Unmixing Convolutional Features for Crisp Edge Detection.

This article presents a context-aware tracing strategy (CATS) for crisp edge detection with deep edge detectors, based on an observation that the localization ambiguity of deep edge detectors is mainly caused by the mixing phenomenon of convolutional neural networks: Feature mixing in edge classification and side mixing during fusing side predictions. The CATS consists of two modules: A novel tracing loss that performs feature unmixing by tracing boundaries for better side edge learning, and a context-aware fusion block that tackles the side mixing by aggregating the complementary merits of learned side edges. Experiments demonstrate that the proposed CATS can be integrated into modern deep edge detectors to improve localization accuracy. With the vanilla VGG16 backbone, in terms of BSDS500 dataset, our CATS improves the F-measure (ODS) of the RCF and BDCN deep edge detectors by 12 and 6 percent, respectively when evaluating without using the morphological non-maximal suppression scheme for edge detection.

A hierarchical temporal attention-based LSTM encoder-decoder model for individual mobility prediction.

Prediction of individual mobility is crucial in human mobility related applications. Whereas, existing research on individual mobility prediction mainly focuses on next location prediction and short-term dependencies between traveling locations. Long-term location sequence prediction is of great importance for long-time traffic planning and location advertising, and long-term dependencies exist as individual mobility regularity typically occurs daily and weekly. This paper proposes a novel hierarchical temporal attention-based LSTM encoder-decoder model for individual location sequence prediction. The proposed hierarchical attention mechanism captures both long-term and short-term dependencies underlying in individual longitudinal trajectories, and uncovers frequential and periodical mobility patterns in an interpretable manner by incorporating the calendar cycle of individual travel regularities into location prediction. More specifically, the hierarchical attention consists of local temporal attention to identify highly related locations in each day, and global temporal attention to discern important travel regularities over a week. Experiments on individual trajectory datasets with varying degree of traveling uncertainty demonstrate that our method outperforms four baseline methods on three evaluation metrics. In addition, we explore the interpretability of the proposed model in understanding individual daily, and weekly mobility patterns by visualizing the temporal attention weights and frequent traveling patterns associated with locations.

High-resolution urban land-cover mapping and landscape analysis of the 42 major cities in China using ZY-3 satellite images.

Detailed and precise urban land-cover maps are crucial for urban-related studies. However, there are limited ways of mapping high-resolution urban land cover over large areas. In this paper, we propose an operational framework to map urban land cover on the basis of Ziyuan-3 satellite images. Based on this framework, we produced the first high-resolution (2 m) urban land-cover map (Hi-ULCM) covering the 42 major cities of China. The overall accuracy of the Hi-ULCM dataset is 88.55%, of which 14 cities have an overall accuracy of over 90%. Most of the producer's accuracies and user's accuracies of the land-cover classes exceed 85%. We further conducted a landscape pattern analysis in the 42 cities based on Hi-ULCM. In terms of the comparison between the 42 cities in China, we found that the difference in the land-cover composition of urban areas is related to the climatic characteristics and urbanization levels, e.g., cities with warm climates generally have higher proportions of green spaces. It is also interesting to find that cities with higher urbanization levels are more habitable, in general. From the landscape viewpoint, the geometric complexity of the landscape increases with the urbanization level. Compared with the existing medium-resolution land-cover/use datasets (at a 30-m resolution), Hi-ULCM represents a significant advance in accurately depicting the detailed land-cover footprint within the urban areas of China, and will be of great use for studies of urban ecosystems.

Analysis of the relationships between environmental noise and urban morphology.

Understanding the effects of urban morphology on urban environmental noise (UEN) at a regional scale is crucial for creating a pleasant urban acoustic environment. This study seeks to investigate how the urban morphology influences the UEN in the Shenzhen metropolitan region of China, by employing remote sensing and geographic information data. The UEN in this study consists of not only regional environmental noise (RN), but also traffic noise (TN). The experimental results reveal the following findings: 1) RN is positively correlated with the nighttime light intensity (NTL) and land surface temperature (LST) (p < 0.05). More interestingly, landscape composition and configuration can also significantly affect RN. For instance, urban vegetation can mitigate the RN (r = -0.411, p < 0.01). There is a reduced RN effect when fewer buildings exist in an urban landscape, in terms of the positive relationship between building density and RN (r = 0.188, p < 0.01). Given the same percentage of building area, buildings are more effective at reducing noise when they are distributed across the urban scenes, rather than being spatially concentrated (r = -0.205, p < 0.01). 2) TN positively relates to large (r = 0.520, p < 0.01) and small-medium (r = 0.508, p < 0.01) vehicle flow. In addition, vegetation along or near roads can alleviate the TN effect (r = -0.342, p < 0.01). TN can also become more severe in urban landscapes where there is higher road density (r = 0.307, p < 0.01). 3) Concerning the urban functional zones, traffic land is the greatest contributor to urban RN, followed by mixed residential and commercial land. The findings revealed by this research will indicate how to mitigate UEN.

SCRMS: An RFID and Sensor Web-Enabled Smart Cultural Relics Management System.

Cultural relics represent national or even global resources of inestimable value. How to efficiently manage and preserve these cultural relics is a vitally important issue. To achieve this goal, this study proposed, designed, and implemented an RFID and Sensor Web-enabled smart cultural relics management system (SCRMS). In this system, active photovoltaic subtle energy-powered Radio Frequency Identification (RFID) is used for long-range contactless identification and lifecycle management of cultural relics during their storage and circulation. In addition, different types of ambient sensors are integrated with the RFID tags and deployed around cultural relics to monitor their environmental parameters, helping to ensure that they remain in good condition. An Android-based smart mobile application, as middleware, is used in collaboration with RFID readers to collect information and provide convenient management for the circulation of cultural relics. Moreover, multiple sensing techniques are taken advantage of simultaneously for preservation of cultural relics. The proposed system was successfully applied to a museum in the Yongding District, Fujian Province, China, demonstrating its feasibility and advantages for smart and efficient management and preservation of cultural relics.

Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping.

For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.

Real-time GIS data model and sensor web service platform for environmental data management.

BACKGROUND: Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework. METHODS: A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies. RESULTS: To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s. CONCLUSIONS: The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework.

Cyber-physical geographical information service-enabled control of diverse in-situ sensors.

Realization of open online control of diverse in-situ sensors is a challenge. This paper proposes a Cyber-Physical Geographical Information Service-enabled method for control of diverse in-situ sensors, based on location-based instant sensing of sensors, which provides closed-loop feedbacks. The method adopts the concepts and technologies of newly developed cyber-physical systems (CPSs) to combine control with sensing, communication, and computation, takes advantage of geographical information service such as services provided by the Tianditu which is a basic geographic information service platform in China and Sensor Web services to establish geo-sensor applications, and builds well-designed human-machine interfaces (HMIs) to support online and open interactions between human beings and physical sensors through cyberspace. The method was tested with experiments carried out in two geographically distributed scientific experimental fields, Baoxie Sensor Web Experimental Field in Wuhan city and Yemaomian Landslide Monitoring Station in Three Gorges, with three typical sensors chosen as representatives using the prototype system Geospatial Sensor Web Common Service Platform. The results show that the proposed method is an open, online, closed-loop means of control.

Web GIS in practice VIII: HTML5 and the canvas element for interactive online mapping.

HTML5 is being developed as the next major revision of HTML (Hypertext Markup Language), the core markup language of the World Wide Web. It aims at reducing the need for proprietary, plug-in-based rich Internet application (RIA) technologies such as Adobe Flash. The canvas element is part of HTML5 and is used to draw graphics using scripting (e.g., JavaScript). This paper introduces Cartagen, an open-source, vector-based, client-side framework for rendering plug-in-free, offline-capable, interactive maps in native HTML5 on a wide range of Web browsers and mobile phones. Cartagen was developed at MIT Media Lab's Design Ecology group. Potential applications of the technology as an enabler for participatory online mapping include mapping real-time air pollution, citizen reporting, and disaster response, among many other possibilities.

[Application of support vector machine in the detection of early cancer].

Support Vector Machine (SVM) is an efficient novel method originated from the statistical learning theory. It is powerful in machine learning to solve problems with finite samples. Due to the deficiency of cancer cells, character of patient and noise in the raw data, it is very difficult to diagnose early cancer accurately. In this paper, SVM is employed in detecting early cancer and the results are encouraged compared with conventional methods. The accuracy of Non-linear SVM classifier is especially high in all kinds of classifiers, which indicates the potential application of SVM in early cancer detection.