title: ÐÑÐµÐ½ÐºÐ° Ð»Ð°Ð½Ð´ÑÐ°ÑÑÐ½ÑÑ Ñ Ð°ÑÐ°ÐºÑÐµÑÐ¸ÑÑÐ¸Ðº Ð¿ÑÐ¸ Ð¼Ð¾Ð½Ð¸ÑÐ¾ÑÐ¸Ð½Ð³Ðµ Ð¿Ð°ÑÐºÐ¾Ð² Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐµÑ Ð½Ð¾Ð»Ð¾Ð³Ð¸Ð¹ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ð³Ð¾ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑÐ° Ð¸ ÐÐÐ¡
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Assessment of landscape characteristics in the monitoring of parks based on artificial intelligence and GIS technologies.
Creators: name: ÐÐ°Ð´ÐµÐ½ÐºÐ¾, ÐÐ¸ÐºÐ¾Ð»Ð°Ð¹
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: Ð³ÐµÐ¾Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½ÑÐµ ÑÐ¸ÑÑÐµÐ¼Ñ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¼Ð¾Ð½Ð¸ÑÐ¾ÑÐ¸Ð½Ð³ Ð»ÐµÑÐ¾Ð¿Ð°ÑÐºÐ¾Ð²ÑÑ Ð·Ð¾Ð½
ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ Ð¾Ð±ÑÐµÐºÑÐ¾Ð²
ÐºÑÐ¾Ð½Ð° Ð´ÐµÑÐµÐ²ÑÐµÐ²
geoinformation systems
machine learning
forest park monitoring
object recognition
tree crown

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description: The subject of the masterâs graduate qualification work: Â«Assessment of landscape characteristics in the monitoring of parks based on artificial intelligence and GIS technologies. Â» The aim of the study is to develop a methodology for constructing a geoinformation database containing landscape objects of forest park zones, recognized by machine learning methods based on aerospace images for their long-range use in assessing landscape characteristics. To do this, the following tasks must be solved: â¢ Analyzed the current state of the use of ML in solving problems of pattern recognition on aerospace images. â¢ For a specifically selected object of recognition - tree crowns, an object recognition method was selected and tested using the Mask R-CNN DetecTree image segmentation model. â¢ A method for transforming marked georeferenced raster into a GIS database of recognized objects was formed. â¢ The proposed method must be approbated. The object of the study is forest park zones, presented in the form of aerospace images. Approbation was carried out on the site of Pavlovsky Park and the Decembrists Garden. During the study, literature sources on similar topics and existing studies were studied. To achieve the results, the following information technologies were used in the work: the QGIS geographic information system and the interpretation environment of the Jupyter Notebook python language. As a result of this work, a methodology was developed for assessing landscape characteristics when monitoring parks based on machine learning and GIS methods. A study was made of the potential of Mask R-CNN DetecTree in tree crown recognition.