The main goal of this study is to evaluate different models for further improvement of the accuracy of land use and land cover (LULC) classification on Google Earth Engine using random forest (RF) and support vector machine (SVM) learning algorithms. Ten indices, namely normalized difference vegetation index, normalized difference soil index, index-based built-up index, biophysical composition index, built-up area extraction index (BAEI), urban index, new built-up index, band ratio for built-up area, bare soil index, and normalized built up area index, were used as input parameters for the machine learning algorithms to improve classification accuracy. The combinatorial analysis of the Sentinel-2 bands and the aforementioned indices allowed us to create four combinations based on surface reflectance characteristics. The study includes data from April 2020 to September 2021 and April 2022 to June 2022. The multitemporal Sentinel-2 data with spatial resolutions of 10 m were used to determine the LULC classification. The major land use classes such as water, forest, grassland, urban areas, and other lands were obtained. Generally, the RF algorithm showed higher accuracy than the SVM. The overall accuracy for RF and SVM was 86.56% and 84.48%, respectively, and the mean Kappa was 0.82 and 0.79, respectively. Using the combination 2 with the RF algorithm and combination 4 with the SVM algorithm for LULC classification was more accurate. The additional use of vegetation indices allowed to increase in the accuracy of LULC classification and separate classes with similar reflection spectra.
Aim of the study: The main purpose of the study is the analysis and assessment of anthropogenically transformed landscapes of Bila Tserkva (Ukraine) based on a combination of remote sensing methods and GIS mapping Material and methods: Usage of geoinformatics methods for mapping anthropogenically transformed landscapes of Bila Tserkva is studied. The data was downloaded and processed using the Semi-Automatic Classification Plugin QGIS for the supervised classification of remote sensing data. Satellite images were radiometrically calibrated and atmospherically corrected, followed by a controlled classification with signature creation, visualization of spectral profiles, quality assessment and post-processing Results and conclusions: The main methods of landscape research are analyzed. The conclusion is made about the expediency of using spectrophotometry of satellite images in order to identify different types of landscapes based on satellite data. An supervised classification of satellite images different-time images was performed, as a result of which the main Bila Tserkva landscape types were identified. Those identified types are: water bodies, vegetation (grass, forest, parks) urban areas and bare soils. Spatio-temporal changes of landscapes are studied and these changes are described in quantitative indicators
У змісті статті актуалізуються такі наукові поняття, як свідомість та такі її форми, як екологічна свідомість, професійна свідомість та інші. Є спроба простежити розвиток змісту цих понять, починаючи з вчення філософів Платона і Арістотеля до сучасних науковців. Авторами підкреслюється теоретична і практична значущість формування екологічної свідомості у майбутніх фахівців природоохоронної діяльності. З метою пошуку шляхів
One of the multifunctional areas of providing accessible rehabilitation and social functions is inclusive tourism with its diverse range of services and methods of providing the necessary assistance. The problem of development and practical implementation of inclusive tourism in the socio-economicsystem of the regions of Ukraine is a new and quite promising trend in tourism, which allows to involve in tourism activities representatives of low-income and socially vulnerable segments of the population. The most unaccepted social category for life and tourism in Ukraine are people with disabilities. Studying the problems of adaptation, recreation, various aspects of rehabilitation of people with inclusion, allows to regulate the issues of socio-economic nature, to develop promising strategies for the gradual implementation of inclusive tourism and to offer programs of practical assistance to people of inclusive categories.The subject-objective essence of inclusive tourism as a new scientific and practical direction in the socio-economic system of regional development of Ukraine allows to talk about inclusive tourism as a segment of tourism activities, which may include not only comfortable tourist services, but also recreational and rehabilitation services as part of tourism activities.
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