Airborne Laser Scanning for the Site Type Identification of Mature Boreal Forest Stands

Abstract

Abstract:In Finland, forest site types are used to assess the need of silvicultural operations and the growth potential of the forests and, therefore, provide important inventory information. This study introduces airborne laser scanner (ALS) data and the k-NN classifier data analysis technique applicable to the site quality assessment of mature forests. Both the echo height and the intensity value percentiles of different echo types of ALS data were used in the analysis. The data are of 274 mature forest stands of different sizes, belonging to five forest site types, varying from very fertile to poor forests, in Koli National Park, eastern Finland. The k-NN classifier was applied with values of k varying from 1 to 5. The best overall classification accuracy achieved for all the forest site types and for a single type, were 58% and 73%, respectively. The conclusion is that when conducting large-scale forest inventories ALS-data based analysis would be a useful technology for the identification of mature boreal site types. However, the technique could still be improved and further studies are needed to ensure its applicability under different local conditions and with data representing earlier stages of stand development.

Remote Sensing Techniques in Monitoring Post-Fire Effects and Patterns of Forest Recovery in Boreal Forest Regions: A Review

“…Selection of data and methods commonly used for mapping successional stages in boreal forests and other regions. Selected studies were found in both Alaskan (e.g., Epting and Verbyla [83] and Tanase et al [183]) and Eurasian (e.g., Vehmas et al [185] and Vehmas et al [184]) boreal regions. However, studies conducted in Eurasia are not specific to post-fire recovery sites.…”

“…Combining field plots with remotely sensed data, however, provides an alternative approach for monitoring successional stages of forests across large spatial extents [177] (Table 6, [83,177,[181][182][183][184][185][186]). In boreal forest ecosystems, there are very few studies using optical sensors, such as Landsat TM/ETM+, to characterize post-fire patterns of succession [83,[187][188][189].…”

“…Therefore, tracking recovery patterns in vegetation using vegetation indices might limit and underestimate the rate of recovery after disturbance [183]. Similar to measuring a forest's structural attributes and successional stages, SAR and LiDAR data have the potential to track the rate of a forest's recovery following disturbance [183,208], since the signal from these data is sensitive and varied by the forest structure and stages of development [184,195] (Table 8). Magnussen and Wulder [208] used LiDAR pulse returns to estimate post-fire recovery rates measured by the mean growth rate of canopy height per year since the recorded fire, over burned areas in Canada's boreal, forest with acceptable levels of precision.…”

“…In Eurasian boreal forests, LiDAR data have been used to separate different types of forest sites in general, ranging from poor (xeric heath forest) to very rich forest [184], and to identify stands of boreal forests with high herbaceous plant diversity [185]. As mentioned by Falkowski et al [186], that classifications of forest succession should reflect all potential stages of forest development, the authors successfully used LiDAR height metrics to classify six stages of forest succession across a structurally diverse and mixed-species conifer forest.…”

“…Generally, the classification of forest successional stages is different from the types of land cover classification, as forest succession involves ecological processes and requires viewing the vegetation community as a continuum rather than as discrete classes [184,197,198]. Classification of forest succession, therefore, not only benefits sustainable forest management, but also effectively quantifies ecological responses and relationships in wildlife habitats [199,200].…”