Line generalisation by repeated elimination of the smallest area

CISRG discussion paper ; 1

The Douglas-Peucker algorithm for line simplification : re-evaluation through visualisation

CISRG discussion paper ;

Development and application of a "spray-can" tool for fuzzy geographical analysis

Most information generated by the general public, particularly for the purpose of decision-support, will inherently contain a spatial component. This spatial data can comprise a very valuable resource for researchers, planners and decision makers, and may be collected for analysis using a Public Participation GIS (PPGIS). The imprecise and abstract nature of the thoughts, feelings and opinions of the public do not, however, lend themselves well to the discrete boundaries enforced by ‘traditional’ GIS data constructs (points, lines and polygons), and as such require data structures that allow for the ‘fuzzy’ nature of these data to be incorporated into their capture, storage and analysis. This paper therefore presents a web-based PPGIS platform with a ‘spray-can’ interface for the capture of fuzzy spatial data; and a relational ‘multi-point-and-attribute’ data structure, which reflects the fuzzy nature of the data, whilst supporting flexible spatial and attribute querying. Whilst the idea of the spray-can interface is not itself novel, the platform demonstrated in this paper has the potential to improve the decision-making process in a number of different areas at a variety of different scales. This is achieved by both increasing levels of interaction with the public through the familiar and user-friendly spray-can interface; and increasing the level of understanding of the spatial and aspatial information that participants contribute, by maximising the potential analytical approaches that may be taken

Visualizing patterns in spatially ambiguous point data

As technologies permitting both the creation and retrieval of data containing spatial information continue to develop, so do the number of visualisations using such data. This spatial information will often comprise a place-name that may be ‘geocoded’ into coordinates, and displayed on a map, frequently using a ‘heatmap-style’ visualisation to reveal patterns in the data. Across a dataset, however, there is often ambiguity in the geographic scale to which a place-name refers (country, county, town, street etc.), and attempts to simultaneously map data at a multitude of different scales will result in the formation of ‘false hotspots’ within the map. These form at the centres of administrative areas (countries, counties, towns etc.) and introduce erroneous patterns into the dataset whilst obscuring real ones, resulting in misleading visualisations of the patterns in the dataset. This paper therefore proposes a new algorithm to intelligently redistribute data that would otherwise contribute to these ‘false hotspots’, removing them to locations that likely reflect real-world patterns at a homogenous scale, and so allow more representative visualisations to be created, without the negative effects of ‘false hotspots’ resulting from multi-scale data. This technique demonstrated on a sample dataset taken from Twitter, and validated against the ‘geotagged’ portion of the same dataset

A network-based approach for estimating pedestrian journey-time exposure to air pollution

Individual exposure to air pollution depends not only upon pollution concentrations in the surrounding environment, but also on the volume of air inhaled, which is determined by an individual’s physiology and activity level. This study focuses on journey-time exposure, using network analysis in a GIS environment to identify pedestrian routes between multiple origins and destinations throughout the city of Lancaster, North West England. For each segment of a detailed footpath network, exposure was calculated accounting for PM2.5 concentrations (estimated using an atmospheric dispersion model) and respiratory minute volume (varying between individuals and with slope). For each of the routes generated the cumulative exposure to PM2.5 was estimated, allowing for easy comparison between multiple routes. Significant variations in exposure were found between routes depending on their geography, as well as in response to variations in background concentrations and meteorology between days. Differences in physiological characteristics such as age or weight were also seen to impact journey-time exposure considerably. In addition to assessing exposure for a given route, the approach was used to identify alternative routes that minimised journey-time exposure. Exposure reduction potential varied considerably between days, with even subtle shifts in route location, such as to the opposite side of the road, showing significant benefits. The method presented is both flexible and scalable, allowing for the interactions between physiology, activity level, pollution concentration and journey duration to be explored. In enabling physiology and activity level to be integrated into exposure calculations a more comprehensive estimate of journey-time exposure can be made, which has potential to provide more realistic inputs for epidemiological studies

Evaluating the spraycan:understanding participant interaction with a PPGIS

Whilst widely accepted as an important facet of software design, the evaluation of PPGIS usability is often overlooked in research. This work comprises a novel approach to the evaluation of the Spraycan PPGIS, whereby rich insights into participant behaviour are drawn from data that are natively collected by the platform as opposed to through additional questionnaires, log files or similar. The approach will be validated against a ‘traditional’ questionnaire, before conclusions are drawn relating to the usability of the Spraycan as a platform for the collection of vague spatial data, in the hope of developing a greater understanding into the way in which people interact with geographic problems

Mapping traffic pollution exposure:the quantified self

The purpose of this paper is to apply recent developments in the areas of the ‘Quantified Self’ and the ‘Internet of Things’ in order to explore the use of low-cost sensors for the collection of a variety of spatially-referenced biometric and environmental data from participants. This is achieved using a specially designed application on the Android mobile platform, which has been developed for this project in order to log serial sensor data via USB against GPS location and timestamp, allowing the spatio-temporal mapping of a variety of personal data. In this case, traffic pollution data is collected and compared with a measures of nasal airflow, permitting an estimate of exposure to traffic pollution for an individual on a given journey. These data will be fed back to individuals in order to assess the level of correlation with their reported perception of exposure to pollution, as well the extent to which this influences subsequent behaviour; such as whether or not an individual will modify their route for a given journey based upon their new knowledge of pollution levels. In this way, personal pollution exposure can be empirically monitored at the individual level, allowing for a more in-depth understanding of these issues than has so far been possible

Towards the integration of urban planning and biodiversity conservation through collaboration

Despite aspirations to halt biodiversity loss by 2020 under the Aichi Biodiversity Targets, urban development continues to negatively impact UK wildlife and habitats. Reasons behind continued biodiversity decline are examined through the use of semi-structured interviews with ecologists, statutory regulators and land developers.. It is found that despite strict legislation and best practice, for both planning and ecology, there is still much room for subjectivity regarding the protection of specific ecological features and the implementation of the mitigation hierarchy. Interviews also revealed that such subjectivity often facilitates the prioritisation of commercial over ecological benefits during site design. Furthermore, many felt an over reliance on the protection of individual animals, as opposed to maintaining functional connectivity for conservation of wider populations was detrimental to both the development industry and ecology. Our findings support the case for further research into the development of innovative geographical information systems to allow spatial deliberation, and collaborative decision-making between the three stakeholder groups

Detecting gas flares and estimating flaring volumes at individual flow stations using MODIS data.

Gas flaring has gained global recognition as a prominent agent of pollution, leading to the establishment of the Global Gas Flaring Reduction (GGFR) initiative, which requires an objective means of monitoring flaring activity. Because auditable information on flaring activity is difficult to obtain there have recently been attempts to detect flares using satellite imagery, typically at global scales. However, to adequately assess the environmental and health impacts of flaring from local to regional scales, it is important that we have a means of acquiring information on the location of individual active flaring sites and the volume of gas combusted at these sites. In this study we developed an approach to the retrieval of such information using nighttime MODIS thermal imagery. The MODIS flare detection technique (MODET) and the MODIS flare volume estimation technique (MOVET) both exploit the absolute and contextual radiometric response of flare sites. The levels of detection accuracy and estimation error were quantified using independent observations of flare location and volume. The MODET and MOVET were applied to an archive of MODIS data spanning 2000–2014 covering the Niger Delta, Nigeria, a significant global hotspot of flaring activity. The results demonstrate the substantial spatial and temporal variability in gas flaring across the region, between states and between onshore and offshore sites. Thus, whilst the estimated total volume of gas flared in the region over the study period is large (350 Billion Cubic Metres), the heterogeneity in the flaring indicates that the impacts of such flares will be highly variable in space and time. In this context, the MODET and MOVET offer a consistent and objective means of monitoring flaring activity over an appropriate range of scales and it is now important that their robustness and transferability is tested in other oil-producing regions of the world

Dynamics and controls of urban heat sink and island phenomena in a desert city:development of a local climate zone scheme using remotely-sensed inputs

This study aims to determine the dynamics and controls of Surface Urban Heat Sinks (SUHS) and Surface Urban Heat Islands (SUHI) in desert cities, using Dubai as a case study. A Local Climate Zone (LCZ) schema was developed to subdivide the city into different zones based on similarities in land cover and urban geometry. Proximity to the Gulf Coast was also determined for each LCZ. The LCZs were then used to sample seasonal and daily imagery from the MODIS thermal sensor to determine Land Surface Temperature (LST) variations relative to desert sand. Canonical correlation techniques were then applied to determine which factors explained the variability between urban and desert LST. Our results indicate that the daytime SUHS effect is greatest during the summer months (typically ∼3.0 °C) with the strongest cooling effects in open high-rise zones of the city. In contrast, the night-time SUHI effect is greatest during the winter months (typically ∼3.5 °C) with the strongest warming effects in compact mid-rise zones of the city. Proximity to the Arabian Gulf had the largest influence on both SUHS and SUHI phenomena, promoting daytime cooling in the summer months and night-time warming in the winter months. However, other parameters associated with the urban environment such as building height had an influence on daytime cooling, with larger buildings promoting shade and variations in airflow. Likewise, other parameters such as sky view factor contributed to night-time warming, with higher temperatures associated with limited views of the sky