Images Of Corona Research Articles

A 54-year record of changes at Chalaati and Zopkhito glaciers, Georgian Caucasus, observed from archival maps, satellite imagery, drone survey and ground-based investigation

Individual glacier changes are still poorly documented in the Georgian Caucasus. In this paper, the change of Chalaati and Zopkhito glaciers in Georgian Caucasus has been studied between 1960 and 2014. Glacier geometries are reconstructed from archival topographic maps, Corona and Landsat images, along with modern field surveys. For the first time in the Georgian Caucasus aerial photogrammetric survey of both glacier termini was performed (2014) using a drone or Unmanned Aerial Vehicle, where high-resolution orthomosaics and digital elevation models were produced. We show that both glaciers have experienced area loss since 1960: 16.2±4.9 per cent for Chalaati Glacier and 14.6±5.1 per cent for Zopkhito Glacier with corresponding respective terminus retreat by ~675 m and ~720 m. These were accompanied by a rise in the equilibrium line altitudes of ~35 m and ~30 m, respectively. The glacier changes are a response to regional warming in surface air temperature over the last half century. We used a long-term temperature record from the town of Mestia and short-term meteorological observations at Chalaati and Zopkhito glaciers to estimate a longer-term air temperature record for both glaciers. This analysis suggests an increase in the duration of the melt season over the 54-year period, indicating the importance of summertime air temperature trends in controlling glacier loss in the Georgian Caucasus. We also observed supra-glacial debris cover increase for both glaciers over the last half century: from 6.16±6.9 per cent to 8.01±6.8 per cent for Chalaati Glacier and from 2.80±6.3 per cent to 8.53±5.7 per cent for Zopkhito Glacier.

Improving Coronal Magnetic Field Models Using Image Optimization

Abstract We have reported previously on our development and testing of a new method for using coronal images to improve coronal magnetic field models. In this technique, which we call image-optimization, coronal magnetic field models are extrapolated from synoptic photospheric magnetograms. The resulting models are then compared to morphological constraints derived from images of the solar corona, and the photospheric magnetograms are perturbed iteratively via an optimization algorithm to achieve optimal agreement with the image-based constraints. Here we present results from the first application of this technique using Mauna Loa Solar Observatory K-Coronagraph images and Global Oscillation Network Group synoptic magnetograms to create optimized models for two time periods, 2014 November 16–29 and 2016 May 16–29. We find that for both time periods the optimization algorithm converges well and results in better agreement between the model and the images, relatively small changes to the synoptic magnetogram, and an overall increase in the amount of open magnetic flux.

Summary of Application Research of Deep Learning in Operational Inspection of Transmission and Distribution Equipment

With the continuous expansion of artificial intelligence in power system, the reliability, security and operation ability of power system have been greatly improved. With the massive collection of data for transmission and transformation operation and maintenance, in-depth learning, as a typical representative of data-driven in the system of artificial intelligence methods, is increasingly appearing in the application scenarios of intelligent state assessment of transmission and transformation equipment. Its excellent robustness can eliminate many kinds of interference in complex environment background, accurately identify and evaluate the target points under test, and greatly reduce the detection of transportation and inspection personnel. The workload of data analysis, processing, evaluation and other links can improve work efficiency and accuracy. This paper attempts to summarize the development process of in-depth learning, relevant landmark achievements and typical applications in the operation and inspection of power transmission and transformation equipment. This paper attempts to summarize the research progress of target recognition, target segmentation, image classification algorithms in depth learning in different spectral cameras of visible light, ultraviolet corona imaging and infrared thermal imaging.

White-light solar corona structure observed by naked eye and processed images

ABSTRACT Light and dark adaptation and luminance contrast enhancement are well-known characteristics of human vision that allow us to observe a wide range of light intensity not fully captured in standard camera images. The naked-eye observations of total eclipses, some recorded with spectacular detail in artists’ paintings, reveal structure that is consistent with images obtained by telescopes equipped with recording media. The actual shape of the corona during a total eclipse depends not only on the phase of the solar cycle but, as can be simply demonstrated, also on the day-to-day variability and spatial distribution of coronal intensity that is determined by solar surface magnetic fields, including the locations of coronal holes that are the sources of high-speed solar wind causing geomagnetic storms. The latter were very similar for the eclipses in 1932, 1994, and 2017, which is the main reason why the naked-eye observations, as well as the processed images (1994 and 2017), of the white-light corona displayed very similar shapes. White-light corona image processing is a useful technique to enhance the contrast to observe fine-scale structure that is consistent with the physics of the solar atmosphere shaped by the magnetic field drawn out into the interplanetary space by solar wind.

Simulating White-Light Images of Coronal Structures for Parker Solar Probe/WISPR: Study of the Total Brightness Profiles

The Wide-field Imager for Parker Solar Probe (WISPR) captures unprecedented white-light images of the solar corona and inner heliosphere. Thanks to the uniqueness of the Parker Solar Probe’s (PSP) orbit, WISPR is able to image “locally” coronal structures at high spatial and time resolutions. The observed plane of sky, however, rapidly changes because of the PSP’s high orbital speed. Therefore, the interpretation of the dynamics of the coronal structures recorded by WISPR is not straightforward. A first study, undertaken by Liewer et al. (Solar Phys.294, 93, 2019), shows how different coronal features (e.g., streamers, flux ropes) appear in the field-of-view of WISPR by means of raytracing simulations. In particular, they analyze the effects of the spatial resolution changes on both the images and the associated height–time maps, and introduce the fundamentals for geometric triangulation. In this follow-up paper, we focus on the study of the total brightness of a simple, spherical, plasma density structure, to understand how the analysis of Thomson-scattered emission by the electrons in a coronal feature can shed light into the determination of its kinematic properties. We investigate two cases: (i) a density sphere at a constant distance from the Sun for different heliographic longitudes; (ii) a density sphere moving outwardly with constant speed. The study allows us to characterize the effects of the varying heliocentric distance of the observer and scattering angle on the total brightness observed, which we exploit to contribute to a better determination of the position and speed of the coronal features observed by WISPR.

Spatial and Temporal Dynamics of Urban Wetlands in an Indian Megacity over the Past 50 Years

Asian megacities have attracted much scientific attention in the context of global urbanization, but few quantitative studies analyze wetland transformation in the rural–urban interface. With its rampant growth and transformation from a tree-lined “Garden City” to a busy megalopolis with often-blocked highways and large built-up areas, Bengaluru (Karnataka, S-India) is a good example for assessing how urbanization has led to the acute degradation of wetlands. We therefore investigated long-term land cover and wetland changes from 1965 to 2018 based on an object-based classification of multi-temporal Corona and Landsat images. To quantify and compare the dynamics of open water surfaces and vegetation, we defined the potential wetland areas (PWA) along the rural–urban gradient and linked our analyses to an index describing the degree of urbanization (survey stratification index (SSI)). During the five decades studied, built-up areas in the Bengaluru Urban district increased ten-fold, with the highest growth rate from 2014 to 2018 (+ 8% annual change). Patches of lake wetlands were highly dynamic in space and time, partly reflecting highly variable annual rainfall patterns ranging from 501 mm in 1965 to 1374 mm in 2005 and monsoon-driven alterations in the hydrologic regime. While water bodies and flooded areas shrunk from 64 km2 in 1965 to 55 km2 in 2018, in 1965, the total rural wetland area with an SSI > 0.5 was twice as high as in 2018. The rural–urban land cover pattern within potential wetland areas changed drastically during this period. This is reflected, for example, by a four-fold increase in the wetland area with an SSI of 0.3, as compared to a decline by 43% in wetland area with an SSI of 0.8. While, in urban areas, wetlands were mostly lost to construction, in areas with a rural character, open water bodies were mainly transformed into green space. The detected changes in urban wetlands were likely accompanied by ecological regime changes, triggering deteriorations in ecosystem services (ESS) which merit further research.

Colorimetric Method for Discharge Status Diagnostics based on Optical Spectroscopy and Digital Images

Discharge is a process, which involves changes in multiple species, and it is important for researchers to be able to describe changes in discharge status holistically. In this study, we applied AC and DC high voltage power sources to a short-gap needle-plane device in an atmospheric environment. We propose two new corona diagnosis methods based on spectral data and visible images. The experimental results demonstrate that, in the RGB system, the proportion of the blue component in AC corona images has the characteristic of decrease-stable-increase with voltage, and the corresponding result of the spectra is stable-increase. In the XYZ system, the AC corona chromaticity coordinates of both images and spectra demonstrate a linear fitting result with the voltage, and the image results contain a retracement process, showing shows the increase-stable-decrease trend of chromaticity coordinates x and y, which correlates well with oscilloscope results. The difference between the image and spectra results indicates that, compared to the spectra, high-resolution visible images are more sensitive to imperceptible changes in colorimetry information. The change of DC corona colorimetry characteristics can illustrate the change in AC corona colorimetry characteristics. Additionally, the dominant wavelength is proven to reflect the discharge species, and can reflect the vibrational temperatures. To the best of our knowledge, this paper represents the first attempt to systematically introduce colorimetry theory into discharge images and spectra. We successfully obtained colorimetric indicators with the linearity and low-dimension characteristics, which correspond well with known physical parameters.

Spatial and Temporal Variations of Erosion and Accretion: A Case of a Large Tropical River

Rapidly changing river systems can impact people, property and infrastructures. This study investigates bank erosion and accretion of the Padma River in Bangladesh, through space and time, using historical topographic maps, Corona and Landsat images and navigational charts. A geographic information system (GIS) was utilised to quantify the erosion and accretion pattern. In addition, volumetric changes in the riverbed were also investigated. Results indicated that the area of erosion and deposition vary both spatially and temporally. However, erosion was more prominent on the left bank, whilst accretion was high along the right bank, over the study period. Overall, average annual erosion rates were higher than accretion rates (17 km2 year−1 versus 13 km2 year−1). The volumes of morphological change for two epochs correspond to a net volume gain of 338.75 million m3 sediment between 1984 and 1992 but a net loss of 295.20 million m3 during the period 1992–2008. Regression analysis between bank erosion and mean annual flow, peak discharge and mean flood flow showed that two of the three independent variables were significantly associated with bank erosion. The area of large mid-channel bars increased over time, which may have had a role in shaping erosion and accretion processes of the river. As increased runoff is expected in the future, as a result of enhanced rainfall under warmer climate, knowledge of this work will help to determine the morphological response of fluvial systems in Bangladesh and elsewhere.

Solar Cycle Variation of Coronal Temperature, Emission Measure, and Soft X-Ray Irradiance Observed with Yohkoh Soft X-Ray Telescope

Abstract This paper presents the solar soft X-ray irradiance (0.3–3.0 nm) obtained from the mission-long full-Sun X-ray images observed with the Soft X-ray Telescope (SXT) of the Yohkoh mission (1991–2001). The irradiance was calculated using filter-ratio temperatures and emission measures (EMs) from the full-Sun integrated X-ray signals employing a coronal spectrum synthesized with CHIANTI atomic database version 8.0. Dependence of the results on the assumption of elemental abundances is investigated. The SXT irradiance for a shorter wavelength range was also calculated and compared with the low energy flux (0.1–0.8 nm) of the X-Ray Sensor on board the GOES satellite. To incorporate the spatial information of the observed corona, we tried the alternative method to derive irradiance by applying the filter-ratio method to the images of northern hemispheric corona instead of spatially integrated signals from there. The EM weighted average of the spatially resolved temperatures turned out to be generally 20%–30% lower than those derived from the integrated signals, while the total of spatially resolved EMs are accordingly 1.5–2 times higher. This trend is enhanced when solar activity is the lowest in early 1996. The irradiance obtained from the alternative method does not significantly vary from the result from the integrated signals. This provides some validation for the simpler full-Sun integrated method. The temporal variation of the EMs of cool (<1.5 MK), medium, and hot (>2.5 MK) components indicates that the ratio of the hot component relative to the medium component is higher in the ascending phase (mid 1998–2001) than in the descending phase (1992–1995) of the solar activity cycle.

Processing methods and approaches for the analysis of images of the eclipsed solar corona taken during campaigns with the participation of amateur astronomers

AbstractThe increase in the amount of scientific information in heliophysics is related to both quantitative – increasing the number of high-power telescopes and the size of light receivers coupled to them, and qualitative reasons – new modes of observation, large-scale and multiple studies of the solar corona in different ranges, large-scale numerical experiments to simulate the evolution of various processes and formations, etc. The paper discusses the role and importance of methods for processing images of the solar corona, the store of obtained “raw” data and the need to access high-performance computing systems in order to obtain scientific results from the observational experiments, the need of international collaboration and access to the data in the era of increase in the amount of scientific information in heliophysics.

A CME Automatic Detection Method Based on Adaptive Background Learning Technology

In this paper, we describe a technique, which uses an adaptive background learning method to detect the CME (coronal mass ejections) automatically from SOHO/LASCO C2 image sequences. The method consists of several modules: adaptive background module, candidate CME area detection module, and CME detection module. The core of the method is based on adaptive background learning, where CMEs are assumed to be a foreground moving object outward as observed in running-difference time series. Using the static and dynamic features to model the corona observation scene can more accurately describe the complex background. Moreover, the method can detect the subtle changes in the corona sequences while filtering their noise effectively. We applied this method to a month of continuous corona images, compared the result with CDAW, CACTus, SEEDS, and CORIMP catalogs and found a good detection rate in the automatic methods. It detected about 73% of the CMEs listed in the CDAW CME catalog, which is identified by human visual inspection. Currently, the derived parameters are position angle, angular width, linear velocity, minimum velocity, and maximum velocity of CMES. Other parameters could also easily be added if needed.

Solar survey at Pic du Midi: Calibrated data and improved images

Context. We carry out a solar survey with images of the photosphere, prominences, and corona at Pic du Midi observatory. This survey, named CLIMSO (for CLIchés Multiples du SOleil), is in the following spectral lines: Fe XIII corona (1.075 μm), Hα (656.3 nm), and He I (1.083 μm) prominences, and Hα and Ca II (393.4 nm) photosphere. All frames cover 1.3 times the diameter of the Sun with an angular resolution approaching one arcsecond. The frame rate is one per minute per channel (weather permitting) for the prominences and chromosphere, and one per hour for the Fe XIII corona. This survey started in 2007 for the disk and prominences and in 2015 for the corona. We have almost completed one solar cycle and hope to cover several more, keeping the same wavelengths or adding others. Aims. We seek to make the CLIMSO images easier to use and more profitable for the scientific community. Methods. At the beginning of the survey, the images that we sent to the CLIMSO database were not calibrated. We have implemented a photometric calibration for the present and future images, in order to provide “science-ready” data. The old images have been calibrated. We have also improved the contrast capabilities of our coronagraphs, which now provide images of the Fe XIII corona, in addition to previous spectral channels. We also implemented an autoguiding system based on a diffractive Fresnel array for precise positioning of the Sun behind coronagraphic masks. Results. The data, including the images and films, are publicly available and downloadable through virtual observatories and dedicated websites (use “CLIMSO” and “IRAP” keywords to find them). For the Hα and Ca II channels we calibrate the data into physical units, independent of atmospheric or instrumental conditions; we provide solar maps of spectral radiances in W m−2 sr−1 nm−1. The instrumental improvements and calibration process are presented in this paper.

A Synergetic Analysis of Sentinel-1 and -2 for Mapping Historical Landslides Using Object-Oriented Random Forest in the Hyrcanian Forests

Despite increasing efforts in the mapping of landslides using Sentinel-1 and -2, research on their combination for discerning historical landslides in forest areas is still lacking, particularly using object-oriented machine learning approaches. This study was accomplished to test the efficiency of Sentinel-derived features and digital elevation model (DEM) derivatives for mapping old and new landslides, using object-oriented random forest. Two forest subsets were selected including a protected and non-protected forest in northeast Iran. Landslide samples were obtained from CORONA images and aerial photos (old landslides), and also field mensuration and high-resolution images (new landslides). Segment objects were generated from a set combination of Sentinel-1A, Sentinel-2A, and some topographic-derived indices using multiresolution segmentation algorithm. Various object features were derived from the main channels of Sentinel images and DEM derivatives in the seven main groups, including spectral layers, spectral indices, geometric, contextual, textural, topographic, and hydrologic features. A single database was created, including landslide samples and Sentinel- and DEM-derived object features. Roughly 20% of landslide-affected objects and non-landslide-affected objects were randomly selected as an input for training the random forest classifier. Two-thirds of the selected objects were assigned as learning samples for classification, and the remainder were used for testing the accuracy of landslide and non-landslide classification. Results indicated that: (1) The sensitivity of mapping historical landslides was 86.6% and 80.3% in the protected and non-protected forests, respectively; (2) the object features of Sentinel-2A and DEM obtained the highest importance with the total scores of 55.6% and 32%, respectively in the protected forests, and 65.4% and 21% respectively in the non-protected forests; (3) the features derived from the combination of Sentinel-1 and -2A demonstrated a total importance of 10% for mapping new landslides; and (4) textural features were obtained in approximately two-thirds of the total scores for mapping new landslides, however a combination of topographic, spectral, textural, and contextual features were the effective predictors for mapping old landslides. This research proposes applying a synergetic analysis of Sentinel- and DEM-derived features for mapping historical landslides; however, there are no uniformly pre-defined influential variables for mapping historical landslides in different forest areas.

SITES: Solar Iterative Temperature Emission Solver for Differential Emission Measure Inversion of EUV Observations

Extreme ultraviolet (EUV) images of the optically-thin solar corona in multiple spectral channels give information on the emission as a function of temperature through differential emission measure (DEM) inversions. The aim of this paper is to describe, test, and apply a new DEM method named the Solar Iterative Temperature Emission Solver (SITES). The method creates an initial DEM estimate through a direct redistribution of observed intensities across temperatures according to the temperature response function of the measurement, and iteratively improves on this estimate through calculation of intensity residuals. It is simple in concept and implementation, is non-subjective in the sense that no prior constraints are placed on the solutions other than positivity and smoothness, and can process a thousand DEMs a second on a standard desktop computer. The resulting DEMs replicate model DEMs well in tests on Atmospheric Imaging Assembly/Solar Dynamics Observatory (AIA/SDO) synthetic data. The same tests show that SITES performs less well on very narrow DEM peaks, and should not be used for temperature diagnostics below {approx,}0.5~mbox{MK} in the case of AIA observations. The SITES accuracy of inversion compares well with two other established methods. A simple yet powerful new method to visualize DEM maps is introduced, based on a fractional emission measure (FEM). Applied to a set of AIA full-disk images, the SITES method and FEM visualization show very effectively the dominance of certain temperature regimes in different large-scale coronal structures. The method can easily be adapted for any multi-channel observations of optically-thin plasma and, given its simplicity and efficiency, will facilitate the processing of large existing and future datasets.

Semi-empirical 2D model of the solar corona and solar wind using solar eclipse images: Progress report

AbstractWe present white light images of the Sun's corona acquired during the total Solar Eclipses on August 21, 2017 in mountains north of Boise Idaho USA and on July 2, 2019 south of Copiapo Chile. In both cases the viewing was excellent, altitudes ∼ 1200 m and relative humidity ∼ 10. We used an Orion equatorial reflecting telescope with 203 mm diameter aperture and 1000 mm focal length for f4.9 optics. A computer-controlled Canon EOS Rebel T3i digital camera was used. We plan to use our 2019 eclipse images for analysis since the Sun is near solar minimum so 2D steady state MHD equations can be used. We present a plan to process the images and convert them into a 2D empirical model of electron density and magnetic field in radial distance and co-latitude, from which 2D maps of flow velocity, effective temperature and effective heat flux can be computed.

Tomography of the Solar Corona with the Wide-Field Imager for the Parker Solar Probe

The Wide-field Imager for the Parker Solar Probe (PSP/WISPR) comprises two telescopes that record white-light total brightness $[B]$ images of the solar corona. Their fields of view cover a widely changing range of heliocentric heights over the 24 highly eccentric orbits planned for the mission. In this work, the capability of PSP/WISPR data to carry out tomographic reconstructions of the three-dimensional (3D) distribution of the coronal electron density is investigated. Based on the precise orbital information of the mission, $B$-images for Orbits 1, 12, and 24 are synthesized from a 3D magnetohydrodynamic model of the corona. For each orbit, the time series of synthetic images is used to carry out a tomographic reconstruction of the coronal electron density and results are compared with the model. As the PSP perihelion decreases, the range of heights that can be tomographically reconstructed progressively shifts to lower values, and the period required to gather the data decreases. For Orbit 1 tomographic reconstruction is not possible. For Orbit 12, tomographic reconstruction is possible in the heliocentric height range ${\approx}\, 5\,\mbox{--}\,15~\mathrm{{R}_{\odot}}$, over a region spanning up to ${\approx}\,160^{\circ}$ in Carrington longitude, with data gathered over a ${\approx}\, 3.4$ day-long period. For Orbit 24, tomographic reconstruction is possible in the heliocentric height range ${\approx}\,3\,\mbox{--}\,10~\mathrm {R}_{\odot}$, over a region spanning up to ${\approx} \,170^{\circ}$ in Carrington longitude, with data gathered over a ${\approx}\, 2.8$ day-long period.

Geospatial analysis of the depletion of surface water body and floodplains in Dhaka City (1967 to 2008) and its implications for earthquake vulnerability

Dhaka city the capital of Bangladesh experienced unprecedented urban growth since the country’s independence in 1971. A significant portion of the urbanization took place in the encroached surface water body and floodplain (SWB and FP) areas. We thus aimed to capture the depletion of SWB and FP in Dhaka city from 1967 to 2008 using geospatial analysis and evaluated its implications for earthquake vulnerability. We used CORONA (1967) and QuickBird (2008) satellite images to compare the pre- and post-urbanization status of SWB and FP. We identified a striking change occurred during this period with a total loss of 33% of SWB and FP areas. The channelized water body faced a depletion of 15%, while the open water body which mainly includes the floodplains experienced a loss of 38%. The urban structures built on the depleted SWB and FP are highly vulnerable to ground motion and liquefaction of earthquake. We found that 90% of the depleted areas have a shear wave velocity in the top 30 m of soil thickness (Vs30) of 180–360 m/s, while the rest has a Vs30 value of 15. We produced an earthquake vulnerability map based on the information of surficial geology, Vs30, LPI and found that substantial areas near the southern, eastern, and western boundaries of the city scored highly in the vulnerability map. The results of the study can support formulation of rational earthquake preparedness strategy for Dhaka.

A multidecadal change analysis for irrigation ponds in Taoyuan, Taiwan, using multisource data

A multidecadal change analysis of the irrigation ponds in Taoyuan, Taiwan, was conducted by using multisource data including digitized ancient maps, declassified single-band CORONA satellite images, and multispectral SPOT images. Ponds and paddy fields are texturally similar but spectrally different, whereas the paddy fields and built-up are texturally different but spectrally similar. In this study, supervised land-use/land-cover classifications were conducted using four textural features derived from the single-band CORONA images and spectral features derived from SPOT images. Post-classification analysis revealed that the number of irrigation ponds in the study area decreased during the post-World War II farmland consolidation period (1945–1965) and the subsequent industrialization period (1970–2000). However, efforts on restoration of irrigation ponds in recent years have resulted in gradual increases in the number (9%) and total area (12%) of irrigation ponds in the study area.

Features of the Dynamics of a Shock Excited by Fast Coronal Mass Ejections

The event on January 27, 2012 is an example of the features of the dynamics of formation of a shock, excited by a fast coronal mass ejection (CME) at a velocity higher than 2000 km/s, are investigated. The following data were used: (a) images of the Sun in the UV channel of 13.1 nm from the AIA instrument at distances of 1.0–1.4 solar radii from the Sun’s center, (b) the images of the white corona from the LASCO C2 and C3 coronographs at R ≈ 2.1–30 solar radii. Investigations indicated the validity of regularities, established earlier for the cases of relatively slow CMEs (at velocities <1500 km/s): (1) The shock front is formed, when the velocity of a leading part of a CME relative to the undisturbed solar wind becomes greater than the local Alfven velocity of wind, which corresponds to the phenomenon of “transition through the sound velocity” for magnetized plasma. (2) The change in the width of a shock front and, accordingly, in the energy dissipation mechanism occurs in a shock front from a “collisional” one, at distances from the Sun’s center lower than 10 solar radii, to a “collisionless” one, at distances greater than ten solar radii. During the event of January 27, 2012, it was possible to investigate in more detail the process of transition from the collisional to collisionless shock front. It was found that the longitudinal length of a shock front, excited by a fast CME at distances lower than 6 solar radii, increased almost 10 times as compared to a slower CME. One of the main causes for this increase, along with a high velocity, is the fact that the motion of CME has occurred in the plane of the belt of coronal streamers. It is concluded that, at distances lower than 6 solar radii, the shock front structure ahead of the CME is of “parallel” type; that is, the angle between the vector of an undisturbed magnetic field and the normal to the front was close to 0°.

Recession and Morphological Changes of the Debris-Covered Milam Glacier in Gori Ganga Valley, Central Himalaya, India, Derived From Satellite Data

We analysed the recession of the Milam glacier in the Gori Ganga River valley, Uttarakhand Himalaya using historical plane-table survey maps, topographical maps, Corona image (1968), Landsat 5 TM (1990), Landsat 7 ETM+ (2001) and Sentinel 2 (2017) satellite data. We estimate that the Milam glacier has receded by 1565.4 ± 20.6 m (31.9 ± 0.4 m a-1) over the period 1968-2017, while lower recession rate (21.1 ± 1.7 m a-1) was observed between 2001 and 2017. The Milam glacier lost 2.27 ± 0.06 km2 of its area from 1968 to 2017 due to recession. Two tributary glaciers detached from the main trunk between 1990 and 2017, which indicates glacier thinning and melting. The glacier recession also resulted in deformation of moraine ridges on either sides in lower ablation zone of Milam glacier, which is caused due to the removal of basal ice support caused by glacier melting.