Outlook for the Next Generation’s Precision Forestry in Finland
By Markus Holopainen, Mikko Vastaranta, Juha Hyyppä. 2014
180 citations recorded by the source corpus.
During the past decade in forest mapping and monitoring applications, the ability to acquire spatially accurate, 3D remote-sensing information by means of laser scanning, digital stereo imagery and radar imagery has been a major turning point. These 3D data sets that use single- or multi-temporal point clouds enable a wide range of applications when combined with other geoinformation and logging machine-measured data. New technologies enable precision forestry, which can be defined as a method to accurately determine characteristics of forests and treatments at stand, sub-stand or individual tree level. In precision forestry, even individual tree-level assessments can be used for simulation and optimization models of the forest management decision support system. At the moment, the forest industry in Finland is looking forward to next generation’s forest inventory techniques to improve the current wood procurement practices. Our vision is that in the future, the data solution for detailed forest management and wood procurement will be to use multi-source and -sensor information. In this communication, we review our recent findings and describe our future vision in precision forestry research in Finland.
Subfields: Environmental Engineering, Insect Science, Nature and Landscape Conservation
View Paper: https://www.semanticscholar.org/paper/4d29ba5a7c05dcfa74449ebc0ad2493662edccd7
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In Environmental Engineering
In Insect Science
In Nature and Landscape Conservation
Citations in the corpus
- A Benchmark of Lidar-Based Single Tree Detection Methods Using Heterogeneous Forest Data from the Alpine Space (2015, background): “The tree matches are sorted to the height layers defined by the intervals (in meters) [2, 5],”