A Multiscale Approach for Spatio-Temporal Outlier Detection

A spatial outlier is a spatially referenced object whose thematic attribute values are significantly different from those of other spatially referenced objects in its spatial neighborhood. It represents an object that is significantly different from its neighbourhoods even though it may not be significantly different from the entire population. Here we extend this concept to the spatio‐temporal domain and define a spatial‐temporal outlier (ST‐outlier) to be a spatial‐temporal object whose thematic attribute values are significantly different from those of other spatially and temporally referenced objects in its spatial or/and temporal neighbourhoods. Identification of ST‐outliers can lead to the discovery of unexpected, interesting, and implicit knowledge, such as local instability or deformation. Many methods have been recently proposed to detect spatial outliers, but how to detect the temporal outliers or spatial‐temporal outliers has been seldom discussed. In this paper we propose a multiscale approach to detect ST‐outliers by evaluating the change between consecutive spatial and temporal scales. A four‐step procedure consisting of classification, aggregation, comparison and verification is put forward to address the semantic and dynamic properties of geographic phenomena for ST‐outlier detection. The effectiveness of the approach is illustrated by a practical coastal geomorphic study.     

Estimating the Effects of Map Error on Habitat Delineation for the California Spotted Owl in Southern California

The reliability of habitat maps that have been generated using Geographic Information Systems (GIS) and image processing of remotely sensed data can be overestimated. Habitat suitability and spatially explicit population viability models are often based on these products without explicit knowledge of the effects of these mapping errors on model results. While research has considered errors in population modeling assumptions, there is no standardized method for measuring the effects of inaccuracies resulting from errors in landscape classification. Using landscape‐scale maps of existing vegetation developed for the USDA Forest Service in southern California from Landsat Thematic Mapper satellite data and GIS modeling, we performed a sensitivity analysis to estimate how mapping errors in vegetation type, forest canopy cover, and tree crown size might affect delineation of suitable habitat for the California spotted owl (Strix occidentalis occidentalis). The resulting simulated uncertainty maps showed an increase in the estimated area of suitable habitat types. Further analysis measuring the fragmentation of the additional patches showed that they were too small to be useful as habitat areas.     

Enabling Spatially Aware Mobile Applications

Recently, increasing numbers of mobile phones are appearing on the market that feature advanced navigation capabilities: embedded GPS receivers for global positioning, integrated digital compasses for detecting the heading of the device, or accelerometer‐based tilt sensors will potentially enable upcoming and future mobile phones to measure their location and orientation in 3D space. In this paper, we present an application framework for building spatially aware mobile applications – applications that visualize, process or exchange geospatial information – on mobile phones equipped with such features. The core component of the framework is a novel, platform‐independent XML data exchange format for the interface between application server and mobile device that describes the geographic vicinity of the user. The format enables a variety of new mobile interaction styles and user interface types – from traditional text‐based local search and information interfaces to innovative real‐time user interfaces like Geo‐Wands and Smart Compasses.     

Using GIS in Areawide Pest Management: A Case Study in South Dakota

Infestations of corn rootworms (Coleoptera: Chrysomelidae) create economic and environmental concerns in the Corn Belt region of the United States. To supplement the population control tactics of areawide pest management programs, we believe that a better understanding of the spatial relationships between biotic and abiotic or physical factors at the landscape scale is needed. Our research used several geographical information systems (GIS) and spatial analytical techniques to examine relationships between corn rootworm metapopulation dynamics, soil texture, and elevation. Within GIS, several spatially explicit procedures were used that include an interpolation technique, spatial autocorrelation analysis, and contingency analysis. Corn rootworm metapopulation distributions were found to be aggregated and related to soil texture and elevation. We review techniques and discuss our preferences for using particular spatially explicit procedures. The information derived from the spatial analyses demonstrates how GIS can be used in areawide pest management to provide inputs for spatially explicit models to predict future pest populations and formulate more well‐informed pest management decisions. The techniques described in this paper could easily be extended to study the spatial dynamics between other pest populations in agricultural landscapes.     

A Spatial Data Infrastructure Approach for the Characterization of New Zealand's Groundwater Systems

The future information needs of stakeholders for hydrogeological and hydro‐climate data management and assessment in New Zealand may be met with an Open Geospatial Consortium (OGC) standards‐compliant publicly accessible web services framework which aims to provide integrated use of groundwater information and environmental observation data in general. The stages of the framework development described in this article are search and discovery as well as data collection and access with (meta)data services, which are developed in a community process. The concept and prototype implementation of OGC‐compliant web services for groundwater and hydro‐climate data include demonstration data services that present multiple distributed datasets of environmental observations. The results also iterate over the stakeholder community process and the refined profile of OGC services for environmental observation data sharing within the New Zealand Spatial Data Infrastructure (SDI) landscape, including datasets from the National Groundwater Monitoring Program and the New Zealand Climate Database along with datasets from affiliated regional councils at regional‐ and sub‐regional scales. With the definition of the New Zealand observation data profile we show that current state‐of‐the‐art standards do not necessarily need to be improved, but that the community has to agree upon how to use these standards in an iterative process.     

Strategically Locating Wildlife Crossing Structures for Florida Panthers Using Maximal Covering Approaches

Crossing structures are an effective method for mitigating habitat fragmentation and reducing wildlife‐vehicle collisions, although high construction costs limit the number that can be implemented in practice. Therefore, optimizing the placement of crossing structures in road networks is suggested as a strategic conservation planning method. This research explores two approaches for using the maximal covering location problem (MCLP) to determine optimal sites to install new wildlife crossing structures. The first approach is based on records of traffic mortality, while the second uses animal tracking data for the species of interest. The objective of the first is to cover the maximum number of collision sites, given a specified number of proposed structures to build, while the second covers as many animal tracking locations as possible under a similar scenario. These two approaches were used to locate potential wildlife crossing structures for endangered Florida panthers (Puma concolor coryi) in Collier, Lee, and Hendry Counties, Florida, a population whose survival is threatened by excessive traffic mortality. Historical traffic mortality records and an extensive radio‐tracking dataset were used in the analyses. Although the two approaches largely select different sites for crossing structures, both models highlight key locations in the landscape where these structures can remedy traffic mortality and habitat fragmentation. These applications demonstrate how the MCLP can serve as a useful conservation planning tool when traffic mortality or animal tracking data are available to researchers.     

A community-based urban forest inventory using online mapping services and consumer-grade digital images

Community involvement in gathering and submitting spatially referenced data via web mapping applications has recently been gaining momentum. Urban forest inventory data analyzed by programs such as the i-Tree ECO inventory method is a good candidate for such an approach. In this research, we tested the feasibility of using spatially referenced data gathered and submitted by non-professional individuals through a web application to augment urban forest inventory data. We examined the use of close range photogrammetry solutions of images taken by consumer-grade cameras to extract quantitative metric information such as crown diameter, tree heights and trunk diameters. Several tests were performed to evaluate the accuracy of the photogrammetric solutions and to examine their use in addition to existing aerial image data to supplement or partially substitute for standard i-Tree ECO field measurements.     

Multi‐temporal AVHRR digital data: An approach for landcover mapping of heterogeneous landscapes

A multi‐temporal sequence of seven NOAA‐n, Advanced Very High Resolution Radiometer (AVHRR) satellite scenes (April 10, May 18, June 6, June 29, July 20, and August 18, 1987) were composited to derive cover‐type information in the heterogeneous landscape of University Lake Watershed, North Carolina, U.S.A. The Normalized Difference Vegetation Index (NDVI) was calculated for each scene and merged into a seven‐dimensional dataset, representing each time period sampled. An unsupervised classification was performed on the multi‐temporal composite to derive five cover‐type classes. Similar classifications were generated on single scene information. Ground control information was derived from an unsupervised classification of one kilometer grid compositional percentages initially derived from photo‐interpreted landcover information. The multi‐temporal NDVI classification more consistently characterized phenologic responses on a spatially dissected landscape than single scene clustering. Sub‐pixel information showed how the algorithm separated compositional information between classes. Temporal vectors were plotted to illustrate differentiation on the basis of NDVI profiles.     

GIS and simple systems for visual,interactive, spatial analysis

Abstract

In much the same way as a spreadsheet is more appropriate to some needs than a fully relational DBMS, many users interested in analysis of spatially referenced data have fairly unsophisticated requirements for extensive data storage or complex retrieval functions, and limited needs for topographic detail, cartographic accuracy or advanced map editing; however, they do require access to a wide range of statistical functions for data transformation, reduction and smoothing, multivariate analysis, and the modelling of spatial relationships. This paper argues that the needs of such users are poorly met by the 'mainstream' model for GIS that is often presented in the literature. A PC-based system, equivalent in GIS terms to the spreadsheet, is described. It integrates simple data structures, limited map creation and editing, a powerful range of standard and spatially orientated statistical functions, and the ability to interactively present results through chloropleth, contour, proportionate symbol, or proximally shaded maps. It is particularly designed to be easily accessible and to encourage visual interactive analysis. For some users such a system has acted as an adequate solution in its own right and for others it has provided a useful educational transition to more extensive and powerful systems.     

Map Symbols for Crisis Mapping: Challenges and Prospects

Crisis maps and visualizations utilized routinely by international agencies, humanitarian organizations, and non-governmental organizations for aid and relief activities commonly require complex sets of map symbols. However, effective map symbology for humanitarian relief purposes entails several challenges, including consideration of the following: (1) taxonomy development, (2) symbol design issues, (3) promulgation and sharing of map symbols, and (4) standardization of symbols within and among organizations. This paper discusses these key challenges to the design and use of crisis map symbology through a review of the cartographic literature as well as results collected from a survey targeted at humanitarian organizations from around the world. The survey was designed to gather information on current symbology design and use practices in order to understand common challenges. Survey results confirm agreement in the persistence of these four primary symbology challenges, especially the importance of intuitive symbol design. Respondents disagreed most about the adequacy of current crisis map symbology standards as well as the ease in which standards may be implemented within and across organizations. Survey results suggest the need for expert systems designed specifically for symbology design to support humanitarian relief activities.     

GIS in Participatory Research: Assessing the Impact of Landmines on Communities in North-west Cambodia

The view of GIS, adopted by many, as an undemocratic and divisive technology is perhaps most poignant in settings where financial and skills‐based resources are limited, notably in lower‐income countries. Where those countries are also recovering from a period of military conflict there would at first sight seem to be little opportunity for employing GIS as part of a socially‐sensitive approach to ‘development’. This paper explores the potential for using GIS in participatory approaches to gathering and analysing geographical information on human‐environment interactions in post‐conflict settings. We discuss empirical work from northwest Cambodia where GIS and participatory methods have been integrated to assess risk to local communities from landmines and to develop priorities for landmine clearance. In juxtaposing ‘official’, spatially‐referenced data with indigenous geographical knowledge in this study we seek to privilege meaningful geographical understandings over conventional notions of spatial ‘accuracy’. In so doing we carry out a Participatory Mine Impact Assessment (PMIA) to explore spatial activities among local populations in mine‐contaminated communities and to help identify improved strategies for returning refugees in re‐establishing livelihoods.     

Integrated Storage and Querying of Spatially Varying Data Quality Information in a Relational Spatial Database

This article investigates a new, integrated technique for storing and retrieving spatially varying data quality information in a relational spatial database. Rather than storing global data quality statements, the system enables data quality information to be referenced to a spatial framework, individual spatial objects, or even parts of spatial objects. The integrated model, called as RDBMS for Spatial Variation in Quality (RSVQ), allows flexible storage of spatially varying data quality information, and seamless querying irrespective of the underlying storage model. RSVQ is founded on a formal model of relational databases, defining a new derived, polymorphic query operator      to join quality data with spatial data. The      operator is implemented in an extension to SQL as a new WITHQUALITY keyword. A performance evaluation of RSVQ was conducted, using an Oracle Spatial database and a case study of cadastral data for parts of Victoria, Australia. The results of this evaluation demonstrated that the system is practical and efficient for a wide range of queries, as well as indicating the performance trade-offs associated with the different data quality storage models. Using the integrated RSVQ approach provides the potential for a single, consistent, database engine for a wide range of existing and proposed spatial data quality management systems.     

Elephants move faster in small fragments of low productivity in Amboseli ecosystems: Kenya

Understanding factors affecting the behaviour and movement patterns of the African elephant is important for wildlife conservation, especially in increasingly human-dominated savanna landscapes. Currently, knowledge on how landscape fragmentation and vegetation productivity affect elephant speed of movement remains poorly understood. In this study, we tested whether landscape fragmentation and vegetation productivity explains elephant speed of movement in the Amboseli ecosystem in Kenya. We used GPS collar data from five elephants to quantify elephant speed of movement for three seasons (wet, dry and transitional). We then used multiple regression to model the relationship between speed of movement and landscape fragmentation, as well as vegetation productivity for each season. Results of this study demonstrate that landscape fragmentation and vegetation productivity predicted elephant speed of movement poorly (R² < 0.4) when used as solitary covariates. However, a combination of the covariates significantly (p < 0.05) explained variance in elephant speed of movement with improved R² values of 0.69, 0.45, 0.47 for wet, transition and dry seasons, respectively.     

GEODESY AND DIGITAL CARTOGRAPHIC SURVEY IN FILDES PENINSULA,REY JORGE ISLAND,ANTARCTICA

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Spatial Approaches to Modeling Dispersion of Communicable Diseases – A Review

The dispersion of communicable diseases in a population is intrinsically spatial. In the last several decades, a range of spatial approaches has been devised to model epidemiological processes; and they differ significantly from each other. A review of spatially oriented epidemiological models is necessary to assess advances in spatial approaches to modeling disease dispersion and to help identify those most appropriate for specific research goals. The most notable difference in the design of these spatially oriented models is the scale and mobility of the modeling unit. Using two criteria, this review identifies six types of spatially oriented models. These include: (1) population‐based wave models, (2) sub‐population models, (3) individual‐based cellular automata models, (4) mobile sub‐population models, (5) individual‐based spatially implicit models, and (6) individual‐based mobile models. Each model type is evaluated in terms of its design principles, assumptions, and intended applications. For the evaluation of design, four aspects of design principles are discussed: the modeling unit, the interaction between the modeling units, the spatial process, and the temporal process utilized in a design. Insights gained from this review can be useful for devising much‐needed spatially and temporally oriented strategies to forecast, prevent, and control communicable diseases.     

A transboundary study of urban sprawl in the Pacific Coast region of North America: The benefits of multiple measurement methods

Sprawling urban development has emerged as a primary concern of policy makers, land preservationists and both urban and rural communities in developing regions across the globe. For the first time in history, more global residents lived in urban areas than not and the trend to urbanization is in full force at the start of the 21st century. An understanding of the nature and character of urban sprawl is complicated by a failure to satisfactorily define it and by the limitations of measurement techniques designed to characterize complex landscape forms. Like other landscape patterns, the quantification of urban sprawl is highly spatially and temporally scale-dependent. This paper summarizes a recent project to measure urban sprawl in the transboundary region of the Pacific Coast of North America. The metropolitan centers of Portland, OR, Seattle, WA and Vancouver, BC, span two nations, three state/provincial governments and dozens of cities. As a region, this was a global leader in population growth in the 1990s. The study relied on three separate methods – an impervious surface metric, a neighborhood density metric and a building permit metric – for quantifying urban growth. The results provide insight on the strengths and shortcomings of different methods with respect to the challenges posed by data availability and format. Taken together they demonstrate the richer understanding that combined methods may offer in characterizing phenomena as difficult to communicate and agree upon as urban sprawl.     

Measuring segregation: an activity space approach

While the literature clearly acknowledges that individuals may experience different levels of segregation across their various socio-geographical spaces, most measures of segregation are intended to be used in the residential space. Using spatially aggregated data to evaluate segregation in the residential space has been the norm and thus individual’s segregation experiences in other socio-geographical spaces are often de-emphasized or ignored. This paper attempts to provide a more comprehensive approach in evaluating segregation beyond the residential space. The entire activity spaces of individuals are taken into account with individuals serving as the building blocks of the analysis. The measurement principle is based upon the exposure dimension of segregation. The proposed measure reflects the exposure of individuals of a referenced group in a neighborhood to the populations of other groups that are found within the activity spaces of individuals in the referenced group. Using the travel diary data collected from the tri-county area in southeast Florida and the imputed racial–ethnic data, this paper demonstrates how the proposed segregation measurement approach goes beyond just measuring population distribution patterns in the residential space and can provide a more comprehensive evaluation of segregation by considering various socio-geographical spaces.     

Detection of clusters in traffic networks based on spatio‐temporal flow modeling

Spatio‐temporal clustering is a highly active research topic and a challenging issue in spatio‐temporal data mining. Many spatio‐temporal clustering methods have been designed for geo‐referenced time series. Under some special circumstances, such as monitoring traffic flow on roads, existing methods cannot handle the temporally dynamic and spatially heterogeneous correlations among road segments when detecting clusters. Therefore, this article develops a spatio‐temporal flow‐based approach to detect clusters in traffic networks. First, a spatio‐temporal flow process is modeled by combining network topology relations with real‐time traffic status. On this basis, spatio‐temporal neighborhoods are captured by considering traffic time‐series similarity in spatio‐temporal flows. Spatio‐temporal clusters are further formed by successive connection of spatio‐temporal neighbors. Experiments on traffic time series of central London's road network on both weekdays and weekends are performed to demonstrate the effectiveness and practicality of the proposed method.     

Visualisation techniques to support public interpretation of future climate change and land-use choices: a case study from N-E Scotland

Mitigating and adapting to climate change includes a requirement to evaluate the role of future land uses in delivering robust integrated responses that are sensitive to local landscape contexts. In practice, this emphasises the need for community engagement, planning and inclusive decision-making. Community engagement may be potentially facilitated by the use of spatially explicit quantitative scenarios of land-use change in combination with interactive visualisation. This requires a coherent framework to integrate spatial data modelling, analytical capabilities and visualisation tools in a format that will also engage diverse public audiences. These challenges were explored with a case study of virtual landscapes from N-E Scotland that was used to test preferences for scenarios of future land use. Visualisations employed texture-based rendering rather than full photo-realistic rendering to facilitate interactivity and this provided additional scope for audiences to explore multiple future scenarios compared to the present landscape. Interactive voting in a virtual landscape theatre suggested preferences for visual diversity, good stewardship and perceived naturalness that should be considered in developing planned responses to change. Further investigation of preferences was conducted using interactive 3D features located within the landscape. Study findings are reviewed against objectives for inclusive engagement in the Digital Earth agenda and used to make further recommendations on the use of scenarios and visualisation tools. In particular, technical advances in user engagement need to be developed in conjunction with emerging good practice that addresses ethical, behavioural and inclusion issues so that the content is presented in as transparent and unbiased format as possible.     

Estimating Small-Area Populations by Age and Sex Using Spatial Interpolation and Statistical Inference Methods

The objective of this research is to compute population estimates by age and sex for small areas whose boundaries are different from those for which the population counts were made. In our approach, population surfaces and age‐sex proportion surfaces are separately estimated. Age‐sex population estimates for small areas and their confidence intervals are then computed using a binomial model with the two surfaces as inputs. The approach was implemented for Iowa using a 90 m resolution population grid (LandScan USA) and U.S. Census 2000 population. Three spatial interpolation methods, the areal weighting (AW) method, the ordinary kriging (OK) method, and a modification of the pycnophylactic method, were used on Census Tract populations to estimate the age‐sex proportion surfaces. To verify the model, age‐sex population estimates were computed for paired Block Groups that straddled Census Tracts and therefore were spatially misaligned with them. The pycnophylactic method and the OK method were more accurate than the AW method. The approach is general and can be used to estimate subgroup‐count types of variables from information in existing administrative areas for custom‐defined areas used as the spatial basis of support in other applications.