Application of DTM to the Spatial Pattern Analysis for Major Forest Types in the Hohuan Mountain Area

碩士 === 國立中興大學 === 森林學系 === 87 === AbstractDue to rapid reduction in the forest resources, people have become aware the necessity of sustainable development. Therefore, it is extremely important to have a thorough grasp of the relationships between forest and its environmental factors. B...

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Bibliographic Details
Main Authors: Hui-Hsin Huang, 黃慧欣
Other Authors: Kai-Yi Huang
Format: Others
Language:zh-TW
Published: 1999
Online Access:http://ndltd.ncl.edu.tw/handle/50901522077179904700
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Summary:碩士 === 國立中興大學 === 森林學系 === 87 === AbstractDue to rapid reduction in the forest resources, people have become aware the necessity of sustainable development. Therefore, it is extremely important to have a thorough grasp of the relationships between forest and its environmental factors. Before the middle of 1980s, many studies in forest ecology involved more qualitative descriptions than quantitatively spatial analyses owing to the restraints of traditional technologies. Not until a great leap forward in computer and remote sensing technologies and widespread availability of these technologies and facilities during 1980s, has research in forest ecology involving quantitatively spatial analyses over large area progressively appeared. The objective of this study was to investigate the characteristics of distribution in elevation, slope, aspect, terrain position, and topographic sheltering index of the seven forest types (including fir type, hemlock type, spruce type, cypress type, pine type, conifer-hardwood forest type, and pine-plantation) in the Hohuan mountain area and to determine the relative weights of the seven forest types in five physiographic factors. It was achieved by using GIS techniques to overlay the digital land-use map and digital terrain model (DTM) data layer and then analyze the composite data layer. The statistics and cumulative frequency graph for five physiographic factors of the entire study area and areas of seven forest types were generated from the composite data layer. This study randomly selected six sets of samples with 200 pixels from each forest type and a set of samples with 600 pixels from each background corresponding to that forest type. Chi-square tests and K-S tests were performed to examine the relative weights among five factors for each forest type and difference in each factor among seven forest types. As results indicated, the relative weights in elevation and topographic sheltering index were the highest among five physiographic factors, and the relative weights in slope, aspect, and terrain position were similar, but much lower than those in elevation and topographic sheltering index. This conclusion dovetailed Kellman's concept of a hierarchical system of environment. As elevation declined, the relative weights in elevation and topographic sheltering index had a tendency to decrease; however, the relative weight in aspect had a tendency to increase; the relative weights in slope and terrain position did not change with the decrease or increase in elevation. Further studies will be needed to confirm the spatial extension of the conclusions mentioned above in other study areas.