Do airborne laser scanning biomass prediction models benefit from Landsat time series, hyperspectral data or forest classification in tropical mosaic landscapes?

Airborne laser scanning (ALS) is considered as the most accurate remote sensing data for the predictive modelling of AGB. However, tropical landscapes experiencing land use changes are typically heterogeneous mosaics of various land cover types with high tree species richness and trees outside forests, making them challenging environments even for ALS. Therefore, combining ALS data with other remote sensing data, or stratification by land cover type could be particularly beneficial in terms of modelling accuracy in such landscapes. Our objective was to test if spectral-temporal metrics from the Landsat time series (LTS), simultaneously acquired hyperspectral (HS) data, or stratification to the forest and non-forest classes improves accuracy of the AGB modelling across an Afromontane landscape in Kenya. The combination of ALS and HS data improved the cross-validated RMSE from 51.5 Mg ha−1 (42.7%) to 47.7 Mg ha−1 (39.5%) in comparison to the use of ALS data only. Furthermore, the combination of ALS data with LTS and HS data improved accuracies of the models for the forest and non-forest classes, and the overall best results were achieved when using ALS and HS data with stratification (RMSE 40.0 Mg ha−1, 33.1%). We conclude that ALS data alone provides robust models for AGB mapping across tropical mosaic landscapes, even without stratification. However, ALS and HS data together, and additional forest classification for stratification, can improve modelling accuracy considerably in similar, tree species rich areas.Peer reviewe

Can models for forest attributes based on airborne laser scanning be generalized for different silvicultural management systems?

In Finland, interest in continuous cover forestry (CCF) has increased rapidly in recent years. During those years CCF has been examined from various viewpoints but not from the perspective of forest inventories. This holds especially true for applications based on remote sensing. Conversely, airborne laser scanning (ALS) data have been widely used to predict forest characteristics such as size distribution and vertical forest structure, which are closely related to the forest information needs of CCF. In this study we used the area-based approach to predict a set of stand attributes from ALS data (5 pulses per m2) in a CCF forest management experiment in Katajama & BULL;ki, eastern Finland. In addition to the CCF stands, the experiment included shelterwood stands and untreated stands. The predicted attributes included volume, biomass, basal area, number of stems, mean diameter, Lorey's height, dominant height, standing dead wood volume, parameters of the theoretical stem diameter distribution model, understory height and number of understory stems. Our main aim was to test whether the same model could be used across different management systems. The accuracy of the attributes predicted for the CCF stands was compared with the predictions for the other management systems in the same experiment. We also compared and discussed our results in relation to the even-aged stand attribute predictions that were conducted by using separate operational forest data collected from sites surrounding Katajama & BULL;ki. The results showed that forest data from the different management systems could be combined into a single model of a stand attribute, i.e., ALS metrics were found to be suitable for comparing different management systems in regard to differences in forest structure. The accuracy of the predicted attributes in the CCF plots was comparable to that of the other management alternatives in the experiment. The accuracy was also comparable to that of even-aged forests. The results of this study were promising; the stand attributes of CCF-managed forests could be predicted analogously to those of other management systems. This indicates that for the purposes of forest inventories there may not be a need to stratify forest lands by management system. It should be noted, however, that the study area was relatively small, that the forest stands were harvested in the 1980 s, and that the attributes may not have been completely exhaustive for CCF

Lapin metsävaratietoa, Valtakunnan metsien inventointi Lapissa

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Comparing regional forest policy scenarios in terms of predicted suitable habitats for the Siberian flying squirrel (Pteromys volans)

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5,7,8,10,15,17,18,20-Octaphenyl-21,23-dithiaporphyrin: synthesis, structure and spectroelectrochemistry

The synthesis, molecular structure as well as in situ spectroelectrochemical and electron spin resonance (ESR) studies of 5,7,8,10,15,17,18,20-octaphenyl-21,23-dithiaporphyrin (SOPP) are presented. The compound investigated can be reversibly oxidised and reduced to yield the corresponding stable monocation and monoanion species, respectively. The experimental ESR spectrum of SOPP can be simulated taking into account the splitting constants 2xa = 2.3\ua0G from two dominating equivalent nitrogen nuclei. The computed spin delocalization at the density functional theory (DFT) for the cation is completely different compared to the spin delocalization of the corresponding monoanion. The largely delocalized unpaired spin density over the heteroatoms of dithiaporphyrin macrocycle was confirmed for the SOPP radical anion. The role of the phenyl substitution in the meso- or β-positions of the parent 21,23-dithiaporphyrin SP was also investigated theoretically and the results are compared with the normal (N core) porphyrin molecule