Taking the 13 years pure artificial forest Phoebe chekiangensis and heterogeneous mixed forests in Tiantong mountain, Zhejiang Province as the research object, the characteristics of stand development, tree competition differentiation, tree height/breast diameter ratio and dominant wood growth were compared and analyzed from the perspective of ecology. The results show that compared with pure forests, the growth advantages of heterogeneous mixed-age forests were significant. Average breast diameter growth of stand increased 1.8%; the growth of single plant wood accumulation increased 7.4%. The relationship between tree height and diameter showed that the high growth of Phoebe chekiangensis individuals in the heterogeneous mixed forest was significantly promoted, and the high growth of the tree was 8.4% higher than that of pure forest. 1–5 grade wood scale sizes Phoebe chekiangensis in heterogeneous mixed forests and pure forests are ranked grade 3 (43.7%) > grade 2 (26.5%) > grade 4 (15.7%) > grade 1 (12.9%) > grade 5 (1.2%); grade 3 (34.7%) > level 2 (25.6%) > level 4 (20.0%) > level 1 (18.2%) > level 5 (1.2%); the straight-diameter structure shows a normal distribution, and the degree of differentiation of pure forests is greater than that of heterogeneous forests. The dominant trees of Phoebe chekiangensis pure forest and heterogeneous forest accounted for 18.2% and 12.9% of the total number of plants respectively, providing a reserve of 51.1% and 35.4% respectively, reflecting the contribution of dominant trees caused by the self-thinning effect.
Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.
[Objective] To understand the relationship between species diversity and tree growth in natural secondary forests in Northeast China, to determine the reasonable size of species diversity, and to carry out appropriate nurturing harvesting and artificial replanting, so as to provide a scientific and theoretical basis for secondary forest management and management. [Methods] A total of 123 sample plots were set up in the Xiaoxinganling (XXAL), Zhangguangcailing (ZGCL), Laojialing (LYL), Changbai Mountain (CBS), Hadaling (HDL) and Longgang Mountain (LGS) areas in Northeast China, they were used to investigate the species composition, importance value, diversity and tree growth in each area. [Results] A total of 48 species belonging to 17 families and 31 genera were investigated in all the sample plots, among which the sample plots in Longgang Mountain contained the largest number of families, genera and species, followed by Hada Ling, Changbai Mountain, Laoyaling, Zhangguangcai Mountain and Xiaoxinganling. The α-diversity index of species in the sample sites was the largest in Changbai Mountain and the smallest in Xiaoxinganling, and the difference between them was significant (P < 0.05), while the richness index was the largest in Longgang Mountain and the smallest in Xiaoxinganling. The difference between them was significant (P < 0.05), while the greater the difference in latitude between the regions, the more obvious the difference in β-diversity index of species in the sample sites, and the fewer species shared between the two regions. The higher the rate of community succession, the higher the average diameter at breast height and the average tree height in each region were CBS > LYL > LGS > ZGCL > HDL > XXAL. The largest breast tree species in each region was Mongolian oak in Changbai Mountain with a diameter at breast height of 64.8 cm, and the smallest breast tree species in each region was Tyrannus sylvestris in Longgang Mountain with a diameter at breast height of 4.0 cm. The highest tree species in each region was Liriodendron sylvestris in Longgang Mountain with a height of 28.9 m, and the smallest species is yellow pineapple with a height of 1.3 m in Longgang Mountain. [Conclusion] Within a certain range, species diversity has a facilitating effect on the average diameter at breast height and average tree height of species within a stand. Therefore, during the management of secondary forests, appropriate nurturing harvesting and artificial replanting should be adopted to ensure reasonable species diversity in the stands and provide optimal space for the growth of natural secondary forests.
Every year, hundreds of fires occur in the forests and rangelands across the world and damage thousands hectare of trees, shrubs, and plants which cause environmental and economic damages. This study aims to establish a real time forest fire alert system for better forest management and monitoring in Golestan Province. In this study, in order to prepare fire hazard maps, the required layers were produced based on fire data in Golestan forests and MODIS sensor data. At first, the natural fire data was divided into two categories of training and test samples randomly. Then, the vegetation moisture stresses and greenness were considered using six indexes of NDVI, MSI, WDVI, OSAVI, GVMI and NDWI in natural fire area of training category on the day before fire occurrence and a long period of 15 years, and the risk threshold of the parameters was considered in addition to selecting the best spectral index of vegetation. Finally, the model output was validated for fire occurrences of the test category. The results showed the possibility of prediction of fire site before occurrence of fire with more than 80 percent accuracy.
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