The Institute of AI of a Russian IT university, together with the Innogeotech company and the Ministry of Natural Resources, Forestry and Ecology of the Perm Territory, has developed a subsystem for monitoring forest changes Smart Forest system. The service monitors illegal logging, fires, and other changes.
Earlier in 2020, the forest change monitoring subsystem was tested in a test mode on the entire territory of the Perm Territory’s forest fund. The goal is to identify illegal logging. During this time, 679 objects with forest changes were identified, and the forestries of the Perm Territory verified the objects of changes. The subsystem has shown high accuracy and efficiency, and now they are preparing to integrate it into the RGIS “Smart Forest fully.”
According to Mikhail Nikitin, head of the department for protection, protection, and supervision in forests of the Ministry of Natural Resources, Forestry and Ecology of the Perm Territory, the system increases the efficiency of control supervision activities in the region. Also, it reduces patrolling costs by streamlining forest surveys. It is much easier and faster to react to specific signals displayed on the map. Thanks to this, more and more objects with alleged violations are found. In the future, these subsystems can be used as an evidence base in control and supervisory activities and courts.
The Innopolis University developers and the Innogeotech company have created an algorithm that eliminates the problem of missing small objects typical for neural networks: algorithms for determining clearings work with objects with a size of 3 * 3 pixels. The problem of haze from clouds in the images was also solved – algorithms automatically distinguish haze in the sky from forest changes. Previously additional processing was carried out for this. The algorithms work in summer and winter with images from the Landsat 8 and Sentinel 2 spacecraft.
“The forest change monitoring service automatically downloads space imagery data weekly. Modern technologies of image processing and deep learning make it possible to solve problems that seemed impossible a few years ago effectively – emphasizes Ramil Kuleev, Director of the Institute of Artificial Intelligence of Innopolis University – The direction of development for the forestry industry is very important for us, we see the prospect in solving problems of automatic taxation forests, the integration of various data sources – space imagery, lidar imagery, and drone imagery, forecasting the development of negative situations, including emergencies – fires, forest drying up ”.
“We have halved – down to 0.1 ha – the minimum area of detected forest changes. Thanks to the large volume of the reference sample, our neural network is currently detecting clear-cuts in images with clouds and cloud shadows – explains Dmitry Shevelev, head of the forestry digitalization project at Innopolis University. – Before that, we had to cut out clouds in the images or use cloudless images. We also continue to work on expanding the base of satellite imagery sources. Now the subsystem is being finalized in terms of using data from domestic satellites Resurs-P and Kanopus-V ”.
On the territory of the Perm Territory, 12.4 million hectares of forest resources will be monitored continuously. Before that, the developers of Innopolis University introduced the technology in the Republic of Tatarstan’s territory. It monitors forests on the territory of 1.2 million hectares – 31 forestry districts of the republic in an automated mode. Using artificial intelligence technology, the service analyzes space images received from Earth satellites, preprocesses them, and sends the results to neural networks. The networks segment these images and issue a vector with polygons. This service has been developed to create an Integrated Remote Monitoring System for the Volga Federal District, which also monitors agricultural land, infrastructure, and capital construction, and waste treatment processes.
“The experience of working on the territory of the Republic of Tatarstan and the Perm Territory allows us to test the work of the forest fund monitoring service in large areas. We see that thanks to work done and continuous improvement, the service can now scale to large areas, soon covering the entire forest fund of Russia,”- concludes Dmitry Shevelev.