a KML (Keyhole Markup Language) format. The alignment and the digital elevation model of the reservoir area from the online database were uploaded to the Global Mapper program which one of the geographic information system programs. Contours were formed in the digital elevation model, there was defined the longitudinal profile of the alignment along dams, surface and volume of the water reservoir were obtained for each circuit and based on the results were obtained curve lines between contour and area F=f(H), contour and volume W=f(H).

scholarly journals Volkanostratigrafi Inderaan Jauh Kompleks Gunungapi Gede dan Sekitarnya, Jawa Barat, Indonesia

2019 ◽  
Vol 20 (1) ◽  
pp. 9
Author(s):  
Fitriani Agustin ◽  
Sutikno Bronto
Keyword(s):  
Remote Sensing ◽  
Geological Mapping ◽  
Lava Flows ◽  
Energy Resources ◽  
Visual Interpretation ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Digital Elevation ◽  
History Of ◽  
Elevation Model

Remote sensing technology greatly helps to identify the various of volcano features, including active, old and ancient volcanoes. The aim of this  paper is intended to introduce various volcanic features in the Gede Volcano Complexs (GVC) and souronding area; compose volcanostratigraphy; and estimate the history of the volcanoes. The method used is a visual interpretation 9 meters spatial resolution of Digital Elevation Model (DEM) TerraSar-x image. Indonesian Stratigraphy Nomenclature Guide 1996 was implemented in vocanostratigraphy unit classification, involving Arc, Super Brigate, Brigate, Crown and Hummockly. Based on the interpretation the DEM image, volcanostratigraphic unit the Gede Volcano Complex consists of Bregade Masigit (Br. M.), which consists of Joklok (Gm.J.) and Gegerbentang (Gm.G.) Hummocs; Crown Lingkung (Kh.L.) consisting of Pangrango (Gm.P.), Situ Gunung (Gm Sg.), Cikahuripan (Gm.Ck.), Pasir Prahu (Gm.Ph) Hummocs; Gege Crown (Kh.G.), which is located in the east of Lingkung Crown. The Gede Crown consists of Gumuruh humock (Gm.Gh.), Gunung Gede lava flows (LG 1,2,3,4,5), and giant debrise avalances (gv-G). The geological mapping based volcanostratigraphy is very useful for exploration of mineral and energy resources, as well as geological hazards.Keywords : volcanostratigraphy, DEM TerraSar-x image, Gunung Gede Complexs.

scholarly journals More dynamic than expected: an updated survey of surging glaciers in the Pamir

2020 ◽  
Vol 12 (4) ◽  
pp. 3161-3176
Author(s):  
Franz Goerlich ◽  
Tobias Bolch ◽  
Frank Paul
Keyword(s):  
Google Earth ◽  
Strong Increase ◽  
High Mountain ◽  
Systematic Analysis ◽  
High Resolution Imagery ◽  
Digital Elevation ◽  
Western Kunlun ◽  
Glacier Surges ◽  
Very High Resolution Imagery ◽  
Very High

Abstract. The investigation of surging glaciers using remote sensing has recently seen a strong increase as freely available satellite data and digital elevation models (DEMs) can provide detailed information about surges that often take place in remote and inaccessible regions. Apart from analysing individual surges, satellite information is increasingly used to collect valuable data on surging glaciers. Related inventories have recently been published for several regions in High Mountain Asia including the Karakoram or parts of the Pamir and western Kunlun Shan, but information for the entire Pamir is solely available from a historic database listing about 80 glaciers with confirmed surges. Here we present an updated inventory of confirmed glacier surges for the Pamir that considers results from earlier studies and is largely based on a systematic analysis of Landsat image time series (1988 to 2018), very high-resolution imagery (Corona, Hexagon, Bing Maps, Google Earth) and DEM differences. Actively surging glaciers (e.g. with advancing termini) were identified from animations and flicker images and the typical elevation change patterns (lowering in an upper reservoir zone and thickening further down in a receiving zone). In total, we identified 206 spatially distinct surges within 186 glacier bodies mostly clustered in the northern and western part of the Pamir. Where possible, minimum and maximum glacier extents were digitised, but often interacting tributaries made a clear separation challenging. Most surging glaciers (n=70) are found in the larger size classes (>10 km2), but two of them are very small (<0.5 km2). We also found several surges where the length of the glacier increased by more than 100 %. The created datasets are available at: https://doi.org/10.1594/PANGAEA.914150 (Goerlich et al., 2020).

scholarly journals A regionally resolved inventory of High Mountain Asia surge-type glaciers, derived from a multi-factor remote sensing approach

2021 ◽  
Author(s):  
Gregoire Guillet ◽  
Owen King ◽  
Mingyang Lv ◽  
Sajid Ghuffar ◽  
Douglas Benn ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Google Earth ◽  
Surface Velocity ◽  
High Mountain ◽  
Abstract Knowledge ◽  
High Resolution Imagery ◽  
Self Organized Criticality ◽  
Glacier Surges ◽  
Very High Resolution Imagery ◽  
The Impact

Abstract. Knowledge about the occurrence and characteristics of surge-type glaciers is crucial due to the impact of surging on glacier melt and glacier related hazards. One of the "super-clusters" of surge-type glaciers is the mountains of Asia. However, no consistent region-wide inventory of surge-type glaciers in High Mountain Asia exists. We present a regionally resolved inventory of surge-type glaciers based on their behaviour across High Mountain Asia between 2000 and 2018. We identify surge-type behaviour from surface velocity, elevation and feature change patterns using a multi-factor remote sensing approach that combines yearly ITS_LIVE velocity data, DEM differences and very-high resolution imagery (Bing Maps, Google Earth). Out of the ≈ 95000 glaciers in HMA, we identified 666 that show diagnostic surge-type glacier behaviour between 2000 and 2018, which are mainly found in the Karakoram (223) and the Pamir regions (223). The total area covered by the 666 surge-type glaciers represents 19.5 % of the glacierized area in Randolph Glacier Inventory (RGI) V6.0 polygons in HMA. Across all regions of HMA, the surge-affected area within glacier complexes displays a significant power law dependency with glacier length. We validate 107 previously identified glaciers as surge-type and newly identify 491 glaciers. We finally discuss the possibility of self-organized criticality in glacier surges.

Improving bioclimatic envelop modeling for Lichens through remote sensing based substratum correction: A study over Indian Himalaya

2016 ◽  
Vol 1 (2) ◽  
Author(s):  
C. P. Singh ◽  
R. Bajpai ◽  
R. P. Singh ◽  
D. K. Upreti
Keyword(s):  
Remote Sensing ◽  
Predictive Accuracy ◽  
Geographic Area ◽  
Jammu And Kashmir ◽  
Indian Himalaya ◽  
Novel Approach ◽  
Digital Elevation ◽  
Average Probability ◽  
Niche Area ◽  
Elevation Model

In alpine Himalaya, the niche map of lichens and its characteristics is a gap area. A novel approach of improving the bioclimatic envelop through use of remote sensing inputs was employed. The 19 bioclimatic indices and digital elevation model were used for training niche models through occurrence records of 33 lichen species across Indian Himalaya. Substratum correction was carried out using LU/LC data. About 45% of the total geographic area studied is found to be very conducive (with niche probability > 70%) for the growth of lichens with predictive accuracy of 91% ascertained through cross-validation. Jammu and Kashmir is having highest niche area (36.02%); however, average probability niche score is highest in Uttarakhand (81.08). Area between 27o - 28o N latitude is having highest area however average probability score is highest in 30o - 31o N. Overall maximum niche area (35.50 %) is found in the regions dominated by alpine meadow, alpine grasslands and parts of cold deserts. The potential use lies in reporting yet to be explored lichens in the Indian Himalaya.

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 Estimation of the HEC-HMS model parameters in data-scarce regions. Application to the Ouergha watershed (Sebou, Morocco)

2021 ◽  
Vol 314 ◽  
pp. 05002
Author(s):  
Hasna Moumni ◽  
Karima Sebari ◽  
Laila Stour ◽  
Abdellatif Ahbari
Keyword(s):  
Remote Sensing ◽  
Hydrological Model ◽  
Model Parameters ◽  
Flow Data ◽  
Random Parameters ◽  
Quality Of Data ◽  
Initial Values ◽  
Digital Elevation ◽  
Elevation Model

The availability, accessibility and quality of data are significant obstacles to hydrological modelling. Estimating the initial values of the hydrological model´’ ’s parameters is a laborious and determining task requiring much attention. Geographic information systems (GIS) and spatial remote sensing are prometting tools for processing and collecting data. In this work, we use an innovative approach to estimate the HEC-HMS hydrological model parameters from the soil map of Africa (250m), the land use map GLC30, the depth to bedrock map, the digital elevation model and observed flow data. The estimation approach is applied to the Ouergha basin (Sebou, Morocco). The proposed approach’s interest is to feed the HEC-HMS hydrological model with initial values of parameters close to the study area reality instead of using random parameters.

Sign in / Sign up

Export Citation Format

Share Document