Geoinformation and remote methods for assessing snow cover pollution (Kyzyl)

№1 (2023)

Chupikova S.А., Chuldum A.F.

УДК 004.550
https://doi.org/10.47148/1609-364X-2022-1-63-70

AbstractAbout the AuthorsReferences
The article presents the results of the use of geoinformation systems (GIS) and Earth remote sensing (ERS) in the mapping and analysis of snow pollution in urban areas. The research was carried out on the basis of the generated database. The use of geoinformation systems tools allows to create electronic maps to assess the current ecological state of the territory, and the use of ERS data helps to simplify the assessment of pollution levels. Thematic maps have been constructed in the geoinformation environment: the level of lead pollution (mg/kg) (m2 *day) by year, the density of atmospheric dust deposition on snow cover, and others. The assessment of the snow cover pollution of the ERS was carried out on the basis of images from the LANDSAT catalog of the Google Earth Engine (GEE) platform. The following indicators were calculated: NDSI — normalized difference index, S3 — normalized index, SCI — pollution index. A significant correlation of the NDSI (or S3) index with the concentrations of Mn, Pb and Zn was revealed. The spatial distribution of the values of these indicators is displayed by the kriging method using the available open modules and scripts of the GEE platform. Maps of the spatial distribution of the main chemical elements of solid snow and meltwater sediment were obtained.
Svetlana A. Chupikova
Candidate of geographic sciences, senior researcher
Tuvinian Institute for Exploration of Natural Resources SB RAS
117a, Internatsionalnaya str., Kyzyl, 667007, Russia
е-mail: s_fom@inbox.ru
SPIN-code: 8367-9071
ORCID: 0000-0002-7904-5847
ResearcherID: R-6738-2016
Scopus ID: 57194128480

Anatoly F. Chuldum
Researcher
Tuvinian Institute for Exploration of Natural Resources SB RAS
117a, Internatsionalnaya str., Kyzyl, 667007, Russia
е-mail: tajkinol@gmail.com
SPIN-code: 9253-9560
ORCID: 0000-0003-2771-3863
Researcher ID: A-3489-2014

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Key words: remote sensing data, databases, GIS technologies, snow cover, indicators, correlation

Section: Geoecology