Estimating Stand Carrying Capacity for Three Common Pine Species Across Various Regions of Türkiye

Forests, Journal Year: 2025, Volume and Issue: 16(2), P. 374 - 374

Published: Feb. 19, 2025

Sustainable management of forest ecosystems requires assessing dynamics and project stand growth yield in order to make strategic decisions. The size–density relationship is one the most important measures quantifying carrying capacity a ecosystem determining appropriate silvicultural In this study, maximum density index (SDImax) was estimated for three common pine species seven different ecological regions across Türkiye. Observations from 14,413 sample plots, including Calabrian (Pinus brutia Ten.; 6266 plots five regions), Black nigra J.F. Arnold; 6106 regions) Scots sylvestris L.; 2041 forests were used covering entire natural range these species. A mixed model with region as random effect developed each estimate SDImax. Results show that slope coefficients self-thinning lines vary by are significantly −1.605. stands exhibited highest SDImax, followed stands. Across regions, SDImax observed Aegean East Anatolia pine. arid Inner yielded lowest humid semi-humid showed higher compared regions. studied up almost half total area results study therefore very terms quantitative assessment country’s forests. differences species, which also widely distributed outside Türkiye under conditions, may be relevant source information other Moreover, considering dry environments have lower than those it seems likely will affected increasing global warming.

Language: Английский

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Analyzing regression models and multi-layer artificial neural network models for estimating taper and tree volume in Crimean pine forests

iForest - Biogeosciences and Forestry, Journal Year: 2024, Volume and Issue: 17(1), P. 36 - 44

Published: Feb. 29, 2024

The taper and merchantable tree volume equations are the most used models in forestry because of their accuracy estimating both total volume. However, numerous studies reported that artificial neural network show fewer errors a greater success rate as compared to regression models. This study data from 200 Crimean pine trees Turkey’s Central Anatolia Mediterranean Region assess performance (ANN) Max-Burkhart’s equation for accurate results were obtained using 3 hidden layers 10 neurons model 1 layer 100 model. hyperbolic tangent sigmoid function was ANN analysis hyper-parameter customization. Using with customization, AAE Max-Burkhart decreased 9.315 6.939 (-25.5%), RMSE 3.072 2.656 (-13.5%), FI increased 0.964 0.966 (+1.23%). Similarly, 0.056 0.013 (-76.6%), 0.247 0.12 (-51.6%), 0.909 0.979 (+7.69%). Our showed models’ predictions more reliable equations. We resolved overfitting via modification, which also allowed monitoring impact error prediction outputs at various learning rates. It possible develop lower rates training validation data, consistent growth trends sets.

Language: Английский

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Ormancılıkta makine öğrenmesi kullanımı

Turkish Journal of Forestry | Türkiye Ormancılık Dergisi, Journal Year: 2023, Volume and Issue: unknown, P. 150 - 177

Published: May 17, 2023

Gelişen teknolojiyle beraber diğer disiplinlerde olduğu gibi ormancılıkta da geleneksel uygulamaların daha ekonomik, etkin, hızlı ve kolay yapılabilmesi için yenilikçi yaklaşımların kullanımına talepler ihtiyaçlar artmaktadır. Özellikle son dönemde ortaya çıkan ormancılık bilişimi, hassas ormancılık, akıllı Ormancılık (Forestry) 4.0, iklim-akıllı sayısal büyük verisi terimler disiplinin gündeminde yer almaya başlamıştır. Bunların neticesinde de makine öğrenmesi otomatik (AutoML) modern karar verme süreçlerine entegre edildiği akademik çalışmaların sayısında önemli artışlar gözlenmektedir. Bu çalışma, algoritmalarının Türkçe dilinde anlaşılırlığını artırmak, yaygınlaştırmak ilgilenen araştırmacılar yönelik bir kaynak olarak değerlendirilmesi amacıyla konulmuştur. Böylece çeşitli faaliyetlerinde öğrenmesinin hem geçmişten günümüze nasıl kullanıldığını gelecekte kullanım potansiyelini koyan derleme makalesinin ulusal literatüre kazandırılması amaçlanmıştır.

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Integration of field measurements with unmanned aerial vehicle to predict forest inventory metrics at tree and stand scales in natural pure Crimean pine forests

International Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: 45(12), P. 3846 - 3870

Published: June 4, 2024

Inventorying forest ecosystems is an essential part of management planning. However, it quite costly and time-consuming, particularly for larger areas. Recently, significant developments have been made in unmanned aerial vehicle (UAV) technology to improve the cost time efficiency inventory. Therefore, UAV images become one inventory tools that produces data with high spatial resolution determining resources. This study aims investigate contribution a case area total 30 sample plots located pure natural Crimean pine (Pinus nigra J.F. Arnold ssp. pallasiana (Lamb.) Holmboe) stands Black Sea backward region Türkiye. Total tree height (h) stem volume (v) were recorded at individual level (n = 367), number trees (N), mean (hmean), top (htop), stand basal (BA) (V) calculated plot 30) from both field UAV-based data. Pearson's correlation coefficients (r) h v 0.96 0.72, respectively, highest was observed hmean - htop (r 0.96), while lowest found BA 0.54). The suitability observation prediction values assessed using t-test levels. According results, h, v, hmean, htop, V metrics be compatible (p > 0.05), but not N < 0.05). Overall results indicated has potential used can contribute determination metrics. Thereby, saves studies helps monitoring dynamic structure ecosystem effective approach

Language: Английский

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Predicting stem taper using artificial neural network and regression models for Scots pine (Pinus sylvestris L.) in northwestern Türkiye

Scandinavian Journal of Forest Research, Journal Year: 2023, Volume and Issue: 38(1-2), P. 97 - 104

Published: Feb. 17, 2023

ABSTRACTStem taper models are helpful tools for predicting diameter of a tree at any height or volume stem section. In this study, traditional and artificial neural network (ANN) approaches were used to predict tapers Scots pine individuals. The data in study correspond destructively sampled trees even-aged forest stands located the three important locations where grows naturally northwestern Türkiye. total, regression type from different categories an ANN model developed evaluated both statistically graphically. best results obtained by Kozak's accounting 99% total variance predictions.KEYWORDS: Artificial intelligenceBayesianmachine learningsegmented modelstem diametertaper modelvariable-form AcknowledgementsI very much appreciate comments associate editor four anonymous reviewers. assistance field collection staff Küre, Taşköprü Yenice Forest Enterprises, Dr. Ferhat Bolat about modeling greatly appreciated.Disclosure statementNo potential conflict interest was reported author(s).Funding statementThe author declares no specific funding work.

Language: Английский

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Exploring machine learning modeling approaches for biomass and carbon dioxide weight estimation in Lebanon cedar trees

iForest - Biogeosciences and Forestry, Journal Year: 2024, Volume and Issue: 17(1), P. 19 - 28

Published: Feb. 12, 2024

Accurate estimates of total tree biomass are critical importance to obtain reliable estimation the carbon dioxide weight sequestered from atmosphere by trees and forest stands. This information has potential guide appropriate management decisions which allow for both improvement sustainability implementation multi-task reforestation designs aimed mitigate detrimental effects climate change. The current laborious tree-destructive procedures needed attain such led development machine learning (ML) models at providing accurate estimations sequestering atmospheric dioxide. We tested Levenberg-Marquardt artificial neural network support vector regression techniques as an alternative non-linear allometric (NLR) modelling approaches commonly used estimation. developed ML using primary ground-truth data Lebanon cedar forests in Western Inner Anatolian regions Turkey, their predictions were compared those NLR same dataset. results showed that outperformed accurately estimating its components (above- belowground dry biomass, branches etc.), (SVR) gave highest accuracy estimates. Therefore, reliably estimated, with aim supporting best practices be applied stands Turkey.

Language: Английский

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Implementing linear mixed effects models to enhance estimation of the dimensional stability of wood of Laurus nobilis L.

Forest Systems, Journal Year: 2024, Volume and Issue: 33(2), P. e05 - e05

Published: June 14, 2024

Aim of study: The properties wood laurel (Laurus nobilis L.) have not yet been adequately described. For example, information on variables related to dimensional stability during drying (shrinkage) is lacking, even though this a key factor determining the suitability material for industrial uses with high added value. aim study was construct models estimating shrinkage by using density as predictor variable. Area Seventeen trees were felled in an inland area Galicia (north-western Spain) order obtain testing and modelling. Material methods: experimental tests performed 958 small standardised, defect-free specimens. Main results: under moderately heavy volumetrically unstable. Density varied only slightly, but volumetric statistically significantly within between trees. A linear mixed effects model constructed predict variation from oven-dry density, including factors tree height stem, random slopes intercepts. Research highlights: proved valid all sampled individuals up two metres thus enabling estimation commercial basal logs.

Language: Английский

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Farklı sıklık ölçütlerinin meşcere hacim tahmini üzerine etkisi

Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, Journal Year: 2024, Volume and Issue: 25(2), P. 249 - 255

Published: Oct. 14, 2024

Meşcere sıklık ölçütü, tek ağaç ve meşcere büyüme simülasyonlarının oluşturulmasında en önemli yardımcı açıklayıcı değişkenlerden birisidir. Bu çalışmada, iki farklı ölçütü değerlendirmeye alınmış bu ölçütlerin hacim tahminleri üzerindeki etkileri araştırılmıştır. ölçütlerden birisi―SD göğüs yüzeyinin orta çapına oranıyla ilgili iken diğeri―SDR belirli bir karşılık gelen birim alandaki sayısının meşcerede bulunabilecek maksimum sayısına bağlantılıdır. Çalışma kapsamındaki veriler, üç ayrı iklim rejimine sahip alandan rasgele örnekleme yöntemiyle seçilen toplam 108 örnek elde edilmiştir. SD SDR'yi kullanarak yeni doğrusal olmayan modelleri geliştirilmiş geliştirilen modellerin başarısı hata ölçütlerine bağlı olarak değerlendirilmiştir. Elde edilen bulgulara göre, modeller gözlemlenen hacmindeki varyansın yaklaşık %80’ni açıklamıştır. Ancak, değişken SD’yi içeren model genç (≈20-30 yıl) ileri yaş sınıflarında (≈60-80 %25 oranında daha fazla hatalı tahminler sunmuştur. Bununla birlikte, dinamik kanuniyetleriyle uyumlu sonuçlar üretmiş, bonitet değiştikçe oranlı büyümeyi başarılı şekilde tahmin etmiştir. Mevcut çalışmadan bilgilere olarak, gerçekçi edebilmek için SDR’nin tercih edilmesi meşcerelerin yapısını temsil edebilen kullanılması önerilmektedir.

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