Automatic discovery of isolated land cover web map services (LCWMSs) can potentially help in sharing land cover data. Currently, various search engine-based and crawler-based approaches have been developed for finding services dispersed throughout the surface web. In fact, with the prevalence of geospatial web applications, a considerable number of LCWMSs are hidden in JavaScript code, which belongs to the deep web. However, discovering LCWMSs from JavaScript code remains an open challenge. This paper aims to solve this challenge by proposing a focused deep web crawler for finding more LCWMSs from deep web JavaScript code and the surface web. First, the names of a group of JavaScript links are abstracted as initial judgements. Through name matching, these judgements are utilized to judge whether or not the fetched webpages contain predefined JavaScript links that may prompt JavaScript code to invoke WMSs. Secondly, some JavaScript invocation functions and URL formats for WMS are summarized as JavaScript invocation rules from prior knowledge of how WMSs are employed and coded in JavaScript. These invocation rules are used to identify the JavaScript code for extracting candidate WMSs through rule matching. The above two operations are incorporated into a traditional focused crawling strategy situated between the tasks of fetching webpages and parsing webpages. Thirdly, LCWMSs are selected by matching services with a set of land cover keywords. Moreover, a search engine for LCWMSs is implemented that uses the focused deep web crawler to retrieve and integrate the LCWMSs it discovers. In the first experiment, eight online geospatial web applications serve as seed URLs (Uniform Resource Locators) and crawling scopes; the proposed crawler addresses only the JavaScript code in these eight applications. All 32 available WMSs hidden in JavaScript code were found using the proposed crawler, while not one WMS was discovered through the focused crawler-based approach. This result shows that the proposed crawler has the ability to discover WMSs hidden in JavaScript code. The second experiment uses 4842 seed URLs updated daily. The crawler found a total of 17,874 available WMSs, of which 11,901 were LCWMSs. Our approach discovered a greater number of services than those found using previous approaches. It indicates that the proposed crawler has a large advantage in discovering LCWMSs from the surface web and from JavaScript code. Furthermore, a simple case study demonstrates that the designed LCWMS search engine represents an important step towards realizing land cover information integration for global mapping and monitoring purposes. Full article

Increasingly, social media data are linked to locations through embedded GPS coordinates. Many local governments are showing interest in the potential to repurpose these firsthand geo-data to gauge spatial and temporal dynamics of public opinions in ways that complement information collected through traditional public engagement methods. Using these geosocial data is not without challenges since they are usually unstructured, vary in quality, and often require considerable effort to extract information that is relevant to local governments’ needs from large data volumes. Understanding local relevance requires development of both data processing methods and their use in empirical studies. This paper addresses this latter need through a case study that demonstrates how spatially-referenced Twitter data can shed light on citizens’ transportation and planning concerns. A web-based toolkit that integrates text processing methods is used to model Twitter data collected for the Region of Waterloo (Ontario, Canada) between March 2014 and July 2015 and assess citizens’ concerns related to the planning and construction of a new light rail transit line. The study suggests that geosocial media can help identify geographies of public perceptions concerning public facilities and services and have potential to complement other methods of gauging public sentiment. Full article

The timely detection of gold foil damage in gold-overlaid stone carvings and the associated maintenance of these relics pose several challenges to both the research and heritage protection communities internationally. This paper presents a new method for detecting gold foil damage by making use of multi-temporal 3D LiDAR point clouds. By analyzing the errors involved in the detection process, a formula is developed for calculation of the damage detection threshold. An improved division method for the linear octree that only allocates memory to the non-blank nodes, is proposed, which improves storage and retrieval efficiency for the point clouds. Meanwhile, the damage-occurrence regions are determined according to Hausdorff distances. Using a triangular mesh, damaged regions can be identified and measured in order to determine the relic’s total damaged area. Results demonstrate that this method can effectively detect gold foil damage in stone carvings. The identified surface area of damaged regions can provide the information needed for subsequent restoration and protection of relics of this type. Full article

Conventional ice navigation in the sea is manually operated by well-trained navigators, whose experiences are heavily relied upon to guarantee the ship’s safety. Despite the increasingly available ice data and information, little has been done to develop an automatic ice navigation support system to better guide ships in the sea. In this study, using the vector-formatted ice data and navigation codes in northern regions, we calculate ice numeral and divide sea area into two parts: continuous navigable area and the counterpart numerous separate unnavigable area. We generate Voronoi Diagrams for the obstacle areas and build a road network-like graph for connections in the sea. Based on such a network, we design and develop a geographic information system (GIS) package to automatically compute the safest-and-shortest routes for different types of ships between origin and destination (OD) pairs. A visibility tool, Isovist, is also implemented to help automatically identify safe navigable areas in emergency situations. The developed GIS package is shared online as an open source project called NavSpace, available for validation and extension, e.g., indoor navigation service. This work would promote the development of ice navigation support system and potentially enhance the safety of ice navigation in the Arctic sea. Full article

Insect infestation behaves as a complex system, characterized by non-linear spatial dynamics and emergent patterns that evolve from smaller to larger spatial scales. The emerald ash borer (EAB) is an invasive species that has infested and killed millions of ash trees across North America. Existing EAB models use traditional statistical approaches that often cannot address the spatiotemporal complexity emerging from EAB infestation processes. Moreover, these studies of insect infestation are limited by a lack of sufficient time series data. The objective of this study is to develop a geosimulation approach to overcome the challenge of data scarcity and represent EAB infestation at a regional scale. Geographic information systems (GIS), multi-criteria evaluation (MCE), and cellular automata (CA) are used to model EAB spread across different hypothetical landscape types. Simulation results represent EAB propagation and indicate different dynamics of spread for each landscape. Urban environments are identified as being at the greatest risk to the infestation. The proposed approach offers a theoretical framework and a modeling tool to represent the propagation of EAB infestation that can be applied with real geospatial datasets and potentially used in forest management strategies. Full article

Spatial interpolation methods are widely used in various fields and have been studied by several scholars with one or a few specific sampling datasets that do not reflect the complexity of the spatial characteristics and lead to conclusions that cannot be widely applied. In this paper, three factors that affect the accuracy of interpolation have been considered, i.e., sampling density, sampling mode, and sampling location. We studied the inverse distance weighted (IDW), regular spline (RS), and ordinary kriging (OK) interpolation methods using 162 DEM datasets considering six sampling densities, nine terrain complexities, and three sampling modes. The experimental results show that, in selective sampling and combined sampling, the maximum absolute errors of interpolation methods rapidly increase and the estimated values are overestimated. In regular-grid sampling, the RS method has the highest interpolation accuracy, and IDW has the lowest interpolation accuracy. However, in both selective and combined sampling, the accuracy of the IDW method is significantly improved and the RS method performs worse. The OK method does not significantly change between the three sampling modes. The following conclusion can be obtained from the above analysis: the combined sampling mode is recommended for sampling, and more sampling points should be added in the ridges, valleys, and other complex terrain. The IDW method should not be used in the regular-grid sampling mode, but it has good performance in the selective sampling mode and combined sampling mode. However, the RS method shows the opposite phenomenon. The sampling dataset should be analyzed before using the OK method, which can select suitable models based on the analysis results of the sampling dataset. Full article

An analysis of global statistics shows a substantial increase in flood damage over the past few decades. Moreover, it is expected that flood risk will continue to rise due to the combined effect of increasing numbers of people and economic assets in risk-prone areas and the effects of climate change. In order to mitigate the impact of natural hazards on European economies and societies, improved risk assessment, and management needs to be pursued. With the recent transition to a more risk-based approach in European flood management policy, flood analysis models have become an important part of flood risk management (FRM). In this context, free and open-source (FOSS) geospatial models provide better and more complete information to stakeholders regarding their compliance with the Flood Directive (2007/60/EC) for effective and collaborative FRM. A geospatial model is an essential tool to address the European challenge for comprehensive and sustainable FRM because it allows for the use of integrated social and economic quantitative risk outcomes in a spatio-temporal domain. Moreover, a FOSS model can support governance processes using an interactive, transparent and collaborative approach, providing a meaningful experience that both promotes learning and generates knowledge through a process of guided discovery regarding flood risk management. This article aims to organize the available knowledge and characteristics of the methods available to give operational recommendations and principles that can support authorities, local entities, and the stakeholders involved in decision-making with regard to flood risk management in their compliance with the Floods Directive (2007/60/EC). Full article

Participants in the land market are usually hampered to browse and analyze the land price information due to the lack of information sources and available analysis tools. A service-oriented GIS-based web system was developed to provide a practical solution, its essential data sources contain basic geographic elements and benchmark land price (BLP)-related information. Core models for land price analysis were implemented, including land price index, spatial distribution, and parcel appraisal. The system was developed based on a four-level Browse Server (B/S) architecture using GIS and web service technologies, which enables the publishing, browsing, and analysis of the land price information via the Internet. With effective functionalities, the system has been employed in a project for updating BLP in a case study city located in China. The main advantage of the GIS-based web approach lies in its integration of spatial-temporal analysis models and web GIS technology, which allows more investors and administrators with limited domain knowledge to obtain further understanding on the change pattern and spatial distribution of land price by an online means. The experience in the case study city demonstrates that the approach has strong practicality for land price information services. Full article

With economic growth and the improvement of the urbanization level, human activities have constantly interfered with landscape patterns, resulting in serious threats to regional ecological security. Therefore, it is of great significance to study the evolution and optimization of the landscape patterns. Based on three TM images from 1990, 2000, and 2010, and selected landscape pattern indexes, the changes in the landscape pattern of Nanjing in the past twenty years were studied based on landscape ecology theory using Remote Sensing (RS) and a Geographical Information System (GIS). The ecological network was built on the basis of extracted ecological nodes and the minimum cumulative resistance. The results show that changes in the landscape pattern of the city of Nanjing were notable. Class-level indexes indicate that the farmland landscape area decreased and the degree of patch fragmentation increased. The construction land area increased, and it tended to show dispersed distribution. The proportion of forest land increased and the shape of patches became more complex. The proportion of water firstly showed a decrease, followed by an increase, and the shape of the water became more regular. Landscape-level indexes indicate that biological diversity and the degree of fragmentation increased. Spatial heterogeneity of the natural landscape increased, and the patch shape of each landscape type developed similarly. The results also call for stepping-stones to enhance the connectivity and optimization of the ecological network, which will help improve ecological services and improve the landscape pattern of the city. Full article

After massive earthquakes and other large-scale disasters, existing communication infrastructure may become unavailable and, therefore, it can be quite difficult for relief organizations to fully grasp the impact of the disaster on the affected region. Consequently, this will be the cause of delays to offer the strategic assistance, and to provide water and food, etc. In order to solve the problem of re-establishing communication infrastructure to allow for information gathering, we developed an ad hoc mobile communications network for disaster-struck areas using ZigBee. As the communication speed of ZigBee is low, we propose a problem-specific image compression method for the multimedia data visualization. By using the proposed method combined with GPS information, it is possible to quickly grasp the damage situation in the region. Through our communication experiments in Tsukuba City, Japan we confirm the effectiveness of our system as a disaster information gathering and management system. Full article

Geographic information systems (GIS) can be effectively utilized to carry out spatio-temporal analysis of spatial accessibility to primary healthcare services. Spatial accessibility to primary healthcare services is commonly measured using floating catchment area models which are generally defined with three variables; namely, an attractiveness component of the service centre, travel time or distance between the locations of the service centre and the population, and population demand for healthcare services. The nearest-neighbour modified two-step floating catchment area (NN-M2SFCA) model is proposed for computing spatial accessibility indices for the entire country. Accessibility values from 2010 to 2013 for Bhutan were analysed both spatially and temporally by producing accessibility ranking maps, plotting Lorenz curves, and conducting spatial clustering analysis. The spatial accessibility indices of the 205 sub-districts show great disparities in healthcare accessibility in the country. The mean- and median-based classification results indicate that, in 2013, 24 percent of Bhutan’s population have poor access to primary healthcare services, 66 percent of the population have medium-level access, and 10 percent have good access. Full article