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Spatial Statistics and Its Application Study in Mapping and Image Processing of Forest

Author: FengYiMing
Tutor: TangShouZheng;LiZengYuan
School: Chinese Academy of Forestry
Course: Forest Management
Keywords: Spatial statistics Krieger Conditional simulation Image interpretation Forest maps
CLC: S711
Type: PhD thesis
Year: 2004
Downloads: 762
Quote: 8
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Abstract


Spatial statistics in less than 50 years of research and practice, its application has been extended to the analysis of a variety of natural phenomena, spatial heterogeneity and spatial pattern. Forest in the process of growth and development, the physical environment, natural disturbance, human disturbance, species characteristics, species responses to disturbance factors, has a high degree of spatial heterogeneity and temporal heterogeneity. Therefore, spatial statistical analysis techniques should have a wide range of application prospects in the field of forestry. But currently, spatial statistics forestry fledgling China and World the Shanglin scholars of spatial statistical applications in forestry papers yet. This paper summarizes the basic theory of spatial statistical analysis, review of spatial statistics in forestry research and application of the status quo, to solve the of forestry image and graphics processing aspects involved in two major categories of problems, ie \missing 'district interpreter \Bureau Jingouling experimental forest TM (30m * 30m resolution) remote sensing image data source selected from the image clouds obscured images as the experimental data, the use of space in the statistical theory of kriging techniques, image four clouds obscured area and clouds shadowed area pixel information recovery, recovery information by the re-classification were compared with the findings of the second-class resource, draw each block classification accuracy in more than 75%, indicating that the application Kriging interpolation model provide a means and method as we interpret images on fuzzy area. Like this article so specific to space statistical theory to interpret images of real information \2) research grade sample material, the application of the categorical variable sequence indicative conditional simulation algorithm northeast Wangqing Bureau revised sequence indicator conditional simulation algorithm samples the center painted squares method, Wangqing forest type distribution Figure drawing. By conditional simulation algorithm, improved conditional simulation algorithm simulation maps and sample point for the distribution center painted square method compared with two types of forest resources survey of forest maps derived sequence indicates conditional simulation algorithm correction sequence directions conditional simulation algorithm and maps the samples obtained by the method of the center draw a square, their overall accuracy of 73.80%, 81.43%, 69.12%, respectively. Two conditional simulation results were more than kind to the accuracy of the maps for the center draw a square, the higher the accuracy of the results obtained by the conditional simulation accuracy. Therefore, the kind of materials, application sequence indicator conditional simulation algorithm can be used as an effective way to obtain maps of forest types. Precision analysis, it can be seen that the rich forest types within the scope of the study, the lot, the simulation accuracy is relatively low, while the single lot of forest types, high simulation accuracy; same time, within the study area, type a larger proportion of the the type simulation accuracy is relatively high. 3) in the the application sequence indicator conditional simulation process, found that the method in determining attribution moot point, between Monte - Carlo method to obtain a random number in [0,1] and all kinds of cumulative conditional probability relationship to determine which have a certain chance on the inside, so the low estimation accuracy, the first proposed algorithm i lt; WP = gt; Abstract amendment. Correction algorithm simulation point type attributable to the kind of moot point at the conditional probability of the share, this method can weaken a chance ingredients. By comparing forest type sequence indicator simulation results, the revised sequence indicator simulation results with the two types of forest resources, forest survey maps, drawn revised sequence indicator conditional simulation accuracy was significantly greater than the sequence indicates the conditional simulation accuracy. 4) true in remote sensing image information \conditional simulation process in the space distribution of forest types involved spatial statistics algorithm, such as classification variable sequence indicator conditional simulation algorithm and improved algorithm. Algorithm process, there are a lot of algorithms such as experimental semivariogram model fitting, the sequence of categorical variables indicating conditional simulation algorithm and experimental half variogram solution to achieve compared with other similar software, specific to some innovative features. 5) research collection, inquired about space at home and abroad statistical analysis software system, trial and analysis of all the functions and features of the software, at the same time, starting from a functional point of view, from the design of the data processing, experimental semivariogram solving semivariogram model intends to co-kriging theory, and conditional simulation theory, the calculation results output spatial statistical analysis software and The illustrated aspects with the third-party tools, statistical analysis software design of the space of the forestry industry characteristics, and forestry characteristics the main program.

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CLC: > Agricultural Sciences > Forestry > Forestry basic science > Forest mathematics
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