Paper Info
Title
Modelling stratified forest attributes using optical/LiDAR features in a central European landscape.
Abstract
Improvements in the acquisition of three-dimensional (3D) information from the Airborne Laser Scanner (ALS) increase its applications for studying Earth's surface. The use of ALS data in natural resource inventories is still in an experimental stage in central Europe. Here, a survey was completed in Germany, where plot-level features from LANDSAT Thematic Mapper and ALS data were applied. An automated process was developed for forest stratification using orthoimages. A genetic algorithm was applied for variable screening. Variable subsets of different sizes were employed for simultaneous predictions of structural forest attributes using the 'Random Forest' (RF) method. Performance was assessed by leave-one-out cross-validations on bootstrap resample data. Results indicate that the stratification of forest notably improved the results of predictions. The improvements were more obvious for the strata-related attributes. Accuracy was enhanced as the number of selected variables increased. However, parsimonious models are still essentially required for practical applications. The RF errors were slightly greater than those from least squares regression, as the non-parametric methods do not share the same mix of error components as regression. Through the combination of remote sensing and modelling, we conclude that our results are helpful for bridging the gap between regional earth observation and on-the-ground forest structure.
Year
DOI
Venue
2012
10.1080/17538947.2011.583992
INTERNATIONAL JOURNAL OF DIGITAL EARTH
Keywords
Field
DocType
spatial prediction,natural resource inventory,ALS,Digital Earth,data fusion,remote sensing
Thematic Mapper,Digital Earth,Laser scanning,Remote sensing,Sensor fusion,Lidar,Random forest,Geography,Genetic algorithm,Bootstrapping (electronics)
Journal
Volume
Issue
ISSN
5
2.0
1753-8947
Citations 
PageRank 
References 
3
0.58
6
Authors
4
Name
Order
Citations
PageRank
Hooman Latifi1294.47
Arne Nothdurft251.27
Christoph Straub3101.69
Barbara Koch4878.38