An individual Tree Basal Area Equation was developed for a Young Tectona grandis plantation of the Department of Forestry and Wildlife Management, Faculty of Agriculture, University of Port Harcourt (UNIPORT) Choba, Rivers State; using diameter at breast height (dbh), diameter at the base (db), crown diameter (CD), and crown projection area (CPA) as predictor variables. The individual basal area estimates were obtained from data collected from 437 trees in the five-year-old plantation of dimensional area of 2737.5m2.The individual trees were measured for dbh, CD, and db using traditional measuring techniques, while individual Basal Area (BA) and CPA were estimated from the data sets. The data collected were further subjected to descriptive, correlation and regression analyses with different empirical models, using STATISTICA statistical package. The results of the descriptive analyses produced a mean values of DBH of 7.89±0.0097 cm, BA with the mean value of 0.0052±0.0001 m2, DB with 32.64±0.397 cm, CD of 3.1004±0.041 m and CPA with a mean value of 8.1268±0.215 m2. The results of regression analyses and modelling with empirical non-linear basal area equations fitted with Quadratic models, Exponential models, Linear Fit models and Polynomial models on STATISTICA produced best fits estimates in accordance with residual analyses and fit indices such as Mean Prediction Residual (MPR), Standard Error of Estimate (SEE), Residual Coefficient Variation (RCV) and Prediction Sum of Squares (PRESS). The Quadratic equation (BA = bo + biCPA + DB2; R2 - 0.8959; SEE - 0.0004) after the evaluation procedures gave the most robust fit indices for the individual basal area, and was thus adjudged the best individual basal area equation for Tectona grandis plantations in the study area. This study has shown that the selected model can be effectively used for predicting individual tree basal area of Tectona grandis both within the study area and in any other Tectona grandis plantations and, hence, for management and for making timber harvest decisions.
Jelutong Kapur and Sanaman are indigenous species at peat swamp forest. These plants have a great economic value. Besides the benefits from wood and sap, leaves can be used for medicinal purposes. The study aimed at obtaining the information related to the potential, distribution and increment diameter. This information was expected to be taken into consideration in the management and development of Jelutong. The study was conducted for 12 months in 12 observation plots, each plot measuring 100x100 m. The data were analyzed descriptively, while the growth patterns were shown graphically. The results showed that there were 100 Jelutong Kapur trees with a range 0–17 trees/plot, an average 8 trees/hectare. It was higher than Jelutong Sanaman, where there were 65 trees with a range of 0–13 trees/plot, an average 5 trees/hectare. However, jelutong Kapur had a diameter range 10.58–35.08 cm, the average increment diameter is 0.69 cm/year, the highest in the diameter class 10–15.9 cm and 22–26.9 cm which is 0.68 cm/year. It is lower than Jelutong Sanaman the diameter of which ranges within 12.61–37.13 cm, the average increment diameter is 0.77 cm/year, the highest increment in the class diameter of 10–15.9 cm is 0.85 cm/year. The highest and lowest number of trees is the same both in the diameter class 16–21.9 cm and 10–15.9 cm. The base area of Jelutong Kapur was 0.41789 m2/hectare, while in the case of Jelutong Sanaman it was 0.30422 m2/hectare. In both of them the 16–21.9 cm diameter class, is dominant, i.e. constitutes 40%. Both species may potentially support the economy for the local people, especially at forest periphery.
Individual-tree models of basal area growth and density were developed for seven plantation species in swamp forest zone of Rivers State, Nigeria. Tree growth data were collected from pure permanent sample plots of seven plantation species within the study area with measurements of diameter at breast height (cm), diameter at the base (cm), total height of tree (m), and also the number of tree per plot was taken and obtained from plantation records. The Quantitative data collected from these selected plantation species were subjected to descriptive analysis, correlation and regression analyses. Linearized models for description of relationship between BA and other growth attributes were developed. The results of the major growth variables by species in the study area showed that Treculia africana has the highest dbh mean value 30.804 ±2.031 (cm) with density 0.0022 and basal area per hectare 1.79×10–4 (m2). Similarly, the results also showed that Nauclea dedirrichii has the lowest dbh mean value 08.484 ±0.339 (cm) with basal area 3.92×10–5 (m2) and density 0.0063 per hectare. The results of correlation analyses showed general associations between basal area and the growth attributes by species with coefficients of correlation ranging from –0.023 to 0.999. The results similarly revealed distinct variations by species in density, basal area and tree number in the study area. The results of relationship between basal area and other growth variables showed significant model fit (best fit) with diameter attributes with model order: LNBA = b0 + b1lnDb + b2Dbh2 in Enthandrophragma angolense (R2 - 0.964, RSME – 0.837). The results of the study revealed that there were significant variations in the growth attributes by species in the study area; with significant associations between the basal area and major growth variables evaluated in the study, while the selected best adjudged fit model in the study area could be reasonably used for predicting basal area which is critical in cubical volume estimation and sustainable management of the study area.
Rozwój technologii pozyskiwania geodanych nabrał w ostatnich latach dużego tempa co skutkuje rewolucyjnymi zmianami w wielu dziedzinach gospodarki, w tym w leśnictwie, gdzie obserwuje się wdrażanie takich rozwiązań jak naziemny skaning laserowy (Terrestrial Laser Scanning; TLS). Pomiary wybranych cech drzew takich jak: wysokość, średnica, zbieżystość i objętości (miąższość grubizny) pnia są przedmiotem badań i wdrożeń. Generowane zbiory danych (chmur punktów) TLS wymagają automatycznego procesu ich przetwarzania. Prezentowana praca dotyczy zastosowania metody TLS w inwentaryzacji lasu, tj. określaniu wybranych parametrów takich jak pole przekroju pierśnicowego drzewa (g), wysokości (h) i w efekcie miąższość pnia (V). Analizie poddano drzewostan sosnowy w Nadleśnictwie Milicz (wydzielenie 236a; wiek 105 lat). Skaning przeprowadzono z 4 stanowisk stosując skaner fazowy FARO LS 880. Dane referencyjne dla średnicy pnia pozyskano tradycyjnymi instrumentami (pierśnicomierz) oraz w oparciu o lotniczy skaning laserowy dla wysokości. Testowano szereg metod i wzorów na obliczenie miąższości grubizny pni 21 drzew, tj.: metodę brył obrotowych (3 różne zestawy par przekrojów: 1.3 /6.0; 2.0/5.0 oraz 2.0/6.0 m nad gruntem) oraz pomiar sekcyjny. Obie bazują na algorytmie określania pola przekroju wycinków pnia metodą otoczki wypukłej. Za referencję przyjęto tzw. wzór empiryczny dla sosny oraz zamiennie pomiar sekcyjny TLS (długość sekcji 0.5m). Stosowano także tradycyjną metodę bazującą na tzw. tablicach miąższości drzew stojących. Wyniki wskazują, iż miąższości uzyskane metodą sekcyjnego pomiaru TLS nie różnią się istotnie statystycznie od stosowanego w praktyce leśnej wzoru empirycznego, a wartości różnic sięgają jedynie 1.5%. W przypadku wzoru na bryły obrotowe, różnice w określaniu miąższości na poziomie powierzchni sięgają od 6.1% (przekroje z wysokości: 2.0/6.0m) do 8.4% (2.0/5.0m;) powodując jej zaniżenie. Wartości maksymalne określone na poziomie pojedynczych drzew różnią się czasem aż o 38.4% (2.0/5.0), co wskazuje na zmienność geometryczną brył pni drzew. Praca potwierdziła przydatność metody pomiaru sekcyjnego TLS oraz potrzebę dalszych prac nad opracowaniem nowych standardów i parametrów w inwentaryzacji lasu oraz konieczność stosowania zautomatyzowanych procesów przetwarzania danych.
EN
The development of geodata acquiring technology has become very fast in recent years and leads to changes in many areas of economy, also in forestry, where new, revolutionary solutions such as terrestrial laser scanning are being implemented. Measurements of such tree characteristics, as the tree height, DBH, taper and the stem volume are subject of a number of studies. Generated sets of data (point clouds) need a chain of automatic processing. This paper describes the application of TLS in forest inventory control, i.e. in determining several parameters such as basal area (g), height (h) and finally the stem volume (V). The 105 years old pine stand in Milicz Forest District was analysed (plot no. 8). Scanning was performed from 4 stations with the use of a FARO LS 880 laser scanner. Reference data were collected using both the traditional instruments (DBH), and airborne laser scanning (h). Several methods and formulas were tested to calculate the stem volume, i.e. methods based on solid of revolution (involving 3 different pairs of cross-sections: 1.3 /6.0; 2.0/5.0 and 2.0/6.0 m above the ground), and sectional measurements. In both methods, the surface area of the crosssections was calculated using the author's algorithm (convex hulls). As the reference, the so-called empirical formula designed for pine was applied, together with volume calculated for 0.5 m sections on TLS point cloud. Traditional methods based on tables with volumes calculated for single trees were also used. The results indicate that volume measurements based on sections do not differ statistically from volumes calculated by means of the empirical formula, while the differences amount to 1.5 % only. As regards the method based on solid of revolution, the differences amount to 6.1% (cross-sections: 2.0/6.0 m, Std. dev 8.0) and 8.4% (2.0/5.0 m) causing the underestimation of the volume. Maximum values, calculated for single trees, are sometimes very high (38.4% for 2.0/5.0 m cross-sections), which indicates geometrical differences in the stem solid. The paper confirmed usability of section measurements within TLS point cloud and the need for further research on defining new standards and parameters for forest inventory control, as well as the necessity of applying automatic algorithms for data processing.
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Pinus cembra forests are limited to the Alps and Carpathians. Although several studies regarding their structure were carried out in some locations in the Tatra Mts. it required further investigations. Therefore, the aims of this study were to describe the stand and shrub structure of P. cembra forests, compare their structure with the Picea abies forests and analyse differences between silicate and calcicolous P. cembra forests in the Tatra Mts. The data were collected on the 16 sampling plots (500 m2), in the Swiss stone pine and Norway spruce forests. We measured the diameter at breast height (dbh) of each tree and recorded the young trees and shrubs. In order to compare species composition between silicate and calcicolous P. cembra forests, we made 91 relevés in their entire range of distribution (917 ha). Furthermore, we examined the share of main tree species along the altitude and inclination gradients, using the GAM models. The tree density in the P. cembra forests reaches 618 stems per ha, whereas their basal area (BA) 23.17 m2 ha-1. Main tree species are P. cembra and P. abies. P. cembra dominates in the higher thickness classes. The BA and dbh structure varies significantly between P. cembra and P. abies forests. The most abundant juveniles are P. abies and Sorbus aucuparia. The differences between forests growing on different substrate are relatively low. The altitude has a significant impact on the share of P. cembra (increase) and P. abies (decrease). The inclination has a significant impact on the increase of share of P. cembra.
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