18 November 2023
Sensor technologies (LiDAR, GIS, soil sensors, etc.) and remote-sensing platforms (satellites, planes, drones, etc.) brought high-resolution spatial and temporal data to forest monitoring, one of the most important tasks related to environmental protection.
However, specialists have to deal with the huge volumes of data these systems provide, which require powerful computing resources that are not always available. Cloud solutions such as CREODIAS, Google Earth Engine, and others provide instant satellite data access and the ability to quickly and conveniently process geospatial data in the cloud and use it to search for information products.
In this work, SWIFTT partners from the Space Research Institute of Ukraine and collaborators analysed Copernicus Sentinel-2 satellite spectral channels for the diseased and healthy forests for the possibility of separating these two classes.
Getting results for large areas will lead to a big data problem. Therefore, the authors also propose the structure of a pilot information system as the basis for a cloud solution with the development of a machine (deep) learning model for forest monitoring in any territory. This system allows monitoring forest dynamics based on time series of satellite data both at the country level and worldwide.
Source: Shelestov, A., Salii, Y., Hordiiko, N., Yailymova, H. (2023). In Lecture Notes in Networks and Systems, vol 809. Springer, Cham. DOI: 10.1007/978-3-031-46880-3_20
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