A survey on image data analysis through clustering techniques for real world applications

The complexity and resilience of urban public transit network (PTN) are the interdisciplinary study area between transportation engineering and system science, which is a good demonstration of applying complex network theory to promote the development of engineering science. The deep understanding of this study helps to provide a new perspective for analyzing the reliability of urban PTN. Following study process of the complexity and resilience of complex network, this paper reviews the complexity and resilience of PTN from four topics, i.e., the PTN complexity, the static resilience of PTN, the dynamic resilience (cascading failures based resilience) of single layered PTN, and the dynamic resilience of interdependent PTN. In the literature review, multiple key items are, respectively, extracted for each topic, and the engineering applicability of each topic is also analyzed, which are both for obtaining the key features of this study area. Finally, in order to realize the development trend of cyclic and forward—complex network theory, network resilience theory, transforming into a realistic model and method that is close to actual public transit operation, engineering application and practice, and contributing to complex network theory, the study status is summarized and the future development trend is prospected.

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A Review and Prospect for the Complexity and Resilience of Urban Public Transit Network Based on Complex Network Theory

Statistical Pattern Recognition is one of the basic techniques for land use/land cover classification of remote sensing image. Focusing on establishing a method to integrate statistical pattern recognition with geosciences' analysis, this paper proposed a segmentation-based remotely sensed imagery classification method, called ISODATA-Geosciences Imagery Classification (ISOGIC). The result from case application of TM image in Yanchi County shows that ISOGIC can distinguish large land types via ISODATA clustering, while geosciences knowledge including topography, soil type and vegetation type, etc. can significantly improve the accuracy of cultivated land, different types of forests, different coverage grassland, sandy land and saline and alkaline land. The average classification accuracy is up to 87.9%. Compared to Pixel-based maximum likelihood method, the segmentation-based remotely sensed imagery classification method can effectively resolve problems such as same object with different spectrums and different object with same spectrums.

A composed statistical pattern recognition and geosciences analysis approach for segmentation-based remotely sensed imagery classification

The demand to alleviate urban traffic and reduce air pollution puts forward high requirements for green travel in public transportation. Thus, study of the feasibility of urban green travel in public transportation is necessary. This study focuses on it from two aspects: City level by complex network and individual level by structural equation model. As for the former, point of interest data on the spatial distribution of urban public transportation in Wuhan city are quantitatively analyzed. Then, a complex network of public transportation in Wuhan is constructed by using the Space L method, and the network characteristics are analyzed. Results show that accessibility coverage is mainly concentrated in the central urban area, and two significant central nodes exist, namely, Linshi and Zhaohu stations. At the individual level, 354 valid questionnaires and the structural equation model were used to explore the factors affecting individual intention of public transportation. Behavioral perceptual outcome, behavioral attitudes, and subjective norms have positive influences on the behavioral intention of public transportation, among which the behavioral attitudes are the most significant, and the subjective norms had the lowest influence. Some suggestions are proposed for Wuhan to improve urban accessibility and for individuals to increase green travel in public transportation.

https://www.mdpi.com/2071-1050/12/16/6531/pdf

Feasibility Analysis of Green Travel in Public Transportation: A Case Study of Wuhan

This research effort proposes a novel method for identifying and extracting roads from aerial images taken after a disaster using graph-based image segmentation. The dataset that is used consists of images taken by an Unmanned Aerial Vehicle (UAV) at the University of West Florida (UWF) after hurricane Sally. Ground truth masks were created for these images, which divide the image pixels into three categories: road, non-road, and uncertain. A specific pre-processing step was implemented, which used Catmull–Rom cubic interpolation to resize the image. Moreover, the Gaussian filter used in Efficient Graph-Based Image Segmentation is replaced with a median filter, and the color space is converted from RGB to HSV. The Efficient Graph-Based Image Segmentation is further modified by (i) changing the Moore pixel neighborhood to the Von Neumann pixel neighborhood, (ii) introducing a new adaptive isoperimetric quotient threshold function, (iii) changing the distance function used to create the graph edges, and (iv) changing the sorting algorithm so that the algorithm can run more effectively. Finally, a simple function to automatically compute the k (scale) parameter is added. A new post-processing heuristic is proposed for road extraction, and the Intersection over Union evaluation metric is used to quantify the road extraction performance. The proposed method maintains high performance on all of the images in the dataset and achieves an Intersection over Union (IoU) score, which is significantly higher than the score of a similar road extraction technique using K-means clustering.

/pdf/graph-based-image-segmentation-for-road-extraction-from-post-1coaflxb.pdf

Graph-Based Image Segmentation for Road Extraction from Post-Disaster Aerial Footage

Remote sensing image segmentation is the basis of image pattern recognition. It is significant for the application and analysis of remote sensing images. Clustering analysis as a non-supervised learning method is widely used in the segmentation of remote sensing images. It has made good results in the segmentation of low-resolution and moderate-resolution remote sensing images. As the improvement of image resolution, however, they have problems in the segmentation of high-resolution remote sensing images. In this paper we propose an agglomerative hierarchical clustering based high-resolution remote sensing image segmentation algorithm. The segmentation experiments show that the result of this algorithm is better than the K-Meanspsila and is close to the results of artificial extraction.

An Agglomerative Hierarchical Clustering Based High-Resolution Remote Sensing Image Segmentation Algorithm

The network structure statistical character of Qingdao′s Public Transport Line Network(PTLN) is analyzed from the view of complex networks in this paper.First,the definition of the PTLN is given,based on which Qingdao′s PTLN is built.Then the degree value distribution,degree distribution,the relationship between the number of bus stations and the degree of the node which stands for the bus line and the distribution of network weight is analyzed.Some network′s statistical features such as the average degree of the network,the shortest average path length and the average of the weigh are calculated.The results show that Qingdao′s public transportation is rather convenient.

Complexity of Qingdao′s Public Transport Line Network

Focusing on the architecture characteristics of the new computer architecture with high-security sCPU-dBUS, this paper designs and implements an Inter-subsystem data transfer mechanism based on the new high-security operating system with internal networking structure netOS-I which is only used by the sCPU-dBUS. The data transfer mechanism mainly contains Inter-subsystem data transfer interface, Inter-subsystem data transfer protocol and operation and management of transit cache memory.

Shao Fengjing

Papers

An Agglomerative Hierarchical Clustering Based High-Resolution Remote Sensing Image Segmentation Algorithm

Complexity of Qingdao′s Public Transport Line Network

An Inter-subsystem Data Transfer Mechanism Based on a New Computer Architecture with Single CPU and Dual Bus