scholarly journals Improving LiDAR-based tree species mapping in Central European mixed forests using multi-temporal digital aerial colour-infrared photographs

Author(s):  
Yifang Shi ◽  
Tiejun Wang ◽  
Andrew K. Skidmore ◽  
Marco Heurich
Ecosystems ◽  
2015 ◽  
Vol 18 (4) ◽  
pp. 560-572 ◽  
Author(s):  
Jorma Zimmermann ◽  
Markus Hauck ◽  
Choimaa Dulamsuren ◽  
Christoph Leuschner

2019 ◽  
Vol 11 (22) ◽  
pp. 2599 ◽  
Author(s):  
Markus Immitzer ◽  
Martin Neuwirth ◽  
Sebastian Böck ◽  
Harald Brenner ◽  
Francesco Vuolo ◽  
...  

Detailed knowledge about tree species composition is of great importance for forest management. The two identical European Space Agency (ESA) Sentinel-2 (S2) satellites provide data with unprecedented spectral, spatial and temporal resolution. Here, we investigated the potential benefits of using high temporal resolution data for classification of five coniferous and seven broadleaved tree species in a diverse Central European Forest. To run the classification, 18 cloud-free S2 acquisitions were analyzed in a two-step approach. The available scenes were first used to stratify the study area into six broad land-cover classes. Subsequently, additional classification models were created separately for the coniferous and the broadleaved forest strata. To permit a deeper analytical insight in the benefits of multi-temporal datasets for species identification, classification models were developed taking into account all 262,143 possible permutations of the 18 S2 scenes. Each model was fine-tuned using a stepwise recursive feature reduction. The additional use of vegetation indices improved the model performances by around 5 percentage points. Individual mono-temporal tree species accuracies range from 48.1% (January 2017) to 78.6% (June 2017). Compared to the best mono-temporal results, the multi-temporal analysis approach improves the out-of-bag overall accuracy from 72.9% to 85.7% for the broadleaved and from 83.8% to 95.3% for the coniferous tree species, respectively. Remarkably, a combination of six–seven scenes achieves a model quality equally high as the model based on all data; images from April until August proved most important. The classes European Beech and European Larch attain the highest user’s accuracies of 96.3% and 95.9%, respectively. The most important spectral variables to distinguish between tree species are located in the Red (coniferous) and short wave infrared (SWIR) bands (broadleaved), respectively. Overall, the study highlights the high potential of multi-temporal S2 data for species-level classifications in Central European forests.


2021 ◽  
Vol 13 (14) ◽  
pp. 2647
Author(s):  
Julia Tatum ◽  
David Wallin

Practical methods for tree species identification are important for both land management and scientific inquiry. LiDAR has been widely used for species mapping due to its ability to characterize 3D structure, but in structurally complex Pacific Northwest forests, additional research is needed. To address this need and to determine the feasibility of species modeling in such forests, we compared six approaches using five algorithms available in R’s lidR package and Trimble’s eCognition software to determine which approach most consistently identified individual trees across a heterogenous riparian landscape. We then classified segments into Douglas fir (Pseudotsuga menziesii), black cottonwood (Populus balsamifera ssp. trichocarpa), and red alder (Alnus rubra). Classification accuracies based on the best-performing segmentation method were 91%, 92%, and 84%, respectively. To our knowledge, this is the first study to investigate tree species modeling from LiDAR in a natural Pacific Northwest forest, and the first to model Pacific Northwest species at the landscape scale. Our results suggest that LiDAR alone may provide enough information on tree species to be useful to land managers in limited applications, even under structurally challenging conditions. With slight changes to the modeling approach, even higher accuracies may be possible.


2009 ◽  
Vol 36 (5) ◽  
pp. 854-864 ◽  
Author(s):  
Benjamin Köckemann ◽  
Holger Buschmann ◽  
Christoph Leuschner

2009 ◽  
pp. 143-158
Author(s):  
Milun Krstic ◽  
Bojana Cevrljakovic

The study was carried out in sessile oak forests and beech forests in the region central Serbia. The stands are classified as pure stands with the percentage of other species up to 10% per tree number, mixed forests of sessile oak with other species, and mixed forests of beech with other species, whose percentage does not exceed 50%. Altogether 257 stands were monitored - 202 beech stands and 55 sessile oak stands. By the applied method of defining the local heat potential (Lujic, 1960), modified by Ratknic et al. (2001) and Krstic (2004, 2008), which represents possibility of soil heating without vegetation, were determined. In this way, a scale of 162 possible combinations of local heat potential was obtained, which explains more precisely the dependence of beech stands and sessile oak stands on the topographic conditions. By applying the weighted values of the thermal co-ordinates of aspect and slope (E) for each altitudinal belt of 100 m, it was concluded that pure stands have the widest ecological range. Pure beech stands occur at the sites with 34 combinations of thermal co-ordinates E.V=4.6 to 8.12. Pure sessile oak stands occur at the sites with 12 combinations of thermal co-ordinates E.V=5.10 to 8.11. The percentage of mixed beech stands with other broadleaf species is the highest at the sites with the co-ordinate V=10-11 (at the altitudes between 700 and 900 m) is about 60 %. Mixed stands of sessile oak and beech are located on the terrains with combinations of thermal co-ordinates E.V=7.9 to 8.12. By using the local heat potential of a region, it can be identified which sites, i.e. which combinations of exposure, slope and altitude belong to the particular tree species. Consequently, a more reliable selection of tree species can be done for the bio-reclamation of barrens and other deforested terrains.


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