scholarly journals Airborne laser scanning for tree diameter distribution modelling: a comparison of different modelling alternatives in a tropical single-species plantation

2017 ◽  
Vol 91 (1) ◽  
pp. 121-131 ◽  
Author(s):  
M Maltamo ◽  
L Mehtätalo ◽  
R Valbuena ◽  
J Vauhkonen ◽  
P Packalen
Keyword(s):  
Laser Scanning ◽  
Single Species ◽  
Airborne Laser Scanning ◽  
Diameter Distribution ◽  
Distribution Modelling ◽  
Tree Diameter ◽  
Airborne Laser ◽  
Tree Diameter Distribution

scholarly journals Terrestrial Laser Scanning for Forest Inventories—Tree Diameter Distribution and Scanner Location Impact on Occlusion

Forests ◽  
2017 ◽  
Vol 8 (6) ◽  
pp. 184 ◽  
Author(s):  
Meinrad Abegg ◽  
Daniel Kükenbrink ◽  
Jürgen Zell ◽  
Michael Schaepman ◽  
Felix Morsdorf
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Diameter Distribution ◽  
Tree Diameter ◽  
Forest Inventories ◽  
Tree Diameter Distribution

scholarly journals Estimating stand level stem diameter distribution utilizing harvester data and airborne laser scanning

Silva Fennica ◽  
2019 ◽  
Vol 53 (3) ◽  
Author(s):  
Matti Maltamo ◽  
Marius Hauglin ◽  
Erik Naesset ◽  
Terje Gobakken
Keyword(s):  
Norway Spruce ◽  
Laser Scanning ◽  
Nearest Neighbor ◽  
Airborne Laser Scanning ◽  
Stem Diameter ◽  
Training Data ◽  
Diameter Distribution ◽  
K Nearest Neighbor ◽  
Airborne Laser ◽  
Error Index

Accurately positioned single-tree data obtained from a cut-to-length harvester were used as training harvester plot data for k-nearest neighbor (k-nn) stem diameter distribution modelling applying airborne laser scanning (ALS) information as predictor variables. Part of the same harvester data were also used for stand-level validation where the validation units were stands including all the harvester plots on a systematic grid located within each individual stand. In the validation all harvester plots within a stand and also the neighboring stands located closer than 200 m were excluded from the training data when predicting for plots of a particular stand. We further compared different training harvester plot sizes, namely 200 m, 400 m, 900 m and 1600 m. Due to this setup the number of considered stands and the areas within the stands varied between the different harvester plot sizes. Our data were from final fellings in Akershus County in Norway and consisted of altogether 47 stands dominated by Norway spruce. We also had ALS data from the area. We concentrated on estimating characteristics of Norway spruce but due to the k-nn approach, species-wise estimates and stand totals as a sum over species were considered as well. The results showed that in the most accurate cases stand-level merchantable total volume could be estimated with RMSE values smaller than 9% of the mean. This value can be considered as highly accurate. Also the fit of the stem diameter distribution assessed by a variant of Reynold’s error index showed values smaller than 0.2 which are superior to those found in the previous studies. The differences between harvester plot sizes were generally small, showing most accurate results for the training harvester plot sizes 200 m and 400 m.222222

Modelling tree diameter from airborne laser scanning derived variables: A comparison of spatial statistical models

2010 ◽  
Vol 114 (6) ◽  
pp. 1277-1285 ◽  
Author(s):  
Christian Salas ◽  
Liviu Ene ◽  
Timothy G. Gregoire ◽  
Erik Næsset ◽  
Terje Gobakken
Keyword(s):  
Statistical Models ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Tree Diameter ◽  
Airborne Laser

Estimation of species-specific diameter distributions using airborne laser scanning and aerial photographs

2008 ◽  
Vol 38 (7) ◽  
pp. 1750-1760 ◽  
Author(s):  
Petteri Packalén ◽  
Matti Maltamo
Keyword(s):  
Weibull Distribution ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Aerial Photographs ◽  
Diameter Distribution ◽  
Tree Level ◽  
Nearest Neighbour ◽  
Airborne Laser ◽  
Species Specific ◽  
Diameter Distributions

The use of diameter distributions originates from a need for tree-level description of forest stands, which is required, for example, in growth simulators and bucking. Diameter distribution models are usually applied, since measuring empirical diameter distributions in practical forest inventories is too laborious. This study investigated the ability of remote sensing information to predict species-specific diameter distributions. The study was carried out in Finland in a typical managed boreal forest area. The tree species considered were Scots pine ( Pinus sylvestris L.), Norway spruce ( Picea abies (L.) Karst.), and deciduous trees as a group. Growing stock was estimated using the k-MSN method using airborne laser scanning data and aerial photographs. Two approaches were compared: first, the nearest neighbour approach based on field measured trees was used as such to predict diameter distribution, and second, a theoretical diameter distribution approach in which the parameters of the Weibull distribution are predicted using the k-MSN estimates was applied. Basically, all test criteria indicated that the diameter distribution based on nearest neighbour imputed trees outperforms the Weibull distribution, but care must be taken to ensure that the modelling data are comprehensive enough.

scholarly journals New Advances in Automated Urban Modelling from Airborne Laser Scanning Data

2011 ◽  
Vol 5 (3) ◽  
pp. 196-208 ◽  
Author(s):  
D. F. Laefer ◽  
T. Hinks ◽  
H. Carr ◽  
L. Truong-Hong
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser ◽  
Urban Modelling
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