scholarly journals Automatic Mapping of Standing Dead Trees after an Insect Outbreak Using the Window Independent Context Segmentation Method

2014 ◽  
Keyword(s):  
Segmentation Method ◽  
Insect Outbreak ◽  
Dead Trees ◽  
Standing Dead ◽  
Automatic Mapping ◽  
Standing Dead Trees

scholarly journals Classification of Tree Species as Well as Standing Dead Trees Using Triple Wavelength ALS in a Temperate Forest

2019 ◽  
Vol 11 (22) ◽  
pp. 2614 ◽  
Author(s):  
Nina Amiri ◽  
Peter Krzystek ◽  
Marco Heurich ◽  
Andrew Skidmore
Keyword(s):  
Tree Species ◽  
Feature Selection Method ◽  
Silver Fir ◽  
Maximum Point ◽  
Individual Tree ◽  
Dead Trees ◽  
Multi Wavelength ◽  
Standing Dead ◽  
Standing Dead Trees ◽  
532 Nm

Knowledge about forest structures, particularly of deadwood, is fundamental for understanding, protecting, and conserving forest biodiversity. While individual tree-based approaches using single wavelength airborne laserscanning (ALS) can successfully distinguish broadleaf and coniferous trees, they still perform multiple tree species classifications with limited accuracy. Moreover, the mapping of standing dead trees is becoming increasingly important for damage calculation after pest infestation or biodiversity assessment. Recent advances in sensor technology have led to the development of new ALS systems that provide up to three different wavelengths. In this study, we present a novel method which classifies three tree species (Norway spruce, European beech, Silver fir), and dead spruce trees with crowns using full waveform ALS data acquired from three different sensors (wavelengths 532 nm, 1064 nm, 1550 nm). The ALS data were acquired in the Bavarian Forest National Park (Germany) under leaf-on conditions with a maximum point density of 200 points/m 2 . To avoid overfitting of the classifier and to find the most prominent features, we embed a forward feature selection method. We tested our classification procedure using 20 sample plots with 586 measured reference trees. Using single wavelength datasets, the highest accuracy achieved was 74% (wavelength = 1064 nm), followed by 69% (wavelength = 1550 nm) and 65% (wavelength = 532 nm). An improvement of 8–17% over single wavelength datasets was achieved when the multi wavelength data were used. Overall, the contribution of the waveform-based features to the classification accuracy was higher than that of the geometric features by approximately 10%. Our results show that the features derived from a multi wavelength ALS point cloud significantly improve the detailed mapping of tree species and standing dead trees.

scholarly journals Standing Dead Trees are a Conduit for the Atmospheric Flux of CH4 and CO2 from Wetlands

Wetlands ◽  
2017 ◽  
Vol 38 (1) ◽  
pp. 133-143 ◽  
Author(s):  
Mary Jane Carmichael ◽  
Ashley M. Helton ◽  
Joseph C. White ◽  
William K. Smith
Keyword(s):  
Atmospheric Flux ◽  
Dead Trees ◽  
Standing Dead ◽  
Standing Dead Trees

scholarly journals MENAKAR SIFAT INVASIF SPESIES AKASIA MANGIUM (Acacia mangium Willd.) DI HUTAN PENELITIAN DAN PENDIDIKAN BUKIT SOEHARTO

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Sutedjo Sutedjo ◽  
Warsudi Warsudi
Keyword(s):  
Acacia Mangium ◽  
Dead Trees ◽  
Standing Dead ◽  
Standing Dead Trees

 Akasia mangium (Acacia mangium Willd) bukan tumbuhan asli Kalimantan namun sejak puluhan tahun tumbuh berkembang pesat di berbagai wilayah Kalimantan termasuk Kalimantan Timur. Dikenal sebagai tumbuhan yang mampu tumbuh di lahan kritis sehingga pada awal tahun 1990-an dijadikan tanaman  reboisasi sekaligus pengendali alang-alang di wilayah kritis hutan penelitian dan pendidikan Universitas Mulawarman di Bukit Soeharto. Mengherankan, bahwa beberapa tahun taerkhir sebagian praktisi kehutanan dan reklamasi pascatambang merasa gamang menggunakan A. mangium, khawatir jika jenis tersebut akan benar benar menjadi spesies invasif.  Gejala untuk menolak bahkan menghindari  A. mangium sebagai komoditas kehutanan terutama sebagai jenis pengendali lahan kritis mulai meluas. Untuk mengetahui seberapa benar anggapan Acacia mangium sebagai jenis invasif maka dilakukan evaluasi dengan melakukan analisis vegetasi terhadap 3 ha tegakan hutan A. mangium yang ditanam di Bukit Soeharto sebagai uji petik yang saat sekarang telah berumur sekitar 25 tahun. Hasil evaluasi membuktikan bahwa jumlah tanaman per ha (kerapatan) pohon A. mangium menurun (kurang dari jumlah saat ditanam atau sekitar 800 individu/ha). Jumlah yang menurun itupun cenderung mengelompok. Sebagian pohon bahkan ditemukan dalam kondisi mati generasi (standing dead trees). Sementara itu jumlah spesies pohon setempat (local trees species) juga mulai muncul di antara tegakan A.mangium. Dengan demikian terbukti  bahwa A. mngium bukanlah tipe invasif  yang sesungguhnya dan tidak ada alasan utuk menolak penggunaannya sebagai tanaman pengendali lahan kritis selama potensi ancaman terjadinya kebakaran lahan hutan dapat dicegah.

scholarly journals The structure of forest stands in the Tatra National Park: The results of 2016–2017 inventory

2019 ◽  
Vol 80 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Jan Bodziarczyk ◽  
Jerzy Szwagrzyk ◽  
Tomasz Zwijacz-Kozica ◽  
Antoni Zięba ◽  
Janusz Szewczyk ◽  
...  
Keyword(s):  
Picea Abies ◽  
Fagus Sylvatica ◽  
National Park ◽  
Forest Stands ◽  
Protection Zone ◽  
Dead Trees ◽  
Standing Dead ◽  
Elevation Zone ◽  
Standing Dead Trees ◽  
Tatra National Park

Abstract The composition and structure of forest stands in the Tatra National Park were examined using data gathered in 2016 and 2017 from 617 circular sample plots (0.05 ha each). The diameter at breast height of all living trees, standing dead trees, snags, and wind throws was measured along with diameters and lengths of fallen logs within the plot boundaries. Tree height was measured for all living trees within the core (0.01 ha) of the sample plots. Using the obtained data, height-diameter curves were calculated for all major tree species and in the case of spruce, the height-diameter relationships were also calculated separately for each of the three elevation zones (up to 1200 m, between 1200 and 1400 m, above 1400 m). For each elevation zone and park protection zone, we also determined the volumes of live and dead trees. The volume of living trees in the Tatra National Park amounted to 259 m3/ha, which was higher than the volume of dead trees (176 m3/ha). Snags constituted the largest part of the dead wood whilst over 97% of the standing dead trees were spruce Picea abies. Among living trees, the share of spruce ranged from 81% in the low elevation zone to 98% in the middle zone. Other significant species in the lower zone were Abies alba (11%) and Fagus sylvatica (4.5%), while in the middle and upper elevation zones only Sorbus aucuparia occurred in significant numbers. Furthermore, in the lower elevation zone, Fagus sylvatica was the only species displaying significantly higher volumes in the ‘strict protection’ zone compared to the other park areas. In the ‘landscape protection’ zone, Picea abies was the most dominant species and the share of other species in the lowest elevation zones calculated based on tree density was smaller than calculated based on tree volume, indicating problems with stand conversion from spruce monoculture to mixed forest.

Decay patterns and carbon density of standing dead trees in California mixed conifer forests

2015 ◽  
Vol 353 ◽  
pp. 136-147 ◽  
Author(s):  
Stella J.M. Cousins ◽  
John J. Battles ◽  
John E. Sanders ◽  
Robert A. York
Keyword(s):  
Conifer Forests ◽  
Carbon Density ◽  
Mixed Conifer ◽  
Dead Trees ◽  
Mixed Conifer Forests ◽  
Standing Dead ◽  
Standing Dead Trees

Relationship of root rot to black spruce windfall and mortality following strip clear-cutting

2002 ◽  
Vol 32 (2) ◽  
pp. 283-294 ◽  
Author(s):  
R D Whitney ◽  
R L Fleming ◽  
K Zhou ◽  
D S Mossa
Keyword(s):  
Relative Abundance ◽  
Root Rot ◽  
Black Spruce ◽  
Strong Association ◽  
Clear Cutting ◽  
Armillaria Ostoyae ◽  
Stem Breakage ◽  
Dead Trees ◽  
Standing Dead ◽  
Standing Dead Trees

Root and butt rots are often implicated as causal factors influencing windfall and mortality of residual trees following partial cutting. Measurements of decay at stump level (i.e., the upward extension of root rot) were made on cross-sectional discs taken from windfallen and standing dead 100- to 130-year-old black spruce (Picea mariana (Mill.) BSP) near Nipigon in northwestern Ontario. Subsequently, causal fungi were identified using laboratory culturing procedures. The incidence and amount of decay in windfallen trees within leave strips following alternate strip clear-cutting was higher than the general stand levels but lower than that found in windfallen trees in uncut forest. The incidence and amount of decay was also higher in windfallen trees near the centres of the leave strips than in those near the edges and corners of these strips. These results indicate a strong association between root rot and windfall and suggest that for comparable windfirmness, trees near the edges of residual stands must have less decay than those in more sheltered locations. Decay levels tended to be lower on poorly drained sites than on well-drained sites. In uncut forest, and especially in the leave strips, more trees were uprooted than died standing or suffered stem breakage. The incidence and amount of decay tended to be lower in uprooted trees than in standing dead trees or those with stem breakage, although in uncut forest virtually all windfallen or standing dead trees had some degree of stump-level decay. Of the 21 wood-rotting Basidiomycetes isolated from windfallen and standing dead trees, Inonotus tomentosus (Fr.:Fr.) Teng was the most frequent, followed in order by Armillaria ostoyae (Romagn.) Herink, Coniophora puteana (Schum.:Fr.) Karst., and Scytinostroma galactinum (Fr.) Donk. The incidence of I. tomentosus, C. puteana, Xeromphalina campanella (Batsch.:Fr.) Kuhner & Maire, and Serpula himantioides (Fr.:Fr.) Karst., but not Armillaria ostoyae, Scytinostroma galactinum, and Sistotrema brinkmanii (Bres.) Erik., was greater in windfallen and standing dead trees from the leave strips than in the general stand populations. In the leave strips, I. tomentosus, Amylostereum chailletii (Pers.:Fr.) Boid., and Trichaptum abietinum (Dickson:Fr.) Ryv. tended to greater relative abundance in standing dead trees, while the relative abundance of C. puteana and Serpula himantioides was greater in trees with stem breakage. Armillaria ostoyae and Scytinostroma galactinum were as abundant in uprooted trees as in standing dead trees or those with stem breakage. Ascocoryne sarcoides (Jacq.:Fr.) G. & W., a staining fungus that may protect against decay fungi, was frequently isolated in this study.

scholarly journals CLASSIFICATION OF TREE SPECIES AND STANDING DEAD TREES BY FUSING UAV-BASED LIDAR DATA AND MULTISPECTRAL IMAGERY IN THE 3D DEEP NEURAL NETWORK POINTNET++

2020 ◽  
Vol V-2-2020 ◽  
pp. 203-210
Author(s):  
S. Briechle ◽  
P. Krzystek ◽  
G. Vosselman
Keyword(s):  
Neural Network ◽  
Tree Species ◽  
Deep Neural Network ◽  
Lidar Data ◽  
Individual Tree ◽  
Dead Trees ◽  
Standing Dead ◽  
Standing Dead Trees ◽  
Multiple Tree

Abstract. Knowledge of tree species mapping and of dead wood in particular is fundamental to managing our forests. Although individual tree-based approaches using lidar can successfully distinguish between deciduous and coniferous trees, the classification of multiple tree species is still limited in accuracy. Moreover, the combined mapping of standing dead trees after pest infestation is becoming increasingly important. New deep learning methods outperform baseline machine learning approaches and promise a significant accuracy gain for tree mapping. In this study, we performed a classification of multiple tree species (pine, birch, alder) and standing dead trees with crowns using the 3D deep neural network (DNN) PointNet++ along with UAV-based lidar data and multispectral (MS) imagery. Aside from 3D geometry, we also integrated laser echo pulse width values and MS features into the classification process. In a preprocessing step, we generated the 3D segments of single trees using a 3D detection method. Our approach achieved an overall accuracy (OA) of 90.2% and was clearly superior to a baseline method using a random forest classifier and handcrafted features (OA = 85.3%). All in all, we demonstrate that the performance of the 3D DNN is highly promising for the classification of multiple tree species and standing dead trees in practice.

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