Information system of analysis of anthropogenic influence on the condition of forest plantations

DOI: 10.31673/2412-4338.2021.032536

Abstract

Remote sensing of the Earth is a new and modern tool for studying the climatic and geographical situation in the world. In recent years, modern satellite systems have been launched to obtain multidimensional images of the earth's surface with high spatial diversity, and are used in many areas: monitoring of marine objects, forest lands, monitoring and forecasting of crops, disaster monitoring, climate research and more. In recent years, the intensity of forest fires, which is due to climate change and anthropogenic factors, is growing in number and area in Ukraine. Accordingly, the share of fires in the forestry fund, which need to grow new forest, is increasing. The number of cases of illegal deforestation has also increased in recent years. All this is irreparable damage to the environmental situation of our country. The development of space remote sensing and geographic information systems allows the development of new effective methods for assessing the state of forests. The forest cover of Ovruch district of Zhytomyr region was analyzed. This information system uses data from space images taken by the Landsat 5 and 8 satellites. In order to analyze the forest cover of the study area, a thematic map of the forest cover of Ovruch district was created and analyzed. The Bayesian classifier was chosen to classify the breed composition from space images. 7 species of tree species in the forest were identified, among which the largest area is occupied by pine. The territory where there are no forest plantations on the territory of the forest is singled out. Also, for the qualitative analysis of forest cover, the forest cover of this area was analyzed by the number of trees for several decades (1999, 2009 and 2019) for each species separately. All these results are presented graphically.

Keywords: remote sensing of the earth, space images, classification of images, decoding of images, species composition of trees.

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