Abstract
Changes in forest areas have great impact on a range of ecosystem functions, and monitoring forest change across different spatial and temporal resolutions is a central task in forestry. At the spatial scales of municipalities, forest properties and stands, local inventories are carried out periodically to inform forest management, in which airborne laser scanner (ALS) data are often used to estimate forest attributes. As local forest inventories are repeated, the availability of bitemporal field and ALS data is increasing. The aim of this study was to assess the utility of bitemporal ALS data for classification of dominant height change, aboveground biomass change, forest disturbances, and forestry activities. We used data obtained from 558 field plots and four repeated ALS-based forest inventories in southeastern Norway, with temporal resolutions ranging from 11 to 15 years. We applied the k-nearest neighbor method for classification of: (i) increasing versus decreasing dominant height, (ii) increasing versus decreasing aboveground biomass, (iii) undisturbed versus disturbed forest, and (iv) forestry activities, namely untouched, partial harvest, and clearcut. Leave-one-out cross-validation revealed overall accuracies of 96%, 95%, 89%, and 88% across districts for the four change classifications, respectively. Thus, our results demonstrate that various changes in forest structure can be classified with high accuracy at plot level using data from repeated ALS-based forest inventories.
Highlights
Changes in land use and land cover have great implications on a range of ecosystem functions [1,2,3]
Our results show that bitemporal data acquired as part of repeated airborne laser scanner (ALS)-based forest inventories are highly suitable for plot-level forest change classification
Using decreases in height of dominant trees (Hdom), aboveground biomass (AGB), and N as proxies for forest disturbances, our results demonstrated that such changes in forest structure can be detected reliably from bitemporal ALS data
Summary
Changes in land use and land cover have great implications on a range of ecosystem functions [1,2,3]. Forest changes typically are monitored in national programs [6,7] and reported at a national level, forest management decisions that directly induce those changes are made locally, namely at the level of municipalities, forest properties, and stands, i.e., treatment units. At such local scales, sampling rates of national monitoring programs are too low to obtain the necessary information [8], and local inventories are carried out to inform forest management
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