scholarly journals High-resolution multispectral mapping facies on glacier surface in the Arctic using WorldView-3 data

2020 ◽  
Vol 10 (1) ◽  
pp. 23-36 ◽  
Author(s):  
Alvarinho J. Luis ◽  
Shubham Singh
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Object Oriented ◽  
The Arctic ◽  
Glacier Mass Balance ◽  
Landsat 8 ◽  
Glacier Surface ◽  
Near Surface ◽  
Facies Classification

Glaciers are important and sensitive part of our environment which can be used as indicator of global warming and climate change. Glacier facies represent distinct regions of a glacier surface characterized by near surface structure and density that develop as a function of spatial variations in surface melt and accumulation. The facies mapping aids in delineating different zones of the glacier, which are useful in computing glacier mass balance and modeling. In this study we tested traditional and advanced classification techniques on the Edithbreen glacier situated in Ny-lesund, Svalbard, using WorldView-3 and Landsat 8 OLI. The comparison of the accuracy was conducted using error matrices. Six measures of accuracy were derived from the error matrices and were compared with each other to find the method delivering the most adequate output for facies mapping. The pixel-based approach applied to Landsat-8 data yielded higher accuracies (>80%) when compared to that. The object-oriented classification revealed a much better accuracy and high kappa coefficient for both low and high-resolution datasets. The study clearly indicates that the object-oriented classification provides better results for glacier facies classification when high spatial resolution is used, but for lower spatial resolution, pixel-based methods are adequate.

scholarly journals High-resolution interactive modelling of the mountain glacier–atmosphere interface: an application over the Karakoram

2013 ◽  
Vol 7 (1) ◽  
pp. 103-144 ◽  
Author(s):  
E. Collier ◽  
T. Mölg ◽  
F. Maussion ◽  
D. Scherer ◽  
C. Mayer ◽  
...  
Keyword(s):  
High Resolution ◽  
Mass Balance ◽  
Land Surface ◽  
Traditional Approach ◽  
Coupled Model ◽  
Glacier Mass Balance ◽  
Glacier Surface ◽  
Mountain Glacier ◽  
Near Surface ◽  
Basin Scale

Abstract. The traditional approach to simulations of alpine glacier mass balance (MB) has been one-way, or offline, thus precluding feedbacks from changing glacier surface conditions on the atmospheric forcing. In addition, alpine glaciers have been only simply, if at all, represented in atmospheric models to date. Here, we extend a recently presented, novel technique for simulating glacier–atmosphere interactions without the need for statistical downscaling, through the use of a coupled high-resolution mesoscale atmospheric and physically-based mass balance modelling system that includes glacier MB and energy balance feedbacks to the atmosphere. We compare the model results over the Karakoram region of the northwestern Himalaya with both remote sensing data and in situ glaciological and meteorological measurements for the ablation season of 2004. We find that interactive coupling has a localized but appreciable impact on the near-surface meteorological forcing data and that incorporation of MB processes improves the simulation of variables such as land surface temperature and snow albedo. Furthermore, including feedbacks from the MB model has a non-negligible effect on simulated mass balance, reducing modelled ablation, on average, by 0.1 m w.e. (−6.0%) to a total of −1.5 m w.e. between 25 June–31 August 2004. The interactively coupled model shows promise as a new, multi-scale tool for explicitly resolving atmospheric-MB processes of mountain glaciers at the basin scale.

scholarly journals High-resolution interactive modelling of the mountain glacier–atmosphere interface: an application over the Karakoram

2013 ◽  
Vol 7 (3) ◽  
pp. 779-795 ◽  
Author(s):  
E. Collier ◽  
T. Mölg ◽  
F. Maussion ◽  
D. Scherer ◽  
C. Mayer ◽  
...  
Keyword(s):  
High Resolution ◽  
Mass Balance ◽  
Land Surface ◽  
Traditional Approach ◽  
Coupled Model ◽  
Glacier Mass Balance ◽  
Glacier Surface ◽  
Mountain Glacier ◽  
Near Surface ◽  
Basin Scale

Abstract. The traditional approach to simulations of alpine glacier mass balance (MB) has been one-way, or offline, thus precluding feedbacks from changing glacier surface conditions on the atmospheric forcing. In addition, alpine glaciers have been only simply, if at all, represented in atmospheric models to date. Here, we extend a recently presented, novel technique for simulating glacier–atmosphere interactions without the need for statistical downscaling, through the use of a coupled high-resolution mesoscale atmospheric and physically-based climatic mass balance (CMB) modelling system that includes glacier CMB feedbacks to the atmosphere. We compare the model results over the Karakoram region of the northwestern Himalaya with remote sensing data for the ablation season of 2004 as well as with in situ glaciological and meteorological measurements from the Baltoro glacier. We find that interactive coupling has a localized but appreciable impact on the near-surface meteorological forcing data and that incorporation of CMB processes improves the simulation of variables such as land surface temperature and snow albedo. Furthermore, including feedbacks from the glacier model has a non-negligible effect on simulated CMB, reducing modelled ablation, on average, by 0.1 m w.e. (−6.0%) to a total of −1.5 m w.e. between 25 June–31 August 2004. The interactively coupled model shows promise as a new, multi-scale tool for explicitly resolving atmospheric-CMB processes of mountain glaciers at the basin scale.

scholarly journals Modeling spatial structure of thermokarst lake fields in permafrost of Western Siberia based on satellite images

2019 ◽  
Vol 19 (1) ◽  
pp. 1-10
Author(s):  
Vladimir Yu. Polishchuk ◽  
Ildar N. Muratov ◽  
Yury M. Polishchuk
Keyword(s):  
Spatial Structure ◽  
Size Distribution ◽  
Spatial Resolution ◽  
Satellite Images ◽  
Western Siberia ◽  
High Spatial Resolution ◽  
The Arctic ◽  
Landsat 8 ◽  
Small Lakes ◽  
Thermokarst Lakes

Deciphering the satellite images of medium and high spatial resolution of the northern territories of Western Siberia has been carried out using geoinformation system ArcGIS 10.3. Images of medium resolution Landsat-8 and high resolution Kanopus-V were used. Kanopus-V images alluded to determine the number and areas of small lakes, which are considered as intensive sources of methane emission into the atmosphere from thermokarst lakes. Data on the spatial characteristics of thermokarst lakes were obtained. Based on the integration of images of medium and high spatial resolution, a synthesized histogram of the distribution of lakes in a wide range of sizes was constructed, taking into account small lakes. The obtained histogram was approximated by a lognormal distribution law by the Pearson criterion with a probability of 0.99. Based on the geo-simulation approach, a new model of the spatial structure of the fields of thermokarst lakes is presented, taking into account the lognormal law of the lake size-distribution. Algorithms for modeling the spatial structure of the fields of thermokarst lakes are described. An example of modeling the field of thermokarst lakes with a lognormal law of their size-distribution is given. The practical applicability of the previously developed model with an exponential distribution of lakes in size, based on data from Landsat images, has been experimentally confirmed. The results can be used to obtain predictions of the dynamics of methane emissions from the thermokarst lakes of the Arctic zone of Northern Eurasia for the coming decades in the context of climate changes.

scholarly journals Modeling spatial structure of thermokarst lake fields in permafrost of Western Siberia based on satellite images

2019 ◽  
Vol 19 (1) ◽  
pp. 1-10
Author(s):  
Vladimir Yu Polishchuk ◽  
Ildar N Muratov ◽  
Yury M Polishchuk
Keyword(s):  
Spatial Structure ◽  
Size Distribution ◽  
Spatial Resolution ◽  
Satellite Images ◽  
Western Siberia ◽  
High Spatial Resolution ◽  
The Arctic ◽  
Landsat 8 ◽  
Small Lakes ◽  
Thermokarst Lakes

Deciphering the satellite images of medium and high spatial resolution of the northern territories of Western Siberia has been carried out using geoinformation system ArcGIS 10.3. Images of medium resolution Landsat-8 and high resolution Kanopus-V were used. Kanopus-V images alluded to determine the number and areas of small lakes, which are considered as intensive sources of methane emission into the atmosphere from thermokarst lakes. Data on the spatial characteristics of thermokarst lakes were obtained. Based on the integration of images of medium and high spatial resolution, a synthesized histogram of the distribution of lakes in a wide range of sizes was constructed, taking into account small lakes. The obtained histogram was approximated by a lognormal distribution law by the Pearson criterion with a probability of 0.99. Based on the geo-simulation approach, a new model of the spatial structure of the fields of thermokarst lakes is presented, taking into account the lognormal law of the lake size-distribution. Algorithms for modeling the spatial structure of the fields of thermokarst lakes are described. An example of modeling the field of thermokarst lakes with a lognormal law of their size-distribution is given. The practical applicability of the previously developed model with an exponential distribution of lakes in size, based on data from Landsat images, has been experimentally confirmed. The results can be used to obtain predictions of the dynamics of methane emissions from the thermokarst lakes of the Arctic zone of Northern Eurasia for the coming decades in the context of climate changes.

Spatial downscaling method of glacier surface albedo based on deep learning

2021 ◽  
Author(s):  
Fuming Xie ◽  
Shiyin Liu ◽  
Yu Zhu ◽  
Yongpeng Gao ◽  
Kunpeng Wu ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Glacier Mass Balance ◽  
Landsat 8 ◽  
Glacier Surface ◽  
Spatial Changes ◽  
Moderate Resolution ◽  
Application Potential ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Fully Connected

<p>Heat exchange in glacier region is strongly affected by the interaction between solar radiation and glacial surface, and albedo is an important index to quantitatively describe energy balance in this interaction process. Under the background of global warming, the observation and modeling of albedo are of great significance in the aspects including identification of snow and ice darkening or pollution, reconstruction of glacier mass balance and inversion of supraglacial debris expansion. However, insufficient observations, coupled with low spatial resolution of satellite derived products (250-1000m), make it difficult to analyze spatial changes at the glacier scale. A convolution neural network (CNN) contains one or more of the convolution layer, in which inputs are neighborhoods of pixels, resulting in a network that is not fully-connected, has great potential to the image segmentation but is also suited to identifying spatial patterns. Therefore, in this study, a CNN model—U-NET was trained to improve the spatial resolution of albedo products. In the U-NET, we took the shortwave black-sky albedo derived from moderate resolution imaging spectroradiometer (MODIS) boarded on Terra/Aqua satellite with a spatial resolution of 500m as response variable, and raw spectral information, band ratios, and color-to-grayscale conversion from Landsat 8 optical satellite imagery and the topographical components derived from SRTM DEM products as feature variables. The predicted albedo has been validated using observations form radiometer mounted on an automatic weather station at Yazgil glacier in Hunza valley, Karakoram. The results show that the accuracy of U-NET predicted albedo (RMSE = 0.071) is similar to that of MODIS albedo (RMSE = 0.074), which proved that U-NET has great application potential. The high spatial resolution albedo estimated by the model enhances its use in the analysis of spatial changes at the glacier scale, especially for small glaciers, but the optimization of its temporal resolution needs to be further studied.</p>

scholarly journals Deriving VIIRS High-Spatial Resolution Water Property Data over Coastal and Inland Waters Using Deep Convolutional Neural Network

2021 ◽  
Vol 13 (10) ◽  
pp. 1944
Author(s):  
Xiaoming Liu ◽  
Menghua Wang
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Ocean Color ◽  
Super Resolution ◽  
Inland Waters ◽  
Coastal Oceans ◽  
Chl A ◽  
Color Data

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been a reliable source of ocean color data products, including five moderate (M) bands and one imagery (I) band normalized water-leaving radiance spectra nLw(λ). The spatial resolutions of the M-band and I-band nLw(λ) are 750 m and 375 m, respectively. With the technique of convolutional neural network (CNN), the M-band nLw(λ) imagery can be super-resolved from 750 m to 375 m spatial resolution by leveraging the high spatial resolution features of I1-band nLw(λ) data. However, it is also important to enhance the spatial resolution of VIIRS-derived chlorophyll-a (Chl-a) concentration and the water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), as well as other biological and biogeochemical products. In this study, we describe our effort to derive high-resolution Kd(490) and Chl-a data based on super-resolved nLw(λ) images at the VIIRS five M-bands. To improve the network performance over extremely turbid coastal oceans and inland waters, the networks are retrained with a training dataset including ocean color data from the Bohai Sea, Baltic Sea, and La Plata River Estuary, covering water types from clear open oceans to moderately turbid and highly turbid waters. The evaluation results show that the super-resolved Kd(490) image is much sharper than the original one, and has more detailed fine spatial structures. A similar enhancement of finer structures is also found in the super-resolved Chl-a images. Chl-a filaments are much sharper and thinner in the super-resolved image, and some of the very fine spatial features that are not shown in the original images appear in the super-resolved Chl-a imageries. The networks are also applied to four other coastal and inland water regions. The results show that super-resolution occurs mainly on pixels of Chl-a and Kd(490) features, especially on the feature edges and locations with a large spatial gradient. The biases between the original M-band images and super-resolved high-resolution images are small for both Chl-a and Kd(490) in moderately to extremely turbid coastal oceans and inland waters, indicating that the super-resolution process does not change the mean values of the original images.

scholarly journals ZnWO4 Nanoparticle Scintillators for High Resolution X-ray Imaging

Nanomaterials ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1721
Author(s):  
Heon Yong Jeong ◽  
Hyung San Lim ◽  
Ju Hyuk Lee ◽  
Jun Heo ◽  
Hyun Nam Kim ◽  
...  
Keyword(s):  
Particle Size ◽  
Zinc Oxide ◽  
High Resolution ◽  
Tungsten Oxide ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
X Ray ◽  
X Ray Imaging ◽  
Average Size ◽  
And Tungsten

The effect of scintillator particle size on high-resolution X-ray imaging was studied using zinc tungstate (ZnWO4) particles. The ZnWO4 particles were fabricated through a solid-state reaction between zinc oxide and tungsten oxide at various temperatures, producing particles with average sizes of 176.4 nm, 626.7 nm, and 2.127 μm; the zinc oxide and tungsten oxide were created using anodization. The spatial resolutions of high-resolution X-ray images, obtained from utilizing the fabricated particles, were determined: particles with the average size of 176.4 nm produced the highest spatial resolution. The results demonstrate that high spatial resolution can be obtained from ZnWO4 nanoparticle scintillators that minimize optical diffusion by having a particle size that is smaller than the emission wavelength.

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