Multispectral and LiDAR data fusion for fuel type mapping using Support Vector Machine and decision rules - García, Mariano; Riaño, David; Chuvieco, Emilio; Salas, Javier; Danson, F. Mark; García, Mariano; Riaño, David; Chuvieco, Emilio; Salas, Javier; Danson, F. Mark (REMOTE SENSING OF ENVIRONMENT, 2011)
This paper presents a method for mapping fuel types using LiDAR and multispectral data. A two-phase classification method is proposed to discriminate the fuel classes of the Prometheus classification system, which is adapted to the ecological characteristics of the European Mediterranean basin. The first step mapped the main fuel groups, namely grass, shrub and tree, as well as non-fuel classes. This phase was carried out using a Support Vector Machine (SVM) classification combining LiDAR and multispectral data. The overall accuracy of this classification was 92.8% with a kappa coefficient of 0.9. The second phase of the proposed method focused on discriminating additional fuel categories based on vertical information provided by the LiDAR measurements. Decision rules were applied to the output of the SVM classification based on the mean height of LiDAR returns and the vertical distribution of fuels, described by the relative LiDAR point density in different height intervals. The final fuel type classification yielded an overall accuracy of 88.24% with a kappa coefficient of 0.86. Some confusion was observed between fuel types 7 (dense tree cover presenting vertical continuity with understory vegetation) and 5 (trees with less than 30% of shrub cover) in some areas covered by Holm oak, which showed low LiDAR pulses penetration so that the understory vegetation was not correctly sampled. (C) 2011 Elsevier Inc. All rights reserved.
The following values have no corresponding Zotero field: pub-location: 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA publisher: ELSEVIER SCIENCE INC
Keywords: Data fusion; Decision rules; Fuel types; LiDAR; Prometheus Classification System; Support Vector Machine

Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data - García, Mariano; Riaño, David; Chuvieco, Emilio; Danson, F. Mark; García, Mariano; Riaño, David; Chuvieco, Emilio; Danson, F. Mark (REMOTE SENSING OF ENVIRONMENT, 2010)
Biomass fractions (total aboveground, branches and foliage) were estimated from a small footprint discrete-return LiDAR system in an unmanaged Mediterranean forest in central Spain. Several biomass estimation models based on LiDAR height, intensity or height combined with intensity data were explored. Raw intensity data were normalized to a standard range in order to remove the range dependence of the intensity signal. In general terms, intensity-based models provided more accurate predictions of the biomass fractions. Height models selected were mainly based on a percentile of the height distribution. Intensity models selected included variables that consider the percentage of the intensity accumulated at different height percentiles, which implicitly take into account the height distribution. The general models derived considering all species together were based on height combined with intensity data. These models yielded R(2) values greater than 0.58 for the different biomass fractions considered and RMSE values of 28.89, 18.28 and 1.51 Mg ha(-1) for aboveground, branch and foliage biomass, respectively. Results greatly improved for species-specific models using the main species present in each plot, with R(2) values greater than 0.85, 0.70 and 0.90 for black pine, Spanish juniper and Holm oak, respectively, and with lower RMSE for the biomass fractions. Reductions in WAR point density had only a small effect on the results obtained, except for those models based on a variation of the Canopy Reflection Sum, which was weighted by the mean point density. Based on the species-specific equations derived, Holm oak dominated plots showed the highest average carbon contained by aboveground biomass and branch biomass 44.66 and 31.42 Mg ha(-1) respectively, while for foliage biomass carbon, Spanish juniper showed the highest average value (3.04 Mg ha(-1)). (C) 2009 Elsevier Inc. All rights reserved.
The following values have no corresponding Zotero field: pub-location: 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA publisher: ELSEVIER SCIENCE INC
Keywords: Biomass fractions; Carbon content; Intensity; LiDAR