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Remote sensing techniques became one of the most used tools in forest monitoring. The advancement in material sciences and computational power led to the development of unnamed aerial systems (UASs) as carrier and various sensors as data collectors. Nevertheless, the data acquired with UASs exhibits errors larger than spaceborne systems, as the equipment is not as accurate as the ones mounted on satellites. Therefore, the scope of the Working Party is to assess and model the errors associated with data acquired with devices installed on unmanned aerial systems (UASs) as well as to extract information supplied by the sensors mounted on the UASs.
The Working Party aims at developing tools and methods for quantifying the errors present in data acquired with the UASs, as well as creating algorithms for reducing the errors in pre-processing and integration of data from various UASs based sources.
The 4.03.04 Working Party is directly related with the research carried out by the 4.03.01 and 4.03.02 units, as it used procedures from representing error and methods of extracting information present in the two Working Parties, respectively. Furthermore, the 4.03.02 is naturally related to the remote sensing inventory 4.02.05.
STATE OF KNOWLEDGE
Unmanned aerial systems (UAS) experienced an explosive development in terms of navigation and flight control as well as in the type of payloads. From fixed to rotary wings, UASs are now able to survey large areas without difficulty considering the easy to maneuverer and to design the flight path, as well as the long duration of a mission. The ability to execute complex flight missions is enhanced by the large palette of sensors that are now carried by each UAS, from cameras to lidar devices, or even radar systems.
The UASs fill an important gap in forest monitoring and assessment, particularly the production of high-resolution representation of reality, either with images or point clouds. Nevertheless, the large amount of data describing the forest is challenged by errors in data acquisition, pre-processing, processing, and analysis. The unit aims at reducing the uncertainty in preprocessing and processing the data acquired with various sensors installed on UASs. This is a crucial task, as data that with significant noise significantly hinder the subsequent analyses.