Abstract
Although wall-to-wall, accurate, and up-to-date forest composition maps at the stand level are a fundamental input for many applications, ranging from global environmental issues to local forest management planning, countrywide mapping approaches on the tree type level remain rare. This paper presents and validates an innovative remote sensing based approach for a countrywide mapping of broadleaved and coniferous trees in Switzerland with a spatial resolution of 3 m. The classification approach incorporates a random forest classifier, explanatory variables from multispectral aerial imagery and a Digital Terrain Model (DTM) from Airborne Laser Scanning (ALS) data, digitized training polygons and independent validation data from the National Forest Inventory (NFI). The methodological workflow was optimized for an area of 41,285 km2 that is characterized by temperate forests within a complex topography. Whereas high model overall accuracies (0.99) and kappa (0.98) were achieved, the comparison of the tree type map with independent NFI data revealed significant deviations that are related to underestimations of broadleaved trees (median of −3.17%). Constraints of the tree type mapping approach are mostly related to the acquisition date and time of the imagery and the topographic (negative) effects on the prediction. A comparison with the most recent High Resolution Layers (HRL) forest 2012 from the European Environmental Agency revealed that the tree type map is superior regarding spatial resolution, level of detail and accuracy. The high-quality map achieved with the approach presented here is of great value for optimizing forest management and planning activities and is also an important information source for applications outside the forestry sector.
Highlights
Precise and regularly updated information on the state, change and distribution of tree types is essential for forest related studies, e.g., growing stock estimation [1], biodiversity assessment and monitoring [2], hazard and disease management [3], and sustainable forest management [4]
We demonstrate a novel approach to deriving a countrywide tree type map with a spatial resolution of 3 m that (i) uses digital aerial imagery and a Random Forest (RF) classifier; (ii) is highly automated and reproducible, minimizes computation time, and produces high model and prediction accuracies; and (iii) uses digitized polygons of broadleaved and coniferous trees for model adjustment; and (iv) independent National Forest Inventory (NFI) data for validation
This study presents a wall-to-wall mapping approach of broadleaved and coniferous trees across
Summary
Precise and regularly updated information on the state, change and distribution of tree types (broadleaved and coniferous tree) is essential for forest related studies, e.g., growing stock estimation [1], biodiversity assessment and monitoring [2], hazard and disease management [3], and sustainable forest management [4]. Maps of broadleaved and coniferous trees are an important source of information for assessing woodland resources and an additional valuable output of National Forest Inventories (NFI) [6]. The development of remote sensing data sets and methods has opened new perspectives and reached an operational level in the last years, countrywide mapping approaches and sound verification on the tree type level remain rare. Information on the state and distribution of tree types on a national level has usually been obtained by field inventories [6]
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