Sean C. Ahearn

TIGMOD: an individual-based spatially explicit model for simulating tiger/human interaction in multiple use forests

Abstract The loss of tiger habitat and the greater dependency of tiger populations on multiple use forests has led to an increase in conflict between tiger and human forest use. Gaining a better understanding of this conflict through a combination of fieldwork and modeling is critical to the survival of tiger populations in these forests. TIGMOD is an individual-based spatially explicit, object-oriented model that simulates key aspects of tiger behavior and its interactions with wild and domestic prey through stochastic processes. It is a dynamic model driven by changes in states of tigers or prey that trigger the behavior and interactions appropriate to these changes. The model permits users to run the simulation based on different scenarios that explore the relationship between prey densities and tiger survivability, as well as those that examine the relationship between villager attitudes towards tiger killing of domestic prey and the likelihood of poisoning a tiger. Model output includes number of tigers born, starved, or poisoned, and number of wild and domestic prey killed. Model simulation results agree well with field observations and data in terms of prey density versus tiger survivability, number of days between two consecutive prey kills, simulated movement of tiger traversal of its home range, and number of cubs born per breeding female tiger. This study shows that tiger populations are sustainable at low density of domestic prey but not sustainable if domestic prey density increases to three or more per square kilometer. Additionally, change in behavior and attitudes of villagers towards tigers, such as increasing guarding of livestock and higher tolerance of domestic prey kills will significantly reduce tiger mortality caused by poisoning. TIGMOD is a useful tool for analyzing the interaction between tigers and humans in multiple use forests. It provides a means of understanding the right balance between forest use by tigers and use by villagers, which can lead to implementation of management strategies that optimize both.

Analysis of movement data

The study of movement is progressing rapidly as a subdiscipline in Geographic Information Science (GIScience). At the fulcrum of this new research area in GIScience are movement observations. Movement observations may be understood as spatiotemporal signals, which carry information on the movement of dynamic entities and the underlying mechanisms that drive their movement. These observations are key to the study and understanding of movement. Technological advancements in global positioning systems (GPS) and related satellite tracking technologies have resulted in significant increases in the availability of highly accurate data on moving phenomena, dramatically outpacing the development of appropriate methods with which to analyze them. In addition to increased spatial accuracy and temporal resolution of the locational information, improvements are being made to accelerometers and ‘biologgers’ that enable the collection of ancillary behavioral and physiological information. This special issue emerged from a pre-conference event associated with the GIScience 2014 conference held in Vienna: a workshop organized by the authors on ‘Analysis of Movement Data’ (AMD 2014). The workshop and this special issue explore recent trends in the study of movement and novel methods for analyzing and contextualizing movement data. A broad range of topics is covered concerning movement analysis, representation, and modeling. The studies presented use movement data from different domains, such as transportation (vehicles, marine traffic), cyclists and athlete tracking data, storm events, and movement ecology (birds, mammals, etc.). This editorial intends to frame and position the papers included in this special issue and to provide recommendations for future directions in the analysis of movement data. In order to frame the work presented here, we use the overarching research framework for the study of movement proposed by Dodge (2015). This framework, shown in an adapted version in Figure 1, posits that the study of movement consists of a continuum of research ranging from understanding movement to construct knowledge of the behavior of dynamic objects, to using this knowledge for modeling and prediction of movement. Visualization facilitates this process through data exploration, hypothesis generation, and communication of the outcomes (Andrienko et al. 2013, Wood et al. 2011, Zhang et al. 2013, Xavier and Dodge 2014). The framework relies on an iterative validation process, where analytics and models are parameterized, calibrated, and improved using real movement observations. Understanding movement, shown on the right side of Figure 1, entails development of methods for quantification of movement and its parameters (Dodge et al. 2008, Long and Nelson 2013, Laube 2014, Demšar et al. 2015); analysis of its context INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2016 VOL. 30, NO. 5, 825–834 http://dx.doi.org/10.1080/13658816.2015.1132424

First evidence of West Nile virus amplification and relationship to human infections

The spatio‐temporal relationship between unusual sightings of dead birds and human West Nile virus infections has been observed in many studies and has been proposed as an indicator of an intense amplification cycle between birds and mosquitoes. However, to date, no single study has provided quantitative evidence that the amplification cycle occurs at the local level and that it operates within certain temporal parameters. Here, we use a novel geostatistical and spatial analytic methodology and present the first evidence that the localized unusual space–time correspondence of dead birds models the amplification cycle and that this cycle peaks 15–16 days prior to human onset of West Nile virus infections. During the process of establishing this relationship, we extend the traditional Knox space–time interaction measure to overcome pair‐dependency limitations and use a novel implementation of the kappa non‐chance agreement measure to identify the temporal characteristics of the association of bird deaths to human West Nile infections.

Re-engineering the GIS&T Body of Knowledge

A computational framework is presented for re-engineering the Geographic Information Science and Technology Body of Knowledge (GIS&T BoK). At its core is an ontology that is meant to simplify and extend the original BoK hierarchical structure to better capture relationships existing among concepts. Our approach builds on several key ideas. First is the notion of a knowledge corpus, an aggregate of both the internal cognitive forms of knowledge held by domain actors and the content of external artifacts that are produced and consumed by domain activities. Second is the notion of a reference system within which such artifacts are located and relationships among artifacts can be expressed. Third is the idea that by structuring the GIS&T concepts through the use of semantic web standards for formal ontologies and envisaging it as a reference system for GIS&T artifacts, activities, and actors, a fundamentally different approach to the redesign, content generation, and maintenance of the GIS&T BoK is enabled. This new approach affords replacing the top-down strategies used to generate the original GIS&T BoK, with a bottom-up strategy that combines analytical and participatory components. On the analytical side, computational and visual techniques are used to provide alternative means for accessing BoK content, examining the semantic consistency of current BoK structures, transforming the existing hierarchy into a semantic network, identifying overlaps and gaps in the current BoK, and performing projection of knowledge artifacts onto the BoK to inform its maintenance and update. Participatory approaches to bottom-up restructuring and maintenance of the BoK will support authoring, editing, and validation of concepts using a wiki-like community editing service. The system we describe is deployed as a web service that can be accessed by a range of applications for visualization, analysis, exploration, and contextualization of concepts and their related classes in the new GIS&T Body of Knowledge. The goal is for the new GIS&T BoK2 to evolve into the centerpiece of a cyberinfrastructure ecosystem for the GIS&T domain.

Toward an Immersive 3D Virtual BoK Exploratorium: A Proof of Concept

The UCGIS GIS&T Body of Knowledge document provided an opportunity for the GIS educational com- munity to link course content and curricular sequencing to a catalog of subject matter. Focusing on learn- ing objectives, a selection of relevant citations, and basic background for each topic, it has been used to a limited degree for both course topic selection and curriculum development. However, the static format of the document, lack of an index, and dated nature of the material limit its utility for education. Based on the success of our research team in developing a virtual platform for a new, more interactive, and collabo- rative environment to catalogue and interactively add to the body knowledge (Ahearn et al. 2013), this article describes efforts to develop a multi-user virtual user environment that will add social presence to the experience. It describes the successes and failures of using Second Life as the initial platform for this work, illustrates the available interactions and limitations, and depicts ongoing efforts to move beyond Second Life for this development. Finally it discusses a possible methodology to leverage the power of virtual crowd sourcing within competitive gaming environments such as Unity to allow for the creation of on-demand virtual 3-D visualizations of GIS&T concepts in a digital Exploratorium.

A Multi-Scale Approach to Mapping Canopy Height

Abstract Mapping vegetation height over large areas presents a prob-lem of scale: height varies with the individual tree or stand, but the resolution of available datasets is too low to char-acterize this variability sufficiently for many applications. We address this problem by fusing 1 km resolution canopy height data derived from satellite-based laser altimetry with higher-resolution land-cover data, resulting in 30 m resolution estimates of canopy height. These are downscaled further to 1 m resolution by simulating individual trees. A web service architecture is used, which allows processing to occur on demand without preprocessing large datasets. We compared the resulting canopy volumes to reference airborne lidar data from 262 randomly located 1 km 2 areas within nine study sites. Results at 30 m resolution show an RMSE of 33 percent of the mean reference volume and an R 2 of 0.77; at 1 m the RMSE is 66 percent and the R 2 is 0.38. Introduction Vegetation height is a key measurement used to estimate a variety of ecological and biophysical variables, including above-ground biomass, surface roughness, and stem volume. Global large-footprint lidar data from the Geoscience Laser Altimeter System (

Modelling forest canopy trends with on-demand spatial simulation

Understanding trends in forest canopy cover at local, national, and global scales is important for many applications, including policymaking related to forest carbon sequestration. Globally consistent land-cover data sets derived from MODerate-resolution Imaging Spectroradiometer (MODIS) are now available for a period of more than 10 years, long enough to detect trends both in deforestation and in afforestation. However, methods of modelling land-cover change normally require specialized software and expertise, limiting the availability of this information. This barrier to access can be eliminated through the use of web services that construct models on demand based on user-specified regions of interest, so that parameters are inferred from, and relevant to, local conditions. In this paper we present a proof-of-concept system for building and running spatial Markov chain models of forest-cover change on demand, and demonstrate how the on-demand approach may be implemented for similar applications.