The article studies tourism eco-environment of 14 cities of Gangsu Province, China, based on GIS with many kinds of multi-subject spatial database, such as remote sensing data, observation data and literature data. Th...The article studies tourism eco-environment of 14 cities of Gangsu Province, China, based on GIS with many kinds of multi-subject spatial database, such as remote sensing data, observation data and literature data. The research results were as follows. First, spatial features of 14 cities' tourism eco-environment are displayed with five levels of vulnerability respectively. The vulnerability in Gansu becomes worse from Gannan City, located in southern Gansu to Hexi Corridor which lies in northwestern Gansu. Second, the areas of above the middle vulnerability level make up 75% of the total areas of Gansu Province. Third, more than 70% of high-level human and natural tourism resources are in the areas with high vulnerability eco-environment. Fourth, it is crucial to develop comprehensive tourism industry in order to improve the harmonious development between tourism industry and eco-environment in Gansu Province.展开更多
Intravascular ultrasound( IVUS) is an important imaging technique that is used to study vascular wall architecture for diagnosis and assessment of the vascular diseases. Segmentation of lumen and media-adventitia boun...Intravascular ultrasound( IVUS) is an important imaging technique that is used to study vascular wall architecture for diagnosis and assessment of the vascular diseases. Segmentation of lumen and media-adventitia boundaries from IVUS images is a basic and necessary step for quantitative assessment of the vascular walls.Due to ultrasound speckles, artifacts and individual differences,automated segmentation of IVUS images represents a challenging task. In this paper,a random walk based method is proposed for fully automated segmentation of IVUS images. Robust and accurate determination of the seed points for different regions is the key to successful use of the random walk algorithm in segmentation of IVUS images and is the focus of the present work. Performance of the proposed algorithm was evaluated over an image database with 900 IVUS image frames of nine patient cases. The preliminary experimental results show the potential of the proposed IVUS image segmentation approach.展开更多
基金supported by National Natural Science Foundation of China (Grant No.40671062) the Third Knowledge Innovation Project of ‘Study on the Regional Eco-economic Development Theory and Patterns',supported by Institute of Geo-graphical Sciences and Natural Resources Research,CAS
文摘The article studies tourism eco-environment of 14 cities of Gangsu Province, China, based on GIS with many kinds of multi-subject spatial database, such as remote sensing data, observation data and literature data. The research results were as follows. First, spatial features of 14 cities' tourism eco-environment are displayed with five levels of vulnerability respectively. The vulnerability in Gansu becomes worse from Gannan City, located in southern Gansu to Hexi Corridor which lies in northwestern Gansu. Second, the areas of above the middle vulnerability level make up 75% of the total areas of Gansu Province. Third, more than 70% of high-level human and natural tourism resources are in the areas with high vulnerability eco-environment. Fourth, it is crucial to develop comprehensive tourism industry in order to improve the harmonious development between tourism industry and eco-environment in Gansu Province.
基金Innovation Program of Shanghai Municipal Education Commission,China(No.13YZ136)National Science&Technology Support Program during the 12th Five-Year Plan Period of China(No.2012BAI13B02)
文摘Intravascular ultrasound( IVUS) is an important imaging technique that is used to study vascular wall architecture for diagnosis and assessment of the vascular diseases. Segmentation of lumen and media-adventitia boundaries from IVUS images is a basic and necessary step for quantitative assessment of the vascular walls.Due to ultrasound speckles, artifacts and individual differences,automated segmentation of IVUS images represents a challenging task. In this paper,a random walk based method is proposed for fully automated segmentation of IVUS images. Robust and accurate determination of the seed points for different regions is the key to successful use of the random walk algorithm in segmentation of IVUS images and is the focus of the present work. Performance of the proposed algorithm was evaluated over an image database with 900 IVUS image frames of nine patient cases. The preliminary experimental results show the potential of the proposed IVUS image segmentation approach.
