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WETLAND RESOURCES INVESTIGATION IN URBAN PARKS BASED ON quickbird REMOTE SENSING image IN JINAN,CHINA

湿地科学 2006年第4期4卷 264-267页

作者： FEI Xian-Yun ZHANG Zhi-Guo College oflnformation Science and Engineering Shandong Agricultural University Tai＇ an 271018 Shandong P.R. China College of Resources and Environment Shandong Agricultural University Tai ＇ an 271018 Shandong P.R. China

Wetlands in urban area are an important part of environment. The status of wetland is tightly related with the security and sustainable development of urban ecosystem and society. Jinan is the capital of Shandong province, China. It is the centre of culture and economy of this province and famous for its springs. So it has important meaning to survey the wetland resources of the urban parks. In this study, the quantity and location of various vegetation types and water areas were obtained using manual classification on quickbird images. Study results showed that arbor vegetation was domain green land type in the urban parks, so the vegetation structure in parks was reasonable; water quality of the wetlands in the parks was poor, and eutrophication phenomena was obvious in some water areas; the quantity of the water areas has been declined. Through the surveying, we should think that it is a big challenge for the government to protect and restore wetland resources in the parks from 2 respects of quantity and quality in urban area.

关键词： wetland in park quickbird image vegetation structure water quality

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维普期刊数据库

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Estimating Stem Volume Using quickbird imagery and Allometric Relationships for Open Populus xiaohei Plantations

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Journal of Integrative Plant Biology 2007年第9期49卷 1304-1312页

作者： Xiao-Qing Wang Zeng-Yuan Li Xing-E Liu Guang Deng Ze-Hui Jiang Research Institute of Wood Industry Chinese Academy of Forestry Beijing 100091 China Research Institute of Forest Resource Information Techniques Chinese Academy of Forestry Beijing 100091 China Intemational Centre for Bamboo and Rattan Beijing 100102 China)

There has been a great deal of interest in studying the crown of trees using remote sensing data. In this study, crown width was extracted from high-resolution quickbird images for open Populus xiaohei plantations. Regression models for predicting the individual stem volumes of Populus xiaohei were established using extracted crown width, as well as estimated tree parameters （i.e. diameter at breast height [DBH] and tree height） as predictors. Our results indicated that crown width could be accurately extracted from quickbird images using a multi-scale segmentation approach with a mean relative error of 5.74%, especially for wide-spacing stands. Using either extracted crown width alone or with estimated DBH and tree height can successfully estimate individual stem volume of Populus xiaohei with the R2 value ranging from 0.87 to 0.92 depending on different model forms. In particular, the two second-order polynomial models （model 2 and model 6）, based on quickbird image-derived crown widths and estimated DBH and tree heights, respectively, were the best at describing the relationship between stem volume and tree characteristics.

关键词： diameter at breast height Populus xiaohei quickbird image stem volume tree crown tree height.

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维普期刊数据库

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Segmentation of High Spatial Resolution Remote Sensing images of Mountainous Areas Based on the Improved Mean Shift Algorithm

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Journal of Mountain Science 2015年第3期12卷 671-681页

作者： LU Heng LIU Chao LI Nai-wen GUO Jia-wei State Key Laboratory of Hydraulics and Mountain River Engineering Sichuan University College of Hydraulic and Hydroelectric Engineering Sichuan University Key Laboratory of Geo-special Information Technology Ministry of Land and ResourcesChengdu University of Technology Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University

Using conventional Mean Shift Algorithm to segment high spatial resolution Remote sensing images of mountainous areas usually leads to an unsatisfactory result, due to its rich texture information. In this paper, we propose an improved Mean Shift Algorithm in consideration of the characteristics of these images. First, images were classified into several homogeneous color regions and texture regions by conducting variance detection on the color space. Next, each homogeneous color region was directly segmented to generate the preliminary results by applying the Mean Shift Algorithm. For each texture region, we conduct a high-dimensional feature space by extracting information such as color, texture and shape comprehensively, and work out a proper bandwidth according to the normalized distribution density. Then the bandwidth variable Mean Shift Algorithm was applied to obtain segmentation results by conducting the pattern classification in feature space. Last, the final results were obtained by merging these regions by means of the constructed cost functions and removing the oversegmented regions from the merged regions. It has been experimentally segmented on the high spatial resolution remote sensing images collected by quickbird and Unmanned Aerial Vehicle(UAV). We put forward an approach to evaluate the segmentation results by using the segmentation matching index(SMI). This takes into consideration both the area and the spectrum. The experimental results suggest that the improved Mean Shift Algorithm outperforms the conventional one in terms of accuracy of segmentation.

关键词： Mean Shift image segmentation Regionmerging UAV image quickbird image

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维普期刊数据库

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