scholarly journals Giant ice rings in Southern Baikal: multi-satellite data help to study ice cover evolution and eddies under ice

2021 ◽  
Author(s):  
Alexei V. Kouraev ◽  
Elena A. Zakharova ◽  
Andrey G. Kostianoy ◽  
Mikhail N. Shimaraev ◽  
Lev V. Desinov ◽  
...  
Keyword(s):  
Satellite Data ◽  
Eddy Currents ◽  
Temporal Evolution ◽  
Meteorological Data ◽  
Ice Cover ◽  
Water Dynamics ◽  
Water Infiltration ◽  
Landsat 8 ◽  
Heat And Mass Exchange ◽  
Large Lakes

Abstract. Ice cover on lakes is subject to atmospheric forcing from above and the influence of water dynamics and heat flux from below. One characteristic example of these influences in some large lakes, such as Lake Baikal in Russia, are the giant ice rings and the associated eddies under the ice cover. In April 2020 a giant ice ring appeared in Southern Baikal and a lens-like eddy was detected below the ice. We analysed the temporal evolution of ice cover using satellite images from multiple satellite missions – MODIS on Terra and Aqua, Sentinel-1 SAR, Sentinel 2 MSI, Landsat-8, PlanetScope, satellite photography from International Space Station, and radar altimetry data from Jason-3. Satellite imagery and meteorological data show an unusual temporal evolution of ice colour in April 2020, which was explained by water infiltration into the ice followed by the competing influences of cold air from above and the warm eddy below the ice. Tracking of ice floe displacement also makes it possible to estimate eddy currents and their influence on the upper water layer. Multi-satellite data contribute to a better understanding of the evolution of ice cover in the presence of eddies, role of eddies in horizontal and vertical heat and mass exchange and their impact on the chemistry and biology of the lakes and on human activity.

scholarly journals Giant ice rings in southern Baikal: multi-satellite data help to study ice cover dynamics and eddies under ice

2021 ◽  
Vol 15 (9) ◽  
pp. 4501-4516
Author(s):  
Alexei V. Kouraev ◽  
Elena A. Zakharova ◽  
Andrey G. Kostianoy ◽  
Mikhail N. Shimaraev ◽  
Lev V. Desinov ◽  
...  
Keyword(s):  
Satellite Data ◽  
Eddy Currents ◽  
Meteorological Data ◽  
Ice Cover ◽  
Temporal Changes ◽  
Water Dynamics ◽  
Water Infiltration ◽  
Landsat 8 ◽  
Heat And Mass Exchange ◽  
Large Lakes

Abstract. Ice cover on lakes is subject to atmospheric forcing from above and the influence of water dynamics and heat flux from below. One characteristic example of these influences in some large lakes, such as Lake Baikal in Russia, are the giant ice rings and the associated eddies under the ice cover. In April 2020 a giant ice ring appeared in southern Baikal, and a lens-like eddy was detected below the ice. We analysed the temporal changes of ice cover using satellite images from multiple satellite missions – MODIS on Terra and Aqua, Sentinel-1 SAR, Sentinel 2 MSI, Landsat 8, PlanetScope, satellite photography from the International Space Station, and radar altimetry data from Jason-3. Satellite imagery and meteorological data show unusual temporal changes of ice colour in April 2020, which were explained by water infiltration into the ice followed by the competing influences of cold air from above and the warm eddy below the ice. Tracking of ice floe displacement also makes it possible to estimate eddy currents and their influence on the upper water layer. Multi-satellite data contribute to a better understanding of the development of ice cover in the presence of eddies, the role of eddies in horizontal and vertical heat and mass exchange, and their impact on the chemistry and biology of the lakes and on human activity.

SATELLITE DATA FOR INVESTIGATION OF RECENT STATE AND PROCESSES IN THE SIVASH BAY

2017 ◽  
Author(s):  
Ekaterina Shchurova ◽  
Ekaterina Shchurova ◽  
Rimma Stanichnaya ◽  
Rimma Stanichnaya ◽  
Sergey Stanichny ◽  
...  
Keyword(s):  
Satellite Data ◽  
Water Exchange ◽  
High Salinity ◽  
Meteorological Data ◽  
Sea Surface ◽  
Azov Sea ◽  
Seasonal Wind ◽  
Ice Regime ◽  
Very High

Sivash bay is the shallow-water lagoon of the Azov Sea. Restricted water exchange and high evaporation form Sivash as the basin with very high salinity. This factor leads to different from the Azov Sea thermal and ice regimes of Sivash. Maine aim of the study presented to investigate recent state and changes of the characteristics and processes in the basin using satellite data. Landsat scanners TM, ETM+, OLI, TIRS together with MODIS and AVHRR were used. Additionally NOMADS NOAA and MERRA meteorological data were analyzed. The next topics are discussed in the work: 1. Changes of the sea surface temperature, ice regime and relation with salinity. 2. Coastal line transformation – long term and seasonal, wind impact. 3. Manifestation of the Azov waters intrusions through the Arabat spit, preferable wind conditions.

Worldview-2 and Landsat 8 Satellite Data for Seaweed Mapping along Karachi Coast

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Muhammad Danish Siddiqui ◽  
Arjumand Z Zaidi
Keyword(s):  
Satellite Data ◽  
Spatial Scales ◽  
Economic Value ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Geographical Information ◽  
Landsat 8 ◽  
Coverage Area ◽  
Breeding Sites ◽  
Marine Plant

<span>Seaweed is a marine plant or algae which has economic value in many parts of the world. The purpose of <span>this study is to evaluate different satellite sensors such as high-resolution WorldView-2 (WV2) satellite <span>data and Landsat 8 30-meter resolution satellite data for mapping seaweed resources along the coastal<br /><span>waters of Karachi. The continuous monitoring and mapping of this precious marine plant and their <span>breeding sites may not be very efficient and cost effective using traditional survey techniques. Remote <span>Sensing (RS) and Geographical Information System (GIS) can provide economical and more efficient <span>solutions for mapping and monitoring coastal resources quantitatively as well as qualitatively at both <span>temporal and spatial scales. Normalized Difference Vegetation Indices (NDVI) along with the image <span>enhancement techniques were used to delineate seaweed patches in the study area. The coverage area of <span>seaweed estimated with WV-2 and Landsat 8 are presented as GIS maps. A more precise area estimation <span>wasachieved with WV-2 data that shows 15.5Ha (0.155 Km<span>2<span>)of seaweed cover along Karachi coast that is <span>more representative of the field observed data. A much larger area wasestimated with Landsat 8 image <span>(71.28Ha or 0.7128 Km<span>2<span>) that was mainly due to the mixing of seaweed pixels with water pixels. The <span>WV-2 data, due to its better spatial resolution than Landsat 8, have proven to be more useful than Landsat<br /><span>8 in mapping seaweed patches</span></span></span></span></span></span></span></span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span></span></span></span></span>

scholarly journals Using Satellite Data for CBRN (Chemical, Biological, Radiological, and Nuclear) Threat Detection, Monitoring, and Modelling

2021 ◽  
Author(s):  
Gary Sutlieff ◽  
Lucy Berthoud ◽  
Mark Stinchcombe
Keyword(s):  
Satellite Data ◽  
Meteorological Data ◽  
Atmospheric Composition ◽  
Chemical Detection ◽  
List Type ◽  
Data Types ◽  
Wide Range ◽  
Future Technologies ◽  
The Impact ◽  
Near Future

Abstract CBRN (Chemical, Biological, Radiological, and Nuclear) threats are becoming more prevalent, as more entities gain access to modern weapons and industrial technologies and chemicals. This has produced a need for improvements to modelling, detection, and monitoring of these events. While there are currently no dedicated satellites for CBRN purposes, there are a wide range of possibilities for satellite data to contribute to this field, from atmospheric composition and chemical detection to cloud cover, land mapping, and surface property measurements. This study looks at currently available satellite data, including meteorological data such as wind and cloud profiles, surface properties like temperature and humidity, chemical detection, and sounding. Results of this survey revealed several gaps in the available data, particularly concerning biological and radiological detection. The results also suggest that publicly available satellite data largely does not meet the requirements of spatial resolution, coverage, and latency that CBRN detection requires, outside of providing terrain use and building height data for constructing models. Lastly, the study evaluates upcoming instruments, platforms, and satellite technologies to gauge the impact these developments will have in the near future. Improvements in spatial and temporal resolution as well as latency are already becoming possible, and new instruments will fill in the gaps in detection by imaging a wider range of chemicals and other agents and by collecting new data types. This study shows that with developments coming within the next decade, satellites should begin to provide valuable augmentations to CBRN event detection and monitoring. Article Highlights There is a wide range of existing satellite data in fields that are of interest to CBRN detection and monitoring. The data is mostly of insufficient quality (resolution or latency) for the demanding requirements of CBRN modelling for incident control. Future technologies and platforms will improve resolution and latency, making satellite data more viable in the CBRN management field

scholarly journals Non-Binary Snow Index for Multi-Component Surfaces

2021 ◽  
Vol 13 (14) ◽  
pp. 2777
Author(s):  
Mario Arreola-Esquivel ◽  
Carina Toxqui-Quitl ◽  
Maricela Delgadillo-Herrera ◽  
Alfonso Padilla-Vivanco ◽  
Gabriel Ortega-Mendoza ◽  
...  
Keyword(s):  
Spectral Characteristics ◽  
Ice Cover ◽  
Landsat 8 ◽  
Water Index ◽  
Bare Land ◽  
Snow Water ◽  
Precision Assessment ◽  
Normalized Difference Snow Index ◽  
Sentinel 2A ◽  
Water Vegetation

A Non-Binary Snow Index for Multi-Component Surfaces (NBSI-MS) is proposed to map snow/ice cover. The NBSI-MS is based on the spectral characteristics of different Land Cover Types (LCTs), such as snow, water, vegetation, bare land, impervious, and shadow surfaces. This index can increase the separability between NBSI-MS values corresponding to snow from other LCTs and accurately delineate the snow/ice cover in non-binary maps. To test the robustness of the NBSI-MS, regions in Greenland and France–Italy where snow interacts with highly diversified geographical ecosystems were examined. Data recorded by Landsat 5 TM, Landsat 8 OLI, and Sentinel-2A MSI satellites were used. The NBSI-MS performance was also compared against the well-known Normalized Difference Snow Index (NDSI), NDSII-1, S3, and Snow Water Index (SWI) methods and evaluated based on Ground Reference Test Pixels (GRTPs) over non-binarized results. The results show that the NBSI-MS achieved an overall accuracy (OA) ranging from 0.99 to 1 with kappa coefficient values in the same range as the OA. The precision assessment confirmed the performance superiority of the proposed NBSI-MS method for removing water and shadow surfaces over the compared relevant indices.

scholarly journals EXTRACTING BUILT-UP FEATURES IN COMPLEX BIOPHYSICAL ENVIRONMENTS BY USING A LANDSAT BANDS RATIO

2020 ◽  
Vol XLIV-M-2-2020 ◽  
pp. 79-85
Author(s):  
A. H. Ngandam Mfondoum ◽  
P. G. Gbetkom ◽  
R. Cooper ◽  
S. Hakdaoui ◽  
M. B. Mansour Badamassi
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Satellite Data ◽  
Kappa Coefficient ◽  
Landsat 8 ◽  
Experimental Site ◽  
Soil Features ◽  
Mixed Pixels ◽  
Shortwave Infrared ◽  
Normalization Process

Abstract. This paper addresses the remote sensing challenging field of urban mixed pixels on a medium spatial resolution satellite data. The tentatively named Normalized Difference Built-up and Surroundings Unmixing Index (NDBSUI) is proposed by using Landsat-8 Operational Land Imager (OLI) bands. It uses the Shortwave Infrared 2 (SWIR2) as the main wavelength, the SWIR1 with the red wavelengths, for the built-up extraction. A ratio is computed based on the normalization process and the application is made on six cities with different urban and environmental characteristics. The built-up of the experimental site of Yaoundé is extracted with an overall accuracy of 95.51% and a kappa coefficient of 0.90. The NDBSUI is validated over five other sites, chosen according to Cameroon’s bioclimatic zoning. The results are satisfactory for the cities of Yokadouma and Kumba in the bimodal and monomodal rainfall zones, where overall accuracies are up to 98.9% and 97.5%, with kappa coefficients of 0.88 and 0.94 respectively, although these values are close to those of three other indices. However, in the cities of Foumban, Ngaoundéré and Garoua, representing the western highlands, the high Guinea savannah and the Sudano-sahelian zones where built-up is more confused with soil features, overall accuracies of 97.06%, 95.29% and 74.86%, corresponding to 0.918, 0.89 and 0.42 kappa coefficients were recorded. Difference of accuracy with EBBI, NDBI and UI are up to 31.66%, confirming the NDBSUI efficiency to automate built-up extraction and unmixing from surrounding noises with less biases.

scholarly journals Surface Heat Budget estimation for Laurance Lake, US

2021 ◽  
Vol 877 (1) ◽  
pp. 012005
Author(s):  
Dahlia S. Abed-Zaid ◽  
Hussein A. M. Al-Zubaidi
Keyword(s):  
Surface Temperature ◽  
Water Surface ◽  
Heat Budget ◽  
Meteorological Data ◽  
Longwave Radiation ◽  
Atmospheric Conditions ◽  
Large Lakes ◽  
Water Surface Temperature ◽  
Maximum Water ◽  
The Many

Abstract Estimating heat budget factors are important to understand the many physical processes of large lakes and their reaction to the atmosphere. Some of these components are affected by water temperature, while the other depends on atmospheric conditions. This paper estimates the total heat flux for Lawrence lake via a code developed in MATLAB environment. The code can deal with different time resolutions if the lake water surface temperature data were at different time resolutions from the meteorological data. Results showed that solar energy peaks at 842 Watt/m2 at 540 Julian day, which is very normal for a sunny summer day, while the longwave radiation has 204 Watt/m2 as a min value. The back radiation did not make any reaction for the variation, but it revealed a small gradient. Furthermore, evaporation recorded - 67 Watt/m2 as a minimum value at 659 Julian day and 360 Watt/m2 as a maximum value at 578.43 Julian day close to the maximum water surface temperature event.

scholarly journals Evapotranspiration Estimation Using Remote Sensing Technology Based on a SEBAL Model in the Upper Reaches of the Huaihe River Basin

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1599
Author(s):  
Linshan Tan ◽  
Kaiyuan Zheng ◽  
Qiangqiang Zhao ◽  
Yanjuan Wu
Keyword(s):  
Remote Sensing ◽  
Meteorological Data ◽  
Regional Scale ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Huaihe River ◽  
Infiltration Capacity ◽  
Mountain Area ◽  
Study Region ◽  
Sebal Model

Understanding the spatial and temporal variations of evapotranspiration (ET) is vital for water resources planning and management and drought monitoring. The development of a satellite remote sensing technique is described to provide insight into the estimation of ET at a regional scale. In this study, the Surface Energy Balance Algorithm for Land (SEBAL) was used to calculate the actual ET on a daily scale from Landsat-8 data and daily ground-based meteorological data in the upper reaches of Huaihe River on 20 November 2013, 16 April 2015 and 23 March 2018. In order to evaluate the performance of the SEBAL model, the daily SEBAL ET (ETSEBAL) was compared against the daily reference ET (ET0) from four theoretical methods: the Penman-Monteith (P-M), Irmak-Allen (I-A), the Turc, and Jensen-Haise (J-H) method, the ETMOD16 product from the MODerate Resolution Imaging Spectrometer (MOD16) and the ETVIC from Variable Infiltration Capacity Model (VIC). A linear regression equation and statistical indices were used to model performance evaluation. The results showed that the daily ETSEBAL correlated very well with the ET0, ETMOD16, and ETVIC, and bias between the ETSEBAL with them was less than 1.5%. In general, the SEBAL model could provide good estimations in daily ET over the study region. In addition, the spatial-temporal distribution of ETSEBAL was explored. The variation of ETSEBAL was significant in seasons with high values during the growth period of vegetation in March and April and low values in November. Spatially, the daily ETSEBAL values in the mountain area were much higher than those in the plain areas over the study region. The variability of ETSEBAL in this study area was positively correlated with elevation and negatively correlated with surface reflectance, which implies that elevation and surface reflectance are the important factors for predicting ET in this study area.

scholarly journals Use of satellite data for detecting icebergs and evaluating the iceberg threats

2018 ◽  
Vol 58 (4) ◽  
pp. 537-551 ◽  
Author(s):  
I. A. Bychkova ◽  
V. G. Smirnov
Keyword(s):  
Satellite Data ◽  
Radar Data ◽  
Arctic Shelf ◽  
The Arctic ◽  
Satellite Monitoring ◽  
Landsat 8 ◽  
Space Resolution ◽  
Detection Techniques ◽  
Satellite Radar ◽  
High Space

Te methods of satellite monitoring of dangerous ice formations, namely icebergs in the Arctic seas, representing a threat to the safety of navigation and economic activity on the Arctic shelf are considered. Te main objective of the research is to develop methods for detecting icebergs using satellite radar data and high space resolution images in the visible spectral range. Te developed method of iceberg detection is based on statistical criteria for fnding gradient zones in the analysis of two-dimensional felds of satellite images. Te algorithms of the iceberg detection, the procedure of the false target identifcation, and determination the horizontal dimensions of the icebergs and their location are described. Examples of iceberg detection using satellite information with high space resolution obtained from Sentinel-1 and Landsat-8 satellites are given. To assess the iceberg threat, we propose to use a model of their drif, one of the input parameters of which is the size of the detected objects. Tree possible situations of observation of icebergs are identifed, namely, the «status» state of objects: icebergs on open water; icebergs in drifing ice; and icebergs in the fast ice. At the same time, in each of these situations, the iceberg can be grounded, that prevents its moving. Specifc features of the iceberg monitoring at various «status» states of them are considered. Te «status» state of the iceberg is also taken into account when assessing the degree of danger of the detected object. Te use of iceberg detection techniques based on satellite radar data and visible range images is illustrated by results of monitoring the coastal areas of the Severnaya Zemlya archipelago. Te approaches proposed to detect icebergs from satellite data allow improving the quality and efciency of service for a wide number of users with ensuring the efciency and safety of Arctic navigation and activities on the Arctic shelf.

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