New Generation Forest Management Includes Satellite Monitoring and Artificial Intelligence
The European Space Agency co-funds a project that makes forest analytics based on satellite monitoring a part of forest systems
The European Space Agency ESA has confirmed co-funding for Bitcomp’s demonstration project called EnviNavigator. In the project, forest services based on satellite monitoring that use self-learning artificial intelligence are being developed. Up-to-date information on the current state of forests, their risks, and changes in them can be produced for the needs of forest professionals and forest owners by combining satellite data with other data sets relating to forestlands.
In the new generation forest management, old practices are accompanied with new ones that will assist in enhancing the correctness and accuracy of forest cover information. The shortcomings of field plot measurements can be compensated and predictions based on laser scanning can be updated with satellite data. Additionally, the objectives and needs have become more diverse. Apart from economic profit, forest owners are interested in diversity, the availability of clean water as well as ensuring the recreational and scenery values. On the other hand, optimizing carbon storage of forests has been seen as an example of a significant measure to address the climate change. Deep analytics on forests as well as recognition of details and variation inaccessible with previous calculation methods can be achieved with artificial intelligence.
Satellite data increases knowledge on forest status
The production of forest services and the development of systems based on these needs have been essential objectives of the EnviNavigator project. Prior to this, Bitcomp has already produced a satellite data basedchange detection service for real-time monitoring of fellings and thinnings. The service is used, among others, for the Finnish Forest Centre’s illegal logging surveillance. With the now secured co-funding, the service will be expanded to recognize health risks related to forests as well as possible storm and insect damages. Especially in the Central Europe, the global warming is already causing big problems for forest owners. Damages can be forecasted and limited when the artificial intelligence recognizes the changes in the health status of a forest cover directly from the satellite data.
Forest variables that can be recognized from the satellite data include
Fellings and thinnings
With AI algorithms, forest analytics can also be deepened with variables the processing of which has not been possible before. One of these is the observations and tacit knowledge of forest professionals.
“Thanks to the upcoming development, we will be able to include field observations by professionals in the analysis and attach them to the training data for artificial intelligence algorithms alongside with other data sets. Forest worker can, for example, inspect a target and detail it further by providing additional information. The analysis learns to be more intelligent the more data it gets to process. From forest services’ point of view, utilizing expertise such as this as part of the analytics is unique,” explains Sanna Härkönen, the project manager of the EnviNavigator project.
Customer oriented approach to be part of forest management services
Another significant object of development has been automating communication. When the analytics recognizes a site that requires special attention or management, the system automatically sends a notification about it. Professionals can then focus forest management work on area where the need is the gravest. At the same time, the sales process of the services from a forest professional to forest owners is streamlined as the communication is supported by the data on management need served by the analysis.
The advantages of the service:
Less field visits
Focusing work on areas with the biggest need
Automatic alerts and management suggestion notifications for forest owners
Interactive forest management process, in which it is easy for the customer to select what kind of management measures they want done
Direct connection with which the forest management work can be automatically transferred to forest professional for execution
Even the best idea works only if it is easy to use
By no means is Bitcomp’s only objective to process and analyze big data masses for forest management needs. Instead, the result must be easy to use and utilize for managing all operations.
“We do not analyze satellite data and develop artificial intelligence algorithms because it is trendy. We develop services that concretely make forest professionals’ work easier and forest owners’ services better. The EnviNavigator project is not only about satellite data but also about enabling its advantages in field work,” Härkönen states.
A significant part of the project is mobile and web applications, with which the results of the analyses can be examined and completed on field. The results of development work will soon be visible in Bitcomp’s own forest applications such as LeafPoint, Foresta, and their forest owner versions.
The first part of the EnviNavigator project, the Feasibility Study, was co-funded by ESA in 2019. The now starting second phase (the Demonstration Project) will last until the year 2022. This project is being co-funded by the European Space Agency under ARTES 4.0 Business Applications – Space Solutions.