Estimation of Deglaciation through Remote Sensing Techniques in Chandra-Bhaga Basin, Western Himalaya

2021 ◽  
Vol 7 (1) ◽  
pp. 79-88
Author(s):  
Shruti Dutta ◽  
AL. Ramanathan
Keyword(s):  
Remote Sensing ◽  
Continuous Monitoring ◽  
Hydrological Cycle ◽  
Western Himalaya ◽  
Western Himalayas ◽  
Hindu Kush ◽  
Micro Level ◽  
Spatio Temporal ◽  
Remote Sensing Techniques ◽  
Increasing Temperature

Glaciers act as natural indicators of climate response and natural buffers of the hydrological cycle. Hence, continuous monitoring of glaciers is very crucial for which remote sensing techniques have emerged as a powerful tool to understand the micro-level variation and dynamics of glaciers. Unfortunately, a database involving complete basin-level approach and an extensive temporal range is not available for the entire Chandra-Bhaga (CB) sub-basin. Thus, the present investigation attempts to account for the extent of deglaciation in the CB basin showing that 16.7 percent of the glaciated area has been lost during 1989-2019. Moreover, the last three decades have witnessed a rapid rate of loss for small and medium-sized glaciers as compared to larger glaciers. Adding to it, the basin has also shown an upwards shift of mean elevation in this period. Over the last decade, an increasing temperature in the western Himalayas and Hindu Kush regions, as asserted by previous studies, have led to spatio-temporal changes in the glaciated area. The extent of deglaciation alongwith the glacier-climate behaviour and response can also provide a link to measure the topographical parameters.

scholarly journals Hydrogeomorphology as a Tool in the Evolutionary Analysis of the Dynamic Landscape—Application to Larrodrigo, Salamanca, Spain

Land ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1407
Author(s):  
Lorena Lombana ◽  
Antonio Martínez-Graña ◽  
Marco Criado ◽  
Carlos Palacios
Keyword(s):  
Remote Sensing ◽  
Management Strategies ◽  
Evolutionary Analysis ◽  
Surface Data ◽  
Dynamic Landscape ◽  
Density Surface ◽  
Fluvial Landscape ◽  
Spatio Temporal ◽  
Remote Sensing Techniques ◽  
Definition Of

Evolutionary analysis of the fluvial landscape provides relevant inputs for the environmental management of a territory, in such a way that the understanding of the dynamics of fluvial spaces becomes a preponderant factor in the definition of protection and management strategies. Although the development of geographic information systems is a step forward in the study of the landscape, it is necessary to establish methodological frameworks that make remote sensing techniques available at multiple spatio-temporal scales, especially in basins with high levels of intervention. In the present study, we develop a methodology for the analysis of the fluvial landscape development in the last century of a highly modified water body, through the detailed study of hydrogeomorphic elements, using remote sensing techniques including high-density surface data (LiDAR) and historical aerial imageries; when supported by fieldwork, these allow for the identification of the sequence of sedimentation–erosion zones, differentiating in detail the zones denominated as areas of current erosion, accretion zones, and historical erosion zones. An application of the methodology was carried out in the Larrodrigo stream, located in Salamanca, Spain.

Bayesian Spatio-temporal Geostatistics-based Method for Multiple Satellite Products Fusion and Downscaling

2020 ◽  
Author(s):  
Yanchen Bo
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Spatial Resolution ◽  
Land Surface ◽  
Satellite Remote Sensing ◽  
Hydrological Cycle ◽  
Microwave Remote Sensing ◽  
Earth Surface ◽  
Spatio Temporal ◽  
High Level

<p>High-level satellite remote sensing products of Earth surface play an irreplaceable role in global climate change, hydrological cycle modeling and water resources management, environment monitoring and assessment. Earth surface high-level remote sensing products released by NASA, ESA and other agencies are routinely derived from any single remote sensor. Due to the cloud contamination and limitations of retrieval algorithms, the remote sensing products derived from single remote senor are suspected to the incompleteness, low accuracy and less consistency in space and time. Some land surface remote sensing products, such as soil moisture products derived from passive microwave remote sensing data have too coarse spatial resolution to be applied at local scale. Fusion and downscaling is an effective way of improving the quality of satellite remote sensing products.</p><p>We developed a Bayesian spatio-temporal geostatistics-based framework for multiple remote sensing products fusion and downscaling. Compared to the existing methods, the presented method has 2 major advantages. The first is that the method was developed in the Bayesian paradigm, so the uncertainties of the multiple remote sensing products being fused or downscaled could be quantified and explicitly expressed in the fusion and downscaling algorithms. The second advantage is that the spatio-temporal autocorrelation is exploited in the fusion approach so that more complete products could be produced by geostatistical estimation.</p><p>This method has been applied to the fusion of multiple satellite AOD products, multiple satellite SST products, multiple satellite LST products and downscaling of 25 km spatial resolution soil moisture products. The results were evaluated in both spatio-temporal completeness and accuracy.</p>

Resolving spatial dynamics at polar latitudes using the GROMOS-C radiometer on Svalbard and the Nordic meteor radar cluster

2020 ◽  
Author(s):  
Gunter Stober ◽  
Franziska Schranz ◽  
Chris Hall ◽  
Alexander Kozlovsky ◽  
Mark Lester ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Temporal Resolution ◽  
Lower Thermosphere ◽  
Winter Season ◽  
Spatial Characteristic ◽  
Small Scale ◽  
Meteor Radar ◽  
Atmospheric Waves ◽  
Spatio Temporal ◽  
Remote Sensing Techniques

<p>The middle polar atmosphere dynamics is driven by atmospheric waves from the planetary scale to small scale perturbation due to gravity waves. The different atmospheric waves are characterized by their temporal and spatial variability posing challenges to ground-based remote sensing techniques to disentangle and resolve the spatio-temporal ambiguity. Here we present two ground-based remote sensing techniques to resolving spatio-temporal variability at the polar middle atmosphere.</p><p>Since 2017 the GROMOS-C radiometer measures ozone and winds at NyÅlesund (78.9°N, 11.9°E) on Svalbard. The radiometer employs four beams in the cardinal directions at 22.5° elevation angle to retrieve ozone profiles and winds at altitudes between 30-75 km. the temporal resolution of the ozone retrievals is 30 minutes. Further, we obtain daily mean winds. Due to the high polar latitude the spatial separation between the beams at stratospheric altitudes covers several degrees in longitude to infer spatial gradients in the ozone densities and their perturbation due to planetary waves.</p><p>Another recently established ground-based remote sensing approach to retrieve the spatial characteristic at the mesosphere and lower thermosphere (MLT) is provided by the Nordic meteor radar cluster consisting of the meteor radars at Tromsø, Alta, Esrange, Sodankylä and on Svalbard. Since October 2019 horizontally resolved winds are obtained using a 3DVAR approach with a temporal resolution of 30 minutes and a vertical resolution of 2 km. Here we present preliminary results to infer horizontal wavelength spectra, the tidal variability as well as gravity activity of the winter season 2019/20.</p><p>Both datasets are of high value for data assimilation into weather forecast and reanalysis models or for cross-comparisons and validation of meteorological analysis systems (e.g. NAVGEM-HA).</p>

Water vapor measurements in central México using two remote sensing techniques: FTIR spectroscopy and GPS

2020 ◽  
Author(s):  
Alain Zuber ◽  
Wolfgang Stremme ◽  
Michel Grutter ◽  
David Adams ◽  
Thomas Blumenstock ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Ftir Spectroscopy ◽  
Hydrological Cycle ◽  
Atmospheric Water Vapor ◽  
Central Mexico ◽  
Atmospheric Water ◽  
Transport Pathways ◽  
Rainy Weather ◽  
Remote Sensing Techniques

<p><span>Atmospheric water vapor plays a key role in weather and climate. Knowledge about its variability, diurnal and seasonal cycles, as well as its long-term trend is necessary to improve our understanding of the hydrological cycle. H2O total columns are measured by the two remote sensing techniques, ground-based solar absorption FTIR spectroscopy and a GPS (Global Positioning System) receiver, over a site in central Mexico. The Altzomoni Atmospheric Observatory (3989 m a.s.l., 19.32ºN, 98.65ºW) is a high altitude station located within the Izta-Popo national park, 60 km SE from Mexico City. The time series of GPS and FTIR show a high correlation between coincident hourly means. Both techniques are complementary since despite that GPS works throughout day and night and also in cloudy and rainy weather conditions, the FTIR data provides in addition altitude-resolved information about the atmospheric water vapor and permits to distinguish different isotopes.</span></p><p><span>In this study, we show water vapor columns in the 2013 to 2019 period for this region retrieved from FTIR and GPS measurements and preliminary results about their isotopic composition (H216O, H218O and HD16O). We discuss the opportunity to study the hydrological cycle in central Mexico using the relationship between light and heavy isotopes, a relationship that gives valuable information about the sources and transport pathways.</span></p>

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