Introducing Digital Technologies to Forest Monitoring in the Baikal Natural Territory

Characteristic features of the Baikal natural territory (BNT) are analyzed and the problems of forest monitoring are highlighted. An approach is proposed for the digital transformation of forest resource monitoring using a service-oriented paradigm, an infrastructure approach, and declarative specifications, as well as end-to-end and Web technologies for collecting and processing large amounts of spatiotemporal data. A scheme of a digital forest monitoring platform based on an information–analytical geoportal environment is described, including a system for processing and storing spatiotemporal data and a catalog of basic and thematic services for assessing the consequences of natural and anthropogenic impacts on forests of the BNT. The experience of using deep learning methods to monitor changes in the state of forests is presented. An automated determination of land cover types is carried out on the basis of Sentinel-2 images. The composition of classes of the training data set created for the BNT is described. The result of satellite image classification with the identified land cover classes is given. The digital platform (DP) thus created can be used to assess and predict the state of forest resources of the BNT and make managerial decisions on effective forest management.