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This paper analyzes and discusses the potential and limits of using Facebook data to analyse spatial-temporal urban rhythms and city centrality through the availability of services and retail. During September 2020, we harvested Facebook Places data using Graph API for our pilot area consisting in the city of Brno. Specifically, we focused on the spatial distribution of 'Food & Beverage', 'Shopping & Retail' and 'Medical & Health' categories, and their associated opening hours. The paper provides a detailed description of data collection and post-processing among possible analysis methods and visualizations presented in the context of our case study. The study focuses on inter-urban structures and urban rhythms through the analysis of opening hours of retail and services. We also discuss the benefits and potential problems associated with the use of these data. [ABSTRACT FROM AUTHOR]

The quality of "non-landslide' samples data impacts the accuracy of geological hazard risk assessment. This research proposed a method to improve the performance of support vector machine (SVM) by perfecting the quality of 'non-landslide' samples in the landslide susceptibility evaluation model through fuzzy c-means (FCM) cluster to generate more reliable susceptibility maps. Firstly, three sample selection scenarios for 'non-landslide' samples include the following principles: 1) select randomly from low-slope areas (scenario-SS), 2) select randomly from areas with no hazards (scenario-RS), 3) obtain samples from the optimal FCM model (scenario-FCM), and then three sample scenarios are constructed with 10,193 landslide positive samples. Next, we have compared and evaluated the performance of three sample scenarios in the SVM models based on the statistical indicators such as the proportion of disaster points, density of disaster points precision, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC). Finally, The evaluation results show that the 'non-landslide' negative samples based on the FCM model are more reasonable. Furthermore, the hybrid method supported by SVM and FCM models exhibits the highest prediction efficiency. Scenario FCM produces an overall accuracy of approximately 89.7% (AUC), followed by scenario-SS (86.7%) and scenario-RS (85.6%). [ABSTRACT FROM AUTHOR]

Looking back over the past decade, superstorms, wildfires, floods, geological hazards, and monster earthquakes have taken unimaginable tolls all over the planet. However, disaster-related data vary in the acquiring methodology and, as such, vary in geographic scope and resolution; thus, how to fuse various disaster-related data is of significance for emergency disaster reduction (Liu I et al i . [7]), visual analysis and risk assessment (Li et al. 2020), and disaster information intelligent service, decision-making information were generated to support disaster emergency management (Liu et al. [5]). [Extracted from the article]

Population distribution modelling can benefit many different domains, for example, transportation, urban planning, ecology or emergency management. Information about the location and number of people in an affected area is crucial for decision-makers during emergencies and crises. Mobile phone data represents relatively reliable and time accurate information on real-time population distribution, movement and behaviour. In this study, we evaluate the spatio-temporal distribution of population derived from phone data of the selected pilot area (City of Brno, Czech Republic). Analysis is based on the dataset describing the estimated human presence (EHP) with two values – visitors and transiting persons. The temporal change of data is first analysed and further processed using two methodological approaches. First, the dasymetric method is used where the building geometry and technical attributes served as a target layer. Second, the results of building level analysis are transformed into a regular grid zone of both visitors and the general EHP. Resulting spatio-temporal patterns are compared to the census data. Results demonstrate how the proposed building level dasymetric approach can improve the spatial granularity of EHP. Potential use of proposed methodology within selected emergency situations is further discussed. [ABSTRACT FROM AUTHOR]

Cartographic communication and support within emergency management (EM) are complicated issues with changing demands according to the incident extent and phase of the EM cycle. Keeping in mind the specifics of each purpose, it is obvious that spatial data used for maps preparation and production must be differently visualized even for the same type of emergency incident (traffic accident, fire, and natural disaster). Context-based cartography is a promising methodology to deal with the changing demands of an operational EM center. An overview of cartographic communication is presented within the context of an operational EM center, activities of particular actors, and map use supporting the incident elimination. The authors of the paper respond to a series of questions, for example: what is the current cartographic support of operational EM in the Czech Republic in Digital Earth conditions? What possibilities are there to improve the cartographic communication? How can contextual cartographic services be implemented in a Web environment and how can the usability of results be tested? The paper gives several examples of the usage of cartographic technologies in map creation for various emergency situations. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the editor discusses an article on the importance of Earth observations in disaster mitigation by Guo Huadong, another on sensor Web enablement for crisis management by Bertrand De Longueville and colleagues, and one on the challenges faced by sensor web in disaster management by Fei Wang and Hongyong Yuan.

The article focuses on adaptive cartography and its potential for geographical education. After briefly describing the wider context of adaptive cartography, it is suggested that this new cartographic approach establishes new demands and benefits for geographical education, especially in offering the possibility for broader individual participation in the learning process. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue, including one by Stanĕk and colleagues on addressing cartographic communication issues, one by Seppänen and Virrantaus on phases of early warning (EW) and by Guo and colleagues on dynamic analysis.