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Agricultural land abandonment and natural forest re-growth in the Swiss mountains: A spatially explicit economic analysis
Abstract Natural forest re-growth reflects a decline in traditional agricultural practices that can be observed worldwide. Over the last few decades, natural forest re-growth has replaced much of theExpand
Detection of individual tree crowns in airborne lidar data
Laser scanning provides a good means to collect information on forest stands. This paper presents an approach to delineate single trees automatically in small footprint light detection and rangingExpand
Comparative testing of single-tree detection algorithms under different types of forest
Airborne laser scanning data and corresponding field data were acquired from boreal forests in Norway and Sweden, coniferous and broadleaved forests in Germany and tropical pulpwood plantations in Brazil, and showed that forest structure strongly affected the performance of all algorithms. Expand
Non-parametric prediction and mapping of standing timber volume and biomass in a temperate forest: application of multiple optical/LiDAR-derived predictors
Summary In a mixed temperate forest landscape in southwestern Germany, multiple remote sensing variables from aerial orthoimages, Thematic Mapper data and small footprint light detection and rangingExpand
A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales
It can be concluded that tree species mapping from imaging spectroscopy for forest sites comparable to the one under investigation is possible with reliable accuracies not only from airborne but also from spaceborne imaging Spectroscopy datasets. Expand
Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment
  • B. Koch
  • Environmental Science
  • 1 November 2010
This is a review of the latest developments in different fields of remote sensing for forest biomass mapping. The main fields of research within the last decade have focused on the use of smallExpand
Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass
) and root mean squared error (RMSE) for bootstrapped estimates using k-fold cross-validation with a varying number of folds. Finally, Analysis of Variance (ANOVA) was used to quantify the influenceExpand
Exploring full-waveform LiDAR parameters for tree species classification
  • J. Heinzel, B. Koch
  • Geography, Computer Science
  • Int. J. Appl. Earth Obs. Geoinformation
  • 1 February 2011
Up to six tree species were classified with an overall accuracy of 57%, limiting to the four main species accuracy was improved to 78% and constraining just to conifers and broadleaved trees even 91% could be classified correctly. Expand
Comparison of Feature Reduction Algorithms for Classifying Tree Species With Hyperspectral Data on Three Central European Test Sites
A number of classification approaches were compared to classify tree species from airborne hyperspectral data across three forest sites to identify a single approach which continuously delivers high classification performances over all test sites and found that SVM wrapper and the GA slightly outperformed the PLS-based algorithm. Expand
Investigating multiple data sources for tree species classification in temperate forest and use for single tree delineation
  • J. Heinzel, B. Koch
  • Computer Science, Geography
  • Int. J. Appl. Earth Obs. Geoinformation
  • 1 August 2012
This study attempts to extend the existing limitations of tree species classification by investigating comprehensive sets of different types of features derived from multiple data sources, which include features from full-waveform LiDAR,LiDAR height metrics, texture, hyperspectral data and colour infrared data. Expand