Suchergebnisse

CC BY-NC-ND ; This study presents generalized European experience in the development of participatory democracy through the study of European regulations and strategies. The purpose of this study is to assess the level of community participation in the pilot region of Ukraine, on which the development prospects of this region are based, using the European tools of territorial administration. There is an objective relationship between the level of participation in the community and the state of its socio-economic development; therefore, increasing the level of participation can improve the welfare of citizens. During this study, with the application of analytical tools, this hypothesis will be confirmed or refuted. This study analyses the main methods of assessment of participation, based on which an original method for estimating the integrated level of participation in united territorial communities is offered, taking into account the specifics of decentralization processes in Ukraine. The proposed method of assessing participation in the pilot region of Ukraine (Zhytomyrska Oblast as a leader of domestic decentralization processes) was tested. The connection between the level of participation and the level of economic capacity of the community was investigated based on: the comparison of indicators of the level of integrated participation; the results of ranking; and the multifactor grouping of united territorial communities according to the level of economic efficiency of their functioning. Measures to increase the level of participation in specific united territorial communities are proposed, taking into account the results of the assessment and European participatory approaches to the management of territorial development.

This article considers the application of remote sensing data to solve the problems of forestry in the Polissia zone (Ukraine). The satellite remote sensing was shown to be applicable to monitoring the damage caused by diseases and pests to forest resources and to assessing the effects of fires. During the research, a detailed analysis and optimization of the information content of Sentinel-2 long-term data sets was performed to detect changes in the forest cover of Polissia, affected by pests and damaged by fires. The following classification algorithms were used for automated decryption: the maximum likelihood method; cluster classification without training; Principal Component Analysis (PCA); Random Forest classification. The results of this study indicate the high potential of Sentinel-2 data for application in applied problems of forestry and vegetation analysis, despite the decametric spatial resolution. Our proposed workflow has achieved an overall classification accuracy of 90 % for the Polissia region, indicating its reliability and potential for scaling to a higher level, and the proposed forecast model is stationary and does not depend on time parameters. To improve the classification results, testing of different combinations of bands emphasized the importance of Band 8 in combination with red edge bands, as well as other bands with a resolution of 10 m for summer scenes. The red margin shows clearly visible differences in the spectral profiles, but bands with a higher resolution of 10 m were crucial for good results.