Nowadays, geomatic techniques are regularly adopted in the context of forest research. Geographic Information Systems (GIS), remote sensing and photogrammetric techniques, and data processing are used in many different types of analyses. These include forest resource management, forest inventory and mapping, forest phenological characterization, wood biomass and carbon stock estimation, and mapping, among others. Geomatics proficiently supports these forestry applications. It supplies technologies that involve satellite/aerial/UAV remote sensing, ground and aerial/UAV-based photogrammetry and LiDAR, GNSS positioning and survey, spatial analysis, and Geostatistics.
Presently, the enormous growth of geomatic approaches is supported by a high level of automation in data processing that equips users with the capacity to access these techniques and analyses.
Unfortunately, though, geomatics requires a huge amount of theoretical knowledge acquisition, including methods, algorithms, and data to generate robust and reliable results, especially when prediction is required. A constant review of approaches, tools, and data is mandatory to trace the limits of their applicability. Accuracy of measures, frequency of acquisitions/surveys, properness of data for the expected analysis scale, and management of uncertainty are basic issues to deal with. Moreover, standardization of data, processing and results is another consequent and focus point to make geomatics-based deductions “official”. A huge work has still to be done from this point of view.
This Research Topic intends to assemble high-quality contributions that provide an overview and critical review of ongoing geomatics applications in the forest sector in the light of climate change, claiming for experiences that could highlight the role, or the need, of standardization of both data and procedures. Contributions from authors should not just report case studies but more properly highlight opportunities, limitations, and concerns still persisting in this context. Papers that explore the following themes are warmly encouraged:
• Design and implementation of institutional services in forestry (controls and management) based on satellite/aerial/UAV data with special concerns about image time series and monitoring instances;
• Technical concerns/limitations/potentialities and possible solutions of new low-cost sensors, especially regarding UAV (unmanned aerial vehicle) and UGV (unmanned ground vehicle)-based systems;
• LiDAR (ALS, Aerial LiDAR and TLS, Terrestrial LiDAR) applications;
• Remote sensing (RS) and GIS for adaptive forest management;
• RS data processing for forest information retrieval (both qualitative and quantitative);
• Wood biomass and carbon stock estimation and mapping;
• Economical evaluations concerning costs of Geomatics-based approaches in the forest context;
• Integration of ground and RS data with special concerns about the current availability of BIG DATA from distributed ground sources (networks of sensors, smartphone-based ground observations, etc.);
• Standards of data and procedures.
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