0000000000014429
AUTHOR
Roberto Barbetti
Comparing data mining and deterministic pedology to assess the frequency of WRB reference soil groups in the legend of small scale maps
Abstract The assessment of class frequency in soil map legends is affected by uncertainty, especially at small scales where generalization is greater. The aim of this study was to test the hypothesis that data mining techniques provide better estimation of class frequency than traditional deterministic pedology in a national soil map. In the 1:5,000,000 map of Italian soil regions, the soil classes are the WRB reference soil groups (RSGs). Different data mining techniques, namely neural networks, random forests, boosted tree, classification and regression tree, and supported vector machine (SVM), were tested and the last one gave the best RSG predictions using selected auxiliary variables a…
Prospettive e potenzialità della digitalizzazione del settore forestale in Italia
Information and Communication Technologies (ICT) play a key role for improving the implementation of sustainable forest management at local, regional, and global level. The ICT potential to easily exploit a wider and more up-to-date set of information on the economic, environmental, and so- cial value of forests is of relevant help for the daily work of technicians, land owners, and companies in boosting the efficiency and effectiveness of forest management. The concept of “Precision Forestry” (PF) was developed from the early 2000s, as a branch of precision farming or precision agriculture. PF includes the use of ICT, remote and proximal sensing technologies, and other devices to coordinat…