Evaluation of Community Livability Using Gridded Basic Urban Geographical Data—A Case Study of Wuhan

The evaluation of community livability quantifies the demands of human settlement at the micro scale, supporting urban governance decision-making at the macro scale. Big data generated by the urban management of government agencies can provide an accurate, real-time, and rich data set for livability evaluation. However, these data are intertwined by overlapping geographical management boundaries of different government agencies. It causes the difficulty of data integration and utilization when evaluating community livability. To address this problem, this paper proposes a scheme of partitioning basic geographical space into grids by optimally integrating various geographical management boundaries relevant to enterprise-level big data. Furthermore, the system of indexes on community livability is created, and the evaluation model of community livability is constructed. Taking Wuhan as an example, the effectiveness of the model is verified. After the evaluation, the experimental results show that the livability evaluation with reference to our basic geographic grids can effectively make use of governmental big data to spatially identify the multi-dimensional characteristics of a community, including management, environment, facility services, safety, and health. Our technical solution to evaluate community livability using gridded basic urban geographical data is of large potential in producing thematic data of community, constructing a 15-min community living circle of Wuhan, and enhancing the ability of the community to resist risks.

Taxonomic revision of the Neotropical ant genus Hylomyrma Forel, 1912 (Hymenoptera: Formicidae: Myrmicinae), with the description of fourteen new species

This paper provides a taxonomic revision of the Neotropical ant genus Hylomyrma Forel (1912) (Myrmicinae: Pogonomyrmecini). Morphological traits combined with geographical data and natural history information led to the recognition of 30 species, fourteen of them described here as new: Hylomyrma adelae sp. n., Hylomyrma dandarae sp. n., Hylomyrma jeronimae sp. n., Hylomyrma lispectorae sp. n., Hylomyrma lopesi sp. n., Hylomyrma macielae sp. n., Hylomyrma margaridae sp. n., Hylomyrma mariae sp. n., Hylomyrma marielleae sp. n., Hylomyrma mitiae sp. n., Hylomyrma peetersi sp. n., Hylomyrma primavesi sp. n., Hylomyrma virginiae sp. n. and Hylomyrma wachiperi sp. n. Lectotypes for H. speciosa (junior synonym of H. balzani) and H. reitteri are here designated from syntypes to improve nomenclatural stability. Except for the three species most recently described (H. montana, H. plumosa, and H. villemantae), the external morphology of workers is described or redescribed, as well as for the known males and queens, most described here for the first time. Of the 30 recognized species herein, 11 present intercastes; at least three of them present female specimens with queen-like traits that may be understood as ergatoids. An updated identification key for Hylomyrma workers is provided, as well as high resolution photographs of all known sexes and castes, species distribution maps, and a summary of what is known from the biology of all species.

Succinct Data Structures in the Realm of GIS

Geographic Information Systems (GIS) have spread all over our technological environment in the last decade. The inclusion of GPS technologies in everyday portable devices along with the creation of massive shareable geographical data banks has boosted the rise of geoinformatics. Despite the technological maturity of this field, there are still relevant research challenges concerning efficient information storage and representation. One of the most powerful techniques to tackle these issues is designing new Succinct Data Structures (SDS). These structures are defined by three main characteristics: they use a compact representation of the data, they have self-index properties and, as a consequence, they do not need decompression to process the enclosed information. Thus, SDS are not only capable of storing geographical data using as little space as possible, but they can also solve queries efficiently without any previous decompression. This work introduces how SDS can be successfully applied in the GIS context through several novel approaches and practical use cases.

Spatial scales, patterns, and positivity trends of SARS-CoV-2 pandemics in mass rapid antigen testing in Slovakia

We study geographical epidemic scales and patterns and positivity trends of SARS-CoV-2 pandemics in mass antigen testing in Slovakia in 2020. The observed test positivity was exponentially distributed with a long scale exponential spatial trend, and its characteristic correlation length was approximately 10 km. Spatial scales also play an important role in test positivity reduction between two consecutive testing rounds. While test positivity decreased in all counties, it increased in individual municipalities with low test positivity in the earlier testing round in a way statistically different from a mean-reversion process. Also, non-residents testing influences the mass testing results as test positivity of non-residents was higher than of residents when testing was offered only in municipalities with the highest positivity in previous rounds. Our results provide direct guidance for pandemic geographical data surveillance and epidemic response management.

Survey on economic considerations and decisions of key geodata providers and users in Czech public administration

This paper presents the results of an empirical economic data-based survey of the costs and revenues of geographical data and Web services across public administration in Czechia. The survey was composed of questionnaires and interviews. The data was collected from the 19 biggest public producers of geographical information and 25 organizations that use geographical information. The results focus on the economic consequences of data opening, splitting finances within public administration bodies, the prioritization of activities related to geographical information, licensing issues and life cycle planning etc. We also consider user opinions on the restrictions on the (re)use of geographical information of public administration, including open data.