АНАЛІЗ МОЖЛИВОСТЕЙ І ДОСВІДУ ВИКОРИСТАННЯ ПЛАТФОРМИ GOOGLE EARTH ENGINE ДЛЯ ВИРІШЕННЯ ЗАДАЧ МОНІТОРИНГУ ДОВКІЛЛЯ

Autor: Давибіда, Л. І.
Zdroj: Ecological Safety & Balanced Use of Resources; 2021, Vol. 24 Issue 2, p75-86, 12p
Abstrakt: The purpose of the study is to assess the potential of using the Google Earth Engine (GEE) platform for processing the Earth remote sensing data in solving various problems of environmental monitoring and in other areas of applied geoinformatics. GEE is an open cloud platform that allows performing the analysis and visualization of large-scale geospatial datasets for scientific, educational, public, governmental and commercial organizations. GEE provides open-source tools for geospatial analysis, as well as access to a public catalogue of raster and vector data, which includes satellite images, meteorological, geophysical observation data, etc. In the paper, the structure and functions of the platform were analyzed, as well as the possibilities of obtaining open data of remote sensing provided by the GEE catalogue for the regional environmental monitoring problems solution. A systematic review of the current scientific publications was carried out, which confirmed the wide range of applications of the platform by the scientists from different countries to analyze the environment both regionally and globally. One of the most common types of tasks implemented by GEE is the calculation of normalized difference indices used for mapping vegetation, crops, land cover, biodiversity and monitoring of fires, droughts and other negative natural and man-made processes. For the studied territory of the Carpathian region, an assessment of the time period of the available observation data, coverage of satellite images, their spatial resolution, decoding characteristics was performed. According to the data of multi-channel space images, the normalized difference indices NDVI, MNDWI, NDBI were calculated using the GEE code editor and JavaScript programming language, and the obtained results were visualized. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index