Search

Spatial structure is an important characteristic of forest and spatial distribution pattern is one part of researches on population spatial behavior, Based on the relationship of neighborhood trees, three kinds of stand spatial structure parameters including uniform angle index, mingling and dominance was proposed by Professor Gangying Hui. In the past decade, stand spatial structure parameters are widely used to analyze stand spatial structure, calculate trees dominance, judge competition among trees, measure species diversity and recover or reconstruct stand structure at domestic and international study.. Measurement accuracy of spatial structural parameters (uniform angle index, mingling degree, and dominance) has a significant role in studying stand spatial structure. In the traditional direct interpretation method(DIM), it is difficult to measure the angle between reference tree and 4 nearest neighbor trees. For this method, the error derived from tree diameters at breast height is not considered in the process of measurement, so uniform angle index value is inaccurate. Moreover, based on DIM, other two parameters of mingle degree and dominance measurement required at least two operators, one person completed measurement and the other recorded field data, thus it is impossible to calculate the observing results immediately In this paper, a new measuring method named as HSSM was proposed using handheld smart station to measure stand spatial structure parameters in order to enhance measurement precision and accuracy, decrease field investigation workload. For measuring uniform angle index, the angle between reference tree and four nearest neighbor trees is not measured directly. Firstly, X-Y coordinates of reference tree and four nearest neighbor trees are measured using handheld smart station. Secondly, the diameters at breast height of five trees are measured corresponding with each tree, specifically, diameters at breast height measurement is to obtain center coordinates of five selected trees so as to increase angle calculation accuracy. Finally, reference tree as central point, intersection angles between four nearest neighbor trees are resolved according to the law of cosines. According to the above-mentioned measurement method, experiment was carried out in one stand forest plot (100 m×100 m) which located at Beijing Olympic Forest Park by three operators. The relative error of uniform angle index average value of HSSM was 2% less than that of DIM, average time-consuming (single person) of HSSM was 90.1s more than that of DIM (double person, 40.7 s), and measurement efficiency of HSSM was 8% lower than that of DIM. The mingle measurement result of HSSM were as the same as that of DIM, but the average time-consuming (single person) of HSSM was 21.5s less than that of DIM (double person, 32.2 s), measurement efficiency of HSSM was about 3 times that of DIM. The results of dominance relative error was 4% between HSSM and DIM, but the average time-consuming (single person) of HSSM was 74.8s more than that of DIM (31.05 s for double person), measurement efficiency of HSSM was 20% lower that of DIM. HSSM had the advantages of single person operation, display and storage directly by the equipment. Moreover, compared with the DIM, HSSM resolved the problem that DIM could not measure the tree center coordinate at breast height of reference tree and nearest neighbor tree, and for HSSM, the distribution of reference tree and nearest neighbor tree could draw conveniently and visually display according to measuring data in the process of interior work . This research can provide references for measuring forest spatial structure measurement accurately and efficiently. [ABSTRACT FROM AUTHOR]

With the increasing of the industrialization and urbanization, respirable particulate matter content in the air was increased, which caused serious damages to the surrounding environment of the capital region. In order to reduce the air pollution, analyzing the relationship between respirable particulate matter content in the air and vegetation cover is necessary. This paper researched and analyzed the relationship between respirable particulate matter and vegetation cover according to the region around the central capital, built the capital region with a virtual radius of 100km for the unit circle and divided the important factors such as vegetation, soil, environment, topography to different scales under rectangular grid. Five-year atmospheric pollutant data from 2008 to 2012 was used in this paper, which was provided by the Beijing Municipal Environmental Protection Bureau. The interpolation method of GS+ software and Moran's index were used to analyze spatial autocorrelation of the above variable factors and to calculate the radius of spatial influence in the capital region. Based on a rectangular grid method and Moran's index method, combined with SPSS software, this paper analyzed the distribution of vegetation and the concentration of respirable particulate matter in the air with the distance between the changes of the relationship. After Moran's index derived vegetation distribution and respirable particulate matter in the region around the capital concluded between the grid scale with increasing autocorrelation reduced. Autocorrelation range of vegetation cover is 6620-7131 m, and respirable particulate matter from the relevant sphere influence is 2 998-6 864 m. The spatial correlation distance between vegetation distribution and respirable particulate matter effect 41.87 km through nonlinear regression analysis with SPSS software, the standard errors(P) are between 0.001-0.003, correlation coefficient R2are more than 80%, and therefore non-linear regression model fits better. The accuracy of the model is more than 90%, while all kinds of factors aside 20% of the sample points to the selected model F-test, get outside accord accuracy above 90%.We use the gravitational extended formula to derive spatial correlation of vegetation (vegetation cover, biomass) and environmental factors-respirable particulate matter, the average spatial correlation of rainfall and temperature and calculate distance. The conclusion is drawn that the vegetation influence is decreased followed by the increase of the distance at different side length range and grid value. The innovation of this study is to establish the rectangular grid center in the Beijing Ring, and develop all kinds of elements in equality inside each grid. Each grid center is taken as the center point of the study sample. Through this study, the environmental pollution area is defined in the space radiation radius, which is helpful to remediation for that specific range, such as the introduction of appropriate measures, carrying out the reasonable control lest the car exhaust and factory emissions exceed the environmental capacity, and enhancing public awareness of environmental protection, afforestation according to "suitable tree" principle and in accordance with the rational allocation of species. Environmental effect of central capital region is closely associated with a variety of factors, and this study only establishes the basis of quantitative factors related to model and solves a major factor and the influence radius of various types of qualitative factors; further related research need to be carried in the further. [ABSTRACT FROM AUTHOR]

The height and volume of trees is one of the most significant factors in a forest survey, it has important significance for the investigation of forest resources and forestry scientific research. In order to solving the problem that we cannot confirm a single tree's volume exactly, which is caused by the inability to determine the tree height, when a part of the tree crown was in the shade, this paper utilized a different method for setting-out the tree height using a total station to measure the diameter at breast height (DBH), the diameter of the maximum observation point and the middle point's diameter of those two points, and the corresponding distance to the ground in the field investigation. This test observed 334 trees including 188 larch (Larix gmelinii) trees and 146 white birch (Betula platyphylla Suk), using a similar triangle method, single tree growth empirical equation method and Kunze, M. stem curve method to estimate the tree height and volume of every standing trees by constructing mathematical model. At the same time, there were four hypotheses of the highest observation points in the test, those four stations respectively being in 1/3H, 1/2H, 2/3H, and 9/10H. The three different methods above was used to calculate the tree height and its volume in this four different maximum observation station, and analyzing the precision of every situation. Respectively, the method of similar triangles, simple growth experience equation method and Kunze, M. stem curve method were used to build mathematical model, and through the model combined with tree growth and stem form theory to estimate the tree height and volume. This method only needs to measure a few stem diameter value and the corresponding height, combined with the tree growth equation and stem curve equation can estimate the height. Compared to the conventional method, the tree height precision using the new method was greatly improved. And using remote sensing technology of image reconstructed images of three-dimensional model for tree height method can simplify huge image data calculation process, and improve the efficiency of tree height measurement. The results show that the estimated height and volume values are more accurate with the increase of the maximum observation points. In those three methods, the accuracy can reach to 70%-80% with the tree growth empirical equation and 70%-90% with the Kunze M. stem curve method. Thus, the new method is satisfactory to measure a single tree's volume when it is in the shadow, and it has a very important significance for the actual production. [ABSTRACT FROM AUTHOR]