The automatic detection of tree species and changes within the forest is a key part in monitoring health status and deforestation / reforestation activities particulary for large forest areas. Especially in densely forested regions, forest inventory and monitoring of forest areas from the ground is extremely time and cost intensive. An effective alternative is the use of remote sensing data, obtained from satellite, airplane or drone recordings. Using the pictures ‘from above’ you get detailed information of large forest areas ‘at the bottom/on the ground’.
In addition to covering large areas, this ‘view from above’ offers further advantages, such as a long temporal resolution, the recording of spectral bands outside of visible light or the acquisition of additional information by laser scanning. For example, even in densely overgrown areas, the extraction of deciduous and coniferous trees and the recording of deforestation areas can be captured and displayed based on satellites and LiDAR data using automatic information extraction.
By creating time series, developments and changes can also be documented for large densely forested areas. The display can be done in a variety of ways, e.g. as a vector file with selected features, in tabular form or as a colored grid.