scholarly journals Investigating the Recent Surge in the Monomah Glacier, Central Kunlun Mountain Range with Multiple Sources of Remote Sensing Data

2020 ◽  
Vol 12 (6) ◽  
pp. 966 ◽  
Author(s):  
Lei Guo ◽  
Jia Li ◽  
Lixin Wu ◽  
Zhiwei Li ◽  
Yanyang Liu ◽  
...  
Keyword(s):  
Remote Sensing Data ◽  
Mountain Range ◽  
Multiple Sources ◽  
Landsat Images ◽  
Kunlun Mountain ◽  
Slow Expansion ◽  
Length Changes ◽  
Pressure Melting ◽  
Mass Accumulation ◽  
Alos Prism

Several glaciers in the Bukatage Massif are surge-type. However, previous studies in this region focused on glacier area and length changes, and more information is needed to support the deep analysis of glacier surge. We determined changes in glacier thickness, motion, and surface features in this region based on TanDEM-X, ALOS/PRISM, Sentinel-1A, and Landsat images. Our results indicated that the recent surge of the Monomah Glacier, the largest glacier in the Bukatage Massif, started in early 2009 and ceased in late 2016. From 2009 to 2016, its area and length respectively increased by 6.27 km2 and 1.45 km, and its ice tongue experienced three periods of changes: side broadening (2009–2010), rapid advancing (2010–2013), and slow expansion (2013–2016). During 2000–2012, its accumulation zone was thinned by 50 m, while its ice tongue was thickened by 90 m. During 2015–2017, its flow velocity reduced from 1.2 to 0.25 m/d, and the summer velocities were much higher than winter velocities. We conclude that the recent Monomah Glacier surge is thermal-controlled. The subglacial temperature rose to the pressure-melting point because of substantial mass accumulation, and then the increased basal meltwater caused the surge.

scholarly journals Glacier variations at Aru Co in western Tibet from 1971 to 2016 derived from remote-sensing data

2018 ◽  
Vol 64 (245) ◽  
pp. 397-406 ◽  
Author(s):  
ZHEN ZHANG ◽  
SHIYIN LIU ◽  
YONG ZHANG ◽  
JUNFENG WEI ◽  
ZONGLI JIANG ◽  
...  
Keyword(s):  
Mass Balance ◽  
Remote Sensing Data ◽  
Topographic Maps ◽  
Glacier Area ◽  
Human Beings ◽  
Positive Mass ◽  
Landsat Images ◽  
Pressure Melting ◽  
Geodetic Mass Balance ◽  
Sustained Increase

ABSTRACTTwin glaciers collapsed in 2016 near Aru Co, western Tibet and caused extreme loss to human beings. In this study, we attempted to track the dynamics of glaciers in the region, for example the glacier area and mass changes in Aru Co for the period 1971–2016, which were determined using topographic maps and Landsat images and ASTER-derived DEMs (2011–16), the Shuttle Radar Terrain Mission DEM (2000) and topographic maps (1971). Our results showed that the glacier area of Aru Co decreased by −0.4 ± 4.1% during 1971–2016. The geodetic mass-balance results showed that the glaciers in Aru Co lost mass at a rate of −0.15 ± 0.30 m w.e. a−1 during 1971–99, while they gained mass at a rate of 0.33 ± 0.61 m w.e. a−1 for the period 1999–2016. The twin glaciers experienced a larger negative mass budget than the others in the region before 1999. This process produced large amounts of meltwater, followed by a sustained increase in the meltwater on the pressure melting point, possibly in response to a period of positive mass balance (1999–2016) and then, transferred to the glacier bed until the glaciers collapsed.

scholarly journals A New Combined Adjustment Model for Geolocation Accuracy Improvement of Multiple Sources Optical and SAR Imagery

2021 ◽  
Vol 13 (3) ◽  
pp. 491
Author(s):  
Niangang Jiao ◽  
Feng Wang ◽  
Hongjian You
Keyword(s):  
Remote Sensing Data ◽  
Observation Data ◽  
Multiple Sources ◽  
Accuracy Improvement ◽  
Geometric Calibration ◽  
Proposed Model ◽  
Calibration Methods ◽  
Earth Observation Data ◽  
Sar Imagery ◽  
Geolocation Accuracy

Numerous earth observation data obtained from different platforms have been widely used in various fields, and geometric calibration is a fundamental step for these applications. Traditional calibration methods are developed based on the rational function model (RFM), which is produced by image vendors as a substitution of the rigorous sensor model (RSM). Generally, the fitting accuracy of the RFM is much higher than 1 pixel, whereas the result decreases to several pixels in mountainous areas, especially for Synthetic Aperture Radar (SAR) imagery. Therefore, this paper proposes a new combined adjustment for geolocation accuracy improvement of multiple sources satellite SAR and optical imagery. Tie points are extracted based on a robust image matching algorithm, and relationships between the parameters of the range-doppler (RD) model and the RFM are developed by transformed into the same Geodetic Coordinate systems. At the same time, a heterogeneous weight strategy is designed for better convergence. Experimental results indicate that our proposed model can achieve much higher geolocation accuracy with approximately 2.60 pixels in the X direction and 3.50 pixels in the Y direction. Compared with traditional methods developed based on RFM, our proposed model provides a new way for synergistic use of multiple sources remote sensing data.

scholarly journals Modern glacier dynamics in Mt. Tsambagarav in the Mongolian Altai Mountain Range

2020 ◽  
Vol 51 ◽  
pp. 12-20
Author(s):  
Tuyagerel Davaagatan ◽  
Alexander Orkhonselenge
Keyword(s):  
Remote Sensing Data ◽  
Principal Component ◽  
Mountain Range ◽  
Glacier Area ◽  
Altai Mountain ◽  
Mongolian Altai ◽  
Surface Water Resources ◽  
Highly Sensitive ◽  
Glacier Dynamics ◽  
Normalized Difference Snow Index

This study presents the modern glacier dynamics in Mt. Tsambagarav in the Mongolian Altai Mountain Range over the last four decades. This is the first review of this type of glacier dynamics for this massif. Changes in glacier area in Mt. Tsambagarav are estimated using normalized indexes (Normalized Difference Snow Index and Normalized Difference Principal Component Snow Index). Spatial distribution of the modern glaciers delineated with Landsat Multispectral Scanner (MSS: resolution of 80 m), Landsat Thematic Mapper (TM: resolution of 30 m) and Landsat Operational Land Imager (OLI: resolution of 30 m) imageries. Result shows that Mt. Tsambagarav has lost 51.7% of the glacier area from 132.24 km2 in 1977 to 63.92 km2 in 2017. The loss in glacier area for Mt. Tsambagarav during the last 40 years reflect the rapid response of the modern glacier to climate change, i.e., it is highly sensitive to solar insolation and/or rapidly rising local and regional mean annual temperatures. The remote sensing data and field survey suggest that the modern glaciers would be disappeared on a scale of decades. Rapid melting of the glacier in this massif contributes to surface water resources in western Mongolia. This study demonstrates the importance of spatial analysis in the remote area for understanding the context of changes in the modern glaciers.

scholarly journals Snow Cover and Snow Persistence Changes in the Mocho-Choshuenco Volcano (Southern Chile) Derived From 35 Years of Landsat Satellite Images

2021 ◽  
Vol 9 ◽  
Author(s):  
Roberto O. Chávez ◽  
Verónica F. Briceño ◽  
José A. Lastra ◽  
Daniel Harris-Pascal ◽  
Sergio A. Estay
Keyword(s):  
Snow Cover ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Microbial Composition ◽  
Mountain Areas ◽  
Pixel Resolution ◽  
Temperature Changes ◽  
Soil Microbial ◽  
Landsat Satellite

Mountain regions have experienced above-average warming in the 20th century and this trend is likely to continue. These accelerated temperature changes in alpine areas are causing reduced snowfall and changes in the timing of snowfall and melt. Snow is a critical component of alpine areas - it drives hibernation of animals, determines the length of the growing season for plants and the soil microbial composition. Thus, changes in snow patterns in mountain areas can have serious ecological consequences. Here we use 35 years of Landsat satellite images to study snow changes in the Mocho-Choshuenco Volcano in the Southern Andes of Chile. Landsat images have 30 m pixel resolution and a revisit period of 16 days. We calculated the total snow area in cloud-free Landsat scenes and the snow frequency per pixel, here called “snow persistence” for different periods and seasons. Permanent snow cover in summer was stable over a period of 30 years and decreased below 20 km2 from 2014 onward at middle elevations (1,530–2,000 m a.s.l.). This is confirmed by negative changes in snow persistence detected at the pixel level, concentrated in this altitudinal belt in summer and also in autumn. In winter and spring, negative changes in snow persistence are concentrated at lower elevations (1,200–1,530 m a.s.l.). Considering the snow persistence of the 1984–1990 period as a reference, the last period (2015–2019) is experiencing a −5.75 km2 reduction of permanent snow area (snow persistence > 95%) in summer, −8.75 km2 in autumn, −42.40 km2 in winter, and −18.23 km2 in spring. While permanent snow at the high elevational belt (>2,000 m a.s.l.) has not changed through the years, snow that used to be permanent in the middle elevational belt has become seasonal. In this study, we use a probabilistic snow persistence approach for identifying areas of snow reduction and potential changes in alpine vegetation. This approach permits a more efficient use of remote sensing data, increasing by three times the amount of usable scenes by including images with spatial gaps. Furthermore, we explore some ecological questions regarding alpine ecosystems that this method may help address in a global warming scenario.

scholarly journals A snow cover climatology for the Pyrenees from MODIS snow products

2014 ◽  
Vol 11 (11) ◽  
pp. 12531-12571 ◽  
Author(s):  
S. Gascoin ◽  
O. Hagolle ◽  
M. Huc ◽  
L. Jarlan ◽  
J.-F. Dejoux ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Forested Areas ◽  
Land Cover Map ◽  
Hydropower Production ◽  
Snow Cover Duration

Abstract. The seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations, satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (we) and 105 mm respectively, for both MOD10A1 and MYD10A1. Kappa coefficients are within 0.74 and 0.92 depending on the product and the variable. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97% (κ = 0.85) for MOD10A1 and 96% (κ = 0.81) for MYD10A1, which indicates a good agreement between both datasets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decreases over the forests but the agreement remains acceptable (MOD10A1: 96%, κ = 0.77; MYD10A1: 95%, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gapfilling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band. We finally analyze the snow patterns for the atypical winter 2011–2012. Snow cover duration anomalies reveal a deficient snowpack on the Spanish side of the Pyrenees, which seems to have caused a drop in the national hydropower production.

scholarly journals Mapping and Analyzing the Evolution of the Butangbunasi Landslide Using Landsat Time Series with Respect to Heavy Rainfall Events during Typhoons

2020 ◽  
Vol 10 (2) ◽  
pp. 630 ◽  
Author(s):  
Daniel Hölbling ◽  
Lorena Abad ◽  
Zahra Dabiri ◽  
Günther Prasicek ◽  
Tsai-Tsung Tsai ◽  
...  
Keyword(s):  
Heavy Rainfall ◽  
Remote Sensing Data ◽  
Rainfall Data ◽  
Disaster Mitigation ◽  
Heavy Rainfall Event ◽  
Landslide Area ◽  
Landsat Images ◽  
South Central ◽  
Hourly Rainfall ◽  
Central Taiwan

Large rainfall-induced landslides are among the most dangerous natural hazards in Taiwan, posing a risk for people and infrastructure. Thus, better knowledge about the evolution of landslides and their impact on the downstream area is of high importance for disaster mitigation. The aim of this study is twofold: (1) to semi-automatically map the evolution of the Butangbunasi landslide in south-central Taiwan using satellite remote sensing data, and (2) to investigate the potential correlation between changes in landslide area and heavy rainfall during typhoon events. Landslide area, as well as temporary landslide-dammed lakes, were semi-automatically identified using object-based image analysis (OBIA), based on 20 Landsat images from 1984 to 2018. Hourly rainfall data from the Taiwan Central Weather Bureau (CWB) was complemented with rainfall data from Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) to examine the potential relationship between landslide area changes and rainfall as a triggering factor. The OBIA mapping results revealed that the most significant landslide extension happened after typhoon Morakot in 2009. We found a moderate positive relationship between the landslide area change and the duration of the heavy rainfall event, whereas daily precipitation, cumulative rainfall and mean intensity did not present strong significant correlations.

scholarly journals CREATION OF GIS-RESOURCES FOR PHYSIOGRAPHIC ZONING OF THE TRANSBOUNDARY RUSSIAN-MONGOLIAN TERRITORY

2021 ◽  
Vol 26 (2) ◽  
pp. 91-102
Author(s):  
Andrew N. Beshentsev ◽  
◽  
Alexander A. Ayurzhanaev ◽  
Bator V. Sodnomov ◽  
◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Statistical Research ◽  
Active Biomass ◽  
Sensing Data ◽  
Digital Elevation ◽  
Geographical Regions ◽  
Elevation Model ◽  
Geographical Characteristics

The article is aimed at the development of methodological foundations for the creation of geoin-formation resources of transboundary territories based on cartographic materials and remote sensing data, as well as physical and geographical zoning of the transboundary Russian-Mongolian territory. The methodological basis of the study is cartographic and statistical research methods, geoinformation technology, as well as processing and analysis of remote sensing data. As a result, the study deter-mines the features of geoinformation resources, presents their characteristics, develops a classification and substantiates their integrating value in making interstate territorial decisions. The article gives the physical and geographical characteristics of the territory, determines the scale of mapping, establishes the basic units of geoinformation mapping and modeling, creates the coverage of the basin division, and proposes a scheme for creating basic geoinformation resources for the physical and geographical zoning of the territory. Based on the analysis of the digital elevation model, the territory was zoned according to the morphometric parameters of the relief. As a result of processing and analysis of Landsat images at different times, the territory was zoned in terms of the amount of photosynthetically active biomass (NDVI). As a result of zoning, 6 physical-geographical regions and 33 physical-geographical areas were identified.

scholarly journals Two decades of distributed global radiation time series across a mountainous semiarid area (Sierra Nevada, Spain)

2021 ◽  
Vol 13 (3) ◽  
pp. 1335-1359
Author(s):  
Cristina Aguilar ◽  
Rafael Pimentel ◽  
María J. Polo
Keyword(s):  
Time Series ◽  
Sierra Nevada ◽  
Global Radiation ◽  
Mountainous Area ◽  
Mountain Range ◽  
Wet Season ◽  
Landsat Images ◽  
Extreme Statistics ◽  
Variation Characteristics ◽  
Weather Stations

Abstract. The main drawback of the reconstruction of high-resolution distributed global radiation (Rg) time series in mountainous semiarid environments is the common lack of station-based solar radiation registers. This work presents 19 years (2000–2018) of high-spatial-resolution (30 m) daily, monthly, and annual global radiation maps derived using the GIS-based model proposed by Aguilar et al. (2010) in a mountainous area in southern Europe: Sierra Nevada (SN) mountain range (Spain). The model was driven by in situ daily global radiation measurements, from 16 weather stations with historical records in the area; a 30 m digital elevation model; and 240 cloud-free Landsat images. The applicability of the modeling scheme was validated against daily global radiation records at the weather stations. Mean RMSE values of 2.63 MJ m−2 d−1 and best estimations on clear-sky days were obtained. Daily Rg at weather stations revealed greater variations in the maximum values but no clear trends with altitude in any of the statistics. However, at the monthly and annual scales, there is an increase in the high extreme statistics with the altitude of the weather station, especially above 1500 m a.s.l. Monthly Rg maps showed significant spatial differences of up to 200 MJ m−2 per month that clearly followed the terrain configuration. July and December were clearly the months with the highest and lowest values of Rg received, and the highest scatter in the monthly Rg values was found in the spring and fall months. The monthly Rg distribution was highly variable along the study period (2000–2018). Such variability, especially in the wet season (October–May), determined the interannual differences of up to 800 MJ m−2 yr−1 in the incoming global radiation in SN. The time series of the surface global radiation datasets here provided can be used to analyze interannual and seasonal variation characteristics of the global radiation received in SN with high spatial detail (30 m). They can also be used as cross-validation reference data for other global radiation distributed datasets generated in SN with different spatiotemporal interpolation techniques. Daily, monthly, and annual datasets in this study are available at https://doi.org/10.1594/PANGAEA.921012 (Aguilar et al., 2021).

scholarly journals Analyze of Dynamics and Degree of Anthropogenic Impacts on the Ecogeomorphological Conditions (Case Study of the Kura-Araz Lowland and Surrounding Areas)

2021 ◽  
pp. 92-102
Author(s):  
J. Y. Gasimov
Keyword(s):  
Land Cover ◽  
Building Materials ◽  
Oil And Gas ◽  
Anthropogenic Impacts ◽  
Remote Sensing Data ◽  
Gas Production ◽  
Anthropogenic Factors ◽  
Stream Network ◽  
Landsat Images ◽  
Irrigation Network

Theoretical base of human effects on geomorphological environment, the evolution of anthropogenic impacts and modern situation of human activity were analyzed in the studied area. On the base of supervised and unsupervised classification of the Landsat images (1976–2017) Land use-Land cover map of the territory was compiled. The dynamic and transformation of land covers were determined with the change detection function. It was defined that the most increasing land cover in the area of transformation since 1976 to 2017 is the sown area. Due to the anthropogenic development of the study area, the largest decrease in the area of exposed (33,85%) and saline (25,43%) land cover occurred during this period. Among the listed anthropogenic factors (oil and gas production, production of building materials, grazing, settlements, etc.), it is established that irrigation erosion has a wide radius of encirclement and a high degree of influence. With the application of Geographic Information System technologies, on the base of remote sensing data the density of the irrigation network has been computed and mapped. Ecogeomorphological assessment and zoning of the territory has been carried out. According to the comparative analysis of horizontal (stream network) and anthropogenic (irrigation network) fragmentation it was determined that the estimated maximum cost of anthropogenic fragmentation in the study area is 2,5 times higher than natural horizontal fragmentation.

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