scholarly journals Online database “See The Sea” for the Caspian Sea

2019 ◽  
Vol 25 ◽  
pp. 79-90 ◽  
Author(s):  
Olga Yu. Lavrova ◽  
Marina I. Mityagina ◽  
Andrey G. Kostianoy

For many years, the primary environmental problem of the Caspian Sea has been oil pollution, which is associated both with oil production and transportation, as well as changes in sea level, leading to secondary pollution, river runoff and even seismic activity, which provokes natural oil spills from the bottom of the sea. Abnormal bloom of waters every year becomes more and more long and covers more and more areas, and also occurs in areas where it was not previously observed. However, the current state of the sea, and the trends of its evolution has not been studied enough, which determines the relevance of the solution of the main task of the ongoing Russian Science Foundation Project “Assessing ecological variability of the Caspian Sea in the current century using satellite remote sensing data”. Implementation of the proposed project will assess the relative contribution of each of the sources of pollution of the Caspian Sea, which varies in different periods depending on climatic factors, on the intensity of various hydrodynamic and hydrometeorological processes, on seismic activity and human economic activity. The goal of the project is to assess the changes in the ecological state of the Caspian Sea since the beginning of the current century under the impact of natural and anthropogenic factors. This calls for a detailed analysis of large banks of satellite data acquired over the Caspian Sea from 1999 to 2022 jointly with multi-year hydrometeorological and in situ data. The goal is achievable due to powerful capabilities of the “See the Sea” (STS) information portal developed by the Space Research Institute of the Russian Academy of Sciences (IKI RAS) as part of IKI - Monitoring Center for Collective Use. STS offers oceanographers new and unique tools to work with remote sensing data, enabling comprehensive analysis of data different in physical nature, spatial resolution and time of acquisition.

Author(s):  
Tigran Shahbazyan

The article considers the methodology of monitoring specially protected natural areas using remote sensing data. The research materials are satellite images of the Landsat 5 and Landsat 8 satellites, obtained from the resource of the US Geological Survey. The key areas of the study were 3 specially protected areas located within the boundaries of the forest-steppe landscapes of the Stavropol upland, the reserves «Alexandrovskiy», «Russkiy Les», «Strizhament». The space survey materials were selected for the period 1991–2020, and the data from the summer seasons were used. The NDVI index is chosen as the method of processing the spectral channels of satellite imagery. To integrate long-term satellite imagery into a single raster image, the method of variance of the variation series for the NDVI index was used. The article describes an algorithm for processing satellite images, which allows us to identify the features of the dynamics of the vegetation state of the studied territory for the period 1991–2020. The bitmap image constructed by means of the variance of the NDVI index was classified by the quantile method, to translate numerical values into classes with qualitative characteristics. There were 4 classes of the territory according to the degree of dynamism of the vegetation state: “stable”, “slightly variable”, “moderately variable”, “highly variable”. The paper highlights the factors of landscape transformation, including natural and anthropogenic ones. In the course of the study, the determining influence of anthropogenic factors of transformation was noted. The greatest impact is on the reserve «Alexandrovskiy», the least on the reserve «Russkiy Les», in the reserve «Strizhament» the impact is expressed locally. The paper identifies the leading anthropogenic factors of vegetation transformation, based on their influence on vegetation.


Formulation of the problem. The Tatarbunars’kyi District is located in the southwestern part of Odessa region and reflects the main features of the landscape-economic structure of the region: water, agricultural, resort and environmental areas. On the other hand, the form of land use is characterized by widespread plowing of land with degradation and erosion of soil cover. Land structure and use patterns have a complex negative impact on ecological and economic processes and cannot ensure the sustainable development of the region, in particular it is antagonistic to the unique transitional wetland ecosystems of international importance located within the area. To solve the issues of balanced environmental management and zoning of the landscape and economic structure of the region, Earth remote sensing (ERS) data can be used - spectrozonal satellite imagery and geographic information systems (GIS), which can simultaneously cover the research area as a whole, carry out regular monitoring and significantly reduce costs by expensive expeditionary work. Using space monitoring data allows you to get a large array of characteristics of the state of the territorial complexes of the region. Purpose of the work is: assessment of the ecological state of the landscape economic structure and development of recommendations for the protection of natural and territorial complexes of the Tatarbunar’skyi District of Odessa region based on the use of GIS and remote sensing data. Methods. Landsat8 satellite images with OLI and TIRS sensors, digital terrain models (SRTM) with a spatial resolution of 30 m were used as initial data. The spatial distribution of the population was carried out on the basis of OpenStreetMap data using automatic interpolation using the IDW method. Spatial analysis and data processing were carried out in the QGIS v3.4.6 software package. To quantify the vegetation cover, the Normalized Difference Vegetation Index - NDVI was calculated. Waterlog distribution was estimated using a modified normalized differential moisture index (NDMI). The analysis of the structure of land use and anthropogenic load was carried out on the basis of ranking of territorial objects into homogeneous groups to calculate geoecological coefficients. Results. The article discusses the possibilities of using Earth remote sensing data for a functional assessment of land changes as a result of anthropogenic activities, primarily arable land, analyzes the ecological and economic equilibrium of the region based on geoecological coefficients, identifies areas that are primarily exposed to environmental risks, exogenous processes and the impact anthropogenic factors. Measures are proposed to increase the environmental sustainability of agrolandscapes and the landscape-anthropogenic structure of the region’s lands. A detailed hydrological and morphometric analysis of the catchment basin was carried out. Karachaus within the boundaries of the District. For the catchment estuary, remediation and nature conservation measures based on GIS are proposed and designed.


2021 ◽  
Vol 13 (10) ◽  
pp. 2014
Author(s):  
Celina Aznarez ◽  
Patricia Jimeno-Sáez ◽  
Adrián López-Ballesteros ◽  
Juan Pablo Pacheco ◽  
Javier Senent-Aparicio

Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment.


2021 ◽  
Vol 6 ◽  
pp. 24-31
Author(s):  
Dmitry A. Baikin

The article analyzes the impact of oil spills on natural objects according to the remote sensing system Sentinel-2 in Eastern Siberia. Remote sensing data analysis is used to detect traces of oil products in the accident area. Conclusions about the usage of Sentinel-2 data for detecting traces of oil products were made.


2020 ◽  
Vol 9 (7) ◽  
pp. 457
Author(s):  
Aspasia Litoseliti ◽  
Ioannis K. Koukouvelas ◽  
Konstantinos G. Nikolakopoulos ◽  
Vasiliki Zygouri

Assessment of landslide hazard across mountains is imperative for public safety. Pre- and post-earthquake landslide mapping envisage that landslides show significant size changes during earthquake activity. One of the purposes of earthquake-induced landslide investigation is to determine the landslide state and geometry and draw conclusions on their mobility. This study was based on remote sensing data that covered 72 years, and focused on the west slopes of the Skolis Mountains, in the northwest Peloponnese. On 8 June 2008, during the strong Movri Mountain earthquake (Mw = 6.4), we mapped the extremely abundant landslide occurrence. Historical seismicity and remote sensing data indicate that the Skolis Mountain west slope is repeatedly affected by landslides. The impact of the earthquakes was based on the estimation of Arias intensity in the study area. We recognized that 89 landslides developed over the last 72 years. These landslides increased their width (W), called herein as inflation or their length (L), termed as enlargement. Length and width changes were used to describe their aspect ratio (L/W). Based on the aspect ratio, the 89 landslides were classified into three types: I, J, and Δ. Taluses, developed at the base of the slope and belonging to the J- and Δ-landslide types, are supplied by narrow or irregular channels. During the earthquakes, the landslide channels migrated upward and downward, outlining the mobility of the earthquake-induced landslides. Landslide mobility was defined by the reach angle. The reach angle is the arctangent of the landslide’s height to length ratio. Furthermore, we analyzed the present slope stability across the Skolis Mountain by using the landslide density (LD), landslide area percentage (LAP), and landslide frequency (LF). All these parameters were used to evaluate the spatial and temporal landslide distribution and evolution with the earthquake activity. These results can be considered as a powerful tool for earthquake-induced landslide disaster mitigation


2014 ◽  
Vol 2 (3) ◽  
pp. 195-207 ◽  
Author(s):  
Meghan C.L. Howey ◽  
Michael Palace ◽  
Crystal H. McMichael ◽  
Bobby Braswell

AbstractRemote sensing applications are increasingly common in archaeology but they often focus on high resolution imagery and direct archaeological site detection. Moderate spatial resolution remote sensing instruments, which have (near) daily repeat intervals, but contain less detailed spectral and spatial information, have been employed much less frequently in archaeology. However, moderate remote sensing data offer distinct advantages for archaeological research as they can be used to relate archaeological, ecological, and climactic data at vast spatial scales. To show this potential, we use moderate remote sensing data to examine the impact of landscape heterogeneity on the spread of indigenous maize horticulture in the northern Great Lakes during Late Precontact (ca. AD 1200-1600). Analyzing National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, we identify differences in freeze/thaw cycles across inland lakes in Michigan, showing that some large inland lakes produce a microclimatic amelioration, possibly extending the growing season for prehistoric maize cultivation. Conducting geospatial analyses, we find that burial mounds and maize cultivation practices were associated preferentially with larger inland lakes with microclimates. We could not have found these dynamic interrelationships between microclimates, burial mounds, and maize cultivation if not for both the frequent temporal imaging and large spatial coverage provided by moderate resolution remote sensing imagery.


Author(s):  
Asset Akhmadiya ◽  
Nabi Nabiyev ◽  
Khuralay Moldamurat ◽  
Kanagat Dyusekeev ◽  
Sabyrzhan Atanov

In this research paper, change detection based methods were considered to find collapsed and intact buildings using radar remote sensing data or radar imageries. Main task of this research paper is collection of most relevant scientific research in field of building damage assessment using radar remote sensing data. Several methods are selected and presented as best methods in present time, there are methods with using interferometric coherence, backscattering coefficients in different spatial resolution. In conclusion, methods are given in end, which show, which methods and radar remote sensing data give more accuracy and more available for building damage assessment. Low resolution Sentinel-1A/B radar remote sensing data are recomended as free available for monitoring of destruction degree in microdistrict level. Change detection and texture based method are used together to increase overall accuracy. Homogeneity and Dissimilarity GLCM texture parameters found as better for separation of a collapsed and intact buildings. Dual polarization (VV,VH) backscattering coefficients and coherence coefficients (before earthquake and coseismic) were fully utilized for this study. There were defined the better multi variable for supervised classification of none building, damaged and intact buildings features in urban areas. In this work, we were achieved overall accuracy 0.77, producer’s accuracy for none building is 0.84, for damaged building case 0.85, for intact building 0.64. Amatrice town was chosen as most damaged from 2016 Central Italy Earthquake.


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