Effect of size and number of calibration plots on the estimation of stem diameter distributions using airborne laser scanning

Author(s):  
Chen Shang ◽  
Trevor Jones ◽  
Paul Treitz
Silva Fennica ◽  
2019 ◽  
Vol 53 (3) ◽  
Author(s):  
Matti Maltamo ◽  
Marius Hauglin ◽  
Erik Naesset ◽  
Terje Gobakken

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


2008 ◽  
Vol 38 (7) ◽  
pp. 1750-1760 ◽  
Author(s):  
Petteri Packalén ◽  
Matti Maltamo

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.


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

2021 ◽  
Vol 13 (4) ◽  
pp. 1917
Author(s):  
Alma Elizabeth Thuestad ◽  
Ole Risbøl ◽  
Jan Ingolf Kleppe ◽  
Stine Barlindhaug ◽  
Elin Rose Myrvoll

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and methodological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for (a) assessing the pros and cons of the different approaches and (b) assessing the potential detection rate of remote sensing. Interpretation of images and a LiDAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both in LiDAR and image data. This study has shown that LiDAR and remote sensing image data are highly applicable for archaeological surveying in northern landscapes. It showed that a multi-sensor approach contributes to high detection rates. Our results have improved the inventory of archaeological sites in a non-destructive and minimally invasive manner.


2021 ◽  
Vol 491 ◽  
pp. 119225
Author(s):  
Einari Heinaro ◽  
Topi Tanhuanpää ◽  
Tuomas Yrttimaa ◽  
Markus Holopainen ◽  
Mikko Vastaranta

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