Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Mapping forest age using National Forest Inventory, airborne laser
  scanning, and Sentinel-2 data   The age of forest stands is critical information for many aspects of forest
management and conservation but area-wide information about forest stand age
often does not exist. In this study, we developed regression models for
large-scale area-wide prediction of age in Norwegian forests. For model
development we used more than 4800 plots of the Norwegian National Forest
Inventory (NFI) distributed over Norway between 58{\deg} and 65{\deg} northern
latitude in a 181,773 km2 study area. Predictor variables were based on
airborne laser scanning (ALS), Sentinel-2, and existing public map data. We
performed model validation on an independent data set consisting of 63 spruce
stands with known age. The best modelling strategy was to fit independent
linear regression models to each observed site index (SI) level and using a SI
prediction map in the application of the models. The most important predictor
variable was an upper percentile of the ALS heights, and
root-mean-squared-errors (RMSE) ranged between 3 and 31 years (6% to 26%) for
SI-specific models, and 21 years (25%) on average. Mean deviance (MD) ranged
between -1 and 3 years. The models improved with increasing SI and the RMSE
were largest for low SI stands older than 100 years. Using a mapped SI, which
is required for practical applications, RMSE and MD on plot-level ranged from
19 to 56 years (29% to 53%), and 5 to 37 years (5% to 31%), respectively. For
the validation stands, the RMSE and MD were 12 (22%) and 2 years (3%). Tree
height estimated from airborne laser scanning and predicted site index were the
most important variables in the models describing age. Overall, we obtained
good results, especially for stands with high SI, that could be considered for
practical applications but see considerable potential for improvements, if
better SI maps were available.

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The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat
1
The categories of this paper are: cs
24
The categories of this paper are: dg-ga
15
The categories of this paper are: nucl-ex
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom