SOFTWARE FOR AUTOMATION OF SPACE IMAGE RECOGNITION

Interexpo GEO-Siberia ◽

10.33764/2618-981x-2021-6-207-212 ◽

2021 ◽

Vol 6 ◽

pp. 207-212

Author(s):

Sergey A. Myasoedov

Keyword(s):

Remote Sensing ◽

Image Recognition ◽

Remote Sensing Data ◽

Urban Infrastructure ◽

Space Images ◽

Automated Recognition ◽

Data Services ◽

Sensing Data ◽

Space Image

The article discusses the main universal systems for working with remote sensing data - services that provide software for automated recognition of urban infrastructure objects in space images. The functions that these products can perform and their structure are considered.

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METHODOLOGY DEVELOPMENT FOR CALCULATING THE AREA OF GREENERY IN A CITY, USING REMOTE SENSING DATA

Географический вестник = Geographical bulletin ◽

10.17072/2079-7877-2021-2-170-181 ◽

2021 ◽

pp. 170-181

Author(s):

Olga S. Sergeeva ◽

◽

Semen P. Pirozhkov ◽

Keyword(s):

Remote Sensing ◽

Urban Environment ◽

Remote Sensing Data ◽

Green Spaces ◽

Space Images ◽

Important Indicator ◽

Sensing Data ◽

Environment Quality ◽

Gis Technologies ◽

Green Areas

This article discusses the possibility of using Earth remote sensing data and GIS technologies for assessing the area of green spaces in a city. Green areas are an important indicator of the urban environment quality. Quantitative information on such areas is necessary to calculate the total index of the urban environment quality, which is provided annually to the state statistics authorities. Various methods of obtaining such data are possible, including by decoding orthophotomaps, aerial photography, and mobile laser scanning. GIS technologies provide ample opportunities in this area: they allow one to create electronic maps, attributive databases, and maintain up-to-date information. The paper provides an example of using space images to calculate green areas in one of the microdistricts in the city of Perm. We describe the technique for recalculating the number of trees in a landscaping area; assess the planting areas of general and limited use and the total area of green spaces in the microdistrict; calculate the share of green areas and the greening level of the microdistrict, which are necessary for calculating the urban environment quality index. The technique proposed in this work can significantly reduce the time and labor costs for finding indicators of the urban environment greening.

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APPLICATION OF REMOTE SENSING DATA TO THE ESTIMATION OF ANTHROPOGENOUS IMPACT ON ECOSYSTEMS (ON THE EXAMPLE WESTERN MONGOLIA)

Interexpo GEO-Siberia ◽

10.33764/2618-981x-2019-6-2-128-133 ◽

2019 ◽

Vol 6 (2) ◽

pp. 128-133

Author(s):

Liyana Abdrashitova ◽

Alexander Chermoshentsev

Keyword(s):

Remote Sensing ◽

Anthropogenic Impact ◽

Remote Sensing Data ◽

Arid Areas ◽

Space Images ◽

Sensing Data ◽

Western Mongolia ◽

Automated Interpretation ◽

Thematic Processing ◽

Data Processing Methods

The article is devoted to the use of remote sensing data for assessing the anthropogenic impact on ecosystems on the example of arid areas. It describes main advantages and problems of the data processing methods, including automated interpretation of images. The technique of thematic processing of a time series of space images is proposed.

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Research and forecasting of landslide phenomena of the Dniper zone of Kyiv based on the remote sensing data and geomorfological studies

Ukrainian journal of remote sensing ◽

10.36023/ujrs.2017.13.104 ◽

2017 ◽

pp. 10-16

Author(s):

Nataliia Pazynych

Keyword(s):

Remote Sensing ◽

Digital Elevation Models ◽

Remote Sensing Data ◽

Space Images ◽

Sensing Data ◽

Digital Elevation ◽

The Right

The article presents the results of the investigation of landslides in the right bank of the Kyiv, on the basis of space images, digital elevation models using two geomorphological methods. The result of the complexization of geomorphological methods was the compilation of a synthetic map of dynamic relief plastics, which reflects the structure of linear and area elements of the relief. The conducted comparison of geomorphological constructions with landslide bodies allowed to identify zones and areas of increased danger of landslide formation.

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Identification of temperature anomalies in the western Caspian Sea in 2017 based on remote sensing data

South of Russia ecology development ◽

10.18470/1992-1098-2020-4-63-74 ◽

2021 ◽

Vol 15 (4) ◽

pp. 63-74

Author(s):

A. A. Bagomaev ◽

N. O. Guseynova

Keyword(s):

Remote Sensing ◽

Water Temperature ◽

Caspian Sea ◽

World Ocean ◽

Remote Sensing Data ◽

Spatial Inhomogeneity ◽

Science Data ◽

Space Images ◽

Sensing Data ◽

Temperature Anomalies

Aim. The study of temperature anomalies in the western Caspian Sea based on space imagery materials in order to detect upwelling phenomena.Materials and Methods. We used temperature indicators of seawater for the summer season of 2017 when a sharp decrease by more than 2 °C in average daily temperature occurred. Space images were obtained from the specialized centres of Ocean Color NASA, Earth Science Data Systems NASA and SATIN. Remote sensing data were processed using SeaDAS and ArcGIS programs. Ground data were obtained from the resources of the Unified State System of Information about the Situation in the World Ocean (ESIMO). An ArcGIS database was created and maps compiled.Results. The first upwelling occurred on 9-17 June 2020. The minimum water temperature in the Makhachkala area was 14°C with an increase in salinity to 12%o over an area of 1,500 sq.km. An increase in the content of dissolved oxygen of up to 9.70 mg/l and pH 8.64 was recorded. A second upwelling of medium intensity occurred from 19 June-July 1 with a minimum temperature of 17.9C. The decrease in temperature was 2.8°C with an increase in salinity by 1%o. The surface area was 454 sq.km. A third case of upwelling was recorded from 26 August-September 1 and was characterised by a decrease in water temperature of 7.4C (near the coast, 17.1°C). The average salinity increase was 0.32%o while the 02 concentration was 8 mg/l over an area of 500 sq.km.Conclusion. Due to its large size, the Caspian Sea is characterised by spatial inhomogeneity of oceanological parameters, which can be recorded based on the results of processing satellite images and their verification using ground data. In the western part of the sea the upwelling is periodic and of different scales.

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Monitoring Coastline Dynamics of Alakol Lake in Kazakhstan Using Remote Sensing Data

Geosciences ◽

10.3390/geosciences9090404 ◽

2019 ◽

Vol 9 (9) ◽

pp. 404

Author(s):

Adilet Valeyev ◽

Marat Karatayev ◽

Ainagul Abitbayeva ◽

Saule Uxukbayeva ◽

Aruzhan Bektursynova ◽

...

Keyword(s):

Remote Sensing ◽

Agricultural Land ◽

Anthropogenic Impacts ◽

Remote Sensing Data ◽

Scale Space ◽

Anthropogenic Factors ◽

Space Images ◽

Essential Information ◽

Water Index ◽

Sensing Data

Alakol Lake is one of the largest hydrologically closed lake located in Balkash-Alakol River Basin in southeast Kazakhstan. Having a coastline approximately at 490 km, Alakol Lake has faced multiple threats due to both natural and anthropogenic factors as a result of tectonic movements, geology, wind-wave conditions, growing tourism activities, fishing, and transport, etc. The present study aims to investigate the historical trends in coastline changes along Alakol Lake in Kazakhstan and estimate its change rate by using remote sensing data in particular scale-space images Landsat-5 TM, 7 ETM+, 8 OLI, and Sentinel-2A. Based on Landsat and Sentinel data, the modified normalized difference water index was calculated to demonstrate the coastline changes along Alakol Lake between 1990 and 2018. Moreover, the monitoring and analysis of coastline dynamics is based on the main morphometric characteristics of Alakol Lake including water surface area, coastline length, geomorphology of the coast, etc. Our results reveal that there is a continuous coastline retreat, depending on the coast types. For example, in the case of the denudation coasts, a land inundation was from 120 to 270 m between 1990 and 2018. In the case of the accumulative coast (mainly northeast, north, and northwest coasts) a land inundation was from 200 to 900 m. A vast area of agricultural land around Alakol Lake become flooded and lost. This study demonstrates the importance of monitoring coastline dynamics because it provides essential information for understanding the coastal response to contemporary nature and anthropogenic impacts.

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