Abstract
Forest mapping is an important source of information for assessing woodland resources and a key issue for any National Forest Inventory (NFI). In the present study, a detailed wall-to-wall forest cover map was generated for all of Switzerland, which meets the requirement of the Swiss NFI forest definition. The workflow is highly automated and based on digital surface models from image-based point clouds of airborne digital sensor data. It fully takes into account the four key criteria of minimum tree height, crown coverage, width, and land use. The forest cover map was validated using almost 10,000 terrestrial and stereo-interpreted NFI plots, which verified 97% agreement overall. This validation implies different categories such as five production regions, altitude, tree type, and distance to the forest border. Overall accuracy was lower at forest borders but increased with increasing distance from the forest border. Commission errors remained stable at around 10%, but increased to 17.6% at the upper tree line. Omission errors were low at 1%–10%, but also increased with altitude and mainly occurred at the upper tree line (19.7%). The main reasons for this are the lower image quality and the NFI height definition for forest which apparently excludes shrub forest from the mask. The presented forest mapping approach is superior to existing products due to its national coverage, high level of detail, regular updating, and implementation of the land use criteria.
Highlights
Wall-to-wall forest mapping is a critical task, because the resulting datasets such as forest cover maps are a fundamental input for a broad range of applications from global environmental change assessment to local forest management planning
Forest maps are essential for governmental authorities, international reporting—including the Kyoto protocol, in the framework of Reducing Emissions from Deforestation and Degradation (REDD), forest disturbance assessments, biodiversity and restoration programs, and our understanding of the distribution of forest patches, which are relevant for connectivity studies [1,2]
The Swiss National Forest Inventory (NFI) had great interest in acquiring additional area-wide data, until recently, forest mapping approaches have only existed at the cantonal level
Summary
Wall-to-wall forest mapping is a critical task, because the resulting datasets such as forest cover maps are a fundamental input for a broad range of applications from global environmental change assessment to local forest management planning. The required information for forest mapping can be provided precisely by combining NFI data with remote sensing data and techniques [9,11] This can be done, for example by extrapolating estimates from field plot samples using the k-nearest neighbor (k-NN) algorithm [12]. The Swiss NFI had great interest in acquiring additional area-wide data, until recently, forest mapping approaches have only existed at the cantonal level (mostly based on manual delineation of aerial images). We (i) demonstrate a straight forward method to use height information from image-based point clouds to derive a countrywide forest cover map; (ii) the implementation of the Swiss NFI forest definition including the land use criterion; and (iii) validate the results using almost 10,000 NFI plots. It can be used as support when assessing the accessibility of any forest area, which is important when dealing with harvesting issues
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