HPDGIS 2010 workshop report

The ACM SIGSPATIAL HPDGIS 2011 workshop was held in Chicago, Illinois, USA on November 1, 2011 in conjunction with the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information System, and was a great success. High performance computing and distributed systems have become prominent elements in the landscape of communication, computing, and information technologies due to the increasingly computationally and data intensive nature of geospatial problems in numerous fields and significant requirements for service-oriented computing and collaborative problem solving. Efficient handling of massive spatial databases, shared and role-based access to distributed data, and high-end computing services are fundamental to the real-time and near-real-time responses required by many GIS and associated decision support applications. The second international ACM SIGSPATIAL HPDGIS workshop was hence designed to bring together researchers and practitioners to map out the fundamental research areas centered on advances in high performance computing, distributed systems, and their applications to Geographic Information Systems (GIS) and spatial analysis. The primary objective of the workshop series is to provide an overarching forum in which participants discuss the state-of- the-art, share research progress and activities, and establish future directions for research and education in HPDGIS.

This chapter examines several typical statements on the role of spatial analysis in geographical information systems (GIS). Spatial analysis will be applied to an ever increasing number of application areas. GIS data manipulation tools will become ever more sophisticated and easier to use. They are already today being included in office software packages such as spreadsheets. Spatial data analysis requires a highly flexible, interactive computing environment which seems to imply relatively tight coupling of the data analysis function with the GIS, and, particularly, with advanced visualisation facilities. A concept that has been developed by Openshaw and his colleagues is that of GI Sable statistics. By this they mean analytical and other approaches that are suited to a world in which computer power, very large data sets, and the availability of GIS should be taken for granted. The chapter concludes that spatial analysis can be defined but that it can refer to several quite distinct approaches to knowledge creation.

One of the hardest terms for students new to geographic information systems to understand is the meaning and application of Aspect. When taking one’s first steps in spatial analysis using data in the form of rasters, the first three things new users are called to learn and use are exporting a digital elevation model, the Slope (land incline) and finally the Aspect (orientation of a slope). While the first two are quite straightforward and easily comprehended even from newcomers to spatial analysis in geographic information systems, Aspect continues throughout the learning process to be difficult as a function with one out of three new students not able to decipher it. This paper attempts to give a simpler definition to Aspect including its analytical significance in geographic information systems.

Geographic information systems (GIS) analysis has not been widely used in underdeveloped countries to ensure that vulnerable populations have accessibility to primary health-care services. This study applied GIS methods to analyse the spatial accessibility to urban primary-care centres of the population in Kermanshah city, Islamic Republic of Iran, by age and sex groups. In a descriptive-analytical study over 3 time periods, network analysis, mean centre and standard distance methods were applied using ArcGIS 9.3. The analysis was based on a standard radius of 750 m distance from health centres, walking speed of 1 m/s and desired access time to health centres of 12.5 mins. The proportion of the population with inadequate geographical access to health centres rose from 47.3% in 1997 to 58.4% in 2012. The mean centre and standard distance mapping showed that the spatial distribution of health centres in Kermanshah needed to be adjusted to changes in population distribution.

In the present era, achieving sustainability requires the development of planning strategies to develop a safer urban infrastructure. This study examines the realistic aspects of cyclist safety by analysing cyclists’ fields of view, using Geographic Information Systems (GIS) and spatial data analysis. The research introduces novel geoprocessing tools-based GIS techniques that mathematically simulate cyclists’ angles of view and the distances to nearby environmental features. It provides precise insights into some potential hazards and infrastructure challenges encountered while cycling. This research focuses on managing and analysing the data collected, utilising OpenStreetMap (OSM) as vector-based supporting data. It integrates cyclists’ behavioural data with the urban environmental features encountered, such as intersections, road design, and traffic controls. The analysis is categorised into specific classes to evaluate the impacts of these aspects of the environment on cyclists’ behaviours. The current investigation highlights the importance of integrating the objective environmental elements surrounding the route with subjective perceptions and then determining the influence of these environmental elements on cyclists’ behaviours. Unlike previous studies that ignore cyclists’ visual perspectives in the context of real-world data, this work integrates objective GIS data with cyclists’ field of view-based modelling to identify high-risk areas and highlight the need for enhanced safety measures. The proposed approach equips urban planners and designers with data-informed strategies for creating safer cycling infrastructure, fostering sustainable mobility, and mitigating urban congestion.

Flooding is an increasingly pervasive global challenge exacerbated by climate change, rapid urbanization, and deforestation. In the Yeh Ho Watershed of Bali, Indonesia, recurrent floods have led to severe environmental, economic, and social consequences, highlighting the urgency for effective flood risk management. This study aims to assess flood hazards within the Yeh Ho Watershed using Geographic Information Systems (GIS) and spatial data analysis. By integrating morphometric analysis, hydrological data, and land-use characteristics, the research provides a detailed flood hazard map to identify flood-prone areas and the underlying factors contributing to flood risks. The research uses drone imagery, GIS tools, and field surveys to create a detailed flood hazard map for the region. The Yeh Ho Watershed, covering 172.943 km², is characterized by diverse soil types, varying topography, and fluctuating rainfall patterns. Using multiple spatial layers, including land use, slope, soil type, and rainfall, the study generates a Flood Hazard Index (FHI) to identify flood-prone zones. The results show that 69% of the watershed is at moderate risk of flooding, with 25% categorized as low risk and 6% at high risk. Field observations confirm the accuracy of the flood hazard map, supporting its use for flood risk assessment and the development of mitigation strategies. This research provides valuable insights for sustainable flood management in Bali, offering a comprehensive framework to address current and future flood risks

The dramatic loss of Louisiana's coastal wetlands and barrier shorelines is well recognized by government agencies, industries, universities, and the public. Between 1932 and 1990, the deltaic plain of the Mississippi River lost over 680,000 acres of land due to a complex suite of causes. Controversy and debate continues as to the causes of coastal land loss in Louisiana. Estimates of the human contribution of man to the land loss problem ranges between 10 percent and 90 percent (Britsch and Kemp, 1990; Penland et al., 1990, Penland et al., 1992; Turner, 1997). Several government agencies and industries have been targeted as the primary agent of coastal land loss including the U.S. Army Corps of Engineers (USACE) and the oil and gas industry. The role of natural processes and the multiple causality of the coastal land loss problem often have been overlooked (Boesch et al., 1994). In an effort to further our understanding and knowledge of the coastal land loss problem in Louisiana, the Gas Research Institute (GRI) sponsored a research project through the Argonne National Laboratory (ANL) entitled Natural and Human Causes of Coastal Land Loss in in cooperation with the U.S. Geological Survey (USGS). The study team consisted of scientists from GRI, ANL, Louisiana State University (LSU), University of New Orleans (UNO), USGS, USACE, and the Louisiana Universities Marine Consortium (LUMCON). This study focused on three major land loss research tasks: 1.) Geologic Processes, 2.) Vegetative processes, and 3.) Spatial Geographical Information System (GIS) Analysis. Through these research tasks, the objectives of this study are to quantify and rank the causes of coastal land loss within the Mississippi River delta plain in southeastern Louisiana. This study took advantage of continuing research by the USGS in framework geology and subsidence processes, and the USACE in GIS analysis, framework geology, and subsidence processes (Dunbar et al., 1990, Dunbar et al., 1992, Britsch and Dunbar, 1993; Williams et al., 1993). The geological processes task focused on the Holocene evolution of the Mississippi River delta plain in an effort to identify the regional geological controls on coastal land loss over the last 18,000 years. The vegetative processes task conducted field investigations into the role of salt-water intrusion and soil inundation in plant dieback. The GIS analysis task focused on quantifying the geomorphic forms and processes of coastal land loss using the USACE coastal land loss database. In this report, the results of the GIS geomorphic classification of coastal land loss are presented.

Remote Sensing, Geospatial Technologies and Coastal Ecosystems.- Remote Sensing, Geospatial Technologies and Coastal Ecosystems.- Conceptual and Technical Issues.- Sensors and Techniques for Observing Coastal Ecosystems.- Geographic Information Systems and Spatial Analysis for Coastal Ecosystem Research and Management.- Fuzzy Approach for Integrated Coastal Zone Management.- Spatial Data Infrastructures for Coastal Environments.- Remote Sensing of Coastal Waters.- Airborne Remote Sensing of Chlorophyll in Chesapeake Bay, USA.- Bio-Optical Characteristics and Remote Sensing in the Mid Chesapeake Bay Through Integration of Observations and Radiative Transfer Closure.- Mapping Submerged Aquatic Vegetation and Benthic Habitats.- High-Resolution Ocean Color Remote Sensing of Coral Reefs and Associated Benthic Habitats.- An Integrated Approach to Benthic Habitat Mapping Using Remote Sensing and GIS: An Example from the Hawaiian Islands.- Assessment of the Abundance of Submersed Aquatic Vegetation (SAV) Communities in the Chesapeake Bay and its Use in SAV Management.- Distribution and Spatial Change of Hudson River Estuary Submerged Aquatic Vegetation: Implications for Coastal Management and Natural Resource Protection.- Mapping Marine Macrophytes along the Atlantic Coast of Tierra Del Fuego (Argentina) by Remote Sensing.- Shoreline Change, Coastal Wetland and Watershed Characterization.- Shoreline Mapping and Coastal Change Studies Using Remote Sensing Imagery and LIDAR Data.- Remote Sensing of Coastal Mangrove Forest.- Remote Sensing Support for Tidal Wetland Vegetation Research and Management.- Assessment of Coastal-Vegetation Habitats Using Airborne Laser Remote Sensing.- Measuring Habitat Changes in Barrier Island Marshes: An Example from Southeastern North Carolina, USA.- Mapping Fire Scars and Marsh Recovery with Remote Sensing Data.- Response of Reed Mudflats in the Caspian Coastal Zone to Sea Level Fluctuations.- Integrating Satellite Imagery and Geospatial Technologies for Coastal Landscape Pattern Characterization.- Integrated Coastal Ecosystem Assessment.- Remote Sensing and Spatial Analysis of Watershed and Estuarine Processes for Conservation Planning in Elkhorn Slough, Monterey County, California.- Runoff Water Quality, Landuse and Environmental Impacts on the Bellairs Fringing Reef, Barbados.

Introduction House fires result in devastating injuries that are costly to individuals and their communities. Low socioeconomic communities experience a disproportionate share of house fires. We noticed an increasing trend in admissions related to house fires at our burn center. Applying Geographic information system (GIS) and spatial analysis, we examined the relationship between residential fires and socioeconomic variables included in well-established vulnerability indices, the area deprivation index (ADI) and social vulnerability index (SVI). Methods This was a retrospective cohort study. Addresses of house fires occurring in our state and resulting in admissions to our burn center were obtained from our burn registry. Socioeconomic and built environment datasets were collected from the 2020 Census Bureau data and transformed into quartiles. The residential addresses of fires were geocoded and spatially merged at the census tract level with the collected Census data. Spatial binary logistic regression models were used to estimate the association between social vulnerability factors and multiple serious house fires. Distance to the burn center was included as a covariate. Results The ADI was more closely associated with residential fires than the SVI. Separate logistic regression models for each predictor suggest that most social vulnerability factors included in ADI and SVI were associated with multiple residential fires: family poverty, unemployment, low education, household income, single parent ratio, house values, Black resident ratio, Hispanic resident ratio, monthly gross rent, no vehicle ratio, home ownership, and overcrowded homes. A spatial multivariable logistic regression model showed that the odds of experiencing multiple serious residential fires were higher in the 4th quartiles of the ADI (higher deprivation; OR = 5.9), the Black resident ratio (OR = 4.9), and the mobile home ratio (OR 2.5) compared to the 1st quartiles (p < 0.05). Conclusions Serious house fires are associated with increasing social disparities. Our results suggest that identifying census tracts with higher ADI, Black resident ratios, and mobile home ratios can improve focused multi-stakeholder community interventions in our state. Further studies are warranted to build a more precise model for house fire prevention. Applicability of Research to Practice GIS and spatial analysis can be used to explore the relationship between socioeconomic and physical environment variables and serious housefires. This knowledge could be used to inform a community intervention to decrease these deadly and expensive fires. Funding for the Study Study was partially funded by Injury Prevention Center

The method based on original metric called Hydromorphological Index for Rivers (HIR) was developed in 2017 for the purpose of the monitoring of the hydromorphological status of flowing waters in Poland. It fulfils the requirements of the EU Water Framework Directive (WFD). It allows the assessment of both lowland rivers as well as mid-altitude and highland streams. The proposed system can be used to assess the natural and heavily modified rivers as well as artificial channels. The basis of the proposed system is a field survey, which is supplemented by the analysis of Geographic Information Systems (GIS) data and remote sensing materials. The analysis of the GIS data and remote sensing materials already enable to estimate preliminary classification of the hydromorphological status of the non-surveyed water bodies. On the basis of the field survey, the principal HIR value can be estimated for the considered river site and comparing with the reference conditions, the hydromorphological quality status in the five-class system can be calculated. The properly selected, representative survey sites (one or more depending on the heterogeneity of the environment), enable the classification and evaluation of entire surface water bodies in the framework of the national environmental monitoring. The GIS component of the HIR proved to be useful in verifying the determination of heavily modified water bodies and in assessing the needs of river restoration. It was also applied in the development of the National river restoration program for predicting the impact of the proposed restoration measure on the state of hydromorphology.

This chapter reviews how geographic information systems (GIS) and spatial analysis are used in the substance use field to enhance community practice and understand changes in substance-related policies. Moving to two specific examples in social work, this chapter describes how GIS is used to map substance use environments and spatial analysis to understand how those environments affect social problems and social work clients. We conclude with recommendations for social work education, research, and practice concerning how to integrate these skills and concepts across all levels of our profession. In particular, we propose that both GIS and spatial analysis are important, underutilized skills that could move our field forward more quickly if we were to better incorporate these skills.

Geographic Information Systems (GIS) and spatiotemporal data analysis play a key role in modern agriculture by enabling farmers to make evidence-based decisions.These technologies integrate meteorological data, satellite imagery, and local sensor measurements to provide precise and localized information for planning and executing agricultural operations.This contribution introduces the info4agro.complatform, which helps farmers implement decision-making workflows by providing actionable insights and tools to support key agricultural activities.Through real-world use cases, the contribution demonstrates how this platform enables efficient decision-making, enhances sustainability, and improves productivity.

This paper investigates the possibility of applying light detection and ranging (LiDAR) point clouds and geographic information system (GIS) analyses for land use and land cover (LULC) change detection, mainly with a view to monitoring uncontrolled forest succession occurring on postagricultural lands. The research was conducted in a part of the administrative district of Milicz (in the central-west area of Poland). The areas of interest were parcels in which agricultural use has been abandoned and forest succession processes have progressed. The airborne laser scanning (ALS) data (acquired in 2007, 2012, and 2015) revealed detailed changes in land cover as a result of the progression in the forest succession process. Using the ALS data, the LULC changes and the progress of secondary forest succession are shown, and the vegetation parameters (LiDAR metrics) are presented.

This article identifies marginal land technically available for the production of energy crops in China, compares three models of yield prediction forMiscanthus × giganteus,Panicum virgatumL.(switchgrass), andJatropha, and estimates their spatially specific yields and technical potential for 2017. Geographic Information System (GIS) analysis of land use maps estimated that 185 Mha of marginal land was technically available for energy crops in China without using areas currently used for food production. Modeled yields were projected forMiscanthus × giganteus, a GIS‐based Environmental Policy Integrated Climate model for switchgrass and Global Agro‐Ecological Zone model forJatropha. GIS analysis and MiscanFor estimated more than 120 Mha marginal land was technically available forMiscanthuswith a total potential of 1,761 dry weight metric million tonne (DW Mt)/year. A total of 284 DW Mt/year of switchgrass could be obtained from 30 Mha marginal land, with an average yield of 9.5 DW t ha−1 year−1. More than 35 Mha marginal land was technically available forJatropha, delivering 9.7 Mt/year ofJatrophaseed. The total technical potential from available marginal land was calculated as 31.7 EJ/year forMiscanthus, 5.1 EJ/year for switchgrass, and 0.13 EJ/year forJatropha. A total technical bioenergy potential of 34.4 EJ/year was calculated by identifying best suited crop for each 1 km2grid cell based on the highest energy value among the three crops. The results indicate that the technical potential per hectare ofJatrophais unable to compete with that of the other two crops in each grid cell. This modeling study provides planners with spatial overviews that demonstrate the potential of these crops and where biomass production could be potentially distributed in China which needs field trials to test model assumptions and build experience necessary to translate into practicality.

For decades, Lawrence Livermore National Laboratory (LLNL) has been engaged in significant research, development, and support for software to enable scientific computing and, particularly, the use of high performance computing (HPC) in the NNSA mission space. In particular, the move in the mid-1990’s to simulation as a leading component of stockpile stewardship through the ASCI and the successor ASC programs, as well as the need for reliable data acquisition and control software for the National Ignition Facility, have been important drivers in building expertise in production-quality software development at LLNL. LLNL has also been a leader in the DOE SciDAC FASTMath Institute and the DOE Exascale Computing Project (ECP), both of which have striven to make scientific computing software – in particular, the enabling technologies underpinning simulation capabilities – more widely adopted and sustainable. As such, we believe that our experience can inform the broader goal of software stewardship for scientific and high-performance computing. LLNL strongly supports the formation of a new DOE ASCR program element in software stewardship and sustainment. Historically, DOE ASCR has funded applied mathematics and computer science research that has led to the development of important new capabilities and algorithms that are expressed as artifacts in research software. Such frameworks, libraries, and tools have seldom been directly funded to address the important issues of code maintenance, documentation, robustness, and community building. Software engineering and support have typically been done on the side in support of the ASCR-driven research products. DOE funding priorities have been slow to recognize that good software engineering, the kind that ensures research investments have more adoption and longevity, requires significant resources. Based upon our experiences, we have prepared this response to highlight the concerns and issues we believe to be important as DOE ASCR considers its role in scientific software stewardship. We believe that role is important and will require a significant investment of new funding to legitimately support the technologies past and future DOE ASCR investments have and will produce to facilitate their uptake and adoption in the broader scientific computing community. Following a summary of our involvement in scientific software development, the remainder our response is organized around the nine topics specifically identified in the RFI.