FÖRECAST 2.0: SCALATING FOREST INTELLIGENCE. A BIGDATA-DRIVEN STEP FORWARD
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- FÖRECAST 2.0: SCALATING FOREST...
To improve the current functionalities of förecast and to address its scalability objectives, förecast 2.0 will improve the architecture and procedures under a Big Data framework and integrate procedures and protocols to upgrade forest inventory using LiDAR data. Furthermore, förecast 2.0 pretends to analize the large-scale, geospatial data, greatly reducing the time required for computation.
Start date: 05/01/2021
Duration in months: 9
Problem Description
The experiment aims to improve the current functionalities of förecast and to address its scalability objectives. Förecast 2.0 will improve the architecture and procedures under a Big Data framework and integrate procedures and protocols to upgrade forest inventory using LiDAR data.
Goals
New services
Challenges
The main objective is to improve the current functionalities of förecast in terms of computational development, geoprocessing optimisation, and business model.
Innovation results
Development of an intelligent workflow architecture to combine the different image layers and forestry algorithms, that can describe the state of every forest,Development of automatic and on demand processes to increase the simultaneous working capacity of the platform.
Business impact
confidential