A Two Stage Method to Estimate Species-specific Growing Stock

Information about tree species-specific forest characteristics is often a compulsory requirement of the forest inventory system. In Finland, the use of a combination of ALS data and orthorectified aerial photographs has been studied previously, but there are some weaknesses in this approach. First, aerial photographs need radiometric correction, and second, the ALS points and aerial photographs are not properly fused due to the radial displacement. In this study, ALS points are linked to unrectified aerial photographs of known orientation parameters, which enables better fusion. Each ALS point is mapped to several aerial photographs, and the average of DN values is utilized; this averaging is considered to be a good substitute for radiometric correction. The new two-stage method is compared to the approach in which only ALS data is used. The results show the benefits of using aerial photographs together with ALS data in order to estimate tree species-specific characteristics. Compared to earlier studies, the new two-stage method shows a considerable improvement in applicability in operational use.

[1]  Manfred Näslund,et al.  Skogsförsöksanstaltens gallringsförsök i tallskog , 1936 .

[2]  K. Korhonen,et al.  Kuvioittaisen arvioinnin luotettavuus , 1970 .

[3]  Suomen metsävarat 2004-2005 , 1970 .

[4]  Jyrki Kangas,et al.  Kuviokohtaisten puustotunnusten ennustaminen laserkeilauksella , 1970 .

[5]  Albert R. Stage,et al.  Most Similar Neighbor: An Improved Sampling Inference Procedure for Natural Resource Planning , 1995, Forest Science.

[6]  Matti Maltamo,et al.  The K‐nearest‐neighbour method for estimating basal‐area diameter distribution , 1997 .

[7]  E. Næsset.  Estimating timber volume of forest stands using airborne laser scanner data , 1997 .

[8]  S. Magnussen,et al.  Derivations of stand heights from airborne laser scanner data with canopy-based quantile estimators , 1998 .

[9]  P. Axelsson.  DEM Generation from Laser Scanner Data Using Adaptive TIN Models , 2000 .

[10]  Matti Maltamo,et al.  Application of Most Similar Neighbor Inference for Estimating Marked Stand Characteristics Using Harvester and Inventory Generated Stem Databases , 2001 .

[11]  E. Mikhail,et al.  Introduction to modern photogrammetry , 2001 .

[12]  E. Næsset.  Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data , 2002 .

[13]  Hannu Hökkä,et al.  Models for predicting stand development in MELA System , 2002 .

[14]  Åsa Persson,et al.  Detecting and measuring individual trees using an airborne laser scanner , 2002 .

[15]  S. Popescu,et al.  Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass , 2003 .

[16]  K. Lim,et al.  Lidar remote sensing of biophysical properties of tolerant northern hardwood forests , 2003 .

[17]  D. A. Hill,et al.  Combined high-density lidar and multispectral imagery for individual tree crown analysis , 2003 .

[18]  A. Pekkarinen,et al.  Local radiometric correction of digital aerial photographs for multi source forest inventory , 2004 .

[19]  E. Næsset.  Accuracy of forest inventory using airborne laser scanning: evaluating the first nordic full-scale operational project , 2004 .

[20]  J. Hyyppä,et al.  Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions , 2004 .

[21]  E. Næsset,et al.  Laser scanning of forest resources: the nordic experience , 2004 .

[22]  Åsa Persson,et al.  Identifying species of individual trees using airborne laser scanner , 2004 .

[23]  J. Holmgren.  Prediction of tree height, basal area and stem volume in forest stands using airborne laser scanning , 2004 .

[24]  Annika Kangas,et al.  Accuracy of partially visually assessed stand characteristics: a case study of Finnish forest inventory by compartments , 2004 .

[25]  K. Mengersen,et al.  Airborne laser scanning: Exploratory data analysis indicates potential variables for classification of individual trees or forest stands according to species , 2005 .

[26]  Extending and improving methods for operational stand-wise forest inventories utilizing multi-resolution airborne laser scanner data , 2006 .

[27]  P. Treitz,et al.  Mapping stand-level forest biophysical variables for a mixedwood boreal forest using lidar: an examination of scanning density , 2006 .

[28]  W. Wagner,et al.  Accuracy of large-scale canopy heights derived from LiDAR data under operational constraints in a complex alpine environment , 2006 .

[29]  P. Gessler,et al.  Automated estimation of individual conifer tree height and crown diameter via two-dimensional spatial wavelet analysis of lidar data , 2006 .

[30]  M. Maltamo,et al.  Nonparametric estimation of stem volume using airborne laser scanning, aerial photography, and stand-register data , 2006 .

[31]  Jennifer L. R. Jensen,et al.  Estimation of biophysical characteristics for highly variable mixed-conifer stands using small-footprint lidar , 2006 .

[32]  Richard G. Oderwald,et al.  Forest Volume and Biomass Estimation Using Small-Footprint Lidar-Distributional Parameters on a Per-Segment Basis , 2006 .

[33]  Juha Hyyppä,et al.  DECIDUOUS-CONIFEROUS TREE CLASSIFICATION USING DIFFERENCE BETWEEN FIRST AND LAST PULSE LASER SIGNATURES , 2007 .

[34]  Tomas Brandtberg.  Classifying individual tree species under leaf-off and leaf-on conditions using airborne lidar , 2007 .

[35]  E. Næsset,et al.  UTILIZING AIRBORNE LASER INTENSITY FOR TREE SPECIES CLASSIFICATION , 2007 .

[36]  Johannes Breidenbach,et al.  A MIXED-EFFECTS MODEL TO ESTIMATE STAND VOLUME BY MEANS OF SMALL FOOTPRINT AIRBORNE LIDAR DATA FOR AN AMERICAN AND A GERMAN STUDY SITE , 2007 .

[37]  E. Næsset,et al.  ASSESSING EFFECTS OF LASER POINT DENSITY ON BIOPHYSICAL STAND PROPERTIES DERIVED FROM AIRBORNE LASER SCANNER DATA IN MATURE FOREST , 2007 .

[38]  M. Maltamo,et al.  The k-MSN method for the prediction of species-specific stand attributes using airborne laser scanning and aerial photographs , 2007 .

[39]  Markus Hollaus,et al.  Airborne Laser Scanning of Forest Stem Volume in a Mountainous Environment , 2007, Sensors (Basel, Switzerland).

[40]  Hans-Erik Andersen,et al.  STATISTICAL PROPERTIES OF MEAN STAND BIOMASS ESTIMATORS IN A LIDAR- BASED DOUBLE SAMPLING FOREST SURVEY DESIGN , 2007 .

[41]  M. Maltamo,et al.  Estimation of species-specific diameter distributions using airborne laser scanning and aerial photographs , 2008 .

[42]  William N. Venables,et al.  Modern Applied Statistics with S , 2010 .