Geocoded Data Sets Research Articles

Urban greenness, mixed land-use, and life satisfaction: Evidence from residential locations and workplace settings in Beijing

China’s unprecedented urbanisation in the last several decades has significantly transformed its urban built environment. On the one hand, such an urbanisation has brought about improvement in infrastructure, access to various public facilities, and opportunities for social connectivity, all of which would benefit citizen’s wellbeing. On the other hand, rapid, unplanned, and unregulated urbanisation may lead to air pollution and water pollution, compact neighbourhoods, traffic noise and congestion, and lack of natural amenity, which pose various threats to urban dwellers’ wellbeing and life satisfaction. Therefore, how to build liveable cities has become one of the key goals and top priorities of urban planning in China and other developing countries. This study investigates the effect of urban greenness and mixed land-use, two key dimensions defining urban liveability, on residents’ life satisfaction at both residence and workplace settings in Beijing. Three big geo-coded datasets are combined, including a social survey about residents’ subjective life satisfaction and demographic characteristics, eye-sensored street greenness data extracted from online platform through machine learning, and fine-grain land-use data based on point-of-interest entropy, and then taken into a Bayesian multilevel ordered logit model. The empirical results reveal that (1) street view greenness could enhance life satisfaction at residence, but depress life satisfaction at workplace; (2) mixed land-use could positively contribute to life satisfaction at both residence and workplace; and (3) there exist positive interactions between greenness and mixed land-use. These empirical findings provide practical implications for planning and constructing liveable cities in China and other countries where both urban greening and mixed land-use are promoted and embraced as core elements of the compact city and smart city ideal.

Introducing SpatialGridBuilder: A new system for creating geo-coded datasets

Researchers in the conflict research community have become increasingly aware that we can no longer depend on state-aggregated data. Numerous factors at the substate level affect the nature of human interactions, so if we really want to understand conflict, we need to find more appropriate units of analysis. However, while many conflict researchers have realized this, actually taking the next step and performing data analysis on spatial data grids has remained a rather elusive goal for many because of the difficulty of learning the new techniques to perform such analyses. This paper introduces SpatialGridBuilder, a new, freely available, open-source system with the goal of empowering conflict researchers with no background in GIS methods to start their own spatial analyses. SpatialGridBuilder allows the researcher to: (a) create entirely new spatial datasets, based on the needs of their own research; (b) import their own spatial data; (c) easily add a range of important variables to the datasets, including commonly used conflict variables, plus new variables that have not been presented before; and (d) visualize graphical renderings of this data. Having done this, SpatialGridBuilder will then export the dataset for the researcher to analyse using conventional statistical methods. This article introduces the new program, and demonstrates how it can be used to set up such a statistical analysis. It also shows how different results can be achieved by building grids of different resolutions, thereby encouraging researchers to choose grid resolutions appropriate to their research questions and data. The article also introduces a novel means of determining infrastructure complexity, using Google maps.

SUPPORTING MANAGEMENT OF EUROPEAN REFUGEE STREAMS BY EARTH OBSERVATION AND GEOINFORMATION

Abstract. The sharp increase in refugee numbers arriving in the European Union has recently caused major and manifold challenges for the member states and their administrative services. Location based situation reports and maps may support the refugee management from local to European level. The first support is mapping of the geographical distribution of migrating people which needs more or less real time data. The actual data sources are location related observations along the routes of refugees, actual satellite observations and data mining results. These tools and data are used to monitor spatial distributions as well as extrapolate the arrival of refugees for the subsequent weeks. The second support is the short term update of the location of initial registration facilities and first reception facilities, their capacities, and their occupancy. The third management level is the systematic inquiry for unoccupied housing facilities and for empty places within build-up areas. Geo-coded data sets of house numbers have to be cross-referenced with city maps and communal inhabitants address data. The legal aspects of data mining and secured access to personal data are strictly controlled by the administration allowing only limited access and distribution of data and results. However, the paper will not disclose scientific progress in Earth Observation and GIS, but will actually demonstrate an urgently needed new combination of existing methods to support actual needs. The societal benefits of EO/GIS are no longer just potential possibilities, but actual results in real political, administrative and humanitarian day to day reality.

SUPPORTING MANAGEMENT OF EUROPEAN REFUGEE STREAMS BY EARTH OBSERVATION AND GEOINFORMATION

The sharp increase in refugee numbers arriving in the European Union has recently caused major and manifold challenges for the member states and their administrative services. Location based situation reports and maps may support the refugee management from local to European level. The first support is mapping of the geographical distribution of migrating people which needs more or less real time data. The actual data sources are location related observations along the routes of refugees, actual satellite observations and data mining results. These tools and data are used to monitor spatial distributions as well as extrapolate the arrival of refugees for the subsequent weeks. The second support is the short term update of the location of initial registration facilities and first reception facilities, their capacities, and their occupancy. The third management level is the systematic inquiry for unoccupied housing facilities and for empty places within build-up areas. Geo-coded data sets of house numbers have to be cross-referenced with city maps and communal inhabitants address data. The legal aspects of data mining and secured access to personal data are strictly controlled by the administration allowing only limited access and distribution of data and results. However, the paper will not disclose scientific progress in Earth Observation and GIS, but will actually demonstrate an urgently needed new combination of existing methods to support actual needs. The societal benefits of EO/GIS are no longer just potential possibilities, but actual results in real political, administrative and humanitarian day to day reality.

Supporting Creativity and Appreciation of Uncertainty in Exploring Geo-coded Public Health Data

We present a prototype visualisation tool, ADVISES (Adaptive Visualization for e-Science), designed to support epidemiologists and public health practitioners in exploring geo-coded datasets and generating spatial epidemiological hypotheses. The tool is designed to support creative thinking while providing the means for the user to evaluate the validity of the visualization in terms of statistical uncertainty. We present an overview of the application and the results of an evaluation exploring public health researchers' responses to maps as a new way of viewing familiar data, in particular the use of thematic maps with adjoining descriptive statistics and forest plots to support the generation and evaluation of new hypotheses. A series of qualitative evaluations involved one experienced researcher asking 21 volunteers to interact with the system to perform a series of relatively complex, realistic map-building and exploration tasks, using a 'think aloud' protocol, followed by a semi-structured interview The volunteers were academic epidemiologists and UK National Health Service analysts. All users quickly and confidently created maps, and went on to spend substantial amounts of time exploring and interacting with system, generating hypotheses about their maps. Our findings suggest that the tool is able to support creativity and statistical appreciation among public health professionals and epidemiologists building thematic maps. Software such as this, introduced appropriately, could increase the capability of existing personnel for generating public health intelligence.

The housing market effects of discrete land use regulations: Evidence from the California coastal boundary zone

The California coast line borders some of the most beautiful and expensive land in the entire world. The California Coastal Commission was created in 1976 to protect the coast line and to regulate land use within the coastal boundary zone. This well defined regulatory boundary offers a unique opportunity to study the consequences of land use regulation on nearby housing located in the same political jurisdiction. Using two different geocoded data sets, we document gentrification within the boundary and discuss possible explanations for these patterns.

Spatio-temporal cluster analysis of the incidence of Campylobacter cases and patients with general diarrhea in a Danish county, 1995–2004

Campylobacter infections are the main cause of bacterial gastroenteritis in Denmark. While primarily foodborne, Campylobacter infections are also to some degree acquired through other sources which may include contact with animals or the environment, locally contaminated drinking water and more. We analyzed Campylobacter cases for clustering in space and time for the large Danish island of Funen in the period 1995–2003, under the assumption that infections caused by 'environmental' factors may show persistent clustering while foodborne infections will occur randomly in space. Input data were geo-coded datasets of the addresses of laboratory-confirmed Campylobacter cases and of the background population of Funen County. The dataset had a spatial extent of 4.900 km2. Data were aggregated into units of analysis (so-called features) of 5 km by 5 km times 1 year, and the Campylobacter incidence calculated. We used a modified form of local Moran's I to test if features with similar incidence rates occurred next to each other in space and time, and compared the observed clusters with simulated clusters. Because clusters may be caused by a high tendency among local GPs to submit stool samples, we also analyzed a dataset of all submitted stool samples for comparison. The results showed a significant persisting clustering of Campylobacter incidence rates in the Western part of Funen. Results were visualized using the Netlogo software. The underlying causes of the observed clustering are not known and will require further examination, but may be partially explained by an increased rate of stool samples submissions by physicians in the area. We hope, by this approach, to have developed a tool which will allow for analyses of geographical clusters which may in turn form a basis for further epidemiological examinations to cast light on the sources of infection.

Land and residential property markets in a booming economy: New evidence from Beijing

Beijing's housing market has boomed over the last fifteen years. The city's population grew by 40.6% and per capita income (in constant RMB) by 273.9% from 1991 to 2005. Using two geocoded data sets, we present new evidence on the real estate price gradient, land price gradient, population densities, and building densities in Beijing's recent free housing market. The classic urban monocentric model's predictions are largely upheld in Beijing. We also document the importance of local public goods, such as access to public transit infrastructure, core high schools, clean air, and major universities, most of which have exogenous locations, as important determinants of real estate prices.

Land and Residential Property Markets in a Booming Economy: New Evidence from Beijing

Beijing's housing market has boomed over the last fifteen years. Its population has grown by 40.6% and per-capita income (in constant RMB) has grown by 273.9% from 1991 to 2005. We study recent patterns in Beijing's free market housing market. Using two geocoded data sets, we present new evidence on the real estate price gradient, land price gradient, population densities and building densities. The classic urban monocentric model's predictions are largely upheld in Beijing. We also document the importance of local public goods such as access to public transit infrastructure, clean air and major universities as important determinants of real estate prices.

A small-scale spatial analysis system for maritime Australia

Within the field of resource and environmental management, the paramount value of a spatial analysis system is as a tool for regionalising a case-area in diverse directed ways, each being useful for (i) increasing scientific understanding of that area (intellectualisation) or (ii) for allocating operational categories (for example, funding categories, regulatory categories) differentially between parts of the case-area (called operations support or policy support). Success in serving these scientific and administrative values depends in turn upon two primary attributes of the spatial analysis system and a larger number of secondary attributes. These primary attributes are (i) the range and quality of geocoded data sets held in store or able to be accessed and (ii) the range of spatial analysis techniques which can be called upon for operating on stored data sets. Secondary attributes influencing a spatial analysis system's value include its accessibility to potential users, its ease of use, the judgment and experience of its users and the quality of its cartographic and other outputs. The present paper is a status report on the Australian Coastal And Marine Resources Information System, CAMRIS, a spatial analysis system developed as a demonstration for Australia. CAMRIS contains or can access raw and value-added data sets which comprehensively cover both terrestrial and marine components of the Australian maritime estate. Onshore, for the immediate coastal strip, data held or accessible include geocoded data on vegetation, geology, landform, wetland and coastline type, land use, climate and population. For coastal drainage basins, data sets include river networks, river flows, wetland attributes, soils, geology, elevation, vegetation, mineral deposits, beach attributes, population and bird distributions. Nearshore data include geocoded data on estuary attributes, island attributes, seagrass beds and marine protected areas. Offshore (oceanic) geocoded data held or accessible include bathymetry, sea surface temperature and salinity/dissolved oxygen profiles, together with a variety of geophysical records including gravity, magnetics, seismic track lines, substrates, waves, winds, storms, tides and cyclones. While raw data are stored as such whenever available, many of these data sets are in value-added form, held perhaps as a surface or choropleth or as a function of primary data items. A range of spatial analysis techniques is routinely available for application to CAMRIS data sets including those within the SPANS, Arc Info, and Idrisi geographic information systems, the S Plus exploratory data analysis package, and specialist in-house packages such as PATN for multivariate positive classification and LUPIS for resource allocation and normative classification. CAMRIS demonstration studies in various stages of completion address: (1) selection of coastal and marine protected areas; (2) identification of priority areas for the management of land-based marine pollution; (3) planning for coastal population growth; and (4) synoptic impacts of climatic change in the coastal zone. Further candidate studies being considered include mariculture prospects and proactive management of oil spills and leaks. An important indicator of success for the CAMRIS project would be for it to be seen as a prototype for a properly-funded multi-agency national maritime (coastal and marine) spatial analysis system. Australia, with one of the worlds largest and most diverse maritime estates and with a small population imposing increasing pressures on that estate, needs powerful policy and operations support tools.

IBIS: A geographic information system based on digital image processing and image raster data type

There is a pressing need for geographic information systems which can manage spatially referenced data, which perform certain types of spatially oriented processing, and which are current and comprehensive. Polygon-overlay and grid-cell information systems access data for selected areas, but their data files are time consuming to generate and frequently costly to process. Updating land use changes for such systems may become prohibitively expensive. In response to the present dilemma, a system is presented that makes use of digital image processing techniques to interface existing geocoded data sets and information management systems with thematic maps and remotely sensed imagery. The basic premise is that geocoded data sets can be referenced to a raster scan that is equivalent to a grid-cell data set. Several technical problems have been overcome to achieve a workable system. First, digital image file handling, image manipulation, and image processing capabilities must be provided. Second, image data must be registered or indexed to spatially referenced tabular data so that processing steps which involve both types can operate. Third, a data interface must be provided between the different data types so that the results of processing can be represented. Finally, image processing analogs must be developed for existing geo-base file computational steps (e.g., overlay, aggregation, cross tabulation, etc). The system is now in use on a test basis.