Identification of boreal forest stands with high herbaceous plant diversity using airborne laser scanning

Vehmas, Mikko; Eerikäinen, Kalle; Peuhkurinen, Jussi; Packalén, Petteri; Maltamo, Matti

doi:10.1016/j.foreco.2008.08.016

Cited by 29 publications

(39 citation statements)

References 19 publications

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“…For forest ecology applications, estimates of structural parameters obtained from lidar data have been used to model the probability of vegetation types in boreal forests (Vehmas et al, 2009), to map woodland understories (Hill & Broughton, 2009) and to quantify forest floristics (Tickle et al, 2006). Hill and Thomson (2005) reported strong relationships between tree and shrub species composition and structure as forest attributes and structural metrics obtained from lidar data.…”

Section: Lidar Metrics As Predictors Of Forest Attributesmentioning

confidence: 99%

Using remotely sensed data to construct and assess forest attribute maps and related spatial products

McRoberts

Cohen

Næsset

et al. 2010

Scandinavian Journal of Forest Research

112

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Tremendous advances in the construction and assessment of forest attribute maps and related spatial products have been realized in recent years, partly as a result of the use of remotely sensed data as an information source. This review focuses on the current state of techniques for the construction and assessment of remote sensing-based maps and addresses five topic areas: statistical classification and prediction techniques used to construct maps and related spatial products, accuracy assessment methods, map-based statistical inference, and two emerging topics, change detection and use of lidar data. Multiple general conclusions were drawn from the review: (1) remotely sensed data greatly contribute to the construction of forest attribute maps and related spatial products and to the reduction of inventory costs; (2) parametric prediction techniques, accuracy assessment methods and probability-based (design-based) inferential methods are generally familiar and mature, although inference is surprisingly seldom addressed; (3) non-parametric prediction techniques and modelbased inferential methods lack maturity and merit additional research; (4) change detection methods, with their great potential for adding a spatial component to change estimates, will mature rapidly; and (5) lidar applications, although currently immature, add an entirely new dimension to remote sensing research and will also mature rapidly. Crucial forest sustainability and climate change applications will continue to push all aspects of remote sensing to the forefront of forest research and operations.

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Section: Lidar Metrics As Predictors Of Forest Attributesmentioning

confidence: 99%

Using remotely sensed data to construct and assess forest attribute maps and related spatial products

McRoberts

Cohen

Næsset

et al. 2010

Scandinavian Journal of Forest Research

112

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“…The European CORINE Land Cover (CLC2000) database in a 25 m grid can help in coarse assessments of some biophysical characteristics of the environment (Vihervaara et al 2010), but it cannot provide accurate information on local species assemblages and biotope types that form the basis of ecosystem service supply. More detailed tools, such as airborne laser scanning (ALS), are needed (Hill and Thomson 2005;Pesonen et al 2008;Vehmas et al 2009;Asner et al 2012;Vihervaara et al 2012;Pippuri et al 2012Pippuri et al , 2013. ALS has revolutionized the ways to measure forest structure in 3D.…”

Section: Introductionmentioning

confidence: 99%

How to integrate remotely sensed data and biodiversity for ecosystem assessments at landscape scale

et al. 2014

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Context Biodiversity and ecosystem functioning underpins the delivery of all ecosystem services and should be accounted for in all decision-making related to the use of natural resources and areas. However, biodiversity and ecosystem services are often inadequately accounted for in land use management decisions. Objective We studied a boreal forest ecosystem by linking citizen-science bird data with detailed information on forest characteristics from airborne laser scanning (ALS). In this paper, we describe this method, and evaluate how similar kinds of biological data sets combined with remote sensing can be used for ecosystem assessments at landscape scale. Methods We analysed data for 41 boreal forest bird species and for 14 structural ALS-based forest parameters.Results The results support the use of the selected method as a basis for quantifying spatially-explicit biodiversity indicators for ecosystem assessments, while suggestions for improvements are also reported. Finally, we evaluate the capacity of those indicators to describe biodiversity-ecosystem service relationships, for example with carbon trade-offs. The results showed clear distinctions between the different species as measured, for example, by above-ground forest biomass at the observation sites. We also assess how Electronic supplementary material The online version of this article

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“…In the recent study by Korpela et al [31] they found that ALS data can be used in assessment of different boreal mire surface patterns, vegetation and habitats. The applicability of ALS data to the identification of forest stands with high herbaceous plant diversity was recently studied by Vehmas et al [32]. One of the discrimination techniques applied by Vehmas et al [32] was the k-nearest neighbor (k-NN) method: In their study the herb-rich forest stands were distinguished from less fertile forest stands.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2011

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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.

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Identification of boreal forest stands with high herbaceous plant diversity using airborne laser scanning

Cited by 29 publications

References 19 publications

Using remotely sensed data to construct and assess forest attribute maps and related spatial products

Using remotely sensed data to construct and assess forest attribute maps and related spatial products

How to integrate remotely sensed data and biodiversity for ecosystem assessments at landscape scale

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

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