Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

Development of a Voice Virtual Assistant for the Geospatial Data Visualization Application on the Web

Voice assistants can elevate interaction in geospatial data web platforms. This research introduces a voice assistant in the BStreams platform and focuses on understanding user commands in the geospatial domain. We developed a specialised geospatial discourse framework through structured prototyping. A survey with 66 participants revealed prevalent English geospatial terminologies. Using ChatGPT, we found the term suggestions aligned with survey results, with a notable correlation (r = 0.81, p < 0.01) between the NPL model’s probability scores and term prevalence in survey data. Our study also incorporated usability tests on the application, which uses tools like Web Speech API, Leaflet, and Mapbox geocoding. Results from these tests reaffirm the potential of voice assistants in enhancing geospatial data visualisation, though challenges persist in areas like language understanding and domain knowledge. The paper advocates for further research to refine the integration of voice technology in this domain

Evaluation of standards and techniques for retrieval of geospatial raster data : a study for the ICOS Carbon Portal

Evaluation of Standards and Techniques for Retrieval of Geospatial Raster Data - A study for ICOS Carbon Portal Geospatial raster data represent the world as a surface with its geographic information which varies continuously. These data can be grid-based data like Digital Terrain Elevation Data (DTED) and geographic image data like multispectral images. The Integrated Carbon Observation System (ICOS) European project is launched to measure greenhouse gases emission. The outputs of these measurements are the data in both geospatial vector (raw data) and raster formats (elaborated data). By using these measurements, scientists create flux maps over Europe. The flux maps are important for many groups such as researchers, stakeholders and public users. In this regard, ICOS Carbon Portal (ICOS CP) looks for a sufficient way to make the ICOS elaborated data available for all of these groups in an online environment. Among others, ICOS CP desires to design a geoportal to let users download the modelled geospatial raster data in different formats and geographic extents. Open GeoSpatial Consortium (OGC) Web Coverage Service (WCS) defines a geospatial web service to render geospatial raster data such as flux maps in any desired subset in space and time. This study presents two techniques to design a geoportal compatible with WCS. This geoportal should be able to retrieve the ICOS data in both NetCDF and GeoTIFF formats as well as allow retrieval of subsets in time and space. In the first technique, a geospatial raster database (Rasdaman) is used to store the data. Rasdaman OGC component (Petascope) as the server tool connects the database to the client side through WCS protocol. In the Second technique, an advanced file-based system (NetCDF) is applied to maintain the data. THREDDS as the WCS server ships the data to the client side through WCS protocol. These two techniques returned good result to download the data in desired formats and subsets.Evaluation of Standards and Techniques for Retrieval of Geospatial Raster Data Geospatial data refer to an object or phenomena located on the specific scene in space, in relation with the other objects. They are linked to geometry and topology. Geospatial raster data are a subset of geospatial data. Geospatial raster data represent the world as a surface with its geographic information which varies continuously. These data can be grid-based data like Digital Terrain Elevation Data (DTED) and geographic image data like multispectral images. The challenges present in working with geospatial raster data are related to three important components: I) storage and management systems, II) standardized services and III) software interface of geospatial raster data. Each component has its own importance in the aim of improving the interaction with geospatial raster data. A proper geospatial raster data storage and management system makes it easy to classify, search and retrieve the data. A standardized service is needed to unify, download, process and share these data among other users. The last challenge is choosing suitable software interface to support the standardized services on the web. The aim is to provide ability for users to download geospatial raster data in different formats in any desired space and time subsets. In this regard, two different techniques are evaluated to connect the main three components to provide such aim. In the first technique, a geospatial raster database is used to store the data. Then this database is connected to the software interface through standardized service. In the Second technique, an advanced file-based system is applied to maintain the data. The server ships the data to software interface through standardized service. Although these two techniques have their own difficulties, they returned good result. Users can download the data in desired formats on the web. In addition, they can download the data for any specific area and specific time

Web GIS in practice IX: a demonstration of geospatial visual analytics using Microsoft Live Labs Pivot technology and WHO mortality data

The goal of visual analytics is to facilitate the discourse between the user and the data by providing dynamic displays and versatile visual interaction opportunities with the data that can support analytical reasoning and the exploration of data from multiple user-customisable aspects. This paper introduces geospatial visual analytics, a specialised subtype of visual analytics, and provides pointers to a number of learning resources about the subject, as well as some examples of human health, surveillance, emergency management and epidemiology-related geospatial visual analytics applications and examples of free software tools that readers can experiment with, such as Google Public Data Explorer. The authors also present a practical demonstration of geospatial visual analytics using partial data for 35 countries from a publicly available World Health Organization (WHO) mortality dataset and Microsoft Live Labs Pivot technology, a free, general purpose visual analytics tool that offers a fresh way to visually browse and arrange massive amounts of data and images online and also supports geographic and temporal classifications of datasets featuring geospatial and temporal components. Interested readers can download a Zip archive (included with the manuscript as an additional file) containing all files, modules and library functions used to deploy the WHO mortality data Pivot collection described in this paper

Probe-based visual analysis of geospatial simulations

This work documents the design, development, refinement, and evaluation of probes as an interaction technique for expanding both the usefulness and usability of geospatial visualizations, specifically those of simulations. Existing applications that allow the visualization of, and interaction with, geospatial simulations and their results generally present views of the data that restrict the user to a single perspective. When zoomed out, local trends and anomalies become suppressed and lost; when zoomed in, spatial awareness and comparison between regions become limited. The probe-based interaction model integrates coordinated visualizations within individual probe interfaces, which depict the local data in user-defined regions-of-interest. It is especially useful when dealing with complex simulations or analyses where behavior in various localities differs from other localities and from the system as a whole. The technique has been incorporated into a number of geospatial simulations and visualization tools. In each of these applications, and in general, probe-based interaction enhances spatial awareness, improves inspection and comparison capabilities, expands the range of scopes, and facilitates collaboration among multiple users. The great freedom afforded to users in defining regions-of-interest can cause modifiable areal unit problems to affect the reliability of analyses without the user’s knowledge, leading to misleading results. However, by automatically alerting the user to these potential issues, and providing them tools to help adjust their selections, these unforeseen problems can be revealed, and even corrected

ITR/IM: Enabling the Creation and Use of GeoGrids for Next Generation Geospatial Information

The objective of this project is to advance science in information management, focusing in particular on geospatial information. It addresses the development of concepts, algorithms, and system architectures to enable users on a grid to query, analyze, and contribute to multivariate, quality-aware geospatial information. The approach consists of three complementary research areas: (1) establishing a statistical framework for assessing geospatial data quality; (2) developing uncertainty-based query processing capabilities; and (3) supporting the development of space- and accuracy-aware adaptive systems for geospatial datasets. The results of this project will support the extension of the concept of the computational grid to facilitate ubiquitous access, interaction, and contributions of quality-aware next generation geospatial information. By developing novel query processes as well as quality and similarity metrics the project aims to enable the integration and use of large collections of disperse information of varying quality and accuracy. This supports the evolution of a novel geocomputational paradigm, moving away from current standards-driven approaches to an inclusive, adaptive system, with example potential applications in mobile computing, bioinformatics, and geographic information systems. This experimental research is linked to educational activities in three different academic programs among the three participating sites. The outreach activities of this project include collaboration with U.S. federal agencies involved in geospatial data collection, an international partner (Brazil\u27s National Institute for Space Research), and the organization of a 2-day workshop with the participation of U.S. and international experts

Global-Scale Resource Survey and Performance Monitoring of Public OGC Web Map Services

One of the most widely-implemented service standards provided by the Open Geospatial Consortium (OGC) to the user community is the Web Map Service (WMS). WMS is widely employed globally, but there is limited knowledge of the global distribution, adoption status or the service quality of these online WMS resources. To fill this void, we investigated global WMSs resources and performed distributed performance monitoring of these services. This paper explicates a distributed monitoring framework that was used to monitor 46,296 WMSs continuously for over one year and a crawling method to discover these WMSs. We analyzed server locations, provider types, themes, the spatiotemporal coverage of map layers and the service versions for 41,703 valid WMSs. Furthermore, we appraised the stability and performance of basic operations for 1210 selected WMSs (i.e., GetCapabilities and GetMap). We discuss the major reasons for request errors and performance issues, as well as the relationship between service response times and the spatiotemporal distribution of client monitoring sites. This paper will help service providers, end users and developers of standards to grasp the status of global WMS resources, as well as to understand the adoption status of OGC standards. The conclusions drawn in this paper can benefit geospatial resource discovery, service performance evaluation and guide service performance improvements.Comment: 24 pages; 15 figure

Accuracy of Unmanned Aerial System (Drone) Height Measurements

Vertical height estimates of earth surface features using an Unmanned Aerial System (UAS) are important in natural resource management quantitative assessments. An important research question concerns both the accuracy and precision of vertical height estimates acquired with a UAS and to determine if it is necessary to land a UAS between individual height measurements or if GPS derived height versus barometric pressure derived height while using a DJI Phantom 3 would affect height accuracy and precision. To examine this question, height along a telescopic height pole on the campus of Stephen F. Austin State University (SFASU) were estimated at 2, 5, 10 and 15 meters above ground using a DJI Phantom 3 UAS. The DJI Phantom 3 UAS (i.e., drone) was flown up and down the telescopic height pole to estimate height at the 2, 5, 10 and 15 meter locations using four different user controlled flight modes with a total of 30 observations per flight mode. Flight mode configurations consisted of having GPS estimate height while landing the drone between flights, non-GPS mode to estimate height via barometric pressure while landing the drone between flights, flying continuously up and down the height pole while estimating height with GPS on, and flying continuously up and down the height pole in non-GPS mode to estimate height via barometric pressure. A total of 480 height measurements were recorded (30 measurements per height interval per all four flight mode combinations). Standard deviation results indicated that height measurements taken with the drone were less precise when landing was not reset between measurements. Root mean square error (RMSE) analysis indicated that having the landing reset without GPS on achieved the highest accuracy of all measurements taken. An ANOVA conducted on the absolute errors reconfirmed that having the landing reset before each height measurement using the drone achieved higher accuracy compared to flying the drone continuously. This indicates the practical application of height measurement of the DJI Phantom 3 UAS and the importance of resetting the UAS before each height measurement