Segment-level stand inventory for forest management

Hyvönen, Pekka; Pekkarinen, Anssi; Tuominen, Sakari

doi:10.1080/02827580510008220

Cited by 33 publications

(23 citation statements)

References 20 publications

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“…In some previous studies (e.g., van Aardt et al 2006;Hyvönen et al 2005;Tuominen and Haapanen 2011), segments have been used as inventory and estimation units. These segments can be small and complicated in size.…”

Section: Discussionmentioning

confidence: 99%

NFI plots as complementary reference data in forest inventory based on airborne laser scanning and aerial photography in Finland

Tuominen¹,

Pitkänen²,

Balazs³

et al. 2014

Silva Fenn.

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In Finland, there are currently two, parallel sample-plot-based forest inventory systems, which differ in their methodologies, sampling designs, and objectives. One is the National Forest Inventory (NFI), aimed at unbiased inventory results at national and regional level. The other is the Forest Centre's management-oriented forest inventory based on interpretation of airborne laser scanning and aerial images, with the aim of locally accurate stand-level forest estimates. The National Forest Inventory utilises relascope sample plots with systematic cluster sampling. This inventory method is optimised for accuracy of regional volume estimates. In contrast, the management-oriented forest inventory utilises circular sample plots with an allocation system covering certain pre-defined forest classes in the inventory area. This method is optimised to produce reference data for interpretation of the remote-sensing materials in use. In this study, we tested the feasibility of the National Forest Inventory sample plots in provision of additional reference data for the management-oriented inventory. Various combinations of NFI plots and management inventory plots were tested in the interpretation of the laser and aerial-image data. Adding NFI plots in the reference data generally improved the accuracy of the volume estimates by tree species but not the estimates of total volume or stand mean height and diameter. The difference between the plot types in the NFI and management inventories causes difficulties in combination of the two datasets.

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Section: Discussionmentioning

confidence: 99%

NFI plots as complementary reference data in forest inventory based on airborne laser scanning and aerial photography in Finland

Tuominen¹,

Pitkänen²,

Balazs³

et al. 2014

Silva Fenn.

Self Cite

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“…In estimating stand level forest attributes (area based approach) the segment size is larger than single tree crowns. Stands delineated automatically on the basis of remote sensing imagery (i.e., image segments) have an advantage over grid elements (e.g., [11,12]). They can be delineated in such a way that they exactly follow the actual stand borders, whereas the grid elements are spatially 'sparse' in relation to the actual stand borders in the forest and they do not follow the borderlines accurately, instead often intersecting trees from more than one stand (e.g., [11]).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Grid-Based and Segment-Based Estimation of Forest Attributes Using Airborne Laser Scanning and Digital Aerial Imagery

Tuominen¹,

Haapanen²

2011

Remote Sensing

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Forest management planning in Finland is currently adopting a new-generation forest inventory method, which is based on interpretation of airborne laser scanning data and digital aerial images. The inventory method is based on a systematic grid, where the grid elements serve as inventory units, for which the laser and aerial image data are extracted and the forest variables estimated. As an alternative or a complement to the grid elements, image segments can be used as inventory units. The image segments are particularly useful as the basis for generation of the silvicultural treatment and cutting units since their boundaries should follow the actual stand borders, whereas when using grid elements it is typical that some of them cover parts of several forest stands. The proportion of the so-called mixed cells depends on the size of the grid elements and the average size and shape of the stands. In this study, we carried out automatic segmentation of two study areas on the basis of laser and aerial image data with a view to delineating micro-stands that are homogeneous in relation to their forest attributes. Further, we extracted laser and aerial image features for both systematic grid elements and segments. For both units, the feature set used for estimating the forest attributes was selected by means of a genetic algorithm. Of the features selected, the majority (61-79%) were based on the airborne laser scanning data. Despite the theoretical advantages of the image segments, the laser and aerial features extracted from grid elements seem to work better than features extracted from image segments in estimation of forest attributes. We conclude that estimation should OPEN ACCESSRemote Sens. 2011, 3 946 be carried out at grid level with an area-specific combination of features and estimates for image segments to be derived on the basis of the grid-level estimates.

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“…With high spatial resolution imagery, such as IKONOS or QuickBird satellite images, aerial photographs and ALS data, image segmentation has been used in the delineation of forest stands or, further, microstands for the estimation of forest characteristics for management planning (e.g. Baatz and Schäpe 2000;Hay et al 2005;Mustonen et al 2008;Pascual et al 2008;Wulder et al 2008) and in extracting segment-based image features to improve estimation results (Pekkarinen 2002b;Hyvönen et al 2005;van Aardt et al 2006;Tuominen and Haapanen 2011). Moreover, segmentation techniques have been applied in detecting individual trees in high spatial resolution imagery (e.g.…”

Section: Image Segmentation In Forest Inventorymentioning

confidence: 99%

Multi-source forest inventory data for forest production and utilization analyses at different levels

Haakana¹

2017

Diss. For.

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National forest inventory (NFI) data are commonly used in national and regional scenario analyses on forest production and utilization possibilities. There is an increased demand for similar analyses at the sub-regional level, and further, to incorporate spatially explicit data into the analyses. However, the fairly sparse network of NFI sample plots allows analyses only for large areas. The present dissertation explored whether satellite imagery, NFI sample plot data and the k nearest neighbour estimation method can be employed in generating spatial forest data for scenario analyses at the local level. The method was first applied in the area of two villages in Eastern Finland to quantify the effects of administrative land use and technical land-form constraints on timber production. Secondly, the impacts of three alternative regional felling strategies on suitable habitat for the Siberian flying squirrel (Pteromys volans) were assessed.As a scenario analysis tool, the Finnish forestry dynamics model MELA was used. Management units for simulations of forest development and management activities were delineated by means of image segmentation and digital maps on restriction areas, and new weights for NFI sample plots, that is, the representativeness in these units, were estimated by means of satellite image data. The performance of different segmentation methods and different spectral features in the estimation were examined. Image segments corresponding to forest stands enabled the use of patch-and landscape-level models in the prediction of suitable habitat.Satellite image-based estimation of new NFI sample plot weights was found to be a feasible method for generating forest data for scenario analyses in areas smaller than is possible with the plot data only, for example, for municipalities. Satellite imagery with large geographic coverage and continuous NFI field measurements provide cost-efficient data sources for versatile impact and scenario analyses at the local level.

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Segment-level stand inventory for forest management

Cited by 33 publications

References 20 publications

NFI plots as complementary reference data in forest inventory based on airborne laser scanning and aerial photography in Finland

NFI plots as complementary reference data in forest inventory based on airborne laser scanning and aerial photography in Finland

Comparison of Grid-Based and Segment-Based Estimation of Forest Attributes Using Airborne Laser Scanning and Digital Aerial Imagery

Multi-source forest inventory data for forest production and utilization analyses at different levels

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