Economic assessment of the use value of geospatial information

USGS Publications Warehouse

Bernknopf, Richard L.; Shapiro, Carl D.

2015-01-01

Geospatial data inform decision makers. An economic model that involves application of spatial and temporal scientific, technical, and economic data in decision making is described. The value of information (VOI) contained in geospatial data is the difference between the net benefits (in present value terms) of a decision with and without the information. A range of technologies is used to collect and distribute geospatial data. These technical activities are linked to examples that show how the data can be applied in decision making, which is a cultural activity. The economic model for assessing the VOI in geospatial data for decision making is applied to three examples: (1) a retrospective model about environmental regulation of agrochemicals; (2) a prospective model about the impact and mitigation of earthquakes in urban areas; and (3) a prospective model about developing private–public geospatial information for an ecosystem services market. Each example demonstrates the potential value of geospatial information in a decision with uncertain information.

GSKY: A scalable distributed geospatial data server on the cloud

NASA Astrophysics Data System (ADS)

Rozas Larraondo, Pablo; Pringle, Sean; Antony, Joseph; Evans, Ben

2017-04-01

Earth systems, environmental and geophysical datasets are an extremely valuable sources of information about the state and evolution of the Earth. Being able to combine information coming from different geospatial collections is in increasing demand by the scientific community, and requires managing and manipulating data with different formats and performing operations such as map reprojections, resampling and other transformations. Due to the large data volume inherent in these collections, storing multiple copies of them is unfeasible and so such data manipulation must be performed on-the-fly using efficient, high performance techniques. Ideally this should be performed using a trusted data service and common system libraries to ensure wide use and reproducibility. Recent developments in distributed computing based on dynamic access to significant cloud infrastructure opens the door for such new ways of processing geospatial data on demand. The National Computational Infrastructure (NCI), hosted at the Australian National University (ANU), has over 10 Petabytes of nationally significant research data collections. Some of these collections, which comprise a variety of observed and modelled geospatial data, are now made available via a highly distributed geospatial data server, called GSKY (pronounced [jee-skee]). GSKY supports on demand processing of large geospatial data products such as satellite earth observation data as well as numerical weather products, allowing interactive exploration and analysis of the data. It dynamically and efficiently distributes the required computations among cloud nodes providing a scalable analysis framework that can adapt to serve large number of concurrent users. Typical geospatial workflows handling different file formats and data types, or blending data in different coordinate projections and spatio-temporal resolutions, is handled transparently by GSKY. This is achieved by decoupling the data ingestion and indexing process as an independent service. An indexing service crawls data collections either locally or remotely by extracting, storing and indexing all spatio-temporal metadata associated with each individual record. GSKY provides the user with the ability of specifying how ingested data should be aggregated, transformed and presented. It presents an OGC standards-compliant interface, allowing ready accessibility for users of the data via Web Map Services (WMS), Web Processing Services (WPS) or raw data arrays using Web Coverage Services (WCS). The presentation will show some cases where we have used this new capability to provide a significant improvement over previous approaches.

Estimating Prediction Uncertainty from Geographical Information System Raster Processing: A User's Manual for the Raster Error Propagation Tool (REPTool)

USGS Publications Warehouse

Gurdak, Jason J.; Qi, Sharon L.; Geisler, Michael L.

2009-01-01

The U.S. Geological Survey Raster Error Propagation Tool (REPTool) is a custom tool for use with the Environmental System Research Institute (ESRI) ArcGIS Desktop application to estimate error propagation and prediction uncertainty in raster processing operations and geospatial modeling. REPTool is designed to introduce concepts of error and uncertainty in geospatial data and modeling and provide users of ArcGIS Desktop a geoprocessing tool and methodology to consider how error affects geospatial model output. Similar to other geoprocessing tools available in ArcGIS Desktop, REPTool can be run from a dialog window, from the ArcMap command line, or from a Python script. REPTool consists of public-domain, Python-based packages that implement Latin Hypercube Sampling within a probabilistic framework to track error propagation in geospatial models and quantitatively estimate the uncertainty of the model output. Users may specify error for each input raster or model coefficient represented in the geospatial model. The error for the input rasters may be specified as either spatially invariant or spatially variable across the spatial domain. Users may specify model output as a distribution of uncertainty for each raster cell. REPTool uses the Relative Variance Contribution method to quantify the relative error contribution from the two primary components in the geospatial model - errors in the model input data and coefficients of the model variables. REPTool is appropriate for many types of geospatial processing operations, modeling applications, and related research questions, including applications that consider spatially invariant or spatially variable error in geospatial data.

An updated geospatial liquefaction model for global application

USGS Publications Warehouse

Zhu, Jing; Baise, Laurie G.; Thompson, Eric M.

2017-01-01

We present an updated geospatial approach to estimation of earthquake-induced liquefaction from globally available geospatial proxies. Our previous iteration of the geospatial liquefaction model was based on mapped liquefaction surface effects from four earthquakes in Christchurch, New Zealand, and Kobe, Japan, paired with geospatial explanatory variables including slope-derived VS30, compound topographic index, and magnitude-adjusted peak ground acceleration from ShakeMap. The updated geospatial liquefaction model presented herein improves the performance and the generality of the model. The updates include (1) expanding the liquefaction database to 27 earthquake events across 6 countries, (2) addressing the sampling of nonliquefaction for incomplete liquefaction inventories, (3) testing interaction effects between explanatory variables, and (4) overall improving model performance. While we test 14 geospatial proxies for soil density and soil saturation, the most promising geospatial parameters are slope-derived VS30, modeled water table depth, distance to coast, distance to river, distance to closest water body, and precipitation. We found that peak ground velocity (PGV) performs better than peak ground acceleration (PGA) as the shaking intensity parameter. We present two models which offer improved performance over prior models. We evaluate model performance using the area under the curve under the Receiver Operating Characteristic (ROC) curve (AUC) and the Brier score. The best-performing model in a coastal setting uses distance to coast but is problematic for regions away from the coast. The second best model, using PGV, VS30, water table depth, distance to closest water body, and precipitation, performs better in noncoastal regions and thus is the model we recommend for global implementation.

Grid computing enhances standards-compatible geospatial catalogue service

NASA Astrophysics Data System (ADS)

Chen, Aijun; Di, Liping; Bai, Yuqi; Wei, Yaxing; Liu, Yang

2010-04-01

A catalogue service facilitates sharing, discovery, retrieval, management of, and access to large volumes of distributed geospatial resources, for example data, services, applications, and their replicas on the Internet. Grid computing provides an infrastructure for effective use of computing, storage, and other resources available online. The Open Geospatial Consortium has proposed a catalogue service specification and a series of profiles for promoting the interoperability of geospatial resources. By referring to the profile of the catalogue service for Web, an innovative information model of a catalogue service is proposed to offer Grid-enabled registry, management, retrieval of and access to geospatial resources and their replicas. This information model extends the e-business registry information model by adopting several geospatial data and service metadata standards—the International Organization for Standardization (ISO)'s 19115/19119 standards and the US Federal Geographic Data Committee (FGDC) and US National Aeronautics and Space Administration (NASA) metadata standards for describing and indexing geospatial resources. In order to select the optimal geospatial resources and their replicas managed by the Grid, the Grid data management service and information service from the Globus Toolkits are closely integrated with the extended catalogue information model. Based on this new model, a catalogue service is implemented first as a Web service. Then, the catalogue service is further developed as a Grid service conforming to Grid service specifications. The catalogue service can be deployed in both the Web and Grid environments and accessed by standard Web services or authorized Grid services, respectively. The catalogue service has been implemented at the George Mason University/Center for Spatial Information Science and Systems (GMU/CSISS), managing more than 17 TB of geospatial data and geospatial Grid services. This service makes it easy to share and interoperate geospatial resources by using Grid technology and extends Grid technology into the geoscience communities.

Social Moderation and Dynamic Elements in Crowdsourced Geospatial Data: A Report on Quality Assessment, Dynamic Extensions and Mobile Device Engagement in the George Mason University Geocrowdsourcing Testbed

DTIC Science & Technology

2015-11-01

GMU) Associate Professor Dieter Pfoser describes an explosion of user generated content (UGC) available over the Internet (Pfoser 2011, Crooks et al...Crowdsourced and User - Generated Geospatial Data,” Annual (Fairfax, VA: George Mason University, November 29, 2012), http://www.dtic.mil/dtic/tr/fulltext/u2...area include GPS-enabled geosocial and 34 Dieter Pfoser, “On User - Generated

Distributed geospatial model sharing based on open interoperability standards

USGS Publications Warehouse

Feng, Min; Liu, Shuguang; Euliss, Ned H.; Fang, Yin

2009-01-01

Numerous geospatial computational models have been developed based on sound principles and published in journals or presented in conferences. However modelers have made few advances in the development of computable modules that facilitate sharing during model development or utilization. Constraints hampering development of model sharing technology includes limitations on computing, storage, and connectivity; traditional stand-alone and closed network systems cannot fully support sharing and integrating geospatial models. To address this need, we have identified methods for sharing geospatial computational models using Service Oriented Architecture (SOA) techniques and open geospatial standards. The service-oriented model sharing service is accessible using any tools or systems compliant with open geospatial standards, making it possible to utilize vast scientific resources available from around the world to solve highly sophisticated application problems. The methods also allow model services to be empowered by diverse computational devices and technologies, such as portable devices and GRID computing infrastructures. Based on the generic and abstract operations and data structures required for Web Processing Service (WPS) standards, we developed an interactive interface for model sharing to help reduce interoperability problems for model use. Geospatial computational models are shared on model services, where the computational processes provided by models can be accessed through tools and systems compliant with WPS. We developed a platform to help modelers publish individual models in a simplified and efficient way. Finally, we illustrate our technique using wetland hydrological models we developed for the prairie pothole region of North America.

Geospatial Data Stream Processing in Python Using FOSS4G Components

NASA Astrophysics Data System (ADS)

McFerren, G.; van Zyl, T.

2016-06-01

One viewpoint of current and future IT systems holds that there is an increase in the scale and velocity at which data are acquired and analysed from heterogeneous, dynamic sources. In the earth observation and geoinformatics domains, this process is driven by the increase in number and types of devices that report location and the proliferation of assorted sensors, from satellite constellations to oceanic buoy arrays. Much of these data will be encountered as self-contained messages on data streams - continuous, infinite flows of data. Spatial analytics over data streams concerns the search for spatial and spatio-temporal relationships within and amongst data "on the move". In spatial databases, queries can assess a store of data to unpack spatial relationships; this is not the case on streams, where spatial relationships need to be established with the incomplete data available. Methods for spatially-based indexing, filtering, joining and transforming of streaming data need to be established and implemented in software components. This article describes the usage patterns and performance metrics of a number of well known FOSS4G Python software libraries within the data stream processing paradigm. In particular, we consider the RTree library for spatial indexing, the Shapely library for geometric processing and transformation and the PyProj library for projection and geodesic calculations over streams of geospatial data. We introduce a message oriented Python-based geospatial data streaming framework called Swordfish, which provides data stream processing primitives, functions, transports and a common data model for describing messages, based on the Open Geospatial Consortium Observations and Measurements (O&M) and Unidata Common Data Model (CDM) standards. We illustrate how the geospatial software components are integrated with the Swordfish framework. Furthermore, we describe the tight temporal constraints under which geospatial functionality can be invoked when processing high velocity, potentially infinite geospatial data streams. The article discusses the performance of these libraries under simulated streaming loads (size, complexity and volume of messages) and how they can be deployed and utilised with Swordfish under real load scenarios, illustrated by a set of Vessel Automatic Identification System (AIS) use cases. We conclude that the described software libraries are able to perform adequately under geospatial data stream processing scenarios - many real application use cases will be handled sufficiently by the software.

Increased Hydrologic Connectivity: Consequences of Reduced Water Storage Capacity in the Delmarva Peninsula (U.S.)

NASA Astrophysics Data System (ADS)

Mclaughlin, D. L.; Jones, C. N.; Evenson, G. R.; Golden, H. E.; Lane, C.; Alexander, L. C.; Lang, M.

2017-12-01

Combined geospatial and modeling approaches are required to fully enumerate wetland hydrologic connectivity and downstream effects. Here, we utilized both geospatial analysis and hydrologic modeling to explore drivers and consequences of modified surface water connectivity in the Delmarva Peninsula, with particular focus on increased connectivity via pervasive wetland ditching. Our geospatial analysis quantified both historical and contemporary wetland storage capacity across the region, and suggests that over 70% of historical storage capacity has been lost due to this ditching. Building upon this analysis, we applied a catchment-scale model to simulate implications of reduced storage capacity on catchment-scale hydrology. In short, increased connectivity (and concomitantly reduced wetland water storage capacity) decreases catchment inundation extent and spatial heterogeneity, shortens cumulative residence times, and increases downstream flow variation with evident effects on peak and baseflow dynamics. As such, alterations in connectivity have implications for hydrologically mediated functions in catchments (e.g., nutrient removal) and downstream systems (e.g., maintenance of flow for aquatic habitat). Our work elucidates such consequences in Delmarva Peninsula while also providing new tools for broad application to target wetland restoration and conservation. Views expressed are those of the authors and do not necessarily reflect policies of the US EPA or US FWS.

Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer.

PubMed

Ghandehari, Masoud; Emig, Thorsten; Aghamohamadnia, Milad

2018-02-02

Despite decades of research seeking to derive the urban energy budget, the dynamics of thermal exchange in the densely constructed environment is not yet well understood. Using New York City as a study site, we present a novel hybrid experimental-computational approach for a better understanding of the radiative heat transfer in complex urban environments. The aim of this work is to contribute to the calculation of the urban energy budget, particularly the stored energy. We will focus our attention on surface thermal radiation. Improved understanding of urban thermodynamics incorporating the interaction of various bodies, particularly in high rise cities, will have implications on energy conservation at the building scale, and for human health and comfort at the urban scale. The platform presented is based on longwave hyperspectral imaging of nearly 100 blocks of Manhattan, in addition to a geospatial radiosity model that describes the collective radiative heat exchange between multiple buildings. Despite assumptions in surface emissivity and thermal conductivity of buildings walls, the close comparison of temperatures derived from measurements and computations is promising. Results imply that the presented geospatial thermodynamic model of urban structures can enable accurate and high resolution analysis of instantaneous urban surface temperatures.

A Geospatial Online Instruction Model

ERIC Educational Resources Information Center

Rodgers, John C., III; Owen-Nagel, Athena; Ambinakudige, Shrinidhi

2012-01-01

The objective of this study is to present a pedagogical model for teaching geospatial courses through an online format and to critique the model's effectiveness. Offering geospatial courses through an online format provides avenues to a wider student population, many of whom are not able to take traditional on-campus courses. Yet internet-based…

GeoSearcher: Location-Based Ranking of Search Engine Results.

ERIC Educational Resources Information Center

Watters, Carolyn; Amoudi, Ghada

2003-01-01

Discussion of Web queries with geospatial dimensions focuses on an algorithm that assigns location coordinates dynamically to Web sites based on the URL. Describes a prototype search system that uses the algorithm to re-rank search engine results for queries with a geospatial dimension, thus providing an alternative ranking order for search engine…

PlanetSense: A Real-time Streaming and Spatio-temporal Analytics Platform for Gathering Geo-spatial Intelligence from Open Source Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thakur, Gautam S; Bhaduri, Budhendra L; Piburn, Jesse O

Geospatial intelligence has traditionally relied on the use of archived and unvarying data for planning and exploration purposes. In consequence, the tools and methods that are architected to provide insight and generate projections only rely on such datasets. Albeit, if this approach has proven effective in several cases, such as land use identification and route mapping, it has severely restricted the ability of researchers to inculcate current information in their work. This approach is inadequate in scenarios requiring real-time information to act and to adjust in ever changing dynamic environments, such as evacuation and rescue missions. In this work, wemore » propose PlanetSense, a platform for geospatial intelligence that is built to harness the existing power of archived data and add to that, the dynamics of real-time streams, seamlessly integrated with sophisticated data mining algorithms and analytics tools for generating operational intelligence on the fly. The platform has four main components i) GeoData Cloud a data architecture for storing and managing disparate datasets; ii) Mechanism to harvest real-time streaming data; iii) Data analytics framework; iv) Presentation and visualization through web interface and RESTful services. Using two case studies, we underpin the necessity of our platform in modeling ambient population and building occupancy at scale.« less

Visualizing dynamic geosciences phenomena using an octree-based view-dependent LOD strategy within virtual globes

NASA Astrophysics Data System (ADS)

Li, Jing; Wu, Huayi; Yang, Chaowei; Wong, David W.; Xie, Jibo

2011-09-01

Geoscientists build dynamic models to simulate various natural phenomena for a better understanding of our planet. Interactive visualizations of these geoscience models and their outputs through virtual globes on the Internet can help the public understand the dynamic phenomena related to the Earth more intuitively. However, challenges arise when the volume of four-dimensional data (4D), 3D in space plus time, is huge for rendering. Datasets loaded from geographically distributed data servers require synchronization between ingesting and rendering data. Also the visualization capability of display clients varies significantly in such an online visualization environment; some may not have high-end graphic cards. To enhance the efficiency of visualizing dynamic volumetric data in virtual globes, this paper proposes a systematic framework, in which an octree-based multiresolution data structure is implemented to organize time series 3D geospatial data to be used in virtual globe environments. This framework includes a view-dependent continuous level of detail (LOD) strategy formulated as a synchronized part of the virtual globe rendering process. Through the octree-based data retrieval process, the LOD strategy enables the rendering of the 4D simulation at a consistent and acceptable frame rate. To demonstrate the capabilities of this framework, data of a simulated dust storm event are rendered in World Wind, an open source virtual globe. The rendering performances with and without the octree-based LOD strategy are compared. The experimental results show that using the proposed data structure and processing strategy significantly enhances the visualization performance when rendering dynamic geospatial phenomena in virtual globes.

Spatial representation of organic carbon and active-layer thickness of high latitude soils in CMIP5 earth system models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, Umakant; Drewniak, Beth; Jastrow, Julie D.

Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (F.SMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for redudng existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Modellntercomparison Project Phase 5 { CMIP5) ESMs with those predicted from geospatial predictions, based on observation datamore » for the state of Alaska, USA. For the geospatial modeling. we used soil profile observations {585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m-2) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors. when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primaly factors leading to observed differences were ( 1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate these factors in F.SMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks.« less

Adoption of Geospatial Systems towards evolving Sustainable Himalayan Mountain Development

NASA Astrophysics Data System (ADS)

Murthy, M. S. R.; Bajracharya, B.; Pradhan, S.; Shestra, B.; Bajracharya, R.; Shakya, K.; Wesselmann, S.; Ali, M.; Bajracharya, S.; Pradhan, S.

2014-11-01

Natural resources dependence of mountain communities, rapid social and developmental changes, disaster proneness and climate change are conceived as the critical factors regulating sustainable Himalayan mountain development. The Himalayan region posed by typical geographic settings, diverse physical and cultural diversity present a formidable challenge to collect and manage data, information and understands varied socio-ecological settings. Recent advances in earth observation, near real-time data, in-situ measurements and in combination of information and communication technology have transformed the way we collect, process, and generate information and how we use such information for societal benefits. Glacier dynamics, land cover changes, disaster risk reduction systems, food security and ecosystem conservation are a few thematic areas where geospatial information and knowledge have significantly contributed to informed decision making systems over the region. The emergence and adoption of near-real time systems, unmanned aerial vehicles (UAV), board-scale citizen science (crowd-sourcing), mobile services and mapping, and cloud computing have paved the way towards developing automated environmental monitoring systems, enhanced scientific understanding of geophysical and biophysical processes, coupled management of socio-ecological systems and community based adaptation models tailored to mountain specific environment. There are differentiated capacities among the ICIMOD regional member countries with regard to utilization of earth observation and geospatial technologies. The region can greatly benefit from a coordinated and collaborative approach to capture the opportunities offered by earth observation and geospatial technologies. The regional level data sharing, knowledge exchange, and Himalayan GEO supporting geospatial platforms, spatial data infrastructure, unique region specific satellite systems to address trans-boundary challenges would go a long way in evolving sustainable Himalayan livelihoods.

Dynamic Server-Based KML Code Generator Method for Level-of-Detail Traversal of Geospatial Data

NASA Technical Reports Server (NTRS)

Baxes, Gregory; Mixon, Brian; Linger, TIm

2013-01-01

Web-based geospatial client applications such as Google Earth and NASA World Wind must listen to data requests, access appropriate stored data, and compile a data response to the requesting client application. This process occurs repeatedly to support multiple client requests and application instances. Newer Web-based geospatial clients also provide user-interactive functionality that is dependent on fast and efficient server responses. With massively large datasets, server-client interaction can become severely impeded because the server must determine the best way to assemble data to meet the client applications request. In client applications such as Google Earth, the user interactively wanders through the data using visually guided panning and zooming actions. With these actions, the client application is continually issuing data requests to the server without knowledge of the server s data structure or extraction/assembly paradigm. A method for efficiently controlling the networked access of a Web-based geospatial browser to server-based datasets in particular, massively sized datasets has been developed. The method specifically uses the Keyhole Markup Language (KML), an Open Geospatial Consortium (OGS) standard used by Google Earth and other KML-compliant geospatial client applications. The innovation is based on establishing a dynamic cascading KML strategy that is initiated by a KML launch file provided by a data server host to a Google Earth or similar KMLcompliant geospatial client application user. Upon execution, the launch KML code issues a request for image data covering an initial geographic region. The server responds with the requested data along with subsequent dynamically generated KML code that directs the client application to make follow-on requests for higher level of detail (LOD) imagery to replace the initial imagery as the user navigates into the dataset. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics. The method yields significant improvements in userinteractive geospatial client and data server interaction and associated network bandwidth requirements. The innovation uses a C- or PHP-code-like grammar that provides a high degree of processing flexibility. A set of language lexer and parser elements is provided that offers a complete language grammar for writing and executing language directives. A script is wrapped and passed to the geospatial data server by a client application as a component of a standard KML-compliant statement. The approach provides an efficient means for a geospatial client application to request server preprocessing of data prior to client delivery. Data is structured in a quadtree format. As the user zooms into the dataset, geographic regions are subdivided into four child regions. Conversely, as the user zooms out, four child regions collapse into a single, lower-LOD region. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics.

Renewable Energy Data Explorer User Guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cox, Sarah L; Grue, Nicholas W; Tran, July

This publication provides a user guide for the Renewable Energy Data Explorer and technical potential tool within the Explorer. The Renewable Energy Data Explorer is a dynamic, web-based geospatial analysis tool that facilitates renewable energy decision-making, investment, and deployment. It brings together renewable energy resource data and other modeled or measured geographic information system (GIS) layers, including land use, weather, environmental, population density, administrative, and grid data.

GeoBrain Computational Cyber-laboratory for Earth Science Studies

NASA Astrophysics Data System (ADS)

Deng, M.; di, L.

2009-12-01

Computational approaches (e.g., computer-based data visualization, analysis and modeling) are critical for conducting increasingly data-intensive Earth science (ES) studies to understand functions and changes of the Earth system. However, currently Earth scientists, educators, and students have met two major barriers that prevent them from being effectively using computational approaches in their learning, research and application activities. The two barriers are: 1) difficulties in finding, obtaining, and using multi-source ES data; and 2) lack of analytic functions and computing resources (e.g., analysis software, computing models, and high performance computing systems) to analyze the data. Taking advantages of recent advances in cyberinfrastructure, Web service, and geospatial interoperability technologies, GeoBrain, a project funded by NASA, has developed a prototype computational cyber-laboratory to effectively remove the two barriers. The cyber-laboratory makes ES data and computational resources at large organizations in distributed locations available to and easily usable by the Earth science community through 1) enabling seamless discovery, access and retrieval of distributed data, 2) federating and enhancing data discovery with a catalogue federation service and a semantically-augmented catalogue service, 3) customizing data access and retrieval at user request with interoperable, personalized, and on-demand data access and services, 4) automating or semi-automating multi-source geospatial data integration, 5) developing a large number of analytic functions as value-added, interoperable, and dynamically chainable geospatial Web services and deploying them in high-performance computing facilities, 6) enabling the online geospatial process modeling and execution, and 7) building a user-friendly extensible web portal for users to access the cyber-laboratory resources. Users can interactively discover the needed data and perform on-demand data analysis and modeling through the web portal. The GeoBrain cyber-laboratory provides solutions to meet common needs of ES research and education, such as, distributed data access and analysis services, easy access to and use of ES data, and enhanced geoprocessing and geospatial modeling capability. It greatly facilitates ES research, education, and applications. The development of the cyber-laboratory provides insights, lessons-learned, and technology readiness to build more capable computing infrastructure for ES studies, which can meet wide-range needs of current and future generations of scientists, researchers, educators, and students for their formal or informal educational training, research projects, career development, and lifelong learning.

Geospatial Service Platform for Education and Research

NASA Astrophysics Data System (ADS)

Gong, J.; Wu, H.; Jiang, W.; Guo, W.; Zhai, X.; Yue, P.

2014-04-01

We propose to advance the scientific understanding through applications of geospatial service platforms, which can help students and researchers investigate various scientific problems in a Web-based environment with online tools and services. The platform also offers capabilities for sharing data, algorithm, and problem-solving knowledge. To fulfil this goal, the paper introduces a new course, named "Geospatial Service Platform for Education and Research", to be held in the ISPRS summer school in May 2014 at Wuhan University, China. The course will share cutting-edge achievements of a geospatial service platform with students from different countries, and train them with online tools from the platform for geospatial data processing and scientific research. The content of the course includes the basic concepts of geospatial Web services, service-oriented architecture, geoprocessing modelling and chaining, and problem-solving using geospatial services. In particular, the course will offer a geospatial service platform for handson practice. There will be three kinds of exercises in the course: geoprocessing algorithm sharing through service development, geoprocessing modelling through service chaining, and online geospatial analysis using geospatial services. Students can choose one of them, depending on their interests and background. Existing geoprocessing services from OpenRS and GeoPW will be introduced. The summer course offers two service chaining tools, GeoChaining and GeoJModelBuilder, as instances to explain specifically the method for building service chains in view of different demands. After this course, students can learn how to use online service platforms for geospatial resource sharing and problem-solving.

a Framework for AN Open Source Geospatial Certification Model

NASA Astrophysics Data System (ADS)

Khan, T. U. R.; Davis, P.; Behr, F.-J.

2016-06-01

The geospatial industry is forecasted to have an enormous growth in the forthcoming years and an extended need for well-educated workforce. Hence ongoing education and training play an important role in the professional life. Parallel, in the geospatial and IT arena as well in the political discussion and legislation Open Source solutions, open data proliferation, and the use of open standards have an increasing significance. Based on the Memorandum of Understanding between International Cartographic Association, OSGeo Foundation, and ISPRS this development led to the implementation of the ICA-OSGeo-Lab imitative with its mission "Making geospatial education and opportunities accessible to all". Discussions in this initiative and the growth and maturity of geospatial Open Source software initiated the idea to develop a framework for a worldwide applicable Open Source certification approach. Generic and geospatial certification approaches are already offered by numerous organisations, i.e., GIS Certification Institute, GeoAcademy, ASPRS, and software vendors, i. e., Esri, Oracle, and RedHat. They focus different fields of expertise and have different levels and ways of examination which are offered for a wide range of fees. The development of the certification framework presented here is based on the analysis of diverse bodies of knowledge concepts, i.e., NCGIA Core Curriculum, URISA Body Of Knowledge, USGIF Essential Body Of Knowledge, the "Geographic Information: Need to Know", currently under development, and the Geospatial Technology Competency Model (GTCM). The latter provides a US American oriented list of the knowledge, skills, and abilities required of workers in the geospatial technology industry and influenced essentially the framework of certification. In addition to the theoretical analysis of existing resources the geospatial community was integrated twofold. An online survey about the relevance of Open Source was performed and evaluated with 105 respondents worldwide. 15 interviews (face-to-face or by telephone) with experts in different countries provided additional insights into Open Source usage and certification. The findings led to the development of a certification framework of three main categories with in total eleven sub-categories, i.e., "Certified Open Source Geospatial Data Associate / Professional", "Certified Open Source Geospatial Analyst Remote Sensing & GIS", "Certified Open Source Geospatial Cartographer", "Certified Open Source Geospatial Expert", "Certified Open Source Geospatial Associate Developer / Professional Developer", "Certified Open Source Geospatial Architect". Each certification is described by pre-conditions, scope and objectives, course content, recommended software packages, target group, expected benefits, and the methods of examination. Examinations can be flanked by proofs of professional career paths and achievements which need a peer qualification evaluation. After a couple of years a recertification is required. The concept seeks the accreditation by the OSGeo Foundation (and other bodies) and international support by a group of geospatial scientific institutions to achieve wide and international acceptance for this Open Source geospatial certification model. A business case for Open Source certification and a corresponding SWOT model is examined to support the goals of the Geo-For-All initiative of the ICA-OSGeo pact.

Global polar geospatial information service retrieval based on search engine and ontology reasoning

USGS Publications Warehouse

Chen, Nengcheng; E, Dongcheng; Di, Liping; Gong, Jianya; Chen, Zeqiang

2007-01-01

In order to improve the access precision of polar geospatial information service on web, a new methodology for retrieving global spatial information services based on geospatial service search and ontology reasoning is proposed, the geospatial service search is implemented to find the coarse service from web, the ontology reasoning is designed to find the refined service from the coarse service. The proposed framework includes standardized distributed geospatial web services, a geospatial service search engine, an extended UDDI registry, and a multi-protocol geospatial information service client. Some key technologies addressed include service discovery based on search engine and service ontology modeling and reasoning in the Antarctic geospatial context. Finally, an Antarctica multi protocol OWS portal prototype based on the proposed methodology is introduced.

Bim and Gis: when Parametric Modeling Meets Geospatial Data

NASA Astrophysics Data System (ADS)

Barazzetti, L.; Banfi, F.

2017-12-01

Geospatial data have a crucial role in several projects related to infrastructures and land management. GIS software are able to perform advanced geospatial analyses, but they lack several instruments and tools for parametric modelling typically available in BIM. At the same time, BIM software designed for buildings have limited tools to handle geospatial data. As things stand at the moment, BIM and GIS could appear as complementary solutions, notwithstanding research work is currently under development to ensure a better level of interoperability, especially at the scale of the building. On the other hand, the transition from the local (building) scale to the infrastructure (where geospatial data cannot be neglected) has already demonstrated that parametric modelling integrated with geoinformation is a powerful tool to simplify and speed up some phases of the design workflow. This paper reviews such mixed approaches with both simulated and real examples, demonstrating that integration is already a reality at specific scales, which are not dominated by "pure" GIS or BIM. The paper will also demonstrate that some traditional operations carried out with GIS software are also available in parametric modelling software for BIM, such as transformation between reference systems, DEM generation, feature extraction, and geospatial queries. A real case study is illustrated and discussed to show the advantage of a combined use of both technologies. BIM and GIS integration can generate greater usage of geospatial data in the AECOO (Architecture, Engineering, Construction, Owner and Operator) industry, as well as new solutions for parametric modelling with additional geoinformation.

Assessing Embedded Geospatial Student Learning Outcomes

ERIC Educational Resources Information Center

Carr, John David

2012-01-01

Geospatial tools and technologies have become core competencies for natural resource professionals due to the monitoring, modeling, and mapping capabilities they provide. To prepare students with needed background, geospatial instructional activities were integrated across Forest Management; Natural Resources; Fisheries, Wildlife, &…

Monitoring Aircraft Motion at Airports by LIDAR

NASA Astrophysics Data System (ADS)

Toth, C.; Jozkow, G.; Koppanyi, Z.; Young, S.; Grejner-Brzezinska, D.

2016-06-01

Improving sensor performance, combined with better affordability, provides better object space observability, resulting in new applications. Remote sensing systems are primarily concerned with acquiring data of the static components of our environment, such as the topographic surface of the earth, transportation infrastructure, city models, etc. Observing the dynamic component of the object space is still rather rare in the geospatial application field; vehicle extraction and traffic flow monitoring are a few examples of using remote sensing to detect and model moving objects. Deploying a network of inexpensive LiDAR sensors along taxiways and runways can provide both geometrically and temporally rich geospatial data that aircraft body can be extracted from the point cloud, and then, based on consecutive point clouds motion parameters can be estimated. Acquiring accurate aircraft trajectory data is essential to improve aviation safety at airports. This paper reports about the initial experiences obtained by using a network of four Velodyne VLP- 16 sensors to acquire data along a runway segment.

Towards Precise Metadata-set for Discovering 3D Geospatial Models in Geo-portals

NASA Astrophysics Data System (ADS)

Zamyadi, A.; Pouliot, J.; Bédard, Y.

2013-09-01

Accessing 3D geospatial models, eventually at no cost and for unrestricted use, is certainly an important issue as they become popular among participatory communities, consultants, and officials. Various geo-portals, mainly established for 2D resources, have tried to provide access to existing 3D resources such as digital elevation model, LIDAR or classic topographic data. Describing the content of data, metadata is a key component of data discovery in geo-portals. An inventory of seven online geo-portals and commercial catalogues shows that the metadata referring to 3D information is very different from one geo-portal to another as well as for similar 3D resources in the same geo-portal. The inventory considered 971 data resources affiliated with elevation. 51% of them were from three geo-portals running at Canadian federal and municipal levels whose metadata resources did not consider 3D model by any definition. Regarding the remaining 49% which refer to 3D models, different definition of terms and metadata were found, resulting in confusion and misinterpretation. The overall assessment of these geo-portals clearly shows that the provided metadata do not integrate specific and common information about 3D geospatial models. Accordingly, the main objective of this research is to improve 3D geospatial model discovery in geo-portals by adding a specific metadata-set. Based on the knowledge and current practices on 3D modeling, and 3D data acquisition and management, a set of metadata is proposed to increase its suitability for 3D geospatial models. This metadata-set enables the definition of genuine classes, fields, and code-lists for a 3D metadata profile. The main structure of the proposal contains 21 metadata classes. These classes are classified in three packages as General and Complementary on contextual and structural information, and Availability on the transition from storage to delivery format. The proposed metadata set is compared with Canadian Geospatial Data Infrastructure (CGDI) metadata which is an implementation of North American Profile of ISO-19115. The comparison analyzes the two metadata against three simulated scenarios about discovering needed 3D geo-spatial datasets. Considering specific metadata about 3D geospatial models, the proposed metadata-set has six additional classes on geometric dimension, level of detail, geometric modeling, topology, and appearance information. In addition classes on data acquisition, preparation, and modeling, and physical availability have been specialized for 3D geospatial models.

Modeling photovoltaic diffusion: an analysis of geospatial datasets

NASA Astrophysics Data System (ADS)

Davidson, Carolyn; Drury, Easan; Lopez, Anthony; Elmore, Ryan; Margolis, Robert

2014-07-01

This study combines address-level residential photovoltaic (PV) adoption trends in California with several types of geospatial information—population demographics, housing characteristics, foreclosure rates, solar irradiance, vehicle ownership preferences, and others—to identify which subsets of geospatial information are the best predictors of historical PV adoption. Number of rooms, heating source and house age were key variables that had not been previously explored in the literature, but are consistent with the expected profile of a PV adopter. The strong relationship provided by foreclosure indicators and mortgage status have less of an intuitive connection to PV adoption, but may be highly correlated with characteristics inherent in PV adopters. Next, we explore how these predictive factors and model performance varies between different Investor Owned Utility (IOU) regions in California, and at different spatial scales. Results suggest that models trained with small subsets of geospatial information (five to eight variables) may provide similar explanatory power as models using hundreds of geospatial variables. Further, the predictive performance of models generally decreases at higher resolution, i.e., below ZIP code level since several geospatial variables with coarse native resolution become less useful for representing high resolution variations in PV adoption trends. However, for California we find that model performance improves if parameters are trained at the regional IOU level rather than the state-wide level. We also find that models trained within one IOU region are generally representative for other IOU regions in CA, suggesting that a model trained with data from one state may be applicable in another state.

THE NEVADA GEOSPATIAL DATA BROWSER

EPA Science Inventory

The Landscape Ecology Branch of the U.S. Environmental Protection Agency (Las Vegas, NV) has developed the Nevada Geospatial Data Browser, a spatial data archive to centralize and distribute the geospatial data used to create the land cover, vertebrate habitat models, and land o...

Climate Change and Future U.S. Electricity Infrastructure: the Nexus between Water Availability, Land Suitability, and Low-Carbon Technologies

NASA Astrophysics Data System (ADS)

Rice, J.; Halter, T.; Hejazi, M. I.; Jensen, E.; Liu, L.; Olson, J.; Patel, P.; Vernon, C. R.; Voisin, N.; Zuljevic, N.

2014-12-01

Integrated assessment models project the future electricity generation mix under different policy, technology, and socioeconomic scenarios, but they do not directly address site-specific factors such as interconnection costs, population density, land use restrictions, air quality, NIMBY concerns, or water availability that might affect the feasibility of achieving the technology mix. Moreover, since these factors can change over time due to climate, policy, socioeconomics, and so on, it is important to examine the dynamic feasibility of integrated assessment scenarios "on the ground." This paper explores insights from coupling an integrated assessment model (GCAM-USA) with a geospatial power plant siting model (the Capacity Expansion Regional Feasibility model, CERF) within a larger multi-model framework that includes regional climate, hydrologic, and water management modeling. GCAM-USA is a dynamic-recursive market equilibrium model simulating the impact of carbon policies on global and national markets for energy commodities and other goods; one of its outputs is the electricity generation mix and expansion at the state-level. It also simulates water demands from all sectors that are downscaled as input to the water management modeling. CERF simulates siting decisions by dynamically representing suitable areas for different generation technologies with geospatial analyses (informed by technology-specific siting criteria, such as required mean streamflow per the Clean Water Act), and then choosing siting locations to minimize interconnection costs (to electric transmission and gas pipelines). CERF results are compared across three scenarios simulated by GCAM-USA: 1) a non-mitigation scenario (RCP8.5) in which conventional fossil-fueled technologies prevail, 2) a mitigation scenario (RCP4.5) in which the carbon price causes a shift toward nuclear, carbon capture and sequestration (CCS), and renewables, and 3) a repeat of scenario (2) in which CCS technologies are made unavailable—resulting in a large increase in the nuclear fraction of the mix.

Validation techniques of agent based modelling for geospatial simulations

NASA Astrophysics Data System (ADS)

Darvishi, M.; Ahmadi, G.

2014-10-01

One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent-based modelling and simulation (ABMS) is a new modelling method comprising of multiple interacting agent. They have been used in the different areas; for instance, geographic information system (GIS), biology, economics, social science and computer science. The emergence of ABM toolkits in GIS software libraries (e.g. ESRI's ArcGIS, OpenMap, GeoTools, etc) for geospatial modelling is an indication of the growing interest of users to use of special capabilities of ABMS. Since ABMS is inherently similar to human cognition, therefore it could be built easily and applicable to wide range applications than a traditional simulation. But a key challenge about ABMS is difficulty in their validation and verification. Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods. Therefore, attempt to find appropriate validation techniques for ABM seems to be necessary. In this paper, after reviewing on Principles and Concepts of ABM for and its applications, the validation techniques and challenges of ABM validation are discussed.

LDRD final report :

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brost, Randolph C.; McLendon, William Clarence,

2013-01-01

Modeling geospatial information with semantic graphs enables search for sites of interest based on relationships between features, without requiring strong a priori models of feature shape or other intrinsic properties. Geospatial semantic graphs can be constructed from raw sensor data with suitable preprocessing to obtain a discretized representation. This report describes initial work toward extending geospatial semantic graphs to include temporal information, and initial results applying semantic graph techniques to SAR image data. We describe an efficient graph structure that includes geospatial and temporal information, which is designed to support simultaneous spatial and temporal search queries. We also report amore » preliminary implementation of feature recognition, semantic graph modeling, and graph search based on input SAR data. The report concludes with lessons learned and suggestions for future improvements.« less

A lake-centric geospatial database to guide research and inform management decisions in an Arctic watershed in northern Alaska experiencing climate and land-use changes

USGS Publications Warehouse

Jones, Benjamin M.; Arp, Christopher D.; Whitman, Matthew S.; Nigro, Debora A.; Nitze, Ingmar; Beaver, John; Gadeke, Anne; Zuck, Callie; Liljedahl, Anna K.; Daanen, Ronald; Torvinen, Eric; Fritz, Stacey; Grosse, Guido

2017-01-01

Lakes are dominant and diverse landscape features in the Arctic, but conventional land cover classification schemes typically map them as a single uniform class. Here, we present a detailed lake-centric geospatial database for an Arctic watershed in northern Alaska. We developed a GIS dataset consisting of 4362 lakes that provides information on lake morphometry, hydrologic connectivity, surface area dynamics, surrounding terrestrial ecotypes, and other important conditions describing Arctic lakes. Analyzing the geospatial database relative to fish and bird survey data shows relations to lake depth and hydrologic connectivity, which are being used to guide research and aid in the management of aquatic resources in the National Petroleum Reserve in Alaska. Further development of similar geospatial databases is needed to better understand and plan for the impacts of ongoing climate and land-use changes occurring across lake-rich landscapes in the Arctic.

Geospatial Information System Capability Maturity Models

DOT National Transportation Integrated Search

2017-06-01

To explore how State departments of transportation (DOTs) evaluate geospatial tool applications and services within their own agencies, particularly their experiences using capability maturity models (CMMs) such as the Urban and Regional Information ...

A robust and flexible Geospatial Modeling Interface (GMI) for environmental model deployment and evaluation

USDA-ARS?s Scientific Manuscript database

This paper provides an overview of the GMI (Geospatial Modeling Interface) simulation framework for environmental model deployment and assessment. GMI currently provides access to multiple environmental models including AgroEcoSystem-Watershed (AgES-W), Nitrate Leaching and Economic Analysis 2 (NLEA...

A model of clutter for complex, multivariate geospatial displays.

PubMed

Lohrenz, Maura C; Trafton, J Gregory; Beck, R Melissa; Gendron, Marlin L

2009-02-01

A novel model of measuring clutter in complex geospatial displays was compared with human ratings of subjective clutter as a measure of convergent validity. The new model is called the color-clustering clutter (C3) model. Clutter is a known problem in displays of complex data and has been shown to affect target search performance. Previous clutter models are discussed and compared with the C3 model. Two experiments were performed. In Experiment 1, participants performed subjective clutter ratings on six classes of information visualizations. Empirical results were used to set two free parameters in the model. In Experiment 2, participants performed subjective clutter ratings on aeronautical charts. Both experiments compared and correlated empirical data to model predictions. The first experiment resulted in a .76 correlation between ratings and C3. The second experiment resulted in a .86 correlation, significantly better than results from a model developed by Rosenholtz et al. Outliers to our correlation suggest further improvements to C3. We suggest that (a) the C3 model is a good predictor of subjective impressions of clutter in geospatial displays, (b) geospatial clutter is a function of color density and saliency (primary C3 components), and (c) pattern analysis techniques could further improve C3. The C3 model could be used to improve the design of electronic geospatial displays by suggesting when a display will be too cluttered for its intended audience.

Terrain Dynamics Analysis Using Space-Time Domain Hypersurfaces and Gradient Trajectories Derived From Time Series of 3D Point Clouds

DTIC Science & Technology

2015-08-01

optimized space-time interpolation method. Tangible geospatial modeling system was further developed to support the analysis of changing elevation surfaces...Evolution Mapped by Terrestrial Laser Scanning, talk, AGU Fall 2012 *Hardin E, Mitas L, Mitasova H., Simulation of Wind -Blown Sand for...Geomorphological Applications: A Smoothed Particle Hydrodynamics Approach, GSA 2012 *Russ, E. Mitasova, H., Time series and space-time cube analyses on

NOAA's National Water Model - Integration of National Water Model with Geospatial Data creating Water Intelligence

NASA Astrophysics Data System (ADS)

Clark, E. P.; Cosgrove, B.; Salas, F.

2016-12-01

As a significant step forward to transform NOAA's water prediction services, NOAA plans to implement a new National Water Model (NWM) Version 1.0 in August 2016. A continental scale water resources model, the NWM is an evolution of the WRF-Hydro architecture developed by the National Center for Atmospheric Research (NCAR). The NWM will provide analyses and forecasts of flow for the 2.7 million stream reaches nationwide in the National Hydrography Dataset Plus v2 (NHDPlusV2) jointly developed by the USGS and EPA. The NWM also produces high-resolution water budget variables of snow, soil moisture, and evapotranspiration on a 1-km grid. NOAA's stakeholders require additional decision support application to be built on these data. The Geo-intelligence division of the Office of Water Prediction is building new products and services that integrate output from the NWM with geospatial datasets such as infrastructure and demographics to better estimate the impacts dynamic water resource states on community resiliency. This presentation will detail the methods and underlying information to produce prototypes water resources intelligence that is timely, actionable and credible. Moreover, it will to explore the NWM capability to support sector-specific decision support services.

Business models for implementing geospatial technologies in transportation decision-making

DOT National Transportation Integrated Search

2007-03-31

This report describes six State DOTs business models for implementing geospatial technologies. It provides a comparison of the organizational factors influencing how Arizona DOT, Delaware DOT, Georgia DOT, Montana DOT, North Carolina DOT, and Okla...

Land degradation assessment by geo-spatially modeling different soil erodibility equations in a semi-arid catchment.

PubMed

Saygın, Selen Deviren; Basaran, Mustafa; Ozcan, Ali Ugur; Dolarslan, Melda; Timur, Ozgur Burhan; Yilman, F Ebru; Erpul, Gunay

2011-09-01

Land degradation by soil erosion is one of the most serious problems and environmental issues in many ecosystems of arid and semi-arid regions. Especially, the disturbed areas have greater soil detachability and transportability capacity. Evaluation of land degradation in terms of soil erodibility, by using geostatistical modeling, is vital to protect and reclaim susceptible areas. Soil erodibility, described as the ability of soils to resist erosion, can be measured either directly under natural or simulated rainfall conditions, or indirectly estimated by empirical regression models. This study compares three empirical equations used to determine the soil erodibility factor of revised universal soil loss equation prediction technology based on their geospatial performances in the semi-arid catchment of the Saraykoy II Irrigation Dam located in Cankiri, Turkey. A total of 311 geo-referenced soil samples were collected with irregular intervals from the top soil layer (0-10 cm). Geostatistical analysis was performed with the point values of each equation to determine its spatial pattern. Results showed that equations that used soil organic matter in combination with the soil particle size better agreed with the variations in land use and topography of the catchment than the one using only the particle size distribution. It is recommended that the equations which dynamically integrate soil intrinsic properties with land use, topography, and its influences on the local microclimates, could be successfully used to geospatially determine sites highly susceptible to water erosion, and therefore, to select the agricultural and bio-engineering control measures needed.

Infrastructure for the Geospatial Web

NASA Astrophysics Data System (ADS)

Lake, Ron; Farley, Jim

Geospatial data and geoprocessing techniques are now directly linked to business processes in many areas. Commerce, transportation and logistics, planning, defense, emergency response, health care, asset management and many other domains leverage geospatial information and the ability to model these data to achieve increased efficiencies and to develop better, more comprehensive decisions. However, the ability to deliver geospatial data and the capacity to process geospatial information effectively in these domains are dependent on infrastructure technology that facilitates basic operations such as locating data, publishing data, keeping data current and notifying subscribers and others whose applications and decisions are dependent on this information when changes are made. This chapter introduces the notion of infrastructure technology for the Geospatial Web. Specifically, the Geography Markup Language (GML) and registry technology developed using the ebRIM specification delivered from the OASIS consortium are presented as atomic infrastructure components in a working Geospatial Web.

The geospatial modeling interface (GMI) framework for deploying and assessing environmental models

USDA-ARS?s Scientific Manuscript database

Geographical information systems (GIS) software packages have been used for close to three decades as analytical tools in environmental management for geospatial data assembly, processing, storage, and visualization of input data and model output. However, with increasing availability and use of ful...

Dylan Hettinger | NREL

Science.gov Websites

Hettinger Photo of Dylan Hettinger Dylan Hettinger Geospatial Data Scientist Dylan.Hettinger @nrel.gov | 303-275-3750 Dylan Hettinger is a member of the Geospatial Data Science team within the Systems Modeling & Geospatial Data Science Group in the Strategic Energy Analysis Center. Areas of Expertise

The National 3-D Geospatial Information Web-Based Service of Korea

NASA Astrophysics Data System (ADS)

Lee, D. T.; Kim, C. W.; Kang, I. G.

2013-09-01

3D geospatial information systems should provide efficient spatial analysis tools and able to use all capabilities of the third dimension, and a visualization. Currently, many human activities make steps toward the third dimension like land use, urban and landscape planning, cadastre, environmental monitoring, transportation monitoring, real estate market, military applications, etc. To reflect this trend, the Korean government has been started to construct the 3D geospatial data and service platform. Since the geospatial information was introduced in Korea, the construction of geospatial information (3D geospatial information, digital maps, aerial photographs, ortho photographs, etc.) has been led by the central government. The purpose of this study is to introduce the Korean government-lead 3D geospatial information web-based service for the people who interested in this industry and we would like to introduce not only the present conditions of constructed 3D geospatial data but methodologies and applications of 3D geospatial information. About 15% (about 3,278.74 km2) of the total urban area's 3D geospatial data have been constructed by the national geographic information institute (NGII) of Korea from 2005 to 2012. Especially in six metropolitan cities and Dokdo (island belongs to Korea) on level of detail (LOD) 4 which is photo-realistic textured 3D models including corresponding ortho photographs were constructed in 2012. In this paper, we represented web-based 3D map service system composition and infrastructure and comparison of V-world with Google Earth service will be presented. We also represented Open API based service cases and discussed about the protection of location privacy when we construct 3D indoor building models. In order to prevent an invasion of privacy, we processed image blurring, elimination and camouflage. The importance of public-private cooperation and advanced geospatial information policy is emphasized in Korea. Thus, the progress of spatial information industry of Korea is expected in the near future.

A robust and flexible Geospatial Modeling Interface (GMI) for deploying and evaluating natural resource models

USDA-ARS?s Scientific Manuscript database

Geographical information systems (GIS) software packages have been used for nearly three decades as analytical tools in natural resource management for geospatial data assembly, processing, storage, and visualization of input data and model output. However, with increasing availability and use of fu...

Prototyping an online wetland ecosystem services model using open model sharing standards

USGS Publications Warehouse

Feng, M.; Liu, S.; Euliss, N.H.; Young, Caitlin; Mushet, D.M.

2011-01-01

Great interest currently exists for developing ecosystem models to forecast how ecosystem services may change under alternative land use and climate futures. Ecosystem services are diverse and include supporting services or functions (e.g., primary production, nutrient cycling), provisioning services (e.g., wildlife, groundwater), regulating services (e.g., water purification, floodwater retention), and even cultural services (e.g., ecotourism, cultural heritage). Hence, the knowledge base necessary to quantify ecosystem services is broad and derived from many diverse scientific disciplines. Building the required interdisciplinary models is especially challenging as modelers from different locations and times may develop the disciplinary models needed for ecosystem simulations, and these models must be identified and made accessible to the interdisciplinary simulation. Additional difficulties include inconsistent data structures, formats, and metadata required by geospatial models as well as limitations on computing, storage, and connectivity. Traditional standalone and closed network systems cannot fully support sharing and integrating interdisciplinary geospatial models from variant sources. To address this need, we developed an approach to openly share and access geospatial computational models using distributed Geographic Information System (GIS) techniques and open geospatial standards. We included a means to share computational models compliant with Open Geospatial Consortium (OGC) Web Processing Services (WPS) standard to ensure modelers have an efficient and simplified means to publish new models. To demonstrate our approach, we developed five disciplinary models that can be integrated and shared to simulate a few of the ecosystem services (e.g., water storage, waterfowl breeding) that are provided by wetlands in the Prairie Pothole Region (PPR) of North America.

Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing.

PubMed

Hellmann, Christine; Große-Stoltenberg, André; Thiele, Jan; Oldeland, Jens; Werner, Christiane

2017-06-23

Spatial heterogeneity of ecosystems crucially influences plant performance, while in return plant feedbacks on their environment may increase heterogeneous patterns. This is of particular relevance for exotic plant invaders that transform native ecosystems, yet, approaches integrating geospatial information of environmental heterogeneity and plant-plant interaction are lacking. Here, we combined remotely sensed information of site topography and vegetation cover with a functional tracer of the N cycle, δ 15 N. Based on the case study of the invasion of an N 2 -fixing acacia in a nutrient-poor dune ecosystem, we present the first model that can successfully predict (R 2  = 0.6) small-scale spatial variation of foliar δ 15 N in a non-fixing native species from observed geospatial data. Thereby, the generalized additive mixed model revealed modulating effects of heterogeneous environments on invader impacts. Hence, linking remote sensing techniques with tracers of biological processes will advance our understanding of the dynamics and functioning of spatially structured heterogeneous systems from small to large spatial scales.

Geospatial Information from Satellite Imagery for Geovisualisation of Smart Cities in India

NASA Astrophysics Data System (ADS)

Mohan, M.

2016-06-01

In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

Towards a Web-Enabled Geovisualization and Analytics Platform for the Energy and Water Nexus

NASA Astrophysics Data System (ADS)

Sanyal, J.; Chandola, V.; Sorokine, A.; Allen, M.; Berres, A.; Pang, H.; Karthik, R.; Nugent, P.; McManamay, R.; Stewart, R.; Bhaduri, B. L.

2017-12-01

Interactive data analytics are playing an increasingly vital role in the generation of new, critical insights regarding the complex dynamics of the energy/water nexus (EWN) and its interactions with climate variability and change. Integration of impacts, adaptation, and vulnerability (IAV) science with emerging, and increasingly critical, data science capabilities offers a promising potential to meet the needs of the EWN community. To enable the exploration of pertinent research questions, a web-based geospatial visualization platform is being built that integrates a data analysis toolbox with advanced data fusion and data visualization capabilities to create a knowledge discovery framework for the EWN. The system, when fully built out, will offer several geospatial visualization capabilities including statistical visual analytics, clustering, principal-component analysis, dynamic time warping, support uncertainty visualization and the exploration of data provenance, as well as support machine learning discoveries to render diverse types of geospatial data and facilitate interactive analysis. Key components in the system architecture includes NASA's WebWorldWind, the Globus toolkit, postgresql, as well as other custom built software modules.

A geospatial modelling approach to predict seagrass habitat recovery under multiple stressor regimes

EPA Science Inventory

Restoration of estuarine seagrass habitats requires a clear understanding of the modes of action of multiple interacting stressors including nutrients, climate change, coastal land-use change, and habitat modification. We have developed and demonstrated a geospatial modeling a...

A geospatial framework for dynamic route planning using congestion prediction in transportation systems.

DOT National Transportation Integrated Search

2011-01-01

The goal this research is to develop an end-to-end data-driven system, dubbed TransDec : (short for Transportation Decision-Making), to enable decision-making queries in : transportation systems with dynamic, real-time and historical data. With Trans...

Urban Expansion: a Geo-Spatial Approach for Temporal Monitoring of Loss of Agricultural Land

NASA Astrophysics Data System (ADS)

Sumari, N. S.; Shao, Z.; Huang, M.; Sanga, C. A.; Van Genderen, J. L.

2017-09-01

This paper presents some preliminary results from research on monitoring the urban growth of Shenzhen in China. Agriculture is still the pillar of national economies in many countries including China. Thus, agriculture contributes to population growth. Population growth follows either exponential or logistic growth models. These models can be examined using a time-series of geospatial data, mainly historical earth observation imagery from satellites such as LANDSAT. Such multitemporal data may provide insights into settlement analysis as well as on population dynamics and hence, quantify the loss of agricultural land. In this study, LANDSAT data of ten dates, at approximately five yearly intervals from 1977 to 2017 were used. The remote sensing techniques used for analysis of data for 40 years were image selection, then followed by geometric and radiometric corrections and mosaicking. Also, classification, remote sensing image fusion, and change detection methods were used. This research extracted the information on the amount, direction, and speed of urbanization, and hence, the number of hectares of agricultural land lost due to urban expansion. Several specific elements were used in the descriptive model of landscape changes and population dynamics of the city of Shenzhen in China. These elements are: i) quantify the urban changes, from a small town (37.000 people in the early 1970's) to the megalopolis of around 20 million habitants today. ii) Examining the rate of urban extension on the loss of agricultural landscape and population growth. iii) The loss of food production was analysed against the economic growth in the region. iv) The aspects of loss of agricultural land, area of built-up urban land, and increase in population are studied quantitatively, by the temporal analysis of earth observation geospatial data. The experimental results from this study show that the proposed method is effective in determining loss of agricultural land in any city due to urbanization. It can be used by town planner and other stakeholders such as land surveyors and agriculture experts to mitigate the mushrooming of unplanned settlements in many town / villages and loss of land for agriculture which might cause problems in food security.

NCI's Distributed Geospatial Data Server

NASA Astrophysics Data System (ADS)

Larraondo, P. R.; Evans, B. J. K.; Antony, J.

2016-12-01

Earth systems, environmental and geophysics datasets are an extremely valuable source of information about the state and evolution of the Earth. However, different disciplines and applications require this data to be post-processed in different ways before it can be used. For researchers experimenting with algorithms across large datasets or combining multiple data sets, the traditional approach to batch data processing and storing all the output for later analysis rapidly becomes unfeasible, and often requires additional work to publish for others to use. Recent developments on distributed computing using interactive access to significant cloud infrastructure opens the door for new ways of processing data on demand, hence alleviating the need for storage space for each individual copy of each product. The Australian National Computational Infrastructure (NCI) has developed a highly distributed geospatial data server which supports interactive processing of large geospatial data products, including satellite Earth Observation data and global model data, using flexible user-defined functions. This system dynamically and efficiently distributes the required computations among cloud nodes and thus provides a scalable analysis capability. In many cases this completely alleviates the need to preprocess and store the data as products. This system presents a standards-compliant interface, allowing ready accessibility for users of the data. Typical data wrangling problems such as handling different file formats and data types, or harmonising the coordinate projections or temporal and spatial resolutions, can now be handled automatically by this service. The geospatial data server exposes functionality for specifying how the data should be aggregated and transformed. The resulting products can be served using several standards such as the Open Geospatial Consortium's (OGC) Web Map Service (WMS) or Web Feature Service (WFS), Open Street Map tiles, or raw binary arrays under different conventions. We will show some cases where we have used this new capability to provide a significant improvement over previous approaches.

Stakeholder Alignment and Changing Geospatial Information Capabilities

NASA Astrophysics Data System (ADS)

Winter, S.; Cutcher-Gershenfeld, J.; King, J. L.

2015-12-01

Changing geospatial information capabilities can have major economic and social effects on activities such as drought monitoring, weather forecasts, agricultural productivity projections, water and air quality assessments, the effects of forestry practices and so on. Whose interests are served by such changes? Two common mistakes are assuming stability in the community of stakeholders and consistency in stakeholder behavior. Stakeholder communities can reconfigure dramatically as some leave the discussion, others enter, and circumstances shift — all resulting in dynamic points of alignment and misalignment . New stakeholders can bring new interests, and existing stakeholders can change their positions. Stakeholders and their interests need to be be considered as geospatial information capabilities change, but this is easier said than done. New ways of thinking about stakeholder alignment in light of changes in capability are presented.

Geospatial techniques for allocating vulnerability zoning of geohazards along the Karakorum Highway, Gilgit-Baltistan-Pakistan

NASA Astrophysics Data System (ADS)

Khan, K. M.; Rashid, S.; Yaseen, M.; Ikram, M.

2016-12-01

The Karakoram Highway (KKH) 'eighth wonder of the world', constructed and completed by the consent of Pakistan and China in 1979 as a Friendship Highway. It connect Gilgit-Baltistan, a strategically prominent region of Pakistan, with Xinjiang region in China. Due to manifold geology/geomorphology, soil formation, steep slopes, climate change well as unsustainable anthropogenic activities, still, KKH is remarkably vulnerable to natural hazards i.e. land subsistence, landslides, erosion, rock fall, floods, debris flows, cyclical torrential rainfall and snowfall, lake outburst etc. Most of the time these geohazard's damaging effects jeopardized the life in the region. To ascertain the nature and frequency of the disaster and vulnerability zoning, a rating and management (logistic) analysis were made to investigate the spatiotemporal sharing of the natural hazard. The substantial dynamics of the physiograpy, geology, geomorphology, soils and climate were carefully understand while slope, aspect, elevation, profile curvature and rock hardness was calculated by different techniques. To assess the nature and intensity geospatial analysis were conducted and magnitude of every factor was gauged by using logistic regression. Moreover, ever relative variable was integrated in the evaluation process. Logistic regression and geospatial techniques were used to map the geohazard vulnerability zoning (GVZ). The GVZ model findings were endorsed by the reviews of documented hazards in the current years and the precision was realized more than 88.1 %. The study has proved the model authentication by highlighting the comfortable indenture among the vulnerability mapping and past documented hazards. By using a receiver operating characteristic curve, the logistic regression model made satisfactory results. The outcomes will be useful in sustainable land use and infrastructure planning, mainly in high risk zones for reduceing economic damages and community betterment.

Identifying high energy density stream-reaches through refined geospatial resolution in hydropower resource assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pasha, M. Fayzul K.; Yang, Majntxov; Yeasmin, Dilruba

Benefited from the rapid development of multiple geospatial data sets on topography, hydrology, and existing energy-water infrastructures, the reconnaissance level hydropower resource assessment can now be conducted using geospatial models in all regions of the US. Furthermore, the updated techniques can be used to estimate the total undeveloped hydropower potential across all regions, and may eventually help identify further hydropower opportunities that were previously overlooked. To enhance the characterization of higher energy density stream-reaches, this paper explored the sensitivity of geospatial resolution on the identification of hydropower stream-reaches using the geospatial merit matrix based hydropower resource assessment (GMM-HRA) model. GMM-HRAmore » model simulation was conducted with eight different spatial resolutions on six U.S. Geological Survey (USGS) 8-digit hydrologic units (HUC8) located at three different terrains; Flat, Mild, and Steep. The results showed that more hydropower potential from higher energy density stream-reaches can be identified with increasing spatial resolution. Both Flat and Mild terrains exhibited lower impacts compared to the Steep terrain. Consequently, greater attention should be applied when selecting the discretization resolution for hydropower resource assessments in the future study.« less

Identifying high energy density stream-reaches through refined geospatial resolution in hydropower resource assessment

DOE PAGES

Pasha, M. Fayzul K.; Yang, Majntxov; Yeasmin, Dilruba; ...

2016-01-07

Benefited from the rapid development of multiple geospatial data sets on topography, hydrology, and existing energy-water infrastructures, the reconnaissance level hydropower resource assessment can now be conducted using geospatial models in all regions of the US. Furthermore, the updated techniques can be used to estimate the total undeveloped hydropower potential across all regions, and may eventually help identify further hydropower opportunities that were previously overlooked. To enhance the characterization of higher energy density stream-reaches, this paper explored the sensitivity of geospatial resolution on the identification of hydropower stream-reaches using the geospatial merit matrix based hydropower resource assessment (GMM-HRA) model. GMM-HRAmore » model simulation was conducted with eight different spatial resolutions on six U.S. Geological Survey (USGS) 8-digit hydrologic units (HUC8) located at three different terrains; Flat, Mild, and Steep. The results showed that more hydropower potential from higher energy density stream-reaches can be identified with increasing spatial resolution. Both Flat and Mild terrains exhibited lower impacts compared to the Steep terrain. Consequently, greater attention should be applied when selecting the discretization resolution for hydropower resource assessments in the future study.« less

Diy Geospatial Web Service Chains: Geochaining Make it Easy

NASA Astrophysics Data System (ADS)

Wu, H.; You, L.; Gui, Z.

2011-08-01

It is a great challenge for beginners to create, deploy and utilize a Geospatial Web Service Chain (GWSC). People in Computer Science are usually not familiar with geospatial domain knowledge. Geospatial practitioners may lack the knowledge about web services and service chains. The end users may lack both. However, integrated visual editing interfaces, validation tools, and oneclick deployment wizards may help to lower the learning curve and improve modelling skills so beginners will have a better experience. GeoChaining is a GWSC modelling tool designed and developed based on these ideas. GeoChaining integrates visual editing, validation, deployment, execution etc. into a unified platform. By employing a Virtual Globe, users can intuitively visualize raw data and results produced by GeoChaining. All of these features allow users to easily start using GWSC, regardless of their professional background and computer skills. Further, GeoChaining supports GWSC model reuse, meaning that an entire GWSC model created or even a specific part can be directly reused in a new model. This greatly improves the efficiency of creating a new GWSC, and also contributes to the sharing and interoperability of GWSC.

Topologically Consistent Models for Efficient Big Geo-Spatio Data Distribution

NASA Astrophysics Data System (ADS)

Jahn, M. W.; Bradley, P. E.; Doori, M. Al; Breunig, M.

2017-10-01

Geo-spatio-temporal topology models are likely to become a key concept to check the consistency of 3D (spatial space) and 4D (spatial + temporal space) models for emerging GIS applications such as subsurface reservoir modelling or the simulation of energy and water supply of mega or smart cities. Furthermore, the data management for complex models consisting of big geo-spatial data is a challenge for GIS and geo-database research. General challenges, concepts, and techniques of big geo-spatial data management are presented. In this paper we introduce a sound mathematical approach for a topologically consistent geo-spatio-temporal model based on the concept of the incidence graph. We redesign DB4GeO, our service-based geo-spatio-temporal database architecture, on the way to the parallel management of massive geo-spatial data. Approaches for a new geo-spatio-temporal and object model of DB4GeO meeting the requirements of big geo-spatial data are discussed in detail. Finally, a conclusion and outlook on our future research are given on the way to support the processing of geo-analytics and -simulations in a parallel and distributed system environment.

Learn More

EPA Pesticide Factsheets

NHDPlus is a geospatial, hydrologic framework dataset that is intended for use by geospatial analysts and modelers to support water resources related applications. NHDPlus was developed by the USEPA in partnership with the US Geologic Survey

Get Data

EPA Pesticide Factsheets

NHDPlus is a geospatial, hydrologic framework dataset that is intended for use by geospatial analysts and modelers to support water resources related applications. NHDPlus was developed by the USEPA in partnership with the US Geologic Survey

Basic Information

EPA Pesticide Factsheets

NHDPlus is a geospatial, hydrologic framework dataset that is intended for use by geospatial analysts and modelers to support water resources related applications. NHDPlus was developed by the USEPA in partnership with the US Geologic Survey

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

PubMed Central

2011-01-01

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. PMID:21410968

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

PubMed

Kamel Boulos, Maged N; Viangteeravat, Teeradache; Anyanwu, Matthew N; Ra Nagisetty, Venkateswara; Kuscu, Emin

2011-03-16

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.

Geospatial Data as a Service: Towards planetary scale real-time analytics

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Larraondo, P. R.; Antony, J.; Richards, C. J.

2017-12-01

The rapid growth of earth systems, environmental and geophysical datasets poses a challenge to both end-users and infrastructure providers. For infrastructure and data providers, tasks like managing, indexing and storing large collections of geospatial data needs to take into consideration the various use cases by which consumers will want to access and use the data. Considerable investment has been made by the Earth Science community to produce suitable real-time analytics platforms for geospatial data. There are currently different interfaces that have been defined to provide data services. Unfortunately, there is considerable difference on the standards, protocols or data models which have been designed to target specific communities or working groups. The Australian National University's National Computational Infrastructure (NCI) is used for a wide range of activities in the geospatial community. Earth observations, climate and weather forecasting are examples of these communities which generate large amounts of geospatial data. The NCI has been carrying out significant effort to develop a data and services model that enables the cross-disciplinary use of data. Recent developments in cloud and distributed computing provide a publicly accessible platform where new infrastructures can be built. One of the key components these technologies offer is the possibility of having "limitless" compute power next to where the data is stored. This model is rapidly transforming data delivery from centralised monolithic services towards ubiquitous distributed services that scale up and down adapting to fluctuations in the demand. NCI has developed GSKY, a scalable, distributed server which presents a new approach for geospatial data discovery and delivery based on OGC standards. We will present the architecture and motivating use-cases that drove GSKY's collaborative design, development and production deployment. We show our approach offers the community valuable exploratory analysis capabilities, for dealing with petabyte-scale geospatial data collections.

GIS applications for military operations in coastal zones

USGS Publications Warehouse

Fleming, S.; Jordan, T.; Madden, M.; Usery, E.L.; Welch, R.

2009-01-01

In order to successfully support current and future US military operations in coastal zones, geospatial information must be rapidly integrated and analyzed to meet ongoing force structure evolution and new mission directives. Coastal zones in a military-operational environment are complex regions that include sea, land and air features that demand high-volume databases of extreme detail within relatively narrow geographic corridors. Static products in the form of analog maps at varying scales traditionally have been used by military commanders and their operational planners. The rapidly changing battlefield of 21st Century warfare, however, demands dynamic mapping solutions. Commercial geographic information system (GIS) software for military-specific applications is now being developed and employed with digital databases to provide customized digital maps of variable scale, content and symbolization tailored to unique demands of military units. Research conducted by the Center for Remote Sensing and Mapping Science at the University of Georgia demonstrated the utility of GIS-based analysis and digital map creation when developing large-scale (1:10,000) products from littoral warfare databases. The methodology employed-selection of data sources (including high resolution commercial images and Lidar), establishment of analysis/modeling parameters, conduct of vehicle mobility analysis, development of models and generation of products (such as a continuous sea-land DEM and geo-visualization of changing shorelines with tidal levels)-is discussed. Based on observations and identified needs from the National Geospatial-Intelligence Agency, formerly the National Imagery and Mapping Agency, and the Department of Defense, prototype GIS models for military operations in sea, land and air environments were created from multiple data sets of a study area at US Marine Corps Base Camp Lejeune, North Carolina. Results of these models, along with methodologies for developing large-scale littoral warfare databases, aid the National Geospatial-Intelligence Agency in meeting littoral warfare analysis, modeling and map generation requirements for US military organizations. ?? 2008 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

GIS applications for military operations in coastal zones

NASA Astrophysics Data System (ADS)

Fleming, S.; Jordan, T.; Madden, M.; Usery, E. L.; Welch, R.

In order to successfully support current and future US military operations in coastal zones, geospatial information must be rapidly integrated and analyzed to meet ongoing force structure evolution and new mission directives. Coastal zones in a military-operational environment are complex regions that include sea, land and air features that demand high-volume databases of extreme detail within relatively narrow geographic corridors. Static products in the form of analog maps at varying scales traditionally have been used by military commanders and their operational planners. The rapidly changing battlefield of 21st Century warfare, however, demands dynamic mapping solutions. Commercial geographic information system (GIS) software for military-specific applications is now being developed and employed with digital databases to provide customized digital maps of variable scale, content and symbolization tailored to unique demands of military units. Research conducted by the Center for Remote Sensing and Mapping Science at the University of Georgia demonstrated the utility of GIS-based analysis and digital map creation when developing large-scale (1:10,000) products from littoral warfare databases. The methodology employed-selection of data sources (including high resolution commercial images and Lidar), establishment of analysis/modeling parameters, conduct of vehicle mobility analysis, development of models and generation of products (such as a continuous sea-land DEM and geo-visualization of changing shorelines with tidal levels)-is discussed. Based on observations and identified needs from the National Geospatial-Intelligence Agency, formerly the National Imagery and Mapping Agency, and the Department of Defense, prototype GIS models for military operations in sea, land and air environments were created from multiple data sets of a study area at US Marine Corps Base Camp Lejeune, North Carolina. Results of these models, along with methodologies for developing large-scale littoral warfare databases, aid the National Geospatial-Intelligence Agency in meeting littoral warfare analysis, modeling and map generation requirements for US military organizations.

Conference on Geospatial Approaches to Cancer Control and Population Sciences

Cancer.gov

The purpose of this conference is to bring together a community of researchers across the cancer control continuum using geospatial tools, models and approaches to address cancer prevention and control.

NHDPlus (National Hydrography Dataset Plus)

EPA Pesticide Factsheets

NHDPlus is a geospatial, hydrologic framework dataset that is intended for use by geospatial analysts and modelers to support water resources related applications. NHDPlus was developed by the USEPA in partnership with the US Geologic Survey

Guidebook on LANDFIRE fuels data acquisition, critique, modification, maintenance, and model calibration

Treesearch

Richard D. Stratton

2009-01-01

With the advent of LANDFIRE fuels layers, an increasing number of specialists are using the data in a variety of fire modeling systems. However, a comprehensive guide on acquiring, critiquing, and editing (ACE) geospatial fuels data does not exist. This paper provides guidance on ACE as well as on assembling a geospatial fuels team, model calibration, and maintaining...

Strategic Model for Future Geospatial Education.

DTIC Science & Technology

1998-05-18

There appears to be only one benefit to doing nothing as option one dictates-there are no up front costs to the government for doing nothing. The costs...the government can ensure that US industry and academia benefit from decades of geospatial information expertise. Industry and academia will be...or militarily unique topics. In summary, option two provides more benefits for both the government and the geospatial information community as a

Center of Excellence for Geospatial Information Science research plan 2013-18

USGS Publications Warehouse

Usery, E. Lynn

2013-01-01

The U.S. Geological Survey Center of Excellence for Geospatial Information Science (CEGIS) was created in 2006 and since that time has provided research primarily in support of The National Map. The presentations and publications of the CEGIS researchers document the research accomplishments that include advances in electronic topographic map design, generalization, data integration, map projections, sea level rise modeling, geospatial semantics, ontology, user-centered design, volunteer geographic information, and parallel and grid computing for geospatial data from The National Map. A research plan spanning 2013–18 has been developed extending the accomplishments of the CEGIS researchers and documenting new research areas that are anticipated to support The National Map of the future. In addition to extending the 2006–12 research areas, the CEGIS research plan for 2013–18 includes new research areas in data models, geospatial semantics, high-performance computing, volunteered geographic information, crowdsourcing, social media, data integration, and multiscale representations to support the Three-Dimensional Elevation Program (3DEP) and The National Map of the future of the U.S. Geological Survey.

Geospatial Database for Strata Objects Based on Land Administration Domain Model (ladm)

NASA Astrophysics Data System (ADS)

Nasorudin, N. N.; Hassan, M. I.; Zulkifli, N. A.; Rahman, A. Abdul

2016-09-01

Recently in our country, the construction of buildings become more complex and it seems that strata objects database becomes more important in registering the real world as people now own and use multilevel of spaces. Furthermore, strata title was increasingly important and need to be well-managed. LADM is a standard model for land administration and it allows integrated 2D and 3D representation of spatial units. LADM also known as ISO 19152. The aim of this paper is to develop a strata objects database using LADM. This paper discusses the current 2D geospatial database and needs for 3D geospatial database in future. This paper also attempts to develop a strata objects database using a standard data model (LADM) and to analyze the developed strata objects database using LADM data model. The current cadastre system in Malaysia includes the strata title is discussed in this paper. The problems in the 2D geospatial database were listed and the needs for 3D geospatial database in future also is discussed. The processes to design a strata objects database are conceptual, logical and physical database design. The strata objects database will allow us to find the information on both non-spatial and spatial strata title information thus shows the location of the strata unit. This development of strata objects database may help to handle the strata title and information.

Learning topography with Tangible Landscape games

NASA Astrophysics Data System (ADS)

Petrasova, A.; Tabrizian, P.; Harmon, B. A.; Petras, V.; Millar, G.; Mitasova, H.; Meentemeyer, R. K.

2017-12-01

Understanding topography and its representations is crucial for correct interpretation and modeling of surface processes. However, novice earth science and landscape architecture students often find reading topographic maps challenging. As a result, many students struggle to comprehend more complex spatial concepts and processes such as flow accumulation or sediment transport.We developed and tested a new method for teaching hydrology, geomorphology, and grading using Tangible Landscape—a tangible interface for geospatial modeling. Tangible Landscape couples a physical and digital model of a landscape through a real-time cycle of hands-on modeling, 3D scanning, geospatial computation, and projection. With Tangible Landscape students can sculpt a projection-augmented topographic model of a landscape with their hands and use a variety of tangible objects to immediately see how they are changing geospatial analytics such as contours, profiles, water flow, or landform types. By feeling and manipulating the shape of the topography, while seeing projected geospatial analytics, students can intuitively learn about 3D topographic form, its representations, and how topography controls physical processes. Tangible Landscape is powered by GRASS GIS, an open source geospatial platform with extensive libraries for geospatial modeling and analysis. As such, Tangible Landscape can be used to design a wide range of learning experiences across a large number of geoscience disciplines.As part of a graduate level course that teaches grading, 16 students participated in a series of workshops, which were developed as serious games to encourage learning through structured play. These serious games included 1) diverting rain water to a specified location with minimal changes to landscape, 2) building different combinations of landforms, and 3) reconstructing landscapes based on projected contour information with feedback.In this poster, we will introduce Tangible Landscape, and describe the games and their implementation. We will then present preliminary results of a user experience survey we conducted as part of the workshops. All developed materials and software are open source and available online.

Examining the Effect of Enactment of a Geospatial Curriculum on Students' Geospatial Thinking and Reasoning

NASA Astrophysics Data System (ADS)

Bodzin, Alec M.; Fu, Qiong; Kulo, Violet; Peffer, Tamara

2014-08-01

A potential method for teaching geospatial thinking and reasoning (GTR) is through geospatially enabled learning technologies. We developed an energy resources geospatial curriculum that included learning activities with geographic information systems and virtual globes. This study investigated how 13 urban middle school teachers implemented and varied the enactment of the curriculum with their students and investigated which teacher- and student-level factors accounted for students' GTR posttest achievement. Data included biweekly implementation surveys from teachers and energy resources content and GTR pre- and posttest achievement measures from 1,049 students. Students significantly increased both their energy resources content knowledge and their GTR skills related to energy resources at the end of the curriculum enactment. Both multiple regression and hierarchical linear modeling found that students' initial GTR abilities and gain in energy content knowledge were significantly explanatory variables for their geospatial achievement at the end of curriculum enactment, p < .001. Teacher enactment factors, including adherence to implementing the critical components of the curriculum or the number of years the teachers had taught the curriculum, did not have significant effects on students' geospatial posttest achievement. The findings from this study provide support that learning with geospatially enabled learning technologies can support GTR with urban middle-level learners.

Modern Technologies aspects for Oceanographic Data Management and Dissemination : The HNODC Implementation

NASA Astrophysics Data System (ADS)

Lykiardopoulos, A.; Iona, A.; Lakes, V.; Batis, A.; Balopoulos, E.

2009-04-01

The development of new technologies for the aim of enhancing Web Applications with Dynamically data access was the starting point for Geospatial Web Applications to developed at the same time as well. By the means of these technologies the Web Applications embed the capability of presenting Geographical representations of the Geo Information. The induction in nowadays, of the state of the art technologies known as Web Services, enforce the Web Applications to have interoperability among them i.e. to be able to process requests from each other via a network. In particular throughout the Oceanographic Community, modern Geographical Information systems based on Geospatial Web Services are now developed or will be developed shortly in the near future, with capabilities of managing the information itself fully through Web Based Geographical Interfaces. The exploitation of HNODC Data Base, through a Web Based Application enhanced with Web Services by the use of open source tolls may be consider as an ideal case of such implementation. Hellenic National Oceanographic Data Center (HNODC) as a National Public Oceanographic Data provider and at the same time a member of the International Net of Oceanographic Data Centers( IOC/IODE), owns a very big volume of Data and Relevant information about the Marine Ecosystem. For the efficient management and exploitation of these Data, a relational Data Base has been constructed with a storage of over 300.000 station data concerning, physical, chemical and biological Oceanographic information. The development of a modern Web Application for the End User worldwide to be able to explore and navigate throughout HNODC data via the use of an interface with the capability of presenting Geographical representations of the Geo Information, is today a fact. The application is constituted with State of the art software components and tools such as: • Geospatial and no Spatial Web Services mechanisms • Geospatial open source tools for the creation of Dynamic Geographical Representations. • Communication protocols (messaging mechanisms) in all Layers such as XML and GML together with SOAP protocol via Apache/Axis. At the same time the application may interact with any other SOA application either in sending or receiving Geospatial Data through Geographical Layers, since it inherits the big advantage of interoperability between Web Services systems. Roughly the Architecture can denoted as follows: • At the back End Open source PostgreSQL DBMS stands as the data storage mechanism with more than one Data Base Schemas cause of the separation of the Geospatial Data and the non Geospatial Data. • UMN Map Server and Geoserver are the mechanisms for: Represent Geospatial Data via Web Map Service (WMS) Querying and Navigating in Geospatial and Meta Data Information via Web Feature Service (WFS) oAnd in the near future Transacting and processing new or existing Geospatial Data via Web Processing Service (WPS) • Map Bender, a geospatial portal site management software for OGC and OWS architectures acts as the integration module between the Geospatial Mechanisms. Mapbender comes with an embedded data model capable to manage interfaces for displaying, navigating and querying OGC compliant web map and feature services (WMS and transactional WFS). • Apache and Tomcat stand again as the Web Service middle Layers • Apache Axis with it's embedded implementation of the SOAP protocol ("Simple Object Access Protocol") acts as the No spatial data Mechanism of Web Services. These modules of the platform are still under development but their implementation will be fulfilled in the near future. • And a new Web user Interface for the end user based on enhanced and customized version of a MapBender GUI, a powerful Web Services client. For HNODC the interoperability of Web Services is the big advantage of the developed platform since it is capable to act in the future as provider and consumer of Web Services in both ways: • Either as data products provider for external SOA platforms. • Or as consumer of data products from external SOA platforms for new applications to be developed or for existing applications to be enhanced. A great paradigm of Data Managenet integration and dissemination via the use of such technologies is the European's Union Research Project Seadatanet, with the main objective to develop a standardized distributed system for managing and disseminating the large and diverse data sets and to enhance the currently existing infrastructures with Web Services Further more and when the technology of Web Processing Service (WPS), will be mature enough and applicable for development, the derived data products will be able to have any kind of GIS functionality for consumers across the network. From this point of view HNODC, joins the global scientific community by providing and consuming application Independent data products.

Urban Climate Resilience - Connecting climate models with decision support cyberinfrastructure using open standards

NASA Astrophysics Data System (ADS)

Bermudez, L. E.; Percivall, G.; Idol, T. A.

2015-12-01

Experts in climate modeling, remote sensing of the Earth, and cyber infrastructure must work together in order to make climate predictions available to decision makers. Such experts and decision makers worked together in the Open Geospatial Consortium's (OGC) Testbed 11 to address a scenario of population displacement by coastal inundation due to the predicted sea level rise. In a Policy Fact Sheet "Harnessing Climate Data to Boost Ecosystem & Water Resilience", issued by White House Office of Science and Technology (OSTP) in December 2014, OGC committed to increase access to climate change information using open standards. In July 2015, the OGC Testbed 11 Urban Climate Resilience activity delivered on that commitment with open standards based support for climate-change preparedness. Using open standards such as the OGC Web Coverage Service and Web Processing Service and the NetCDF and GMLJP2 encoding standards, Testbed 11 deployed an interoperable high-resolution flood model to bring climate model outputs together with global change assessment models and other remote sensing data for decision support. Methods to confirm model predictions and to allow "what-if-scenarios" included in-situ sensor webs and crowdsourcing. A scenario was in two locations: San Francisco Bay Area and Mozambique. The scenarios demonstrated interoperation and capabilities of open geospatial specifications in supporting data services and processing services. The resultant High Resolution Flood Information System addressed access and control of simulation models and high-resolution data in an open, worldwide, collaborative Web environment. The scenarios examined the feasibility and capability of existing OGC geospatial Web service specifications in supporting the on-demand, dynamic serving of flood information from models with forecasting capacity. Results of this testbed included identification of standards and best practices that help researchers and cities deal with climate-related issues. Results of the testbeds will now be deployed in pilot applications. The testbed also identified areas of additional development needed to help identify scientific investments and cyberinfrastructure approaches needed to improve the application of climate science research results to urban climate resilence.

Agricultural capacity to increase the production of select fruits and vegetables in the US: A geospatial modeling analysis

USDA-ARS?s Scientific Manuscript database

The capacity of US agriculture to increase the output of specific foods to accommodate increased demand is not well documented. This research uses geospatial modeling to examine the capacity of the US agricultural land base to increase the per capita availability of an example set of nutrient-dense ...

Complex network description of the ionosphere

NASA Astrophysics Data System (ADS)

Lu, Shikun; Zhang, Hao; Li, Xihai; Li, Yihong; Niu, Chao; Yang, Xiaoyun; Liu, Daizhi

2018-03-01

Complex networks have emerged as an essential approach of geoscience to generate novel insights into the nature of geophysical systems. To investigate the dynamic processes in the ionosphere, a directed complex network is constructed, based on a probabilistic graph of the vertical total electron content (VTEC) from 2012. The results of the power-law hypothesis test show that both the out-degree and in-degree distribution of the ionospheric network are not scale-free. Thus, the distribution of the interactions in the ionosphere is homogenous. None of the geospatial positions play an eminently important role in the propagation of the dynamic ionospheric processes. The spatial analysis of the ionospheric network shows that the interconnections principally exist between adjacent geographical locations, indicating that the propagation of the dynamic processes primarily depends on the geospatial distance in the ionosphere. Moreover, the joint distribution of the edge distances with respect to longitude and latitude directions shows that the dynamic processes travel further along the longitude than along the latitude in the ionosphere. The analysis of small-world-ness indicates that the ionospheric network possesses the small-world property, which can make the ionosphere stable and efficient in the propagation of dynamic processes.

Distributed Multi-interface Catalogue for Geospatial Data

NASA Astrophysics Data System (ADS)

Nativi, S.; Bigagli, L.; Mazzetti, P.; Mattia, U.; Boldrini, E.

2007-12-01

Several geosciences communities (e.g. atmospheric science, oceanography, hydrology) have developed tailored data and metadata models and service protocol specifications for enabling online data discovery, inventory, evaluation, access and download. These specifications are conceived either profiling geospatial information standards or extending the well-accepted geosciences data models and protocols in order to capture more semantics. These artifacts have generated a set of related catalog -and inventory services- characterizing different communities, initiatives and projects. In fact, these geospatial data catalogs are discovery and access systems that use metadata as the target for query on geospatial information. The indexed and searchable metadata provide a disciplined vocabulary against which intelligent geospatial search can be performed within or among communities. There exists a clear need to conceive and achieve solutions to implement interoperability among geosciences communities, in the context of the more general geospatial information interoperability framework. Such solutions should provide search and access capabilities across catalogs, inventory lists and their registered resources. Thus, the development of catalog clearinghouse solutions is a near-term challenge in support of fully functional and useful infrastructures for spatial data (e.g. INSPIRE, GMES, NSDI, GEOSS). This implies the implementation of components for query distribution and virtual resource aggregation. These solutions must implement distributed discovery functionalities in an heterogeneous environment, requiring metadata profiles harmonization as well as protocol adaptation and mediation. We present a catalog clearinghouse solution for the interoperability of several well-known cataloguing systems (e.g. OGC CSW, THREDDS catalog and data services). The solution implements consistent resource discovery and evaluation over a dynamic federation of several well-known cataloguing and inventory systems. Prominent features include: 1)Support to distributed queries over a hierarchical data model, supporting incremental queries (i.e. query over collections, to be subsequently refined) and opaque/translucent chaining; 2)Support to several client protocols, through a compound front-end interface module. This allows to accommodate a (growing) number of cataloguing standards, or profiles thereof, including the OGC CSW interface, ebRIM Application Profile (for Core ISO Metadata and other data models), and the ISO Application Profile. The presented catalog clearinghouse supports both the opaque and translucent pattern for service chaining. In fact, the clearinghouse catalog may be configured either to completely hide the underlying federated services or to provide clients with services information. In both cases, the clearinghouse solution presents a higher level interface (i.e. OGC CSW) which harmonizes multiple lower level services (e.g. OGC CSW, WMS and WCS, THREDDS, etc.), and handles all control and interaction with them. In the translucent case, client has the option to directly access the lower level services (e.g. to improve performances). In the GEOSS context, the solution has been experimented both as a stand-alone user application and as a service framework. The first scenario allows a user to download a multi-platform client software and query a federation of cataloguing systems, that he can customize at will. The second scenario support server-side deployment and can be flexibly adapted to several use-cases, such as intranet proxy, catalog broker, etc.

Geospatial-enabled Data Exploration and Computation through Data Infrastructure Building Blocks

NASA Astrophysics Data System (ADS)

Song, C. X.; Biehl, L. L.; Merwade, V.; Villoria, N.

2015-12-01

Geospatial data are present everywhere today with the proliferation of location-aware computing devices and sensors. This is especially true in the scientific community where large amounts of data are driving research and education activities in many domains. Collaboration over geospatial data, for example, in modeling, data analysis and visualization, must still overcome the barriers of specialized software and expertise among other challenges. The GABBs project aims at enabling broader access to geospatial data exploration and computation by developing spatial data infrastructure building blocks that leverage capabilities of end-to-end application service and virtualized computing framework in HUBzero. Funded by NSF Data Infrastructure Building Blocks (DIBBS) initiative, GABBs provides a geospatial data architecture that integrates spatial data management, mapping and visualization and will make it available as open source. The outcome of the project will enable users to rapidly create tools and share geospatial data and tools on the web for interactive exploration of data without requiring significant software development skills, GIS expertise or IT administrative privileges. This presentation will describe the development of geospatial data infrastructure building blocks and the scientific use cases that help drive the software development, as well as seek feedback from the user communities.

Cloud computing geospatial application for water resources based on free and open source software and open standards - a prototype

NASA Astrophysics Data System (ADS)

Delipetrev, Blagoj

2016-04-01

Presently, most of the existing software is desktop-based, designed to work on a single computer, which represents a major limitation in many ways, starting from limited computer processing, storage power, accessibility, availability, etc. The only feasible solution lies in the web and cloud. This abstract presents research and development of a cloud computing geospatial application for water resources based on free and open source software and open standards using hybrid deployment model of public - private cloud, running on two separate virtual machines (VMs). The first one (VM1) is running on Amazon web services (AWS) and the second one (VM2) is running on a Xen cloud platform. The presented cloud application is developed using free and open source software, open standards and prototype code. The cloud application presents a framework how to develop specialized cloud geospatial application that needs only a web browser to be used. This cloud application is the ultimate collaboration geospatial platform because multiple users across the globe with internet connection and browser can jointly model geospatial objects, enter attribute data and information, execute algorithms, and visualize results. The presented cloud application is: available all the time, accessible from everywhere, it is scalable, works in a distributed computer environment, it creates a real-time multiuser collaboration platform, the programing languages code and components are interoperable, and it is flexible in including additional components. The cloud geospatial application is implemented as a specialized water resources application with three web services for 1) data infrastructure (DI), 2) support for water resources modelling (WRM), 3) user management. The web services are running on two VMs that are communicating over the internet providing services to users. The application was tested on the Zletovica river basin case study with concurrent multiple users. The application is a state-of-the-art cloud geospatial collaboration platform. The presented solution is a prototype and can be used as a foundation for developing of any specialized cloud geospatial applications. Further research will be focused on distributing the cloud application on additional VMs, testing the scalability and availability of services.

Statistical relations of salt and selenium loads to geospatial characteristics of corresponding subbasins of the Colorado and Gunnison Rivers in Colorado

USGS Publications Warehouse

Leib, Kenneth J.; Linard, Joshua I.; Williams, Cory A.

2012-01-01

Elevated loads of salt and selenium can impair the quality of water for both anthropogenic and natural uses. Understanding the environmental processes controlling how salt and selenium are introduced to streams is critical to managing and mitigating the effects of elevated loads. Dominant relations between salt and selenium loads and environmental characteristics can be established by using geospatial data. The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, investigated statistical relations between seasonal salt or selenium loads emanating from the Upper Colorado River Basin and geospatial data. Salt and selenium loads measured during the irrigation and nonirrigation seasons were related to geospatial variables for 168 subbasins within the Gunnison and Colorado River Basins. These geospatial variables represented subbasin characteristics of the physical environment, precipitation, geology, land use, and the irrigation network. All subbasin variables with units of area had statistically significant relations with load. The few variables that were not in units of area but were statistically significant helped to identify types of geospatial data that might influence salt and selenium loading. Following a stepwise approach, combinations of these statistically significant variables were used to develop multiple linear regression models. The models can be used to help prioritize areas where salt and selenium control projects might be most effective.

Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin

USGS Publications Warehouse

Tillman, Fred D.; Flynn, Marilyn E.; Anning, David W.

2015-01-01

In 2009, the U.S. Geological Survey (USGS) developed a Spatially Referenced Regressions on Watershed Attributes (SPARROW) surface-water quality model for the Upper Colorado River Basin (UCRB) relating dissolved-solids sources and transport in the 1991 water year to upstream catchment characteristics. The SPARROW model focused on geologic and agricultural sources of dissolved solids in the UCRB and was calibrated using water-year 1991 dissolved-solids loads from 218 monitoring sites. A new UCRB SPARROW model is planned that will update the investigation of dissolved-solids sources and transport in the basin to circa 2010 conditions and will improve upon the 2009 model by incorporating more detailed information about agricultural-irrigation and rangeland-management practices, among other improvements. Geospatial datasets relating to circa 2010 rangeland conditions are required for the new UCRB SPARROW modeling effort. This study compiled geospatial datasets for the UCRB that relate to the biotic alterations and rangeland conditions of grazing, fire and other land disturbance, and vegetation type and cover. Datasets representing abiotic alterations of access control (off-highway vehicles) and sediment generation and transport in general, were also compiled. These geospatial datasets may be tested in the upcoming SPARROW model to better understand the potential contribution of rangelands to dissolved-solids loading in UCRB streams.

A comparison of geospatially modeled fire behavior and fire management utility of three data sources in the southeastern United States

Treesearch

LaWen T. Hollingsworth; Laurie L. Kurth; Bernard R. Parresol; Roger D. Ottmar; Susan J. Prichard

2012-01-01

Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation...

Ready or Not? Assessing Change Readiness for Implementation of the Geospatial Technology Competency Model[c

ERIC Educational Resources Information Center

Annulis, Heather M.; Gaudet, Cyndi H.

2007-01-01

A shortage of a qualified and skilled workforce exists to meet the demands of the geospatial industry (NASA, 2002). Solving today's workforce issues requires new and innovative methods and techniques for this high growth, high technology industry. One tool to support workforce development is a competency model which can be used to build a…

A geospatial database model for the management of remote sensing datasets at multiple spectral, spatial, and temporal scales

NASA Astrophysics Data System (ADS)

Ifimov, Gabriela; Pigeau, Grace; Arroyo-Mora, J. Pablo; Soffer, Raymond; Leblanc, George

2017-10-01

In this study the development and implementation of a geospatial database model for the management of multiscale datasets encompassing airborne imagery and associated metadata is presented. To develop the multi-source geospatial database we have used a Relational Database Management System (RDBMS) on a Structure Query Language (SQL) server which was then integrated into ArcGIS and implemented as a geodatabase. The acquired datasets were compiled, standardized, and integrated into the RDBMS, where logical associations between different types of information were linked (e.g. location, date, and instrument). Airborne data, at different processing levels (digital numbers through geocorrected reflectance), were implemented in the geospatial database where the datasets are linked spatially and temporally. An example dataset consisting of airborne hyperspectral imagery, collected for inter and intra-annual vegetation characterization and detection of potential hydrocarbon seepage events over pipeline areas, is presented. Our work provides a model for the management of airborne imagery, which is a challenging aspect of data management in remote sensing, especially when large volumes of data are collected.

Geospatial optimization of siting large-scale solar projects

USGS Publications Warehouse

Macknick, Jordan; Quinby, Ted; Caulfield, Emmet; Gerritsen, Margot; Diffendorfer, James E.; Haines, Seth S.

2014-01-01

guidelines by being user-driven, transparent, interactive, capable of incorporating multiple criteria, and flexible. This work provides the foundation for a dynamic siting assistance tool that can greatly facilitate siting decisions among multiple stakeholders.

3D Geospatial Models for Visualization and Analysis of Groundwater Contamination at a Nuclear Materials Processing Facility

NASA Astrophysics Data System (ADS)

Stirewalt, G. L.; Shepherd, J. C.

2003-12-01

Analysis of hydrostratigraphy and uranium and nitrate contamination in groundwater at a former nuclear materials processing facility in Oklahoma were undertaken employing 3-dimensional (3D) geospatial modeling software. Models constructed played an important role in the regulatory decision process of the U.S. Nuclear Regulatory Commission (NRC) because they enabled visualization of temporal variations in contaminant concentrations and plume geometry. Three aquifer systems occur at the site, comprised of water-bearing fractured shales separated by indurated sandstone aquitards. The uppermost terrace groundwater system (TGWS) aquifer is composed of terrace and alluvial deposits and a basal shale. The shallow groundwater system (SGWS) aquifer is made up of three shale units and two sandstones. It is separated from the overlying TGWS and underlying deep groundwater system (DGWS) aquifer by sandstone aquitards. Spills of nitric acid solutions containing uranium and radioactive decay products around the main processing building (MPB), leakage from storage ponds west of the MPB, and leaching of radioactive materials from discarded equipment and waste containers contaminated both the TGWS and SGWS aquifers during facility operation between 1970 and 1993. Constructing 3D geospatial property models for analysis of groundwater contamination at the site involved use of EarthVision (EV), a 3D geospatial modeling software developed by Dynamic Graphics, Inc. of Alameda, CA. A viable 3D geohydrologic framework model was initially constructed so property data could be spatially located relative to subsurface geohydrologic units. The framework model contained three hydrostratigraphic zones equivalent to the TGWS, SGWS, and DGWS aquifers in which groundwater samples were collected, separated by two sandstone aquitards. Groundwater data collected in the three aquifer systems since 1991 indicated high concentrations of uranium (>10,000 micrograms/liter) and nitrate (> 500 milligrams/liter) around the MPB and elevated nitrate (> 2000 milligrams/ liter) around storage ponds. Vertical connectivity was suggested between the TGWS and SGWS, while the DGWS appeared relatively isolated from the overlying aquifers. Lateral movement of uranium was also suggested over time. For example, lateral migration in the TGWS is suggested along a shallow depression in the bedrock surface trending south-southwest from the southwest corner of the MPB. Another pathway atop the buried bedrock surface, trending west-northwest from the MPB and partially reflected by current surface topography, suggested lateral migration of nitrate in the SGWS. Lateral movement of nitrate in the SGWS was also indicated north, south, and west of the largest storage pond. Definition of contaminant plume movement over time is particularly important for assessing direction and rate of migration and the potential need for preventive measures to control contamination of groundwater outside facility property lines. The 3D geospatial property models proved invaluable for visualizing and analyzing variations in subsurface uranium and nitrate contamination in space and time within and between the three aquifers at the site. The models were an exceptional visualization tool for illustrating extent, volume, and quantitative amounts of uranium and nitrate contamination in the subsurface to regulatory decision-makers in regard to site decommissioning issues, including remediation concerns, providing a perspective not possible to achieve with traditional 2D maps. The geohydrologic framework model provides a conceptual model for consideration in flow and transport analyses.

GeoNotebook: Browser based Interactive analysis and visualization workflow for very large climate and geospatial datasets

NASA Astrophysics Data System (ADS)

Ozturk, D.; Chaudhary, A.; Votava, P.; Kotfila, C.

2016-12-01

Jointly developed by Kitware and NASA Ames, GeoNotebook is an open source tool designed to give the maximum amount of flexibility to analysts, while dramatically simplifying the process of exploring geospatially indexed datasets. Packages like Fiona (backed by GDAL), Shapely, Descartes, Geopandas, and PySAL provide a stack of technologies for reading, transforming, and analyzing geospatial data. Combined with the Jupyter notebook and libraries like matplotlib/Basemap it is possible to generate detailed geospatial visualizations. Unfortunately, visualizations generated is either static or does not perform well for very large datasets. Also, this setup requires a great deal of boilerplate code to create and maintain. Other extensions exist to remedy these problems, but they provide a separate map for each input cell and do not support map interactions that feed back into the python environment. To support interactive data exploration and visualization on large datasets we have developed an extension to the Jupyter notebook that provides a single dynamic map that can be managed from the Python environment, and that can communicate back with a server which can perform operations like data subsetting on a cloud-based cluster.

A Geospatial Semantic Enrichment and Query Service for Geotagged Photographs

PubMed Central

Ennis, Andrew; Nugent, Chris; Morrow, Philip; Chen, Liming; Ioannidis, George; Stan, Alexandru; Rachev, Preslav

2015-01-01

With the increasing abundance of technologies and smart devices, equipped with a multitude of sensors for sensing the environment around them, information creation and consumption has now become effortless. This, in particular, is the case for photographs with vast amounts being created and shared every day. For example, at the time of this writing, Instagram users upload 70 million photographs a day. Nevertheless, it still remains a challenge to discover the “right” information for the appropriate purpose. This paper describes an approach to create semantic geospatial metadata for photographs, which can facilitate photograph search and discovery. To achieve this we have developed and implemented a semantic geospatial data model by which a photograph can be enrich with geospatial metadata extracted from several geospatial data sources based on the raw low-level geo-metadata from a smartphone photograph. We present the details of our method and implementation for searching and querying the semantic geospatial metadata repository to enable a user or third party system to find the information they are looking for. PMID:26205265

The Role of Discrete Global Grid Systems in the Global Statistical Geospatial Framework

NASA Astrophysics Data System (ADS)

Purss, M. B. J.; Peterson, P.; Minchin, S. A.; Bermudez, L. E.

2016-12-01

The United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) has proposed the development of a Global Statistical Geospatial Framework (GSGF) as a mechanism for the establishment of common analytical systems that enable the integration of statistical and geospatial information. Conventional coordinate reference systems address the globe with a continuous field of points suitable for repeatable navigation and analytical geometry. While this continuous field is represented on a computer in a digitized and discrete fashion by tuples of fixed-precision floating point values, it is a non-trivial exercise to relate point observations spatially referenced in this way to areal coverages on the surface of the Earth. The GSGF states the need to move to gridded data delivery and the importance of using common geographies and geocoding. The challenges associated with meeting these goals are not new and there has been a significant effort within the geospatial community to develop nested gridding standards to tackle these issues over many years. These efforts have recently culminated in the development of a Discrete Global Grid Systems (DGGS) standard which has been developed under the auspices of Open Geospatial Consortium (OGC). DGGS provide a fixed areal based geospatial reference frame for the persistent location of measured Earth observations, feature interpretations, and modelled predictions. DGGS address the entire planet by partitioning it into a discrete hierarchical tessellation of progressively finer resolution cells, which are referenced by a unique index that facilitates rapid computation, query and analysis. The geometry and location of the cell is the principle aspect of a DGGS. Data integration, decomposition, and aggregation is optimised in the DGGS hierarchical structure and can be exploited for efficient multi-source data processing, storage, discovery, transmission, visualization, computation, analysis, and modelling. During the 6th Session of the UN-GGIM in August 2016 the role of DGGS in the context of the GSGF was formally acknowledged. This paper proposes to highlight the synergies and role of DGGS in the Global Statistical Geospatial Framework and to show examples of the use of DGGS to combine geospatial statistics with traditional geoscientific data.

Benefits of using Open Geo-spatial Data for valorization of Cultural Heritage: GeoPan app

NASA Astrophysics Data System (ADS)

Cuca, Branka; Previtali, Mattia; Barazzetti, Luigi; Brumana, Raffaella

2017-04-01

Experts evaluate the spatial data to be one of the categories of Public Sector Information (PSI), of which the exchange is particularly important. On the other side an initiative with a great vision such as Digital Agenda for Europe, emphasizes on intelligent processing of information as essential factor for tackling the challenges of the contemporary society. In such context, the Open Data are considered to be crucial in addressing, environmental pressures, energy efficiency issues, land use and climate change, pollution and traffic management. Furthermore, Open Data are thought to have an important impact on more informed decision making and policy creation for multiple domains that could be addressed even through "apps" of our smart devices. Activities performed in ENERGIC OD project - "European NEtwork for Redistributing Geospatial Information to user Communities - Open Data" have led to some first conclusions on the use and re-use of geo-spatial Open Data by means of Virtual Hubs - an innovative method for brokering of geo-spatial information. This paper illustrates some main benefits of using Open Geo-spatial Data for valorisation of Cultural Heritage through a case of an innovative app called "GeoPan Atl@s". GeoPan, inserted in a dynamic policy context described, aims to provide all information valuable for a sustainable territorial development in a common platform, in particular the material that regards history and changes of the cultural landscapes in Lombardy region. Furthermore, this innovative app is used as a test-bed to facilitate and encourage a more active exchange and exploitation of open geo-spatial information for purposes of valorisation of cultural heritage and landscapes. The aim of this practice is also to achieve a more active participation of experts, VGI communities and citizens and a higher awareness of the multiple use-possibilities of historic and contemporary geo-spatial information for smarter decision making.

Increasing the value of geospatial informatics with open approaches for Big Data

NASA Astrophysics Data System (ADS)

Percivall, G.; Bermudez, L. E.

2017-12-01

Open approaches to big data provide geoscientists with new capabilities to address problems of unmatched size and complexity. Consensus approaches for Big Geo Data have been addressed in multiple international workshops and testbeds organized by the Open Geospatial Consortium (OGC) in the past year. Participants came from government (NASA, ESA, USGS, NOAA, DOE); research (ORNL, NCSA, IU, JPL, CRIM, RENCI); industry (ESRI, Digital Globe, IBM, rasdaman); standards (JTC 1/NIST); and open source software communities. Results from the workshops and testbeds are documented in Testbed reports and a White Paper published by the OGC. The White Paper identifies the following set of use cases: Collection and Ingest: Remote sensed data processing; Data stream processing Prepare and Structure: SQL and NoSQL databases; Data linking; Feature identification Analytics and Visualization: Spatial-temporal analytics; Machine Learning; Data Exploration Modeling and Prediction: Integrated environmental models; Urban 4D models. Open implementations were developed in the Arctic Spatial Data Pilot using Discrete Global Grid Systems (DGGS) and in Testbeds using WPS and ESGF to publish climate predictions. Further development activities to advance open implementations of Big Geo Data include the following: Open Cloud Computing: Avoid vendor lock-in through API interoperability and Application portability. Open Source Extensions: Implement geospatial data representations in projects from Apache, Location Tech, and OSGeo. Investigate parallelization strategies for N-Dimensional spatial data. Geospatial Data Representations: Schemas to improve processing and analysis using geospatial concepts: Features, Coverages, DGGS. Use geospatial encodings like NetCDF and GeoPackge. Big Linked Geodata: Use linked data methods scaled to big geodata. Analysis Ready Data: Support "Download as last resort" and "Analytics as a service". Promote elements common to "datacubes."

Using Immersive Visualizations to Improve Decision Making and Enhancing Public Understanding of Earth Resource and Climate Issues

NASA Astrophysics Data System (ADS)

Yu, K. C.; Raynolds, R. G.; Dechesne, M.

2008-12-01

New visualization technologies, from ArcGIS to Google Earth, have allowed for the integration of complex, disparate data sets to produce visually rich and compelling three-dimensional models of sub-surface and surface resource distribution patterns. The rendering of these models allows the public to quickly understand complicated geospatial relationships that would otherwise take much longer to explain using traditional media. We have impacted the community through topical policy presentations at both state and city levels, adult education classes at the Denver Museum of Nature and Science (DMNS), and public lectures at DMNS. We have constructed three-dimensional models from well data and surface observations which allow policy makers to better understand the distribution of groundwater in sandstone aquifers of the Denver Basin. Our presentations to local governments in the Denver metro area have allowed resource managers to better project future ground water depletion patterns, and to encourage development of alternative sources. DMNS adult education classes on water resources, geography, and regional geology, as well as public lectures on global issues such as earthquakes, tsunamis, and resource depletion, have utilized the visualizations developed from these research models. In addition to presenting GIS models in traditional lectures, we have also made use of the immersive display capabilities of the digital "fulldome" Gates Planetarium at DMNS. The real-time Uniview visualization application installed at Gates was designed for teaching astronomy, but it can be re-purposed for displaying our model datasets in the context of the Earth's surface. The 17-meter diameter dome of the Gates Planetarium allows an audience to have an immersive experience---similar to virtual reality CAVEs employed by the oil exploration industry---that would otherwise not be available to the general public. Public lectures in the dome allow audiences of over 100 people to comprehend dynamically- changing geospatial datasets in an exciting and engaging fashion. In our presentation, we will demonstrate how new software tools like Uniview can be used to dramatically enhance and accelerate public comprehension of complex, multi-scale geospatial phenomena.

Mapping and monitoring of crop intensity, calendar and irrigation using multi-temporal MODIS data

NASA Astrophysics Data System (ADS)

Xiao, X.; Boes, S.; Mulukutla, G.; Proussevitch, A.; Routhier, M.

2005-12-01

Agriculture is the most extensive land use and water use on the Earth. Because of the diverse range of natural environments and human needs, agriculture is also the most complicated land use and water use system, which poses an enormous challenge to the scientific community, the public and decision-makers. Updated and geo-referenced information on crop intensity (number of crops per year), calendar (planting date, harvesting date) and irrigation is critically needed to better understand the impacts of agriculture on biogeochemical cycles (e.g., carbon, nitrogen, trace gases), water and climate dynamics. Here we present an effort to develop a novel approach for mapping and monitoring crop intensity, calendar and irrigation, using multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) image data. Our algorithm employed three vegetation indices that are sensitive to the seasonal dynamics of leaf area index, light absorption by leaf chlorophyll and land surface water content. Our objective is to generate geospatial databases of crop intensity, calendar and irrigation at 500-m spatial resolution and at 8-day temporal resolution. In this presentation, we report a preliminary geospatial dataset of paddy rice crop intensity, calendar and irrigation in Asia, which is developed from the 8-day composite images of MODIS in 2002. The resultant dataset could be used in many applications, including hydrological and climate modeling.

A geospatial soil-based DSS to reconcile landscape management and land protection

NASA Astrophysics Data System (ADS)

Manna, Piero; Basile, Angelo; Bonfante, Antonello; D'Antonio, Amedeo; De Michele, Carlo; Iamarino, Michela; Langella, Giuliano; Florindo Mileti, Antonio; Pileri, Paolo; Vingiani, Simona; Terribile, Fabio

2017-04-01

The implementation of UN Agenda 2030 may represent a great opportunity to place soil science at the hearth of many Sustainable Development Goals (e.g. SDGs 2, 3, 13, 15, 15.3, 16.7). On the other side the high complexity embedded in the factual implementation of SDG and many others ambitious objectives (e.g. FAO goals) may cause new frustrations if these policy documents will not bring real progresses. The scientific communities are asked to contribute to disentangle this complexity and possibly identifying a "way to go". This may help the large number of European directives (e.g. WFD, EIA), regulations and communications aiming to achieve a better environment but still facing large difficulties in their full implementation (e.g. COM2015/120; COM2013/683). This contribution has the motivation to provide a different perspective, thinking that the full implementation of SDGs and integrated land policies requires to challenge some key overlooked issues including full competence (and managing capability) about the landscape variability, its multi-functionalities (e.g. agriculture / environment) and its dynamic nature (many processes, including crops growth and fate of pollutants, are dynamic); moreover, it requires to support actions at a very detailed local scale since many processes and problems are site specific. The landscape and all the above issues have the soil as pulsing heart. Accordingly, we aim to demonstrate the multiple benefits in using a smart geoSpatial Decision Support System (S-DSS) grounded on soil modelling, called SOILCONSWEB (EU LIFE+ project and its extensions). It is a freely-accessible web platform based on a Geospatial Cyber-Infrastructure (GCI) and developed in Valle Telesina (South Italy) over an area of 20,000 ha. It supports a multilevel decision-making in agriculture and environment including the interaction with other land uses (such as landscape and urban planning) and thus it simultaneously delivers to SDGs 2, 3, 13, 15, 15.3, 16.7.

Integrating fire behavior models and geospatial analysis for wildland fire risk assessment and fuel management planning

Treesearch

Alan A. Ager; Nicole M. Vaillant; Mark A. Finney

2011-01-01

Wildland fire risk assessment and fuel management planning on federal lands in the US are complex problems that require state-of-the-art fire behavior modeling and intensive geospatial analyses. Fuel management is a particularly complicated process where the benefits and potential impacts of fuel treatments must be demonstrated in the context of land management goals...

Dynamic modeling of Tampa Bay urban development using parallel computing

USGS Publications Warehouse

Xian, G.; Crane, M.; Steinwand, D.

2005-01-01

Urban land use and land cover has changed significantly in the environs of Tampa Bay, Florida, over the past 50 years. Extensive urbanization has created substantial change to the region's landscape and ecosystems. This paper uses a dynamic urban-growth model, SLEUTH, which applies six geospatial data themes (slope, land use, exclusion, urban extent, transportation, hillside), to study the process of urbanization and associated land use and land cover change in the Tampa Bay area. To reduce processing time and complete the modeling process within an acceptable period, the model is recoded and ported to a Beowulf cluster. The parallel-processing computer system accomplishes the massive amount of computation the modeling simulation requires. SLEUTH calibration process for the Tampa Bay urban growth simulation spends only 10 h CPU time. The model predicts future land use/cover change trends for Tampa Bay from 1992 to 2025. Urban extent is predicted to double in the Tampa Bay watershed between 1992 and 2025. Results show an upward trend of urbanization at the expense of a decline of 58% and 80% in agriculture and forested lands, respectively.

Combining multiple approaches and optimized data resolution for an improved understanding of stream temperature dynamics of a forested headwater basin in the Southern Appalachians

NASA Astrophysics Data System (ADS)

Belica, L.; Mitasova, H.; Caldwell, P.; McCarter, J. B.; Nelson, S. A. C.

2017-12-01

Thermal regimes of forested headwater streams continue to be an area of active research as climatic, hydrologic, and land cover changes can influence water temperature, a key aspect of aquatic ecosystems. Widespread monitoring of stream temperatures have provided an important data source, yielding insights on the temporal and spatial patterns and the underlying processes that influence stream temperature. However, small forested streams remain challenging to model due to the high spatial and temporal variability of stream temperatures and the climatic and hydrologic conditions that drive them. Technological advances and increased computational power continue to provide new tools and measurement methods and have allowed spatially explicit analyses of dynamic natural systems at greater temporal resolutions than previously possible. With the goal of understanding how current stream temperature patterns and processes may respond to changing landcover and hydroclimatoligical conditions, we combined high-resolution, spatially explicit geospatial modeling with deterministic heat flux modeling approaches using data sources that ranged from traditional hydrological and climatological measurements to emerging remote sensing techniques. Initial analyses of stream temperature monitoring data revealed that high temporal resolution (5 minutes) and measurement resolutions (<0.1°C) were needed to adequately describe diel stream temperature patterns and capture the differences between paired 1st order and 4th order forest streams draining north and south facing slopes. This finding along with geospatial models of subcanopy solar radiation and channel morphology were used to develop hypotheses and guide field data collection for further heat flux modeling. By integrating multiple approaches and optimizing data resolution for the processes being investigated, small, but ecologically significant differences in stream thermal regimes were revealed. In this case, multi-approach research contributed to the identification of the dominant mechanisms driving stream temperature in the study area and advanced our understanding of the current thermal fluxes and how they may change as environmental conditions change in the future.

To ontologise or not to ontologise: An information model for a geospatial knowledge infrastructure

NASA Astrophysics Data System (ADS)

Stock, Kristin; Stojanovic, Tim; Reitsma, Femke; Ou, Yang; Bishr, Mohamed; Ortmann, Jens; Robertson, Anne

2012-08-01

A geospatial knowledge infrastructure consists of a set of interoperable components, including software, information, hardware, procedures and standards, that work together to support advanced discovery and creation of geoscientific resources, including publications, data sets and web services. The focus of the work presented is the development of such an infrastructure for resource discovery. Advanced resource discovery is intended to support scientists in finding resources that meet their needs, and focuses on representing the semantic details of the scientific resources, including the detailed aspects of the science that led to the resource being created. This paper describes an information model for a geospatial knowledge infrastructure that uses ontologies to represent these semantic details, including knowledge about domain concepts, the scientific elements of the resource (analysis methods, theories and scientific processes) and web services. This semantic information can be used to enable more intelligent search over scientific resources, and to support new ways to infer and visualise scientific knowledge. The work describes the requirements for semantic support of a knowledge infrastructure, and analyses the different options for information storage based on the twin goals of semantic richness and syntactic interoperability to allow communication between different infrastructures. Such interoperability is achieved by the use of open standards, and the architecture of the knowledge infrastructure adopts such standards, particularly from the geospatial community. The paper then describes an information model that uses a range of different types of ontologies, explaining those ontologies and their content. The information model was successfully implemented in a working geospatial knowledge infrastructure, but the evaluation identified some issues in creating the ontologies.

Lowering the barriers for accessing distributed geospatial big data to advance spatial data science: the PolarHub solution

NASA Astrophysics Data System (ADS)

Li, W.

2017-12-01

Data is the crux of science. The widespread availability of big data today is of particular importance for fostering new forms of geospatial innovation. This paper reports a state-of-the-art solution that addresses a key cyberinfrastructure research problem—providing ready access to big, distributed geospatial data resources on the Web. We first formulate this data-access problem and introduce its indispensable elements, including identifying the cyber-location, space and time coverage, theme, and quality of the dataset. We then propose strategies to tackle each data-access issue and make the data more discoverable and usable for geospatial data users and decision makers. Among these strategies is large-scale web crawling as a key technique to support automatic collection of online geospatial data that are highly distributed, intrinsically heterogeneous, and known to be dynamic. To better understand the content and scientific meanings of the data, methods including space-time filtering, ontology-based thematic classification, and service quality evaluation are incorporated. To serve a broad scientific user community, these techniques are integrated into an operational data crawling system, PolarHub, which is also an important cyberinfrastructure building block to support effective data discovery. A series of experiments were conducted to demonstrate the outstanding performance of the PolarHub system. We expect this work to contribute significantly in building the theoretical and methodological foundation for data-driven geography and the emerging spatial data science.

Nicholas Gilroy | NREL

Science.gov Websites

Nicholas Gilroy desc Nicholas Gilroy Geospatial Data Scientist II Nicholas.Gilroy@nrel.gov | 303 -384-7354 Nicholas Gilroy is a member of the Geospatial Data Science team within the Systems Modeling (AAG) Featured Publications Veda, Santosh, Zhang, Yingchen, Tan, Jin, Chartan, Erol Kevin, Gilroy

Ricardo Oliveira | NREL

Science.gov Websites

the System Modeling & Geospatial Data Science Group in the Strategic Energy Analysis Center. Areas Publications Oliveira, R and Moreno, R. 2016. Harvesting, Integrating and Distributing Large Open Geospatial Datasets Using Free and Open-Source Software. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7

Representation of activity in images using geospatial temporal graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brost, Randolph; McLendon, III, William C.; Parekh, Ojas D.

Various technologies pertaining to modeling patterns of activity observed in remote sensing images using geospatial-temporal graphs are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Activity patterns may be discerned from the graphs by coding nodes representing persistent objects like buildings differently from nodes representing ephemeral objects like vehicles, and examining the geospatial-temporal relationships of ephemeral nodes within the graph.

Geospatial clustering in sugar-sweetened beverage consumption among Boston youth.

PubMed

Tamura, Kosuke; Duncan, Dustin T; Athens, Jessica K; Bragg, Marie A; Rienti, Michael; Aldstadt, Jared; Scott, Marc A; Elbel, Brian

2017-09-01

The objective was to detect geospatial clustering of sugar-sweetened beverage (SSB) intake in Boston adolescents (age = 16.3 ± 1.3 years [range: 13-19]; female = 56.1%; White = 10.4%, Black = 42.6%, Hispanics = 32.4%, and others = 14.6%) using spatial scan statistics. We used data on self-reported SSB intake from the 2008 Boston Youth Survey Geospatial Dataset (n = 1292). Two binary variables were created: consumption of SSB (never versus any) on (1) soda and (2) other sugary drinks (e.g., lemonade). A Bernoulli spatial scan statistic was used to identify geospatial clusters of soda and other sugary drinks in unadjusted models and models adjusted for age, gender, and race/ethnicity. There was no statistically significant clustering of soda consumption in the unadjusted model. In contrast, a cluster of non-soda SSB consumption emerged in the middle of Boston (relative risk = 1.20, p = .005), indicating that adolescents within the cluster had a 20% higher probability of reporting non-soda SSB intake than outside the cluster. The cluster was no longer significant in the adjusted model, suggesting spatial variation in non-soda SSB drink intake correlates with the geographic distribution of students by race/ethnicity, age, and gender.

GISpark: A Geospatial Distributed Computing Platform for Spatiotemporal Big Data

NASA Astrophysics Data System (ADS)

Wang, S.; Zhong, E.; Wang, E.; Zhong, Y.; Cai, W.; Li, S.; Gao, S.

2016-12-01

Geospatial data are growing exponentially because of the proliferation of cost effective and ubiquitous positioning technologies such as global remote-sensing satellites and location-based devices. Analyzing large amounts of geospatial data can provide great value for both industrial and scientific applications. Data- and compute- intensive characteristics inherent in geospatial big data increasingly pose great challenges to technologies of data storing, computing and analyzing. Such challenges require a scalable and efficient architecture that can store, query, analyze, and visualize large-scale spatiotemporal data. Therefore, we developed GISpark - a geospatial distributed computing platform for processing large-scale vector, raster and stream data. GISpark is constructed based on the latest virtualized computing infrastructures and distributed computing architecture. OpenStack and Docker are used to build multi-user hosting cloud computing infrastructure for GISpark. The virtual storage systems such as HDFS, Ceph, MongoDB are combined and adopted for spatiotemporal data storage management. Spark-based algorithm framework is developed for efficient parallel computing. Within this framework, SuperMap GIScript and various open-source GIS libraries can be integrated into GISpark. GISpark can also integrated with scientific computing environment (e.g., Anaconda), interactive computing web applications (e.g., Jupyter notebook), and machine learning tools (e.g., TensorFlow/Orange). The associated geospatial facilities of GISpark in conjunction with the scientific computing environment, exploratory spatial data analysis tools, temporal data management and analysis systems make up a powerful geospatial computing tool. GISpark not only provides spatiotemporal big data processing capacity in the geospatial field, but also provides spatiotemporal computational model and advanced geospatial visualization tools that deals with other domains related with spatial property. We tested the performance of the platform based on taxi trajectory analysis. Results suggested that GISpark achieves excellent run time performance in spatiotemporal big data applications.

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT (AGWA): A GIS-BASED HYDROLOGIC MODELING TOOL FOR WATERSHED ASSESSMENT AND ANALYSIS

EPA Science Inventory

The Automated Geospatial Watershed Assessment tool (AGWA) is a GIS interface jointly developed by the USDA Agricultural Research Service, the U.S. Environmental Protection Agency, the University of Arizona, and the University of Wyoming to automate the parameterization and execu...

ADDING GLOBAL SOILS DATA TO THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT TOOL (AGWA)

EPA Science Inventory

The Automated Geospatial Watershed Assessment Tool (AGWA) is a GIS-based hydrologic modeling tool that is available as an extension for ArcView 3.x from the USDA-ARS Southwest Watershed Research Center (www.tucson.ars.ag.gov/agwa). AGWA is designed to facilitate the assessment of...

Data Visualization and Geospatial Tools | Geospatial Data Science | NREL

Science.gov Websites

renewable resources are available in a specific areas. General Analysis Renewable Energy Atlas View the geographic distribution of wind, solar, geothermal, hydropower, and biomass resources in the United States . Solar and Wind Energy Resource Assessment (SWERA) Model Access international renewable energy resource

Meghan Mooney | NREL

Science.gov Websites

@nrel.gov | 303-384-7315 Meghan Mooney is a member of the Geospatial Data Science team within the Systems Modeling & Geospatial Data Science Group in the Strategic Energy Analysis Center. Areas of Expertise and resiliency Education M.A., Geography, University of Denver B.S., Geographic Science, James Madison

Tiered Internship Model for Undergraduate Students in Geospatial Science and Technology

ERIC Educational Resources Information Center

Kopteva, Irina A.; Arkowski, Donna; Craft, Elaine L.

2015-01-01

This article discusses the development, implementation, and evaluation of a tiered internship program for undergraduate students in geospatial science and technology (TIMSGeoTech). The internship program assists education programs in providing skill development that is relevant and useful, and it aligns graduates and their skills with industry…

Predicting breeding habitat for amphibians: a spatiotemporal analysis across Yellowstone National Park

USGS Publications Warehouse

Bartelt, Paul E.; Gallant, Alisa L.; Klaver, Robert W.; Wright, Christopher K.; Patla, Debra A.; Peterson, Charles R.

2011-01-01

The ability to predict amphibian breeding across landscapes is important for informing land management decisions and helping biologists better understand and remediate factors contributing to declines in amphibian populations. We built geospatial models of likely breeding habitats for each of four amphibian species that breed in Yellowstone National Park (YNP). We used field data collected in 2000-2002 from 497 sites among 16 basins and predictor variables from geospatial models produced from remotely sensed data (e.g., digital elevation model, complex topographic index, landform data, wetland probabililty, and vegetative cover). Except for 31 sites in one basin that were surveyed in both 2000 and 2002, all sites were surveyed once. We used polytomous regression to build statistical models for each species of amphibian from 1) field survey site data only, 2) field data combined with data from geospatial models, and 3) data from geospatial models only. Based on measures of receiver operating characteristic (ROC) scores, models of the second type best explained likely breeding habitat because they contained the most information (ROC values ranged from 0.70 - 0.88). However, models of the third type could be applied to the entire YNP landscape and produced maps that could be verified with reserve field data. Accuracy rates for models built for single years were highly variable, ranging from 0.30 to 0.78. Accuracy rates for models built with data combined from multiple years were higher and less variable, ranging from 0.60 to 0.80. Combining results from the geospatial multiyear models yielded maps of "core" breeding areas (areas with high probability values for all three years) surrounded by areas that scored high for only one or two years, providing an estimate of variability among years. Such information can highlight landscape options for amphibian conservation. For example, our models identify alternative for areas that could be protected for each species, including 6828-10 764 ha for tiger salamanders; 971-3017 ha for western toads; 4732-16 696 ha for boreal chorus frogs; 4940-19 690 hectares for Columbia spotted frogs.

Predicting breeding habitat for amphibians: A spatiotemporal analysis across Yellowstone National Park

USGS Publications Warehouse

Bartelt, Paul E.; Gallant, Alisa L.; Klaver, Robert W.; Wright, C.K.; Patla, Debra A.; Peterson, Charles R.

2011-01-01

The ability to predict amphibian breeding across landscapes is important for informing land management decisions and helping biologists better understand and remediate factors contributing to declines in amphibian populations. We built geospatial models of likely breeding habitats for each of four amphibian species that breed in Yellowstone National Park (YNP). We used field data collected in 2000-2002 from 497 sites among 16 basins and predictor variables from geospatial models produced from remotely sensed data (e.g., digital elevation model, complex topographic index, landform data, wetland probability, and vegetative cover). Except for 31 sites in one basin that were surveyed in both 2000 and 2002, all sites were surveyed once. We used polytomous regression to build statistical models for each species of amphibian from (1) field survey site data only, (2) field data combined with data from geospatial models, and (3) data from geospatial models only. Based on measures of receiver operating characteristic (ROC) scores, models of the second type best explained likely breeding habitat because they contained the most information (ROC values ranged from 0.70 to 0.88). However, models of the third type could be applied to the entire YNP landscape and produced maps that could be verified with reserve field data. Accuracy rates for models built for single years were highly variable, ranging from 0.30 to 0.78. Accuracy rates for models built with data combined from multiple years were higher and less variable, ranging from 0.60 to 0.80. Combining results from the geospatial multiyear models yielded maps of "core" breeding areas (areas with high probability values for all three years) surrounded by areas that scored high for only one or two years, providing an estimate of variability among years. Such information can highlight landscape options for amphibian conservation. For example, our models identify alternative areas that could be protected for each species, including 6828-10 764 ha for tiger salamanders, 971-3017 ha for western toads, 4732-16 696 ha for boreal chorus frogs, and 4940-19 690 ha for Columbia spotted frogs. ?? 2011 by the Ecological Society of America.

Predicting breeding habitat for amphibians: a spatiotemporal analysis across Yellowstone National Park.

PubMed

Bartelt, Paul E; Gallant, Alisa L; Klaver, Robert W; Wright, Chris K; Patla, Debra A; Peterson, Charles R

2011-10-01

The ability to predict amphibian breeding across landscapes is important for informing land management decisions and helping biologists better understand and remediate factors contributing to declines in amphibian populations. We built geospatial models of likely breeding habitats for each of four amphibian species that breed in Yellowstone National Park (YNP). We used field data collected in 2000-2002 from 497 sites among 16 basins and predictor variables from geospatial models produced from remotely sensed data (e.g., digital elevation model, complex topographic index, landform data, wetland probability, and vegetative cover). Except for 31 sites in one basin that were surveyed in both 2000 and 2002, all sites were surveyed once. We used polytomous regression to build statistical models for each species of amphibian from (1) field survey site data only, (2) field data combined with data from geospatial models, and (3) data from geospatial models only. Based on measures of receiver operating characteristic (ROC) scores, models of the second type best explained likely breeding habitat because they contained the most information (ROC values ranged from 0.70 to 0.88). However, models of the third type could be applied to the entire YNP landscape and produced maps that could be verified with reserve field data. Accuracy rates for models built for single years were highly variable, ranging from 0.30 to 0.78. Accuracy rates for models built with data combined from multiple years were higher and less variable, ranging from 0.60 to 0.80. Combining results from the geospatial multiyear models yielded maps of "core" breeding areas (areas with high probability values for all three years) surrounded by areas that scored high for only one or two years, providing an estimate of variability among years. Such information can highlight landscape options for amphibian conservation. For example, our models identify alternative areas that could be protected for each species, including 6828-10 764 ha for tiger salamanders, 971-3017 ha for western toads, 4732-16 696 ha for boreal chorus frogs, and 4940-19 690 ha for Columbia spotted frogs.

Geospatial Technology and Geosciences - Defining the skills and competencies in the geosciences needed to effectively use the technology (Invited)

NASA Astrophysics Data System (ADS)

Johnson, A.

2010-12-01

Maps, spatial and temporal data and their use in analysis and visualization are integral components for studies in the geosciences. With the emergence of geospatial technology (Geographic Information Systems (GIS), remote sensing and imagery, Global Positioning Systems (GPS) and mobile technologies) scientists and the geosciences user community are now able to more easily accessed and share data, analyze their data and present their results. Educators are also incorporating geospatial technology into their geosciences programs by including an awareness of the technology in introductory courses to advanced courses exploring the capabilities to help answer complex questions in the geosciences. This paper will look how the new Geospatial Technology Competency Model from the Department of Labor can help ensure that geosciences programs address the skills and competencies identified by the workforce for geospatial technology as well as look at new tools created by the GeoTech Center to help do self and program assessments.

Assessment of economically optimal water management and geospatial potential for large-scale water storage

NASA Astrophysics Data System (ADS)

Weerasinghe, Harshi; Schneider, Uwe A.

2010-05-01

Assessment of economically optimal water management and geospatial potential for large-scale water storage Weerasinghe, Harshi; Schneider, Uwe A Water is an essential but limited and vulnerable resource for all socio-economic development and for maintaining healthy ecosystems. Water scarcity accelerated due to population expansion, improved living standards, and rapid growth in economic activities, has profound environmental and social implications. These include severe environmental degradation, declining groundwater levels, and increasing problems of water conflicts. Water scarcity is predicted to be one of the key factors limiting development in the 21st century. Climate scientists have projected spatial and temporal changes in precipitation and changes in the probability of intense floods and droughts in the future. As scarcity of accessible and usable water increases, demand for efficient water management and adaptation strategies increases as well. Addressing water scarcity requires an intersectoral and multidisciplinary approach in managing water resources. This would in return safeguard the social welfare and the economical benefit to be at their optimal balance without compromising the sustainability of ecosystems. This paper presents a geographically explicit method to assess the potential for water storage with reservoirs and a dynamic model that identifies the dimensions and material requirements under an economically optimal water management plan. The methodology is applied to the Elbe and Nile river basins. Input data for geospatial analysis at watershed level are taken from global data repositories and include data on elevation, rainfall, soil texture, soil depth, drainage, land use and land cover; which are then downscaled to 1km spatial resolution. Runoff potential for different combinations of land use and hydraulic soil groups and for mean annual precipitation levels are derived by the SCS-CN method. Using the overlay and decision tree algorithms in GIS, potential water storage sites are identified for constructing regional reservoirs. Subsequently, sites are prioritized based on runoff generation potential (m3 per unit area), and geographical suitability for constructing storage structures. The results from the spatial analysis are used as input for the optimization model. Allocation of resources and appropriate dimension for dams and associated structures are identified using the optimization model. The model evaluates the capability of alternative reservoirs for cost-efficient water management. The Geographic Information System is used to store, analyze, and integrate spatially explicit and non-spatial attribute information whereas the algebraic modeling platform is used to develop the dynamic optimization model. The results of this methodology are validated over space against satellite remote sensing data and existing data on reservoir capacities and runoff. The method is suitable for application of on-farm water storage structures, water distribution networks, and moisture conservation structures in a global context.

A spatial information crawler for OpenGIS WFS

NASA Astrophysics Data System (ADS)

Jiang, Jun; Yang, Chong-jun; Ren, Ying-chao

2008-10-01

The growth of the internet makes it non-trivial to search for the accuracy information efficiently. Topical crawler, which is aiming at a certain area, attracts more and more intention now because it can help people to find out what they need. Furthermore, with the OpenGIS WFS (Web Feature Service) Specification developed by OGC (Open GIS Consortium), much more geospatial data providers adopt this protocol to publish their data on the internet. In this case, a crawler which is aiming at the WFS servers can help people to find the geospatial data from WFS servers. In this paper, we propose a prototype system of a WFS crawler based on the OpenGIS WFS Specification. The crawler architecture, working principles, and detailed function of each component are introduced. This crawler is capable of discovering WFS servers dynamically, saving and updating the service contents of the servers. The data collect by the crawler can be supported to a geospatial data search engine as its data source.

Mapping the world: cartographic and geographic visualization by the United Nations Geospatial Information Section (formerly Cartographic Section)

NASA Astrophysics Data System (ADS)

Kagawa, Ayako; Le Sourd, Guillaume

2018-05-01

United Nations Secretariat activities, mapping began in 1946, and by 1951, the need for maps increased and an office with a team of cartographers was established. Since then, with the development of technologies including internet, remote sensing, unmanned aerial systems, relationship database management and information systems, geospatial information provides an ever-increasing variation of support to the work of the Organization for planning of operations, decision-making and monitoring of crises. However, the need for maps has remained intact. This presentation aims to highlight some of the cartographic representation styles over the decades by reviewing the evolution of selected maps by the office, and noting the changing cognitive and semiotic aspects of cartographic and geographic visualization required by the United Nations. Through presentation and analysis of these maps, the changing dynamics of the Organization in information management can be reflected, with a reminder of the continuing and expanding deconstructionist role of a cartographer, now geospatial information management experts.

Large Scale Analysis of Geospatial Data with Dask and XArray

NASA Astrophysics Data System (ADS)

Zender, C. S.; Hamman, J.; Abernathey, R.; Evans, K. J.; Rocklin, M.; Zender, C. S.; Rocklin, M.

2017-12-01

The analysis of geospatial data with high level languages has acceleratedinnovation and the impact of existing data resources. However, as datasetsgrow beyond single-machine memory, data structures within these high levellanguages can become a bottleneck. New libraries like Dask and XArray resolve some of these scalability issues,providing interactive workflows that are both familiar tohigh-level-language researchers while also scaling out to much largerdatasets. This broadens the access of researchers to larger datasets on highperformance computers and, through interactive development, reducestime-to-insight when compared to traditional parallel programming techniques(MPI). This talk describes Dask, a distributed dynamic task scheduler, Dask.array, amulti-dimensional array that copies the popular NumPy interface, and XArray,a library that wraps NumPy/Dask.array with labeled and indexes axes,implementing the CF conventions. We discuss both the basic design of theselibraries and how they change interactive analysis of geospatial data, and alsorecent benefits and challenges of distributed computing on clusters ofmachines.

A Practice Approach of Multi-source Geospatial Data Integration for Web-based Geoinformation Services

NASA Astrophysics Data System (ADS)

Huang, W.; Jiang, J.; Zha, Z.; Zhang, H.; Wang, C.; Zhang, J.

2014-04-01

Geospatial data resources are the foundation of the construction of geo portal which is designed to provide online geoinformation services for the government, enterprise and public. It is vital to keep geospatial data fresh, accurate and comprehensive in order to satisfy the requirements of application and development of geographic location, route navigation, geo search and so on. One of the major problems we are facing is data acquisition. For us, integrating multi-sources geospatial data is the mainly means of data acquisition. This paper introduced a practice integration approach of multi-source geospatial data with different data model, structure and format, which provided the construction of National Geospatial Information Service Platform of China (NGISP) with effective technical supports. NGISP is the China's official geo portal which provides online geoinformation services based on internet, e-government network and classified network. Within the NGISP architecture, there are three kinds of nodes: national, provincial and municipal. Therefore, the geospatial data is from these nodes and the different datasets are heterogeneous. According to the results of analysis of the heterogeneous datasets, the first thing we do is to define the basic principles of data fusion, including following aspects: 1. location precision; 2.geometric representation; 3. up-to-date state; 4. attribute values; and 5. spatial relationship. Then the technical procedure is researched and the method that used to process different categories of features such as road, railway, boundary, river, settlement and building is proposed based on the principles. A case study in Jiangsu province demonstrated the applicability of the principle, procedure and method of multi-source geospatial data integration.

The Geoinformatica free and open source software stack

NASA Astrophysics Data System (ADS)

Jolma, A.

2012-04-01

The Geoinformatica free and open source software (FOSS) stack is based mainly on three established FOSS components, namely GDAL, GTK+, and Perl. GDAL provides access to a very large selection of geospatial data formats and data sources, a generic geospatial data model, and a large collection of geospatial analytical and processing functionality. GTK+ and the Cairo graphics library provide generic graphics and graphical user interface capabilities. Perl is a programming language, for which there is a very large set of FOSS modules for a wide range of purposes and which can be used as an integrative tool for building applications. In the Geoinformatica stack, data storages such as FOSS RDBMS PostgreSQL with its geospatial extension PostGIS can be used below the three above mentioned components. The top layer of Geoinformatica consists of a C library and several Perl modules. The C library comprises a general purpose raster algebra library, hydrological terrain analysis functions, and visualization code. The Perl modules define a generic visualized geospatial data layer and subclasses for raster and vector data and graphs. The hydrological terrain functions are already rather old and they suffer for example from the requirement of in-memory rasters. Newer research conducted using the platform include basic geospatial simulation modeling, visualization of ecological data, linking with a Bayesian network engine for spatial risk assessment in coastal areas, and developing standards-based distributed water resources information systems in Internet. The Geoinformatica stack constitutes a platform for geospatial research, which is targeted towards custom analytical tools, prototyping and linking with external libraries. Writing custom analytical tools is supported by the Perl language and the large collection of tools that are available especially in GDAL and Perl modules. Prototyping is supported by the GTK+ library, the GUI tools, and the support for object-oriented programming in Perl. New feature types, geospatial layer classes, and tools as extensions with specific features can be defined, used, and studied. Linking with external libraries is possible using the Perl foreign function interface tools or with generic tools such as Swig. We are interested in implementing and testing linking Geoinformatica with existing or new more specific hydrological FOSS.

WC WAVE - Integrating Diverse Hydrological-Modeling Data and Services Into an Interoperable Geospatial Infrastructure

NASA Astrophysics Data System (ADS)

Hudspeth, W. B.; Baros, S.; Barrett, H.; Savickas, J.; Erickson, J.

2015-12-01

WC WAVE (Western Consortium for Watershed Analysis, Visualization and Exploration) is a collaborative research project between the states of Idaho, Nevada, and New Mexico that is funded under the National Science Foundation's Experimental Program to Stimulate Competitive Research (EPSCoR). The goal of the project is to understand and document the effects of climate change on interactions between precipitation, vegetation growth, soil moisture and other landscape properties. These interactions are modeled within a framework we refer to as a virtual watershed (VW), a computer infrastructure that simulates watershed dynamics by linking scientific modeling, visualization, and data management components into a coherent whole. Developed and hosted at the Earth Data Analysis Center, University of New Mexico, the virtual watershed has a number of core functions which include: a) streamlined access to data required for model initialization and boundary conditions; b) the development of analytic scenarios through interactive visualization of available data and the storage of model configuration options; c) coupling of hydrological models through the rapid assimilation of model outputs into the data management system for access and use by sequent models. The WC-WAVE virtual watershed accomplishes these functions by provision of large-scale vector and raster data discovery, subsetting, and delivery via Open Geospatial Consortium (OGC) and REST web service standards. Central to the virtual watershed is the design and use of an innovative array of metadata elements that permits the stepwise coupling of diverse hydrological models (e.g. ISNOBAL, PRMS, CASiMiR) and input data to rapidly assess variation in outcomes under different climatic conditions. We present details on the architecture and functionality of the virtual watershed, results from three western U.S. watersheds, and discuss the realized benefits to watershed science of employing this integrated solution.

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT (AGWA): A GIS-BASED HYRDOLOGIC MODELING TOOL FOR WATERSHED ASSESSMENT AND ANALYSIS

EPA Science Inventory

The Automated Geospatial Watershed Assessment tool (AGWA) is a GIS interface jointly

developed by the USDA Agricultural Research Service, the U.S. Environmental Protection

Agency, the University of Arizona, and the University of Wyoming to automate the

parame...

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT (AGWA): A GIS-BASED HYDROLOGICAL MODELING TOOL FOR WATERSHED MANAGEMENT AND LANDSCAPE ASSESSMENT

EPA Science Inventory

The Automated Geospatial Watershed Assessment (http://www.epa.gov/nerlesd1/land-sci/agwa/introduction.htm and www.tucson.ars.ag.gov/agwa) tool is a GIS interface jointly developed by the U.S. Environmental Protection Agency, USDA-Agricultural Research Service, and the University ...

Representing Geospatial Environment Observation Capability Information: A Case Study of Managing Flood Monitoring Sensors in the Jinsha River Basin

PubMed Central

Hu, Chuli; Guan, Qingfeng; Li, Jie; Wang, Ke; Chen, Nengcheng

2016-01-01

Sensor inquirers cannot understand comprehensive or accurate observation capability information because current observation capability modeling does not consider the union of multiple sensors nor the effect of geospatial environmental features on the observation capability of sensors. These limitations result in a failure to discover credible sensors or plan for their collaboration for environmental monitoring. The Geospatial Environmental Observation Capability (GEOC) is proposed in this study and can be used as an information basis for the reliable discovery and collaborative planning of multiple environmental sensors. A field-based GEOC (GEOCF) information representation model is built. Quintuple GEOCF feature components and two GEOCF operations are formulated based on the geospatial field conceptual framework. The proposed GEOCF markup language is used to formalize the proposed GEOCF. A prototype system called GEOCapabilityManager is developed, and a case study is conducted for flood observation in the lower reaches of the Jinsha River Basin. The applicability of the GEOCF is verified through the reliable discovery of flood monitoring sensors and planning for the collaboration of these sensors. PMID:27999247

Representing Geospatial Environment Observation Capability Information: A Case Study of Managing Flood Monitoring Sensors in the Jinsha River Basin.

PubMed

Hu, Chuli; Guan, Qingfeng; Li, Jie; Wang, Ke; Chen, Nengcheng

2016-12-16

Sensor inquirers cannot understand comprehensive or accurate observation capability information because current observation capability modeling does not consider the union of multiple sensors nor the effect of geospatial environmental features on the observation capability of sensors. These limitations result in a failure to discover credible sensors or plan for their collaboration for environmental monitoring. The Geospatial Environmental Observation Capability (GEOC) is proposed in this study and can be used as an information basis for the reliable discovery and collaborative planning of multiple environmental sensors. A field-based GEOC (GEOCF) information representation model is built. Quintuple GEOCF feature components and two GEOCF operations are formulated based on the geospatial field conceptual framework. The proposed GEOCF markup language is used to formalize the proposed GEOCF. A prototype system called GEOCapabilityManager is developed, and a case study is conducted for flood observation in the lower reaches of the Jinsha River Basin. The applicability of the GEOCF is verified through the reliable discovery of flood monitoring sensors and planning for the collaboration of these sensors.

Insights into lahar deposition processes in the Curah Lengkong (Semeru Volcano, Indonesia) using photogrammetry-based geospatial analysis, near-surface geophysics and CFD modelling

NASA Astrophysics Data System (ADS)

Gomez, C.; Lavigne, F.; Sri Hadmoko, D.; Wassmer, P.

2018-03-01

Semeru Volcano is an active stratovolcano located in East Java (Indonesia), where historic lava flows, occasional pyroclastic flows and vulcanian explosions (on average every 5 min to 15 min) generate a stock of material that is remobilized by lahars, mostly occurring during the rainy season between October and March. Every year, several lahars flow down the Curah Lengkong Valley on the South-east flank of the volcano, where numerous lahar studies have been conducted. In the present contribution, the objective was to study the spatial distribution of boulder-size clasts and try to understand how this distribution relates to the valley morphology and to the dynamic and deposition dynamic of lahars. To achieve this objective, the method relies on a combination of (1) aerial photogrammetry-derived geospatial data on boulders' distribution, (2) ground penetrating radar data collected along a 2 km series of transects and (3) a CFD model of flow to analyse the results from the deposits. Results show that <1 m diameter boulders are evenly distributed along the channel, but that lava flow deposits visible at the surface of the river bed and SABO dams increase the concentration of clasts upstream of their position. Lateral input of boulders from collapsing lava-flow deposits can bring outsized clasts in the system that tend to become trapped at one location. Finally, the comparison between the CFD simulation and previous research using video imagery of lahars put the emphasis the fact that there is no direct link between the sedimentary units observed in the field and the flow that deposited them. Both grain size, flow orientation, matrix characteristics can be very different in a deposit for one single flow, even in confined channels like the Curah Lengkong.

Footprint of recycled water subsidies downwind of Lake Michigan

USDA-ARS?s Scientific Manuscript database

Continental evaporation is a significant and dynamic flux within the atmospheric water budget, but few methods provide robust observational constraints on the large-scale hydroclimatological and hydroecological impacts of this ‘recycled-water’ flux. We demonstrate a geospatial analysis that provides...

Leveraging Geospatial Intelligence (GEOINT) in Mission Command

DTIC Science & Technology

2009-03-21

Operational artists at all levels need new conceptual tools commensurate to today’s demands. Conceptual aids derived from old, industrial-age analogies...are not up to the mental gymnastics demanded by 21 st –century missions. Because operational environments evince increasingly dynamic complexity

Lsiviewer 2.0 - a Client-Oriented Online Visualization Tool for Geospatial Vector Data

NASA Astrophysics Data System (ADS)

Manikanta, K.; Rajan, K. S.

2017-09-01

Geospatial data visualization systems have been predominantly through applications that are installed and run in a desktop environment. Over the last decade, with the advent of web technologies and its adoption by Geospatial community, the server-client model for data handling, data rendering and visualization respectively has been the most prevalent approach in Web-GIS. While the client devices have become functionally more powerful over the recent years, the above model has largely ignored it and is still in a mode of serverdominant computing paradigm. In this paper, an attempt has been made to develop and demonstrate LSIViewer - a simple, easy-to-use and robust online geospatial data visualisation system for the user's own data that harness the client's capabilities for data rendering and user-interactive styling, with a reduced load on the server. The developed system can support multiple geospatial vector formats and can be integrated with other web-based systems like WMS, WFS, etc. The technology stack used to build this system is Node.js on the server side and HTML5 Canvas and JavaScript on the client side. Various tests run on a range of vector datasets, upto 35 MB, showed that the time taken to render the vector data using LSIViewer is comparable to a desktop GIS application, QGIS, over an identical system.

A resource-oriented architecture for a Geospatial Web

NASA Astrophysics Data System (ADS)

Mazzetti, Paolo; Nativi, Stefano

2010-05-01

In this presentation we discuss some architectural issues on the design of an architecture for a Geospatial Web, that is an information system for sharing geospatial resources according to the Web paradigm. The success of the Web in building a multi-purpose information space, has raised questions about the possibility of adopting the same approach for systems dedicated to the sharing of more specific resources, such as the geospatial information, that is information characterized by spatial/temporal reference. To this aim an investigation on the nature of the Web and on the validity of its paradigm for geospatial resources is required. The Web was born in the early 90's to provide "a shared information space through which people and machines could communicate" [Berners-Lee 1996]. It was originally built around a small set of specifications (e.g. URI, HTTP, HTML, etc.); however, in the last two decades several other technologies and specifications have been introduced in order to extend its capabilities. Most of them (e.g. the SOAP family) actually aimed to transform the Web in a generic Distributed Computing Infrastructure. While these efforts were definitely successful enabling the adoption of service-oriented approaches for machine-to-machine interactions supporting complex business processes (e.g. for e-Government and e-Business applications), they do not fit in the original concept of the Web. In the year 2000, R. T. Fielding, one of the designers of the original Web specifications, proposes a new architectural style for distributed systems, called REST (Representational State Transfer), aiming to capture the fundamental characteristics of the Web as it was originally conceived [Fielding 2000]. In this view, the nature of the Web lies not so much in the technologies, as in the way they are used. Maintaining the Web architecture conform to the REST style would then assure the scalability, extensibility and low entry barrier of the original Web. On the contrary, systems using the same Web technologies and specifications but according to a different architectural style, despite their usefulness, should not be considered part of the Web. If the REST style captures the significant Web characteristics, then, in order to build a Geospatial Web it is necessary that its architecture satisfies all the REST constraints. One of them is of particular importance: the adoption of a Uniform Interface. It prescribes that all the geospatial resources must be accessed through the same interface; moreover according to the REST style this interface must satisfy four further constraints: a) identification of resources; b) manipulation of resources through representations; c) self-descriptive messages; and, d) hypermedia as the engine of application state. In the Web, the uniform interface provides basic operations which are meaningful for generic resources. They typically implement the CRUD pattern (Create-Retrieve-Update-Delete) which demonstrated to be flexible and powerful in several general-purpose contexts (e.g. filesystem management, SQL for database management systems, etc.). Restricting the scope to a subset of resources it would be possible to identify other generic actions which are meaningful for all of them. For example for geospatial resources, subsetting, resampling, interpolation and coordinate reference systems transformations functionalities are candidate functionalities for a uniform interface. However an investigation is needed to clarify the semantics of those actions for different resources, and consequently if they can really ascend the role of generic interface operation. Concerning the point a), (identification of resources), it is required that every resource addressable in the Geospatial Web has its own identifier (e.g. a URI). This allows to implement citation and re-use of resources, simply providing the URI. OPeNDAP and KVP encodings of OGC data access services specifications might provide a basis for it. Concerning point b) (manipulation of resources through representations), the Geospatial Web poses several issues. In fact, while the Web mainly handles semi-structured information, in the Geospatial Web the information is typically structured with several possible data models (e.g. point series, gridded coverages, trajectories, etc.) and encodings. A possibility would be to simplify the interchange formats, choosing to support a subset of data models and format(s). This is what actually the Web designers did choosing to define a common format for hypermedia (HTML), although the underlying protocol would be generic. Concerning point c), self-descriptive messages, the exchanged messages should describe themselves and their content. This would not be actually a major issue considering the effort put in recent years on geospatial metadata models and specifications. The point d), hypermedia as the engine of application state, is actually where the Geospatial Web would mainly differ from existing geospatial information sharing systems. In fact the existing systems typically adopt a service-oriented architecture, where applications are built as a single service or as a workflow of services. On the other hand, in the Geospatial Web, applications should be built following the path between interconnected resources. The link between resources should be made explicit as hyperlinks. The adoption of Semantic Web solutions would allow to define not only the existence of a link between two resources, but also the nature of the link. The implementation of a Geospatial Web would allow to build an information system with the same characteristics of the Web sharing its points-of-strength and weaknesses. The main advantages would be the following: • The user would interact with the Geospatial Web according to the well-known Web navigation paradigm. This would lower the barrier to the access to geospatial applications for non-specialists (e.g. the success of Google Maps and other Web mapping applications); • Successful Web and Web 2.0 applications - search engines, feeds, social network - could be integrated/replicated in the Geospatial Web; The main drawbacks would be the following: • The Uniform Interface simplifies the overall system architecture (e.g. no service registry, and service descriptors required), but moves the complexity to the data representation. Moreover since the interface must stay generic, it results really simple and therefore complex interactions would require several transfers. • In the geospatial domain one of the most valuable resources are processes (e.g. environmental models). How they can be modeled as resources accessed through the common interface is an open issue. Taking into account advantages and drawback it seems that a Geospatial Web would be useful, but its use would be limited to specific use-cases not covering all the possible applications. The Geospatial Web architecture could be partly based on existing specifications, while other aspects need investigation. References [Berners-Lee 1996] T. Berners-Lee, "WWW: Past, present, and future". IEEE Computer, 29(10), Oct. 1996, pp. 69-77. [Fielding 2000] Fielding, R. T. 2000. Architectural styles and the design of network-based software architectures. PhD Dissertation. Dept. of Information and Computer Science, University of California, Irvine

Geospatial datasets for watershed delineation and characterization used in the Hawaii StreamStats web application

USGS Publications Warehouse

Rea, Alan; Skinner, Kenneth D.

2012-01-01

The U.S. Geological Survey Hawaii StreamStats application uses an integrated suite of raster and vector geospatial datasets to delineate and characterize watersheds. The geospatial datasets used to delineate and characterize watersheds on the StreamStats website, and the methods used to develop the datasets are described in this report. The datasets for Hawaii were derived primarily from 10 meter resolution National Elevation Dataset (NED) elevation models, and the National Hydrography Dataset (NHD), using a set of procedures designed to enforce the drainage pattern from the NHD into the NED, resulting in an integrated suite of elevation-derived datasets. Additional sources of data used for computing basin characteristics include precipitation, land cover, soil permeability, and elevation-derivative datasets. The report also includes links for metadata and downloads of the geospatial datasets.

Developing Daily Quantitative Damage Estimates From Geospatial Layers To Support Post Event Recovery

NASA Astrophysics Data System (ADS)

Woods, B. K.; Wei, L. H.; Connor, T. C.

2014-12-01

With the growth of natural hazard data available in near real-time it is increasingly feasible to deliver damage estimates caused by natural disasters. These estimates can be used in disaster management setting or by commercial entities to optimize the deployment of resources and/or routing of goods and materials. This work outlines an end-to-end, modular process to generate estimates of damage caused by severe weather. The processing stream consists of five generic components: 1) Hazard modules that provide quantitate data layers for each peril. 2) Standardized methods to map the hazard data to an exposure layer based on atomic geospatial blocks. 3) Peril-specific damage functions that compute damage metrics at the atomic geospatial block level. 4) Standardized data aggregators, which map damage to user-specific geometries. 5) Data dissemination modules, which provide resulting damage estimates in a variety of output forms. This presentation provides a description of this generic tool set, and an illustrated example using HWRF-based hazard data for Hurricane Arthur (2014). In this example, the Python-based real-time processing ingests GRIB2 output from the HWRF numerical model, dynamically downscales it in conjunctions with a land cover database using a multiprocessing pool, and a just-in-time compiler (JIT). The resulting wind fields are contoured, and ingested into a PostGIS database using OGR. Finally, the damage estimates are calculated at the atomic block level and aggregated to user-defined regions using PostgreSQL queries to construct application specific tabular and graphics output.

Database Organisation in a Web-Enabled Free and Open-Source Software (foss) Environment for Spatio-Temporal Landslide Modelling

NASA Astrophysics Data System (ADS)

Das, I.; Oberai, K.; Sarathi Roy, P.

2012-07-01

Landslides exhibit themselves in different mass movement processes and are considered among the most complex natural hazards occurring on the earth surface. Making landslide database available online via WWW (World Wide Web) promotes the spreading and reaching out of the landslide information to all the stakeholders. The aim of this research is to present a comprehensive database for generating landslide hazard scenario with the help of available historic records of landslides and geo-environmental factors and make them available over the Web using geospatial Free & Open Source Software (FOSS). FOSS reduces the cost of the project drastically as proprietary software's are very costly. Landslide data generated for the period 1982 to 2009 were compiled along the national highway road corridor in Indian Himalayas. All the geo-environmental datasets along with the landslide susceptibility map were served through WEBGIS client interface. Open source University of Minnesota (UMN) mapserver was used as GIS server software for developing web enabled landslide geospatial database. PHP/Mapscript server-side application serve as a front-end application and PostgreSQL with PostGIS extension serve as a backend application for the web enabled landslide spatio-temporal databases. This dynamic virtual visualization process through a web platform brings an insight into the understanding of the landslides and the resulting damage closer to the affected people and user community. The landslide susceptibility dataset is also made available as an Open Geospatial Consortium (OGC) Web Feature Service (WFS) which can be accessed through any OGC compliant open source or proprietary GIS Software.

Water sources and mixing in riparian wetlands revealed by tracers and geospatial analysis.

PubMed

Lessels, Jason S; Tetzlaff, Doerthe; Birkel, Christian; Dick, Jonathan; Soulsby, Chris

2016-01-01

Mixing of waters within riparian zones has been identified as an important influence on runoff generation and water quality. Improved understanding of the controls on the spatial and temporal variability of water sources and how they mix in riparian zones is therefore of both fundamental and applied interest. In this study, we have combined topographic indices derived from a high-resolution Digital Elevation Model (DEM) with repeated spatially high-resolution synoptic sampling of multiple tracers to investigate such dynamics of source water mixing. We use geostatistics to estimate concentrations of three different tracers (deuterium, alkalinity, and dissolved organic carbon) across an extended riparian zone in a headwater catchment in NE Scotland, to identify spatial and temporal influences on mixing of source waters. The various biogeochemical tracers and stable isotopes helped constrain the sources of runoff and their temporal dynamics. Results show that spatial variability in all three tracers was evident in all sampling campaigns, but more pronounced in warmer dryer periods. The extent of mixing areas within the riparian area reflected strong hydroclimatic controls and showed large degrees of expansion and contraction that was not strongly related to topographic indices. The integrated approach of using multiple tracers, geospatial statistics, and topographic analysis allowed us to classify three main riparian source areas and mixing zones. This study underlines the importance of the riparian zones for mixing soil water and groundwater and introduces a novel approach how this mixing can be quantified and the effect on the downstream chemistry be assessed.

Restful Implementation of Catalogue Service for Geospatial Data Provenance

NASA Astrophysics Data System (ADS)

Jiang, L. C.; Yue, P.; Lu, X. C.

2013-10-01

Provenance, also known as lineage, is important in understanding the derivation history of data products. Geospatial data provenance helps data consumers to evaluate the quality and reliability of geospatial data. In a service-oriented environment, where data are often consumed or produced by distributed services, provenance could be managed by following the same service-oriented paradigm. The Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) is used for the registration and query of geospatial data provenance by extending ebXML Registry Information Model (ebRIM). Recent advance of the REpresentational State Transfer (REST) paradigm has shown great promise for the easy integration of distributed resources. RESTful Web Service aims to provide a standard way for Web clients to communicate with servers based on REST principles. The existing approach for provenance catalogue service could be improved by adopting the RESTful design. This paper presents the design and implementation of a catalogue service for geospatial data provenance following RESTful architecture style. A middleware named REST Converter is added on the top of the legacy catalogue service to support a RESTful style interface. The REST Converter is composed of a resource request dispatcher and six resource handlers. A prototype service is developed to demonstrate the applicability of the approach.

Recent innovation of geospatial information technology to support disaster risk management and responses

NASA Astrophysics Data System (ADS)

Une, Hiroshi; Nakano, Takayuki

2018-05-01

Geographic location is one of the most fundamental and indispensable information elements in the field of disaster response and prevention. For example, in the case of the Tohoku Earthquake in 2011, aerial photos taken immediately after the earthquake greatly improved information sharing among different government offices and facilitated rescue and recovery operations, and maps prepared after the disaster assisted in the rapid reconstruction of affected local communities. Thanks to the recent development of geospatial information technology, this information has become more essential for disaster response activities. Advancements in web mapping technology allows us to better understand the situation by overlaying various location-specific data on base maps on the web and specifying the areas on which activities should be focused. Through 3-D modelling technology, we can have a more realistic understanding of the relationship between disaster and topography. Geospatial information technology can sup-port proper preparation and emergency responses against disasters by individuals and local communities through hazard mapping and other information services using mobile devices. Thus, geospatial information technology is playing a more vital role on all stages of disaster risk management and responses. In acknowledging geospatial information's vital role in disaster risk reduction, the Sendai Framework for Disaster Risk Reduction 2015-2030, adopted at the Third United Nations World Conference on Disaster Risk Reduction, repeatedly reveals the importance of utilizing geospatial information technology for disaster risk reduction. This presentation aims to report the recent practical applications of geospatial information technology for disaster risk management and responses.

Generating a geospatial database of U.S. regional feedstock production for use in evaluating the environmental footprint of biofuels.

PubMed

Holder, Christopher T; Cleland, Joshua C; LeDuc, Stephen D; Andereck, Zac; Hogan, Chris; Martin, Kristen M

2016-04-01

The potential environmental effects of increased U.S. biofuel production often vary depending upon the location and type of land used to produce biofuel feedstocks. However, complete, annual data are generally lacking regarding feedstock production by specific location. Corn is the dominant biofuel feedstock in the U.S., so here we present methods for estimating where bioethanol corn feedstock is grown annually and how much is used by U.S. ethanol biorefineries. We use geospatial software and publicly available data to map locations of biorefineries, estimate their corn feedstock requirements, and estimate the feedstock production locations and quantities. We combined these data and estimates into a Bioethanol Feedstock Geospatial Database (BFGD) for years 2005-2010. We evaluated the performance of the methods by assessing how well the feedstock geospatial model matched our estimates of locally-sourced feedstock demand. On average, the model met approximately 89 percent of the total estimated local feedstock demand across the studied years-within approximately 25-to-40 kilometers of the biorefinery in the majority of cases. We anticipate that these methods could be used for other years and feedstocks, and can be subsequently applied to estimate the environmental footprint of feedstock production. Methods used to develop the Bioethanol Feedstock Geospatial Database (BFGD) provide a means of estimating the amount and location of U.S. corn harvested for use as U.S. bioethanol feedstock. Such estimates of geospatial feedstock production may be used to evaluate environmental impacts of bioethanol production and to identify conservation priorities. The BFGD is available for 2005-2010, and the methods may be applied to additional years, locations, and potentially other biofuels and feedstocks.

Characterization and visualization of the accuracy of FIA's CONUS-wide tree species datasets

Treesearch

Rachel Riemann; Barry T. Wilson

2014-01-01

Modeled geospatial datasets have been created for 325 tree species across the contiguous United States (CONUS). Effective application of all geospatial datasets depends on their accuracy. Dataset error can be systematic (bias) or unsystematic (scatter), and their magnitude can vary by region and scale. Each of these characteristics affects the locations, scales, uses,...

Impact of Robotics and Geospatial Technology Interventions on Youth STEM Learning and Attitudes

ERIC Educational Resources Information Center

Nugent, Gwen; Barker, Bradley; Grandgenett, Neal; Adamchuk, Viacheslav I.

2010-01-01

This study examined the impact of robotics and geospatial technologies interventions on middle school youth's learning of and attitudes toward science, technology, engineering, and mathematics (STEM). Two interventions were tested. The first was a 40-hour intensive robotics/GPS/GIS summer camp; the second was a 3-hour event modeled on the camp…

Geospatial economics of the woody biomass supply in Kansas -- A case study

Treesearch

Olga Khaliukova; Darci Paull; Sarah L. Lewis-Gonzales; Nicolas Andre; Larry E. Biles; Timothy M. Young; James H. Perdue

2017-01-01

This research assessed the geospatial supply of cellulosic feedstocks for potential mill sites in Kansas (KS), with procurement zones extending to Arkansas (AR), Iowa(IA), Missouri(MO), Oklahoma (OK), and Nebraska (NE). A web-based modeling system, the Kansas Biomass Supply Assessment Tool, was developed to identify least-cost sourcing areas for logging residues and...

Google Earth and Geo Applications: A Toolset for Viewing Earth's Geospatial Information

NASA Astrophysics Data System (ADS)

Tuxen-Bettman, K.

2016-12-01

Earth scientists measure and derive fundamental data that can be of broad general interest to the public and policy makers. Yet, one of the challenges that has always faced the Earth science community is how to present their data and findings in an easy-to-use and compelling manner. Google's Geo Tools offer an efficient and dynamic way for scientists, educators, journalists and others to both access data and view or tell stories in a dynamic three-dimensional geospatial context. Google Earth in particular provides a dense canvas of satellite imagery on which can be viewed rich vector and raster datasets using the medium of Keyhole Markup Language (KML). Through KML, Google Earth can combine the analytical capabilities of Earth Engine, collaborative mapping of My Maps, and storytelling of Tour Builder and more to make Google's Geo Applications a coherent suite of tools for exploring our planet.https://earth.google.com/https://earthengine.google.com/https://mymaps.google.com/https://tourbuilder.withgoogle.com/https://www.google.com/streetview/

Transforming Undergraduate Education Through the use of Analytical Reasoning (TUETAR)

NASA Astrophysics Data System (ADS)

Bishop, M. P.; Houser, C.; Lemmons, K.

2015-12-01

Traditional learning limits the potential for self-discovery, and the use of data and knowledge to understand Earth system relationships, processes, feedback mechanisms and system coupling. It is extremely difficult for undergraduate students to analyze, synthesize, and integrate quantitative information related to complex systems, as many concepts may not be mathematically tractable or yet to be formalized. Conceptual models have long served as a means for Earth scientists to organize their understanding of Earth's dynamics, and have served as a basis for human analytical reasoning and landscape interpretation. Consequently, we evaluated the use of conceptual modeling, knowledge representation and analytical reasoning to provide undergraduate students with an opportunity to develop and test geocomputational conceptual models based upon their understanding of Earth science concepts. This study describes the use of geospatial technologies and fuzzy cognitive maps to predict desertification across the South-Texas Sandsheet in an upper-level geomorphology course. Students developed conceptual models based on their understanding of aeolian processes from lectures, and then compared and evaluated their modeling results against an expert conceptual model and spatial predictions, and the observed distribution of dune activity in 2010. Students perceived that the analytical reasoning approach was significantly better for understanding desertification compared to traditional lecture, and promoted reflective learning, working with data, teamwork, student interaction, innovation, and creative thinking. Student evaluations support the notion that the adoption of knowledge representation and analytical reasoning in the classroom has the potential to transform undergraduate education by enabling students to formalize and test their conceptual understanding of Earth science. A model for developing and utilizing this geospatial technology approach in Earth science is presented.

OGC and Grid Interoperability in enviroGRIDS Project

NASA Astrophysics Data System (ADS)

Gorgan, Dorian; Rodila, Denisa; Bacu, Victor; Giuliani, Gregory; Ray, Nicolas

2010-05-01

EnviroGRIDS (Black Sea Catchment Observation and Assessment System supporting Sustainable Development) [1] is a 4-years FP7 Project aiming to address the subjects of ecologically unsustainable development and inadequate resource management. The project develops a Spatial Data Infrastructure of the Black Sea Catchment region. The geospatial technologies offer very specialized functionality for Earth Science oriented applications as well as the Grid oriented technology that is able to support distributed and parallel processing. One challenge of the enviroGRIDS project is the interoperability between geospatial and Grid infrastructures by providing the basic and the extended features of the both technologies. The geospatial interoperability technology has been promoted as a way of dealing with large volumes of geospatial data in distributed environments through the development of interoperable Web service specifications proposed by the Open Geospatial Consortium (OGC), with applications spread across multiple fields but especially in Earth observation research. Due to the huge volumes of data available in the geospatial domain and the additional introduced issues (data management, secure data transfer, data distribution and data computation), the need for an infrastructure capable to manage all those problems becomes an important aspect. The Grid promotes and facilitates the secure interoperations of geospatial heterogeneous distributed data within a distributed environment, the creation and management of large distributed computational jobs and assures a security level for communication and transfer of messages based on certificates. This presentation analysis and discusses the most significant use cases for enabling the OGC Web services interoperability with the Grid environment and focuses on the description and implementation of the most promising one. In these use cases we give a special attention to issues such as: the relations between computational grid and the OGC Web service protocols, the advantages offered by the Grid technology - such as providing a secure interoperability between the distributed geospatial resource -and the issues introduced by the integration of distributed geospatial data in a secure environment: data and service discovery, management, access and computation. enviroGRIDS project proposes a new architecture which allows a flexible and scalable approach for integrating the geospatial domain represented by the OGC Web services with the Grid domain represented by the gLite middleware. The parallelism offered by the Grid technology is discussed and explored at the data level, management level and computation level. The analysis is carried out for OGC Web service interoperability in general but specific details are emphasized for Web Map Service (WMS), Web Feature Service (WFS), Web Coverage Service (WCS), Web Processing Service (WPS) and Catalog Service for Web (CSW). Issues regarding the mapping and the interoperability between the OGC and the Grid standards and protocols are analyzed as they are the base in solving the communication problems between the two environments: grid and geospatial. The presetation mainly highlights how the Grid environment and Grid applications capabilities can be extended and utilized in geospatial interoperability. Interoperability between geospatial and Grid infrastructures provides features such as the specific geospatial complex functionality and the high power computation and security of the Grid, high spatial model resolution and geographical area covering, flexible combination and interoperability of the geographical models. According with the Service Oriented Architecture concepts and requirements of interoperability between geospatial and Grid infrastructures each of the main functionality is visible from enviroGRIDS Portal and consequently, by the end user applications such as Decision Maker/Citizen oriented Applications. The enviroGRIDS portal is the single way of the user to get into the system and the portal faces a unique style of the graphical user interface. Main reference for further information: [1] enviroGRIDS Project, http://www.envirogrids.net/

Not Just a Game … When We Play Together, We Learn Together: Interactive Virtual Environments and Gaming Engines for Geospatial Visualization

NASA Astrophysics Data System (ADS)

Shipman, J. S.; Anderson, J. W.

2017-12-01

An ideal tool for ecologists and land managers to investigate the impacts of both projected environmental changes and policy alternatives is the creation of immersive, interactive, virtual landscapes. As a new frontier in visualizing and understanding geospatial data, virtual landscapes require a new toolbox for data visualization that includes traditional GIS tools and uncommon tools such as the Unity3d game engine. Game engines provide capabilities to not only explore data but to build and interact with dynamic models collaboratively. These virtual worlds can be used to display and illustrate data that is often more understandable and plausible to both stakeholders and policy makers than is achieved using traditional maps.Within this context we will present funded research that has been developed utilizing virtual landscapes for geographic visualization and decision support among varied stakeholders. We will highlight the challenges and lessons learned when developing interactive virtual environments that require large multidisciplinary team efforts with varied competences. The results will emphasize the importance of visualization and interactive virtual environments and the link with emerging research disciplines within Visual Analytics.

A geospatial model of ambient sound pressure levels in the contiguous United States.

PubMed

Mennitt, Daniel; Sherrill, Kirk; Fristrup, Kurt

2014-05-01

This paper presents a model that predicts measured sound pressure levels using geospatial features such as topography, climate, hydrology, and anthropogenic activity. The model utilizes random forest, a tree-based machine learning algorithm, which does not incorporate a priori knowledge of source characteristics or propagation mechanics. The response data encompasses 270 000 h of acoustical measurements from 190 sites located in National Parks across the contiguous United States. The explanatory variables were derived from national geospatial data layers and cross validation procedures were used to evaluate model performance and identify variables with predictive power. Using the model, the effects of individual explanatory variables on sound pressure level were isolated and quantified to reveal systematic trends across environmental gradients. Model performance varies by the acoustical metric of interest; the seasonal L50 can be predicted with a median absolute deviation of approximately 3 dB. The primary application for this model is to generalize point measurements to maps expressing spatial variation in ambient sound levels. An example of this mapping capability is presented for Zion National Park and Cedar Breaks National Monument in southwestern Utah.

Browsing and Visualization of Linked Environmental Data

NASA Astrophysics Data System (ADS)

Nikolaou, Charalampos; Kyzirakos, Kostis; Bereta, Konstantina; Dogani, Kallirroi; Koubarakis, Manolis

2014-05-01

Linked environmental data has started to appear on the Web as environmental researchers make use of technologies such as ontologies, RDF, and SPARQL. Many of these datasets have an important geospatial and temporal dimension. The same is true also for the Web of data that is being rapidly populated not only with geospatial information, but also with temporal information. As the real-world entities represented in linked geospatial datasets evolve over time, the datasets themselves get updated and both the spatial and the temporal dimension of data become significant for users. For example, in the Earth Observation and Environment domains, data is constantly produced by satellite sensors and is associated with metadata containing, among others, temporal attributes, such as the time that an image was acquired. In addition, the acquisitions are considered to be valid for specific periods of time, for example until they get updated by new acquisitions. Satellite acquisitions might be utilized in applications such as the CORINE Land Cover programme operated by the European Environment Agency that makes available as a cartographic product the land cover of European areas. Periodically CORINE publishes the changes in the land cover of these areas in the form of changesets. Tools for exploiting the abundance of geospatial information have also started to emerge. However, these tools are designed for browsing a single data source, while in addition they cannot represent the temporal dimension. This is for two reasons: a) the lack of an implementation of a data model and a query language with temporal features covering the various semantics associated with the representation of time (e.g., valid and user-defined), and b) the lack of a standard temporal extension of RDF that would allow practitioners to utilize when publishing RDF data. Recently, we presented the temporal features of the data model stRDF, the query language stSPARQL, and their implementation in the geospatial RDF store Strabon (http://www.strabon.di.uoa.gr/) which, apart from querying geospatial information, can also be used to query both the valid time of a triple and user-defined time. With the aim of filling the aforementioned gaps and going beyond data exploration to map creation and sharing, we have designed and developed SexTant (http://sextant.di.uoa.gr/). SexTant can be used to produce thematic maps by layering spatiotemporal information which exists in a number of data sources ranging from standard SPARQL endpoints, to SPARQL endpoints following the standard GeoSPARQL defined by the Open Geospatial Consortium (OGC) for the modelling and querying of geospatial information, and other well-adopted geospatial file formats, such as KML and GeoJSON. In this work, we pick some real use cases from the environment domain to showcase the usefulness of SexTant to the environmental studies of a domain expert by presenting its browsing and visualization capabilities using a number of environmental datasets that we have published as linked data and also other geospatial data sources publicly available on the Web, such as KML files.

Assessing the Impacts of Flooding Caused by Extreme Rainfall Events Through a Combined Geospatial and Numerical Modeling Approach

NASA Astrophysics Data System (ADS)

Santillan, J. R.; Amora, A. M.; Makinano-Santillan, M.; Marqueso, J. T.; Cutamora, L. C.; Serviano, J. L.; Makinano, R. M.

2016-06-01

In this paper, we present a combined geospatial and two dimensional (2D) flood modeling approach to assess the impacts of flooding due to extreme rainfall events. We developed and implemented this approach to the Tago River Basin in the province of Surigao del Sur in Mindanao, Philippines, an area which suffered great damage due to flooding caused by Tropical Storms Lingling and Jangmi in the year 2014. The geospatial component of the approach involves extraction of several layers of information such as detailed topography/terrain, man-made features (buildings, roads, bridges) from 1-m spatial resolution LiDAR Digital Surface and Terrain Models (DTM/DSMs), and recent land-cover from Landsat 7 ETM+ and Landsat 8 OLI images. We then used these layers as inputs in developing a Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS)-based hydrologic model, and a hydraulic model based on the 2D module of the latest version of HEC River Analysis System (RAS) to dynamically simulate and map the depth and extent of flooding due to extreme rainfall events. The extreme rainfall events used in the simulation represent 6 hypothetical rainfall events with return periods of 2, 5, 10, 25, 50, and 100 years. For each event, maximum flood depth maps were generated from the simulations, and these maps were further transformed into hazard maps by categorizing the flood depth into low, medium and high hazard levels. Using both the flood hazard maps and the layers of information extracted from remotely-sensed datasets in spatial overlay analysis, we were then able to estimate and assess the impacts of these flooding events to buildings, roads, bridges and landcover. Results of the assessments revealed increase in number of buildings, roads and bridges; and increase in areas of land-cover exposed to various flood hazards as rainfall events become more extreme. The wealth of information generated from the flood impact assessment using the approach can be very useful to the local government units and the concerned communities within Tago River Basin as an aid in determining in an advance manner all those infrastructures (buildings, roads and bridges) and land-cover that can be affected by different extreme rainfall event flood scenarios.

FASTMap v. 2010.01

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bynum, Leo

FASTMap is mapping application available for the web or on mobile devices (IOS and Android) that browses geospatial data and produces detailed reports of objects within any area of analysis. FASTMap can access any geospatial dataset. The software can provide immediate access to the selected data through a fully symbolized interactive mapping interface. FASTMap can load arbitrary contours that represent a region of interest and can dynamically identify and geospatially select objects that reside within the region. The software can produce a report listing the objects and aggregations for the region, as well as producing publication quality maps. FASTMap alsomore » has the ability to post and maintain authored maps, any GIS data included in the map, areas of interest, as well as any titles, and labels. These defining ingredients of a map are called map contexts. These mao contexts can be instantly broadcast via the internet through any of an infinite number of named channels to small or large numbers of users monitouring any of the channels being posted to, so a user can author a map and immediately share that map with others instantly, whether they are on traditional desktop computer, laptop, mobile tablet or smartphone. Further, users receiving broadcast maps can also alter the maps can also alter the maps, or create new ones and publish back to the channel in a collaborative manner. FASTMap can be configured to access virtually any geospatial data.« less

A Transient Landscape: Geospatial Analysis and Numerical Modeling of Coastal Geomorphology in the Outer Banks, North Carolina

NASA Astrophysics Data System (ADS)

Hardin, Eric Jon

Coastal landscapes can be relentlessly dynamic---owing to wave energy, tidal cycles, extreme weather events, and perpetual coastal winds. In these settings, the ever-changing landscape can threaten assets and infrastructure, necessitating costly measures to mitigate associated risks and to repair or maintain the changing landscape. Mapping and monitoring of terrain change, identification of areas susceptible to dramatic change, and understanding the processes that drive landscape change are critical for the development of responsible coastal management strategies and policies. Over the past two decades, LiDAR mapping has been conducted along the U.S. east coast (including the Outer Banks, North Carolina) on a near annual basis---generating a rich time series of topographic data with unprecedented accuracy, resolution, and extent. This time series has captured the response of the landscape to episodic storms, daily forcing of wind and waves, and anthropogenic activities. This work presents raster-based geospatial techniques developed to gain new insights into coastal geomorphology from the time series of available LiDAR. Per-cell statistical techniques derive information that is typically not obtained through the techniques traditionally employed by coastal scientists and engineers. Application of these techniques to study sites along the Outer Banks, NC, revealed substantial spatial and temporal variations in terrain change. Additionally, they identify the foredunes as being the most geomorphologically dynamic coastal features. In addition to per-cell statistical analysis, an approach is presented for the extraction of the dune ridge and dune toe (two features that are essential to standard vulnerability assessment). The approach employs a novel application of least cost path analysis and a physics-based model of an elastic sheet. The spatially distributed nature of the approach achieves a high level of automation and repeatability that semi-automated methods and manual digitization lack. Furthermore, the approach can be fully implemented with standard Geographic Information System (GIS) functionality, resulting in efficiency and ease of implementation. With this approach, a raster-based implementation of the U.S. Geological Survey (USGS) storm impact scale (designed to assess storm vulnerability of barrier islands) was developed. Vulnerability of 4km of the Outer Banks to Hurricane Isabel (2003) was assessed. The demonstrated approach produced vulnerability mapping at the high resolution of the input Digital Elevation Model (DEM)---providing results at the scale needed for local management, in contrast to the USGS approach, which is designed for continental scale vulnerability assessment. However, geospatial techniques cannot fully explain the observed geomorphology. Therefore, we present the Smoothed Particle Hydrodynamics (SPH) implementation of the Sauermann model for wind-driven sand transport. The SPH implementation enables the full nonlinearity of the model to be applied to complex scenarios that are typical of coastal landscapes. Through application of the SPH model and Computational Fluid Dynamics (CFD) modeling of the windborne surface shear stress (which drives sand transport), we present the sediment flux at two study sites along the Outer Banks. Scenarios were tested that involved steady-state surface shear stress as well as scenarios with intermittent variations in the surface shear stress. Results showed that intermittency in the surface shear stress has the potential to greatly influence the resulting flux. However, the degree to which intermittency does alter the flux is highly dependent on wind characteristics and wind direction relative to the orientation of salient topographic features.

An effective assessment protocol for continuous geospatial datasets of forest characteristics using USFS Forest Inventory and Analysis (FIA) data

Treesearch

Rachel Riemann; Barry Tyler Wilson; Andrew Lister; Sarah Parks

2010-01-01

Geospatial datasets of forest characteristics are modeled representations of real populations on the ground. The continuous spatial character of such datasets provides an incredible source of information at the landscape level for ecosystem research, policy analysis, and planning applications, all of which are critical for addressing current challenges related to...

Incorporating Historic Facility Geospatial Data and Federal Preservation Requirements into SDSFIE/FMSFIE

DTIC Science & Technology

2006-11-01

29 3.2.4 National Register Information System Model ............................................................... 30 3.3 Summary of...are later based on that information . Despite their general level of power and resolution, Federal data management and accounting tools have not yet...have begun tracking their historic building and structure inven- tories using geographic information systems (GISs). A geospatial-referenced data

Quantum Leap in Cartography as a requirement of Sustainable Development of the World

NASA Astrophysics Data System (ADS)

Tikunov, Vladimir S.; Tikunova, Iryna N.; Eremchenko, Eugene N.

2018-05-01

Sustainable development is one of the most important challenges for humanity and one of the priorities of the United Nations. Achieving sustainability of the whole World is a main goal of management at all levels - from personal to local to global. Therefore, decision making should be supported by relevant geospatial information system. Nevertheless, classical geospatial products, maps and GIS, violate fundamental demand of `situational awareness' concept, well-known philosophy of decision-making - same representation of situation within a same volume of time and space for all decision-makers. Basic mapping principles like generalization and projections split the universal single model of situation on number of different separate and inconsistent replicas. It leads to wrong understanding of situation and, after all - to incorrect decisions. In another words, quality of the sustainable development depends on effective decision-making support based on universal global scale-independent and projection-independent model. This new way for interacting with geospatial information is a quantum leap in cartography method. It is implemented in the so-called `Digital Earth' paradigm and geospatial services like Google Earth. Com-paring of both methods, as well as possibilities of implementation of Digital Earth in the sustain-able development activities, are discussed.

Real-time GIS data model and sensor web service platform for environmental data management.

PubMed

Gong, Jianya; Geng, Jing; Chen, Zeqiang

2015-01-09

Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework. A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies. To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s. The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework.

Multiscale model for pedestrian and infection dynamics during air travel

NASA Astrophysics Data System (ADS)

Namilae, Sirish; Derjany, Pierrot; Mubayi, Anuj; Scotch, Mathew; Srinivasan, Ashok

2017-05-01

In this paper we develop a multiscale model combining social-force-based pedestrian movement with a population level stochastic infection transmission dynamics framework. The model is then applied to study the infection transmission within airplanes and the transmission of the Ebola virus through casual contacts. Drastic limitations on air-travel during epidemics, such as during the 2014 Ebola outbreak in West Africa, carry considerable economic and human costs. We use the computational model to evaluate the effects of passenger movement within airplanes and air-travel policies on the geospatial spread of infectious diseases. We find that boarding policy by an airline is more critical for infection propagation compared to deplaning policy. Enplaning in two sections resulted in fewer infections than the currently followed strategy with multiple zones. In addition, we found that small commercial airplanes are better than larger ones at reducing the number of new infections in a flight. Aggregated results indicate that passenger movement strategies and airplane size predicted through these network models can have significant impact on an event like the 2014 Ebola epidemic. The methodology developed here is generic and can be readily modified to incorporate the impact from the outbreak of other directly transmitted infectious diseases.

New Geodetic Infrastructure for Australia: The NCRIS / AuScope Geospatial Component

NASA Astrophysics Data System (ADS)

Tregoning, P.; Watson, C. S.; Coleman, R.; Johnston, G.; Lovell, J.; Dickey, J.; Featherstone, W. E.; Rizos, C.; Higgins, M.; Priebbenow, R.

2009-12-01

In November 2006, the Australian Federal Government announced AUS15.8M in funding for geospatial research infrastructure through the National Collaborative Research Infrastructure Strategy (NCRIS). Funded within a broader capability area titled ‘Structure and Evolution of the Australian Continent’, NCRIS has provided a significant investment across Earth imaging, geochemistry, numerical simulation and modelling, the development of a virtual core library, and geospatial infrastructure. Known collectively as AuScope (www.auscope.org.au), this capability area has brought together Australian’s leading Earth scientists to decide upon the most pressing scientific issues and infrastructure needs for studying Earth systems and their impact on the Australian continent. Importantly and at the same time, the investment in geospatial infrastructure offers the opportunity to raise Australian geodetic science capability to the highest international level into the future. The geospatial component of AuScope builds onto the AUS15.8M of direct funding through the NCRIS process with significant in-kind and co-investment from universities and State/Territory and Federal government departments. The infrastructure to be acquired includes an FG5 absolute gravimeter, three gPhone relative gravimeters, three 12.1 m radio telescopes for geodetic VLBI, a continent-wide network of continuously operating geodetic quality GNSS receivers, a trial of a mobile SLR system and access to updated cluster computing facilities. We present an overview of the AuScope geospatial capability, review the current status of the infrastructure procurement and discuss some examples of the scientific research that will utilise the new geospatial infrastructure.

The dynamics of household dissolution and change in socio-economic position: A survival model in a rural South Africa

PubMed Central

Sartorius, Kurt; Sartorius, Benn KD; Collinson, Mark A; Tollman, Stephen M

2014-01-01

This paper investigates household dissolution and changes in asset wealth (socio-economic position) in a rural South African community containing settled refugees. Survival analysis applied to a longitudinal dataset indicated that the covariates increasing the risk of forced household dissolution were a reduction in socio-economic position (asset wealth), adult deaths and the permanent outmigration of more than 40% of the household. Conversely, the risk of dissolution was reduced by bigger households, state grants and older household heads. Significant spatial clusters of former refugee villages also showed a higher risk of dissolution after 20 years of permanent residence. A discussion of the dynamics of dissolution showed how an outflow/inflow of household assets (socio-economic position) was precipitated by each of the selected covariates. The paper shows how an understanding of the dynamics of forced household dissolution, combined with the use of geo-spatial mapping, can inform inter-disciplinary policy in a rural community. PMID:25937697

The dynamics of household dissolution and change in socio-economic position: A survival model in a rural South Africa.

PubMed

Sartorius, Kurt; Sartorius, Benn Kd; Collinson, Mark A; Tollman, Stephen M

2014-11-02

This paper investigates household dissolution and changes in asset wealth (socio-economic position) in a rural South African community containing settled refugees. Survival analysis applied to a longitudinal dataset indicated that the covariates increasing the risk of forced household dissolution were a reduction in socio-economic position (asset wealth), adult deaths and the permanent outmigration of more than 40% of the household. Conversely, the risk of dissolution was reduced by bigger households, state grants and older household heads. Significant spatial clusters of former refugee villages also showed a higher risk of dissolution after 20 years of permanent residence. A discussion of the dynamics of dissolution showed how an outflow/inflow of household assets (socio-economic position) was precipitated by each of the selected covariates. The paper shows how an understanding of the dynamics of forced household dissolution, combined with the use of geo-spatial mapping, can inform inter-disciplinary policy in a rural community.

Interoperability in planetary research for geospatial data analysis

NASA Astrophysics Data System (ADS)

Hare, Trent M.; Rossi, Angelo P.; Frigeri, Alessandro; Marmo, Chiara

2018-01-01

For more than a decade there has been a push in the planetary science community to support interoperable methods for accessing and working with geospatial data. Common geospatial data products for planetary research include image mosaics, digital elevation or terrain models, geologic maps, geographic location databases (e.g., craters, volcanoes) or any data that can be tied to the surface of a planetary body (including moons, comets or asteroids). Several U.S. and international cartographic research institutions have converged on mapping standards that embrace standardized geospatial image formats, geologic mapping conventions, U.S. Federal Geographic Data Committee (FGDC) cartographic and metadata standards, and notably on-line mapping services as defined by the Open Geospatial Consortium (OGC). The latter includes defined standards such as the OGC Web Mapping Services (simple image maps), Web Map Tile Services (cached image tiles), Web Feature Services (feature streaming), Web Coverage Services (rich scientific data streaming), and Catalog Services for the Web (data searching and discoverability). While these standards were developed for application to Earth-based data, they can be just as valuable for planetary domain. Another initiative, called VESPA (Virtual European Solar and Planetary Access), will marry several of the above geoscience standards and astronomy-based standards as defined by International Virtual Observatory Alliance (IVOA). This work outlines the current state of interoperability initiatives in use or in the process of being researched within the planetary geospatial community.

Modeling Being "Lost": Imperfect Situation Awareness

NASA Technical Reports Server (NTRS)

Middleton, Victor E.

2011-01-01

Being "lost" is an exemplar of imperfect Situation Awareness/Situation Understanding (SA/SU) -- information/knowledge that is uncertain, incomplete, and/or just wrong. Being "lost" may be a geo-spatial condition - not knowing/being wrong about where to go or how to get there. More broadly, being "lost" can serve as a metaphor for uncertainty and/or inaccuracy - not knowing/being wrong about how one fits into a larger world view, what one wants to do, or how to do it. This paper discusses using agent based modeling (ABM) to explore imperfect SA/SU, simulating geo-spatially "lost" intelligent agents trying to navigate in a virtual world. Each agent has a unique "mental map" -- its idiosyncratic view of its geo-spatial environment. Its decisions are based on this idiosyncratic view, but behavior outcomes are based on ground truth. Consequently, the rate and degree to which an agent's expectations diverge from ground truth provide measures of that agent's SA/SU.

Get a Grip on Demographics with Geospatial Technology

ERIC Educational Resources Information Center

Raymond, Randall E.

2009-01-01

Aging school infrastructure, changing population dynamics, decreased funding, and increased accountability for reporting school success all require today's school business officials to combine a variety of disparate data sets into a coherent system that enables effective and efficient decision making. School business officials are required to: (1)…

A Land-Use-Planning Simulation Using Google Earth

ERIC Educational Resources Information Center

Bodzin, Alec M.; Cirucci, Lori

2009-01-01

Google Earth (GE) is proving to be a valuable tool in the science classroom for understanding the environment and making responsible environmental decisions (Bodzin 2008). GE provides learners with a dynamic mapping experience using a simple interface with a limited range of functions. This interface makes geospatial analysis accessible and…

Multi-source Geospatial Data Analysis with Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T.

2014-12-01

The Google Earth Engine platform is a cloud computing environment for data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog is a multi-petabyte archive of georeferenced datasets that include images from Earth observing satellite and airborne sensors (examples: USGS Landsat, NASA MODIS, USDA NAIP), weather and climate datasets, and digital elevation models. Earth Engine supports both a just-in-time computation model that enables real-time preview and debugging during algorithm development for open-ended data exploration, and a batch computation mode for applying algorithms over large spatial and temporal extents. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, and resampling, which facilitates writing algorithms that combine data from multiple sensors and/or models. Although the primary use of Earth Engine, to date, has been the analysis of large Earth observing satellite datasets, the computational platform is generally applicable to a wide variety of use cases that require large-scale geospatial data analyses. This presentation will focus on how Earth Engine facilitates the analysis of geospatial data streams that originate from multiple separate sources (and often communities) and how it enables collaboration during algorithm development and data exploration. The talk will highlight current projects/analyses that are enabled by this functionality.https://earthengine.google.org

Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields

PubMed Central

Weller, Daniel; Shiwakoti, Suvash; Bergholz, Peter; Grohn, Yrjo; Wiedmann, Martin

2015-01-01

Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce. PMID:26590280

Open cyberGIS software for geospatial research and education in the big data era

NASA Astrophysics Data System (ADS)

Wang, Shaowen; Liu, Yan; Padmanabhan, Anand

CyberGIS represents an interdisciplinary field combining advanced cyberinfrastructure, geographic information science and systems (GIS), spatial analysis and modeling, and a number of geospatial domains to improve research productivity and enable scientific breakthroughs. It has emerged as new-generation GIS that enable unprecedented advances in data-driven knowledge discovery, visualization and visual analytics, and collaborative problem solving and decision-making. This paper describes three open software strategies-open access, source, and integration-to serve various research and education purposes of diverse geospatial communities. These strategies have been implemented in a leading-edge cyberGIS software environment through three corresponding software modalities: CyberGIS Gateway, Toolkit, and Middleware, and achieved broad and significant impacts.

New Techniques for Deep Learning with Geospatial Data using TensorFlow, Earth Engine, and Google Cloud Platform

NASA Astrophysics Data System (ADS)

Hancher, M.

2017-12-01

Recent years have seen promising results from many research teams applying deep learning techniques to geospatial data processing. In that same timeframe, TensorFlow has emerged as the most popular framework for deep learning in general, and Google has assembled petabytes of Earth observation data from a wide variety of sources and made them available in analysis-ready form in the cloud through Google Earth Engine. Nevertheless, developing and applying deep learning to geospatial data at scale has been somewhat cumbersome to date. We present a new set of tools and techniques that simplify this process. Our approach combines the strengths of several underlying tools: TensorFlow for its expressive deep learning framework; Earth Engine for data management, preprocessing, postprocessing, and visualization; and other tools in Google Cloud Platform to train TensorFlow models at scale, perform additional custom parallel data processing, and drive the entire process from a single familiar Python development environment. These tools can be used to easily apply standard deep neural networks, convolutional neural networks, and other custom model architectures to a variety of geospatial data structures. We discuss our experiences applying these and related tools to a range of machine learning problems, including classic problems like cloud detection, building detection, land cover classification, as well as more novel problems like illegal fishing detection. Our improved tools will make it easier for geospatial data scientists to apply modern deep learning techniques to their own problems, and will also make it easier for machine learning researchers to advance the state of the art of those techniques.

Geospatial Applications on Different Parallel and Distributed Systems in enviroGRIDS Project

NASA Astrophysics Data System (ADS)

Rodila, D.; Bacu, V.; Gorgan, D.

2012-04-01

The execution of Earth Science applications and services on parallel and distributed systems has become a necessity especially due to the large amounts of Geospatial data these applications require and the large geographical areas they cover. The parallelization of these applications comes to solve important performance issues and can spread from task parallelism to data parallelism as well. Parallel and distributed architectures such as Grid, Cloud, Multicore, etc. seem to offer the necessary functionalities to solve important problems in the Earth Science domain: storing, distribution, management, processing and security of Geospatial data, execution of complex processing through task and data parallelism, etc. A main goal of the FP7-funded project enviroGRIDS (Black Sea Catchment Observation and Assessment System supporting Sustainable Development) [1] is the development of a Spatial Data Infrastructure targeting this catchment region but also the development of standardized and specialized tools for storing, analyzing, processing and visualizing the Geospatial data concerning this area. For achieving these objectives, the enviroGRIDS deals with the execution of different Earth Science applications, such as hydrological models, Geospatial Web services standardized by the Open Geospatial Consortium (OGC) and others, on parallel and distributed architecture to maximize the obtained performance. This presentation analysis the integration and execution of Geospatial applications on different parallel and distributed architectures and the possibility of choosing among these architectures based on application characteristics and user requirements through a specialized component. Versions of the proposed platform have been used in enviroGRIDS project on different use cases such as: the execution of Geospatial Web services both on Web and Grid infrastructures [2] and the execution of SWAT hydrological models both on Grid and Multicore architectures [3]. The current focus is to integrate in the proposed platform the Cloud infrastructure, which is still a paradigm with critical problems to be solved despite the great efforts and investments. Cloud computing comes as a new way of delivering resources while using a large set of old as well as new technologies and tools for providing the necessary functionalities. The main challenges in the Cloud computing, most of them identified also in the Open Cloud Manifesto 2009, address resource management and monitoring, data and application interoperability and portability, security, scalability, software licensing, etc. We propose a platform able to execute different Geospatial applications on different parallel and distributed architectures such as Grid, Cloud, Multicore, etc. with the possibility of choosing among these architectures based on application characteristics and complexity, user requirements, necessary performances, cost support, etc. The execution redirection on a selected architecture is realized through a specialized component and has the purpose of offering a flexible way in achieving the best performances considering the existing restrictions.

Promising Practices in Building Geospatial Academic Pathways and Educator Capacity: Findings from a Multiyear Evaluation Study.

NASA Astrophysics Data System (ADS)

Peery, B.; Wilkerson, S.

2015-12-01

Geospatial technology, including geographical information systems, global positioning systems, remote sensing and the analysis and interpretation of spatial data, is a rapidly growing industry in the United States and touches almost every discipline from business to the environment to health and sciences. The demand for a larger and more qualified geospatial workforce is simultaneously increasing. The GeoTEd project aims to meet this demand in Virginia and the surrounding region by 1) developing academic-to-workforce pathways, 2) providing professional development for educators, and 3) increasing student participation and impact. Since 2009, Magnolia Consulting has been evaluating the GeoTEd project, particularly its professional development work through the GeoTEd Institute. This presentation will provide a look into the challenges and successes of GeoTEd, and examine its impact on the geospatial academic pathways in the Virginia region. The presentation will highlight promising elements of this project that could serve as models for other endeavors.

Simulation-based decision support framework for dynamic ambulance redeployment in Singapore.

PubMed

Lam, Sean Shao Wei; Ng, Clarence Boon Liang; Nguyen, Francis Ngoc Hoang Long; Ng, Yih Yng; Ong, Marcus Eng Hock

2017-10-01

Dynamic ambulance redeployment policies tend to introduce much more flexibilities in improving ambulance resource allocation by capitalizing on the definite geospatial-temporal variations in ambulance demand patterns over the time-of-the-day and day-of-the-week effects. A novel modelling framework based on the Approximate Dynamic Programming (ADP) approach leveraging on a Discrete Events Simulation (DES) model for dynamic ambulance redeployment in Singapore is proposed in this paper. The study was based on the Singapore's national Emergency Medical Services (EMS) system. Based on a dataset comprising 216,973 valid incidents over a continuous two-years study period from 1 January 2011-31 December 2012, a DES model for the EMS system was developed. An ADP model based on linear value function approximations was then evaluated using the DES model via the temporal difference (TD) learning family of algorithms. The objective of the ADP model is to derive approximate optimal dynamic redeployment policies based on the primary outcome of ambulance coverage. Considering an 8min response time threshold, an estimated 5% reduction in the proportion of calls that cannot be reached within the threshold (equivalent to approximately 8000 dispatches) was observed from the computational experiments. The study also revealed that the redeployment policies which are restricted within the same operational division could potentially result in a more promising response time performance. Furthermore, the best policy involved the combination of redeploying ambulances whenever they are released from service and that of relocating ambulances that are idle in bases. This study demonstrated the successful application of an approximate modelling framework based on ADP that leverages upon a detailed DES model of the Singapore's EMS system to generate approximate optimal dynamic redeployment plans. Various policies and scenarios relevant to the Singapore EMS system were evaluated. Copyright © 2017 Elsevier B.V. All rights reserved.

A flexible geospatial sensor observation service for diverse sensor data based on Web service

NASA Astrophysics Data System (ADS)

Chen, Nengcheng; Di, Liping; Yu, Genong; Min, Min

Achieving a flexible and efficient geospatial Sensor Observation Service (SOS) is difficult, given the diversity of sensor networks, the heterogeneity of sensor data storage, and the differing requirements of users. This paper describes development of a service-oriented multi-purpose SOS framework. The goal is to create a single method of access to the data by integrating the sensor observation service with other Open Geospatial Consortium (OGC) services — Catalogue Service for the Web (CSW), Transactional Web Feature Service (WFS-T) and Transactional Web Coverage Service (WCS-T). The framework includes an extensible sensor data adapter, an OGC-compliant geospatial SOS, a geospatial catalogue service, a WFS-T, and a WCS-T for the SOS, and a geospatial sensor client. The extensible sensor data adapter finds, stores, and manages sensor data from live sensors, sensor models, and simulation systems. Abstract factory design patterns are used during design and implementation. A sensor observation service compatible with the SWE is designed, following the OGC "core" and "transaction" specifications. It is implemented using Java servlet technology. It can be easily deployed in any Java servlet container and automatically exposed for discovery using Web Service Description Language (WSDL). Interaction sequences between a Sensor Web data consumer and an SOS, between a producer and an SOS, and between an SOS and a CSW are described in detail. The framework has been successfully demonstrated in application scenarios for EO-1 observations, weather observations, and water height gauge observations.

Data Collection and Management with ENSITE HUB: ENSITE HUB Version 1.0

DTIC Science & Technology

2017-08-01

Model (GGDM) standards. The Army Geospatial Enterprise (AGE) is where the standardized geospatial information is collected, managed , ana- lyzed...acquisition information management . (http://asc.army.mil/web/organization) ERDC/CERL SR-17-14 6 • Static feature classes with a yearly vintage must...ER D C/ CE RL S R- 17 -1 4 Engineer Site Identification for the Tactical Environment (ENSITE) Data Collection and Management with ENSITE

Hitting the Moving Target: Challenges of Creating a Dynamic Curriculum Addressing the Ethical Dimensions of Geospatial Data

ERIC Educational Resources Information Center

Carr, John; Vallor, Shannon; Freundschuh, Scott; Gannon, William L.; Zandbergen, Paul

2014-01-01

While established ethical norms and core legal principles concerning the protection of privacy may be easily identified, applying these standards to rapidly evolving digital information technologies, markets for digital information and convulsive changes in social understandings of privacy is increasingly challenging. This challenge has been…

Creating 3D models of historical buildings using geospatial data

NASA Astrophysics Data System (ADS)

Alionescu, Adrian; Bǎlǎ, Alina Corina; Brebu, Floarea Maria; Moscovici, Anca-Maria

2017-07-01

Recently, a lot of interest has been shown to understand a real world object by acquiring its 3D images of using laser scanning technology and panoramic images. A realistic impression of geometric 3D data can be generated by draping real colour textures simultaneously captured by a colour camera images. In this context, a new concept of geospatial data acquisition has rapidly revolutionized the method of determining the spatial position of objects, which is based on panoramic images. This article describes an approach that comprises inusing terrestrial laser scanning and panoramic images captured with Trimble V10 Imaging Rover technology to enlarge the details and realism of the geospatial data set, in order to obtain 3D urban plans and virtual reality applications.

EPA Geospatial Quality Council Promoting Quality Assurance in the Geospatial Coummunity

EPA Science Inventory

After establishing a foundation for the EPA National Geospatial Program, the EPA Geospatial Quality Council (GQC) is, in part, focusing on improving administrative efficiency in the geospatial community. To realize this goal, the GQC is developing Standard Operating Procedures (S...

A Python Geospatial Language Toolkit

NASA Astrophysics Data System (ADS)

Fillmore, D.; Pletzer, A.; Galloy, M.

2012-12-01

The volume and scope of geospatial data archives, such as collections of satellite remote sensing or climate model products, has been rapidly increasing and will continue to do so in the near future. The recently launched (October 2011) Suomi National Polar-orbiting Partnership satellite (NPP) for instance, is the first of a new generation of Earth observation platforms that will monitor the atmosphere, oceans, and ecosystems, and its suite of instruments will generate several terabytes each day in the form of multi-spectral images and derived datasets. Full exploitation of such data for scientific analysis and decision support applications has become a major computational challenge. Geophysical data exploration and knowledge discovery could benefit, in particular, from intelligent mechanisms for extracting and manipulating subsets of data relevant to the problem of interest. Potential developments include enhanced support for natural language queries and directives to geospatial datasets. The translation of natural language (that is, human spoken or written phrases) into complex but unambiguous objects and actions can be based on a context, or knowledge domain, that represents the underlying geospatial concepts. This poster describes a prototype Python module that maps English phrases onto basic geospatial objects and operations. This module, along with the associated computational geometry methods, enables the resolution of natural language directives that include geographic regions of arbitrary shape and complexity.

Geospatial decision support framework for critical infrastructure interdependency assessment

NASA Astrophysics Data System (ADS)

Shih, Chung Yan

Critical infrastructures, such as telecommunications, energy, banking and finance, transportation, water systems and emergency services are the foundations of modern society. There is a heavy dependence on critical infrastructures at multiple levels within the supply chain of any good or service. Any disruptions in the supply chain may cause profound cascading effect to other critical infrastructures. A 1997 report by the President's Commission on Critical Infrastructure Protection states that a serious interruption in freight rail service would bring the coal mining industry to a halt within approximately two weeks and the availability of electric power could be reduced in a matter of one to two months. Therefore, this research aimed at representing and assessing the interdependencies between coal supply, transportation and energy production. A proposed geospatial decision support framework was established and applied to analyze interdependency related disruption impact. By utilizing the data warehousing approach, geospatial and non-geospatial data were retrieved, integrated and analyzed based on the transportation model and geospatial disruption analysis developed in the research. The results showed that by utilizing this framework, disruption impacts can be estimated at various levels (e.g., power plant, county, state, etc.) for preventative or emergency response efforts. The information derived from the framework can be used for data mining analysis (e.g., assessing transportation mode usages; finding alternative coal suppliers, etc.).

Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data

USGS Publications Warehouse

Yuan, Shuai; Zhou, Jiayu; Tan, Pang-Ning; Fergus, Emi; Wagner, Tyler; Sorrano, Patricia

2017-01-01

Predictive modeling of nested geospatial data is a challenging problem as the models must take into account potential interactions among variables defined at different spatial scales. These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.

Long-Term Audience Impacts of Live Fulldome Planetarium Lectures for Earth Science and Global Change Education

NASA Astrophysics Data System (ADS)

Yu, K. C.; Champlin, D. M.; Goldsworth, D. A.; Raynolds, R. G.; Dechesne, M.

2011-09-01

Digital Earth visualization technologies, from ArcGIS to Google Earth, have allowed for the integration of complex, disparate data sets to produce visually rich and compelling three-dimensional models of sub-surface and surface resource distribution patterns. The rendering of these models allows the public to quickly understand complicated geospatial relationships that would otherwise take much longer to explain using traditional media. At the Denver Museum of Nature & Science (DMNS), we have used such visualization technologies, including real-time virtual reality software running in the immersive digital "fulldome" Gates Planetarium, to impact the community through topical policy presentations. DMNS public lectures have covered regional issues like water resources, as well as global topics such as earthquakes, tsunamis, and resource depletion. The Gates Planetarium allows an audience to have an immersive experience-similar to virtual reality "CAVE" environments found in academia-that would otherwise not be available to the general public. Public lectures in the dome allow audiences of over 100 people to comprehend dynamically changing geospatial datasets in an exciting and engaging fashion. Surveys and interviews show that these talks are effective in heightening visitor interest in the subjects weeks or months after the presentation. Many visitors take additional steps to learn more, while one was so inspired that she actively worked to bring the same programming to her children's school. These preliminary findings suggest that fulldome real-time visualizations can have a substantial long-term impact on an audience's engagement and interest in science topics.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

From Particles and Point Clouds to Voxel Models: High Resolution Modeling of Dynamic Landscapes in Open Source GIS

NASA Astrophysics Data System (ADS)

Mitasova, H.; Hardin, E. J.; Kratochvilova, A.; Landa, M.

2012-12-01

Multitemporal data acquired by modern mapping technologies provide unique insights into processes driving land surface dynamics. These high resolution data also offer an opportunity to improve the theoretical foundations and accuracy of process-based simulations of evolving landforms. We discuss development of new generation of visualization and analytics tools for GRASS GIS designed for 3D multitemporal data from repeated lidar surveys and from landscape process simulations. We focus on data and simulation methods that are based on point sampling of continuous fields and lead to representation of evolving surfaces as series of raster map layers or voxel models. For multitemporal lidar data we present workflows that combine open source point cloud processing tools with GRASS GIS and custom python scripts to model and analyze dynamics of coastal topography (Figure 1) and we outline development of coastal analysis toolbox. The simulations focus on particle sampling method for solving continuity equations and its application for geospatial modeling of landscape processes. In addition to water and sediment transport models, already implemented in GIS, the new capabilities under development combine OpenFOAM for wind shear stress simulation with a new module for aeolian sand transport and dune evolution simulations. Comparison of observed dynamics with the results of simulations is supported by a new, integrated 2D and 3D visualization interface that provides highly interactive and intuitive access to the redesigned and enhanced visualization tools. Several case studies will be used to illustrate the presented methods and tools and demonstrate the power of workflows built with FOSS and highlight their interoperability.Figure 1. Isosurfaces representing evolution of shoreline and a z=4.5m contour between the years 1997-2011at Cape Hatteras, NC extracted from a voxel model derived from series of lidar-based DEMs.

Methods and Tools to Align Curriculum to the Skills and Competencies Needed by the Workforce - an Example from Geospatial Science and Technology

NASA Astrophysics Data System (ADS)

Johnson, A. B.

2012-12-01

Geospatial science and technology (GST) including geographic information systems, remote sensing, global positioning systems and mobile applications, are valuable tools for geoscientists and students learning to become geoscientists. GST allows the user to analyze data spatially and temporarily and then visualize the data and outcomes in multiple formats (digital, web and paper). GST has evolved rapidly and it has been difficult to create effective curriculum as few guidelines existed to help educators. In 2010, the US Department of Labor (DoL), in collaboration with the National Geospatial Center of Excellence (GeoTech Center), a National Science Foundation supported grant, approved the Geospatial Technology Competency Mode (GTCM). The GTCM was developed and vetted with industry experts and provided the structure and example competencies needed across the industry. While the GTCM was helpful, a more detailed list of skills and competencies needed to be identified in order to build appropriate curriculum. The GeoTech Center carried out multiple DACUM events to identify the skills and competencies needed by entry-level workers. DACUM (Developing a Curriculum) is a job analysis process whereby expert workers are convened to describe what they do for a specific occupation. The outcomes from multiple DACUMs were combined into a MetaDACUM and reviewed by hundreds of GST professionals. This provided a list of more than 320 skills and competencies needed by the workforce. The GeoTech Center then held multiple workshops across the U.S. where more than 100 educators knowledgeable in teaching GST parsed the list into Model Courses and a Model Certificate Program. During this process, tools were developed that helped educators define which competency should be included in a specific course and the depth of instruction for that competency. This presentation will provide details about the process, methodology and tools used to create the Models and suggest how they can be used to create customized curriculum integrating geospatial science and technology into geoscience programs.

Nebraska NativeGEM (Geospatial Extension Model)

NASA Technical Reports Server (NTRS)

Bowen, Brent

2004-01-01

This proposal, Nebraska NativeGEM (Geospatial Extension Model) features a unique diversity component stemming from the exceptional reputation NNSGC has built by delivering geospatial science experiences to Nebraska s Native Americans. For 7 years, NNSGC has partner4 with the 2 tribal colleges and 4 reservation school districts in Nebraska to form the Nebraska Native American Outreach Program (NNAOP), a partnership among tribal community leaders, academia, tribal schools, and industry reaching close to 1,OOO Native American youth, over 1,200 community members (Lehrer & Zendajas, 2001).NativeGEM addresses all three key components of Cooperative State Research, Education, and Extension Service (CSREES) goals for advancing decision support, education, and workforce development through the GES. The existing long term commitments that the NNSGC and the GES have in these areas allow for the pursuit of a broad range of activities. NativeGEM builds upon these existing successful programs and collaborations. Outcomes and metrics for each proposed project are detailed in the Approach section of this document.

Robert Spencer | NREL

Science.gov Websites

& Simulation Research Interests Remote Sensing Natural Resource Modeling Machine Learning Education Analysis Center. Areas of Expertise Geospatial Analysis Data Visualization Algorithm Development Modeling

Landscape Characterization of Arctic Ecosystems Using Data Mining Algorithms and Large Geospatial Datasets

NASA Astrophysics Data System (ADS)

Langford, Z. L.; Kumar, J.; Hoffman, F. M.

2015-12-01

Observations indicate that over the past several decades, landscape processes in the Arctic have been changing or intensifying. A dynamic Arctic landscape has the potential to alter ecosystems across a broad range of scales. Accurate characterization is useful to understand the properties and organization of the landscape, optimal sampling network design, measurement and process upscaling and to establish a landscape-based framework for multi-scale modeling of ecosystem processes. This study seeks to delineate the landscape at Seward Peninsula of Alaska into ecoregions using large volumes (terabytes) of high spatial resolution satellite remote-sensing data. Defining high-resolution ecoregion boundaries is difficult because many ecosystem processes in Arctic ecosystems occur at small local to regional scales, which are often resolved in by coarse resolution satellites (e.g., MODIS). We seek to use data-fusion techniques and data analytics algorithms applied to Phased Array type L-band Synthetic Aperture Radar (PALSAR), Interferometric Synthetic Aperture Radar (IFSAR), Satellite for Observation of Earth (SPOT), WorldView-2, WorldView-3, and QuickBird-2 to develop high-resolution (˜5m) ecoregion maps for multiple time periods. Traditional analysis methods and algorithms are insufficient for analyzing and synthesizing such large geospatial data sets, and those algorithms rarely scale out onto large distributed- memory parallel computer systems. We seek to develop computationally efficient algorithms and techniques using high-performance computing for characterization of Arctic landscapes. We will apply a variety of data analytics algorithms, such as cluster analysis, complex object-based image analysis (COBIA), and neural networks. We also propose to use representativeness analysis within the Seward Peninsula domain to determine optimal sampling locations for fine-scale measurements. This methodology should provide an initial framework for analyzing dynamic landscape trends in Arctic ecosystems, such as shrubification and disturbances, and integration of ecoregions into multi-scale models.

Use of ebRIM-based CSW with sensor observation services for registry and discovery of remote-sensing observations

NASA Astrophysics Data System (ADS)

Chen, Nengcheng; Di, Liping; Yu, Genong; Gong, Jianya; Wei, Yaxing

2009-02-01

Recent advances in Sensor Web geospatial data capture, such as high-resolution in satellite imagery and Web-ready data processing and modeling technologies, have led to the generation of large numbers of datasets from real-time or near real-time observations and measurements. Finding which sensor or data complies with criteria such as specific times, locations, and scales has become a bottleneck for Sensor Web-based applications, especially remote-sensing observations. In this paper, an architecture for use of the integration Sensor Observation Service (SOS) with the Open Geospatial Consortium (OGC) Catalogue Service-Web profile (CSW) is put forward. The architecture consists of a distributed geospatial sensor observation service, a geospatial catalogue service based on the ebXML Registry Information Model (ebRIM), SOS search and registry middleware, and a geospatial sensor portal. The SOS search and registry middleware finds the potential SOS, generating data granule information and inserting the records into CSW. The contents and sequence of the services, the available observations, and the metadata of the observations registry are described. A prototype system is designed and implemented using the service middleware technology and a standard interface and protocol. The feasibility and the response time of registry and retrieval of observations are evaluated using a realistic Earth Observing-1 (EO-1) SOS scenario. Extracting information from SOS requires the same execution time as record generation for CSW. The average data retrieval response time in SOS+CSW mode is 17.6% of that of the SOS-alone mode. The proposed architecture has the more advantages of SOS search and observation data retrieval than the existing sensor Web enabled systems.

An on-demand provision model for geospatial multisource information with active self-adaption services

NASA Astrophysics Data System (ADS)

Fan, Hong; Li, Huan

2015-12-01

Location-related data are playing an increasingly irreplaceable role in business, government and scientific research. At the same time, the amount and types of data are rapidly increasing. It is a challenge how to quickly find required information from this rapidly growing volume of data, as well as how to efficiently provide different levels of geospatial data to users. This paper puts forward a data-oriented access model for geographic information science data. First, we analyze the features of GIS data including traditional types such as vector and raster data and new types such as Volunteered Geographic Information (VGI). Taking into account these analyses, a classification scheme for geographic data is proposed and TRAFIE is introduced to describe the establishment of a multi-level model for geographic data. Based on this model, a multi-level, scalable access system for geospatial information is put forward. Users can select different levels of data according to their concrete application needs. Pull-based and push-based data access mechanisms based on this model are presented. A Service Oriented Architecture (SOA) was chosen for the data processing. The model of this study has been described by providing decision-making process of government departments with a simulation of fire disaster data collection. The use case shows this data model and the data provision system is flexible and has good adaptability.

SPARROW MODELING - Enhancing Understanding of the Nation's Water Quality

USGS Publications Warehouse

Preston, Stephen D.; Alexander, Richard B.; Woodside, Michael D.; Hamilton, Pixie A.

2009-01-01

The information provided here is intended to assist water-resources managers with interpretation of the U.S. Geological Survey (USGS) SPARROW model and its products. SPARROW models can be used to explain spatial patterns in monitored stream-water quality in relation to human activities and natural processes as defined by detailed geospatial information. Previous SPARROW applications have identified the sources and transport of nutrients in the Mississippi River basin, Chesapeake Bay watershed, and other major drainages of the United States. New SPARROW models with improved accuracy and interpretability are now being developed by the USGS National Water Quality Assessment (NAWQA) Program for six major regions of the conterminous United States. These new SPARROW models are based on updated geospatial data and stream-monitoring records from local, State, and other federal agencies.

A Geospatial Database for Wind and Solar Energy Applications: The Kingdom of Bahrain Study Case

NASA Astrophysics Data System (ADS)

Al-Joburi, Khalil; Dahman, Nidal

2017-11-01

This research is aimed at designing, implementing, and testing a geospatial database for wind and solar energy applications in the Kingdom of Bahrain. All decision making needed to determine economic feasibility and establish site location for wind turbines or solar panels depends primarily on geospatial feature theme information and non-spatial (attribute) data for wind, solar, rainfall, temperature and weather characteristics of a particular region. Spatial data includes, but is not limited to, digital elevation, slopes, land use, zonings, parks, population density, road utility maps, and other related information. Digital elevations for over 450,000 spot at 50 m spatial horizontal resolution plus field surveying and GPS (at selected locations) was obtained from the Surveying and Land Registration Bureau (SLRB). Road, utilities, and population density are obtained from the Central Information Organization (CIO). Land use zoning, recreational parks, and other data are obtained from the Ministry of Municipalities and Agricultural Affairs. Wind, solar, humidity, rainfall, and temperature data are obtained from the Ministry of Transportation, Civil Aviation Section. LandSat Satellite and others images are obtained from NASA and online sources respectively. The collected geospatial data was geo-referenced to Ain el-Abd UTM Zone 39 North. 3D Digital Elevation Model (DEM)-50 m spatial resolutions was created using SLRB spot elevations. Slope and aspect maps were generate based on the DEM. Supervised image classification to identify open spaces was performed utilizing satellite images. Other geospatial data was converted to raster format with the same cell resolution. Non-spatial data are entered as an attribute to spatial features. To eliminate ambiguous solution, multi-criteria GIS model is developed based on, vector (discrete point, line, and polygon representations) as well as raster model (continuous representation). The model was tested at the Al-Areen proposed project, a relatively small area (15 km2). Optimum site spatial location for the location of wind turbines and solar panels was determined and initial results indicates that the combination of wind and solar energy would be sufficient for the project to meet the energy demand at the present per capita consummation rate..

Geospatial considerations for a multiorganizational, landscape-scale program

USGS Publications Warehouse

O'Donnell, Michael S.; Assal, Timothy J.; Anderson, Patrick J.; Bowen, Zachary H.

2013-01-01

Geospatial data play an increasingly important role in natural resources management, conservation, and science-based projects. The management and effective use of spatial data becomes significantly more complex when the efforts involve a myriad of landscape-scale projects combined with a multiorganizational collaboration. There is sparse literature to guide users on this daunting subject; therefore, we present a framework of considerations for working with geospatial data that will provide direction to data stewards, scientists, collaborators, and managers for developing geospatial management plans. The concepts we present apply to a variety of geospatial programs or projects, which we describe as a “scalable framework” of processes for integrating geospatial efforts with management, science, and conservation initiatives. Our framework includes five tenets of geospatial data management: (1) the importance of investing in data management and standardization, (2) the scalability of content/efforts addressed in geospatial management plans, (3) the lifecycle of a geospatial effort, (4) a framework for the integration of geographic information systems (GIS) in a landscape-scale conservation or management program, and (5) the major geospatial considerations prior to data acquisition. We conclude with a discussion of future considerations and challenges.

Considerations on Geospatial Big Data

NASA Astrophysics Data System (ADS)

LIU, Zhen; GUO, Huadong; WANG, Changlin

2016-11-01

Geospatial data, as a significant portion of big data, has recently gained the full attention of researchers. However, few researchers focus on the evolution of geospatial data and its scientific research methodologies. When entering into the big data era, fully understanding the changing research paradigm associated with geospatial data will definitely benefit future research on big data. In this paper, we look deep into these issues by examining the components and features of geospatial big data, reviewing relevant scientific research methodologies, and examining the evolving pattern of geospatial data in the scope of the four ‘science paradigms’. This paper proposes that geospatial big data has significantly shifted the scientific research methodology from ‘hypothesis to data’ to ‘data to questions’ and it is important to explore the generality of growing geospatial data ‘from bottom to top’. Particularly, four research areas that mostly reflect data-driven geospatial research are proposed: spatial correlation, spatial analytics, spatial visualization, and scientific knowledge discovery. It is also pointed out that privacy and quality issues of geospatial data may require more attention in the future. Also, some challenges and thoughts are raised for future discussion.

Geospatial distribution modeling and determining suitability of groundwater quality for irrigation purpose using geospatial methods and water quality index (WQI) in Northern Ethiopia

NASA Astrophysics Data System (ADS)

Gidey, Amanuel

2018-06-01

Determining suitability and vulnerability of groundwater quality for irrigation use is a key alarm and first aid for careful management of groundwater resources to diminish the impacts on irrigation. This study was conducted to determine the overall suitability of groundwater quality for irrigation use and to generate their spatial distribution maps in Elala catchment, Northern Ethiopia. Thirty-nine groundwater samples were collected to analyze and map the water quality variables. Atomic absorption spectrophotometer, ultraviolet spectrophotometer, titration and calculation methods were used for laboratory groundwater quality analysis. Arc GIS, geospatial analysis tools, semivariogram model types and interpolation methods were used to generate geospatial distribution maps. Twelve and eight water quality variables were used to produce weighted overlay and irrigation water quality index models, respectively. Root-mean-square error, mean square error, absolute square error, mean error, root-mean-square standardized error, measured values versus predicted values were used for cross-validation. The overall weighted overlay model result showed that 146 km2 areas are highly suitable, 135 km2 moderately suitable and 60 km2 area unsuitable for irrigation use. The result of irrigation water quality index confirms 10.26% with no restriction, 23.08% with low restriction, 20.51% with moderate restriction, 15.38% with high restriction and 30.76% with the severe restriction for irrigation use. GIS and irrigation water quality index are better methods for irrigation water resources management to achieve a full yield irrigation production to improve food security and to sustain it for a long period, to avoid the possibility of increasing environmental problems for the future generation.

Creating of Central Geospatial Database of the Slovak Republic and Procedures of its Revision

NASA Astrophysics Data System (ADS)

Miškolci, M.; Šafář, V.; Šrámková, R.

2016-06-01

The article describes the creation of initial three dimensional geodatabase from planning and designing through the determination of technological and manufacturing processes to practical using of Central Geospatial Database (CGD - official name in Slovak language is Centrálna Priestorová Databáza - CPD) and shortly describes procedures of its revision. CGD ensures proper collection, processing, storing, transferring and displaying of digital geospatial information. CGD is used by Ministry of Defense (MoD) for defense and crisis management tasks and by Integrated rescue system. For military personnel CGD is run on MoD intranet, and for other users outside of MoD is transmutated to ZbGIS (Primary Geodatabase of Slovak Republic) and is run on public web site. CGD is a global set of geo-spatial information. CGD is a vector computer model which completely covers entire territory of Slovakia. Seamless CGD is created by digitizing of real world using of photogrammetric stereoscopic methods and measurements of objects properties. Basic vector model of CGD (from photogrammetric processing) is then taken out to the field for inspection and additional gathering of objects properties in the whole area of mapping. Finally real-world objects are spatially modeled as a entities of three-dimensional database. CGD gives us opportunity, to get know the territory complexly in all the three spatial dimensions. Every entity in CGD has recorded the time of collection, which allows the individual to assess the timeliness of information. CGD can be utilized for the purposes of geographical analysis, geo-referencing, cartographic purposes as well as various special-purpose mapping and has the ambition to cover the needs not only the MoD, but to become a reference model for the national geographical infrastructure.

Visualizing and Understanding Socio-Environmental Dynamics in Baltimore

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.; Omeara, K.; Guikema, S.; Scott, A.; Bessho, A.; Logan, T. M.

2015-12-01

The City of Baltimore, like any city, is the sum of its component neighborhoods, institutions, businesses, cultures, and, ultimately, its people. It is also an organism in its own right, with distinct geography, history, infrastructure, and environments that shape its residents even as it is shaped by them. Sometimes these interactions are obvious but often they are not; while basic economic patterns are widely documented, the distribution of socio-spatial and environmental connections often hides below the surface, as does the potential that those connections hold. Here we present results of a collaborative initiative on the geography, design, and policy of socio-environmental dynamics of Baltimore. Geospatial data derived from satellite imagery, demographic databases, social media feeds, infrastructure plans, and in situ environmental networks, among other sources, are applied to generate an interactive portrait of Baltimore City's social, health, and well-being dynamics. The layering of data serves as a platform for visualizing the interconnectedness of the City and as a database for modeling risk interactions, vulnerabilities, and strengths within and between communities. This presentation will provide an overview of project findings and highlight linkages to education and policy.

A Hybrid Semi-supervised Classification Scheme for Mining Multisource Geospatial Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vatsavai, Raju; Bhaduri, Budhendra L

2011-01-01

Supervised learning methods such as Maximum Likelihood (ML) are often used in land cover (thematic) classification of remote sensing imagery. ML classifier relies exclusively on spectral characteristics of thematic classes whose statistical distributions (class conditional probability densities) are often overlapping. The spectral response distributions of thematic classes are dependent on many factors including elevation, soil types, and ecological zones. A second problem with statistical classifiers is the requirement of large number of accurate training samples (10 to 30 |dimensions|), which are often costly and time consuming to acquire over large geographic regions. With the increasing availability of geospatial databases, itmore » is possible to exploit the knowledge derived from these ancillary datasets to improve classification accuracies even when the class distributions are highly overlapping. Likewise newer semi-supervised techniques can be adopted to improve the parameter estimates of statistical model by utilizing a large number of easily available unlabeled training samples. Unfortunately there is no convenient multivariate statistical model that can be employed for mulitsource geospatial databases. In this paper we present a hybrid semi-supervised learning algorithm that effectively exploits freely available unlabeled training samples from multispectral remote sensing images and also incorporates ancillary geospatial databases. We have conducted several experiments on real datasets, and our new hybrid approach shows over 25 to 35% improvement in overall classification accuracy over conventional classification schemes.« less

Multi-focused geospatial analysis using probes.

PubMed

Butkiewicz, Thomas; Dou, Wenwen; Wartell, Zachary; Ribarsky, William; Chang, Remco

2008-01-01

Traditional geospatial information visualizations often present views that restrict the user to a single perspective. When zoomed out, local trends and anomalies become suppressed and lost; when zoomed in for local inspection, spatial awareness and comparison between regions become limited. In our model, coordinated visualizations are integrated within individual probe interfaces, which depict the local data in user-defined regions-of-interest. Our probe concept can be incorporated into a variety of geospatial visualizations to empower users with the ability to observe, coordinate, and compare data across multiple local regions. 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. We illustrate the effectiveness of our technique over traditional interfaces by incorporating it within three existing geospatial visualization systems: an agent-based social simulation, a census data exploration tool, and an 3D GIS environment for analyzing urban change over time. In each case, the probe-based interaction enhances spatial awareness, improves inspection and comparison capabilities, expands the range of scopes, and facilitates collaboration among multiple users.

Smart Cities Intelligence System (SMACiSYS) Integrating Sensor Web with Spatial Data Infrastructures (sensdi)

NASA Astrophysics Data System (ADS)

Bhattacharya, D.; Painho, M.

2017-09-01

The paper endeavours to enhance the Sensor Web with crucial geospatial analysis capabilities through integration with Spatial Data Infrastructure. The objective is development of automated smart cities intelligence system (SMACiSYS) with sensor-web access (SENSDI) utilizing geomatics for sustainable societies. There has been a need to develop automated integrated system to categorize events and issue information that reaches users directly. At present, no web-enabled information system exists which can disseminate messages after events evaluation in real time. Research work formalizes a notion of an integrated, independent, generalized, and automated geo-event analysing system making use of geo-spatial data under popular usage platform. Integrating Sensor Web With Spatial Data Infrastructures (SENSDI) aims to extend SDIs with sensor web enablement, converging geospatial and built infrastructure, and implement test cases with sensor data and SDI. The other benefit, conversely, is the expansion of spatial data infrastructure to utilize sensor web, dynamically and in real time for smart applications that smarter cities demand nowadays. Hence, SENSDI augments existing smart cities platforms utilizing sensor web and spatial information achieved by coupling pairs of otherwise disjoint interfaces and APIs formulated by Open Geospatial Consortium (OGC) keeping entire platform open access and open source. SENSDI is based on Geonode, QGIS and Java, that bind most of the functionalities of Internet, sensor web and nowadays Internet of Things superseding Internet of Sensors as well. In a nutshell, the project delivers a generalized real-time accessible and analysable platform for sensing the environment and mapping the captured information for optimal decision-making and societal benefit.

The geo-spatial information infrastructure at the Centre for Control and Prevention of Zoonoses, University of Ibadan, Nigeria: an emerging sustainable One-Health pavilion.

PubMed

Olugasa, B O

2014-12-01

The World-Wide-Web as a contemporary means of information sharing offers a platform for geo-spatial information dissemination to improve education about spatio-temporal patterns of disease spread at the human-animal-environment interface in developing countries of West Africa. In assessing the quality of exposure to geospatial information applications among students in five purposively selected institutions in West Africa, this study reviewed course contents and postgraduate programmes in zoonoses surveillance. Geospatial information content and associated practical exercises in zoonoses surveillance were scored.. Seven criteria were used to categorize and score capability, namely, spatial data capture; thematic map design and interpretation; spatio-temporal analysis; remote sensing of data; statistical modelling; the management of spatial data-profile; and web-based map sharing operation within an organization. These criteria were used to compute weighted exposure during training at the institutions. A categorical description of institution with highest-scoring of computed Cumulative Exposure Point Average (CEPA) was based on an illustration with retrospective records of rabies cases, using data from humans, animals and the environment, that were sourced from Grand Bassa County, Liberia to create and share maps and information with faculty, staff, students and the neighbourhood about animal bite injury surveillance and spatial distribution of rabies-like illness. Uniformly low CEPA values (0-1.3) were observed across academic departments. The highest (3.8) was observed at the Centre for Control and Prevention of Zoonoses (CCPZ), University of Ibadan, Nigeria, where geospatial techniques were systematically taught, and thematic and predictive maps were produced and shared online with other institutions in West Africa. In addition, a short course in zoonosis surveillance, which offers inclusive learning in geospatial applications, is taught at CCPZ. The paper presents a graded capability for geospatial data capture, analysis and an emerging sustainable map pavilion dedicated to zoonoses disease surveillance training among collaborating institutions in West Africa.

Barriers to use of geospatial data for adaptation to climate change and variability: case studies in public health.

PubMed

Aron, Joan L

2006-11-01

This paper presents two case studies of the barriers to the use of geospatial data in the context of public health adaptation to climate change and variability. The first case study is on the hazards of coastal zone development in the United States with the main emphasis on Hurricane Katrina. An important barrier to the use of geospatial data is that the legal system does not support restrictions on land use intended to protect the coastal zone. Economic interests to develop New Orleans and the Mississippi River, both over the long term and the short term, had the effect of increasing the impact of the hurricane. The second case study is epidemics of climate-sensitive diseases with the main emphasis on malaria in Africa. Limits to model accuracy may present a problem in using climate data for an early warning system, and some geographic locations are likely to be more suitable than others. Costs of the system, including the costs of errors, may also inhibit implementation. Deriving societal benefits from geospatial data requires an understanding of the particular decision contexts and organizational processes in which knowledge is developed and used. The data by themselves will not usually generate a societal response. Scientists working in applications should develop partnerships to address the use of geospatial data for societal benefit.

A Dynamic Information Framework: A Multi-Sector, Geospatial Gateway for Environmental Conservation and Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Fernandes, E. C.; Norbu, C.; Juizo, D.; Wangdi, T.; Richey, J. E.

2011-12-01

Landscapes, watersheds, and their downstream coastal and lacustrine zones are facing a series of challenges critical to their future, centered on the availability and distribution of water. Management options cover a range of issues, from bringing safe water to local villages for the rural poor, developing adaptation strategies for both rural and urban populations and large infrastructure, and sustaining environmental flows and ecosystem services needed for natural and human-dominated ecosystems. These targets represent a very complex set of intersecting issues of scale, cross-sector science and technology, education, politics, and economics, and the desired sustainable development is closely linked to how the nominally responsible governmental Ministries respond to the information they have. In practice, such information and even perspectives are virtually absent, in much of the developing world. A Dynamic Information Framework (DIF) is being designed as a knowledge platform whereby decision-makers in information-sparse regions can consider rigorous scenarios of alternative futures and obtain decision support for complex environmental and economic decisions is essential. The DIF is geospatial gateway, with functional components of base data layers, directed data layers focused on synthetic objectives, geospatially-explicit, process-based, cross-sector simulation models (requiring data from the directed data layers), and facilitated input/output (including visualizations), and decision support system and scenario testing capabilities. A fundamental aspect to a DIF is not only the convergence of multi-sector information, but how that information can be (a) integrated (b) used for robust simulations and projections, and (c) conveyed to policymakers and stakeholders, in the most compelling, and visual, manner. Examples are given of emerging applications. The ZambeziDIF was used to establish baselines for agriculture, biodiversity, and water resources in the lower Zambezi valley of Mozambique. The DrukDIF for Bhutan is moving from a test-of-concept to an operational phase, with uses from extending local biodiversity to computing how much energy can be sold tomorrow, based on waterflows today. AralDIF is being developed to serve as a neutral and transparent platform, as a catalyst for open and transparent discussion on water and energy linkages, for central Asia. ImisoziDIF is now being ramped up in Rwanda, to help guide scaling up of agricultural practices and biodiversity from sites to the country. The Virtual Mekong Basin, "tells the story" of the multiple issues facing the Mekong Basin.

The road to NHDPlus — Advancements in digital stream networks and associated catchments

USGS Publications Warehouse

Moore, Richard B.; Dewald, Thomas A.

2016-01-01

A progression of advancements in Geographic Information Systems techniques for hydrologic network and associated catchment delineation has led to the production of the National Hydrography Dataset Plus (NHDPlus). NHDPlus is a digital stream network for hydrologic modeling with catchments and a suite of related geospatial data. Digital stream networks with associated catchments provide a geospatial framework for linking and integrating water-related data. Advancements in the development of NHDPlus are expected to continue to improve the capabilities of this national geospatial hydrologic framework. NHDPlus is built upon the medium-resolution NHD and, like NHD, was developed by the U.S. Environmental Protection Agency and U.S. Geological Survey to support the estimation of streamflow and stream velocity used in fate-and-transport modeling. Catchments included with NHDPlus were created by integrating vector information from the NHD and from the Watershed Boundary Dataset with the gridded land surface elevation as represented by the National Elevation Dataset. NHDPlus is an actively used and continually improved dataset. Users recognize the importance of a reliable stream network and associated catchments. The NHDPlus spatial features and associated data tables will continue to be improved to support regional water quality and streamflow models and other user-defined applications.

Challenges in sharing of geospatial data by data custodians in South Africa

NASA Astrophysics Data System (ADS)

Kay, Sissiel E.

2018-05-01

As most development planning and rendering of public services happens at a place or in a space, geospatial data is required. This geospatial data is best managed through a spatial data infrastructure, which has as a key objective to share geospatial data. The collection and maintenance of geospatial data is expensive and time consuming and so the principle of "collect once - use many times" should apply. It is best to obtain the geospatial data from the authoritative source - the appointed data custodian. In South Africa the South African Spatial Data Infrastructure (SASDI) is the means to achieve the requirement for geospatial data sharing. This requires geospatial data sharing to take place between the data custodian and the user. All data custodians are expected to comply with the Spatial Data Infrastructure Act (SDI Act) in terms of geo-spatial data sharing. Currently data custodians are experiencing challenges with regard to the sharing of geospatial data. This research is based on the current ten data themes selected by the Committee for Spatial Information and the organisations identified as the data custodians for these ten data themes. The objectives are to determine whether the identified data custodians comply with the SDI Act with respect to geospatial data sharing, and if not what are the reasons for this. Through an international comparative assessment it then determines if the compliance with the SDI Act is not too onerous on the data custodians. The research concludes that there are challenges with geospatial data sharing in South Africa and that the data custodians only partially comply with the SDI Act in terms of geospatial data sharing. However, it is shown that the South African legislation is not too onerous on the data custodians.

Nebhydro: Sharing Geospatial Data to Supportwater Management in Nebraska

NASA Astrophysics Data System (ADS)

Kamble, B.; Irmak, A.; Hubbard, K.; Deogun, J.; Dvorak, B.

2012-12-01

Recent advances in web-enabled geographical technologies have the potential to make a dramatic impact on development of highly interactive spatial applications on the web for visualization of large-scale geospatial data by water resources and irrigation scientists. Spatial and point scale water resources data visualization are an emerging and challenging application domain. Query based visual explorations of geospatial hydrological data can play an important role in stimulating scientific hypotheses and seeking causal relationships among hydro variables. The Nebraska Hydrological Information System (NebHydro) utilizes ESRI's ArcGIS server technology to increase technological awareness among farmers, irrigation managers and policy makers. Web-based geospatial applications are an effective way to expose scientific hydrological datasets to the research community and the public. NebHydro uses Adobe Flex technology to offer an online visualization and data analysis system for presentation of social and economic data. Internet mapping services is an integrated product of GIS and Internet technologies; it is a favored solution to achieve the interoperability of GIS. The development of Internet based GIS services in the state of Nebraska showcases the benefits of sharing geospatial hydrological data among agencies, resource managers and policy makers. Geospatial hydrological Information (Evapotranspiration from Remote Sensing, vegetation indices (NDVI), USGS Stream gauge data, Climatic data etc.) is generally generated through model simulation (METRIC, SWAP, Linux, Python based scripting etc). Information is compiled into and stored within object oriented relational spatial databases using a geodatabase information model that supports the key data types needed by applications including features, relationships, networks, imagery, terrains, maps and layers. The system provides online access, querying, visualization, and analysis of the hydrological data from several sources at one place. The study indicates that internet GIS, developed using advanced technologies, provides valuable education potential to users in hydrology and irrigation engineering and suggests that such a system can support advanced hydrological data access and analysis tools to improve utility of data in operations. Keywords: Hydrological Information System, NebHydro, Water Management, data sharing, data visualization, ArcGIS server.

Geospatial Data Science Research Staff | Geospatial Data Science | NREL

Science.gov Websites

Oliveira, Ricardo Researcher II-Geospatial Science Ricardo.Oliveira@nrel.gov 303-275-3272 Gilroy, Nicholas Specialist Pamela.Gray.hann@nrel.gov 303-275-4626 Grue, Nicholas Researcher III-Geospatial Science Nick.Grue

PLANNING QUALITY IN GEOSPATIAL PROJECTS

EPA Science Inventory

This presentation will briefly review some legal drivers and present a structure for the writing of geospatial Quality Assurance Projects Plans. In addition, the Geospatial Quality Council geospatial information life-cycle and sources of error flowchart will be reviewed.

Automatic geospatial information Web service composition based on ontology interface matching

NASA Astrophysics Data System (ADS)

Xu, Xianbin; Wu, Qunyong; Wang, Qinmin

2008-10-01

With Web services technology the functions of WebGIS can be presented as a kind of geospatial information service, and helped to overcome the limitation of the information-isolated situation in geospatial information sharing field. Thus Geospatial Information Web service composition, which conglomerates outsourced services working in tandem to offer value-added service, plays the key role in fully taking advantage of geospatial information services. This paper proposes an automatic geospatial information web service composition algorithm that employed the ontology dictionary WordNet to analyze semantic distances among the interfaces. Through making matching between input/output parameters and the semantic meaning of pairs of service interfaces, a geospatial information web service chain can be created from a number of candidate services. A practice of the algorithm is also proposed and the result of it shows the feasibility of this algorithm and the great promise in the emerging demand for geospatial information web service composition.

75 FR 6056 - National Geospatial Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-05

... DEPARTMENT OF THE INTERIOR Office of the Secretary National Geospatial Advisory Committee AGENCY: Office of the Secretary, Interior. ACTION: Notice of renewal of National Geospatial Advisory Committee... renewed the National Geospatial Advisory Committee. The Committee will provide advice and recommendations...

Building asynchronous geospatial processing workflows with web services

NASA Astrophysics Data System (ADS)

Zhao, Peisheng; Di, Liping; Yu, Genong

2012-02-01

Geoscience research and applications often involve a geospatial processing workflow. This workflow includes a sequence of operations that use a variety of tools to collect, translate, and analyze distributed heterogeneous geospatial data. Asynchronous mechanisms, by which clients initiate a request and then resume their processing without waiting for a response, are very useful for complicated workflows that take a long time to run. Geospatial contents and capabilities are increasingly becoming available online as interoperable Web services. This online availability significantly enhances the ability to use Web service chains to build distributed geospatial processing workflows. This paper focuses on how to orchestrate Web services for implementing asynchronous geospatial processing workflows. The theoretical bases for asynchronous Web services and workflows, including asynchrony patterns and message transmission, are examined to explore different asynchronous approaches to and architecture of workflow code for the support of asynchronous behavior. A sample geospatial processing workflow, issued by the Open Geospatial Consortium (OGC) Web Service, Phase 6 (OWS-6), is provided to illustrate the implementation of asynchronous geospatial processing workflows and the challenges in using Web Services Business Process Execution Language (WS-BPEL) to develop them.

Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics

USGS Publications Warehouse

Pervez, Md Shahriar; Brown, Jesslyn F.

2010-01-01

Accurate geospatial information on the extent of irrigated land improves our understanding of agricultural water use, local land surface processes, conservation or depletion of water resources, and components of the hydrologic budget. We have developed a method in a geospatial modeling framework that assimilates irrigation statistics with remotely sensed parameters describing vegetation growth conditions in areas with agricultural land cover to spatially identify irrigated lands at 250-m cell size across the conterminous United States for 2002. The geospatial model result, known as the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset (MIrAD-US), identified irrigated lands with reasonable accuracy in California and semiarid Great Plains states with overall accuracies of 92% and 75% and kappa statistics of 0.75 and 0.51, respectively. A quantitative accuracy assessment of MIrAD-US for the eastern region has not yet been conducted, and qualitative assessment shows that model improvements are needed for the humid eastern regions where the distinction in annual peak NDVI between irrigated and non-irrigated crops is minimal and county sizes are relatively small. This modeling approach enables consistent mapping of irrigated lands based upon USDA irrigation statistics and should lead to better understanding of spatial trends in irrigated lands across the conterminous United States. An improved version of the model with revised datasets is planned and will employ 2007 USDA irrigation statistics.

Geospatial Web Services in Real Estate Information System

NASA Astrophysics Data System (ADS)

Radulovic, Aleksandra; Sladic, Dubravka; Govedarica, Miro; Popovic, Dragana; Radovic, Jovana

2017-12-01

Since the data of cadastral records are of great importance for the economic development of the country, they must be well structured and organized. Records of real estate on the territory of Serbia met many problems in previous years. To prevent problems and to achieve efficient access, sharing and exchange of cadastral data on the principles of interoperability, domain model for real estate is created according to current standards in the field of spatial data. The resulting profile of the domain model for the Serbian real estate cadastre is based on the current legislation and on Land Administration Domain Model (LADM) which is specified in the ISO19152 standard. Above such organized data, and for their effective exchange, it is necessary to develop a model of services that must be provided by the institutions interested in the exchange of cadastral data. This is achieved by introducing a service-oriented architecture in the information system of real estate cadastre and with that ensures efficiency of the system. It is necessary to develop user services for download, review and use of the real estate data through the web. These services should be provided to all users who need access to cadastral data (natural and legal persons as well as state institutions) through e-government. It is also necessary to provide search, view and download of cadastral spatial data by specifying geospatial services. Considering that real estate contains geometric data for parcels and buildings it is necessary to establish set of geospatial services that would provide information and maps for the analysis of spatial data, and for forming a raster data. Besides the theme Cadastral parcels, INSPIRE directive specifies several themes that involve data on buildings and land use, for which data can be provided from real estate cadastre. In this paper, model of geospatial services in Serbia is defined. A case study of using these services to estimate which household is at risk of flooding using the Web Processing Service (WPS) spatial analysis is described.

Development of a landscape integrity model framework to support regional conservation planning.

PubMed

Walston, Leroy J; Hartmann, Heidi M

2018-01-01

Land managers increasingly rely upon landscape assessments to understand the status of natural resources and identify conservation priorities. Many of these landscape planning efforts rely on geospatial models that characterize the ecological integrity of the landscape. These general models utilize measures of habitat disturbance and human activity to map indices of ecological integrity. We built upon these modeling frameworks by developing a Landscape Integrity Index (LII) model using geospatial datasets of the human footprint, as well as incorporation of other indicators of ecological integrity such as biodiversity and vegetation departure. Our LII model serves as a general indicator of ecological integrity in a regional context of human activity, biodiversity, and change in habitat composition. We also discuss the application of the LII framework in two related coarse-filter landscape conservation approaches to expand the size and connectedness of protected areas as regional mitigation for anticipated land-use changes.

Development of a landscape integrity model framework to support regional conservation planning

PubMed Central

Hartmann, Heidi M.

2018-01-01

Land managers increasingly rely upon landscape assessments to understand the status of natural resources and identify conservation priorities. Many of these landscape planning efforts rely on geospatial models that characterize the ecological integrity of the landscape. These general models utilize measures of habitat disturbance and human activity to map indices of ecological integrity. We built upon these modeling frameworks by developing a Landscape Integrity Index (LII) model using geospatial datasets of the human footprint, as well as incorporation of other indicators of ecological integrity such as biodiversity and vegetation departure. Our LII model serves as a general indicator of ecological integrity in a regional context of human activity, biodiversity, and change in habitat composition. We also discuss the application of the LII framework in two related coarse-filter landscape conservation approaches to expand the size and connectedness of protected areas as regional mitigation for anticipated land-use changes. PMID:29614093

Student Focused Geospatial Curriculum Initiatives: Internships and Certificate Programs at NCCU

NASA Astrophysics Data System (ADS)

Vlahovic, G.; Malhotra, R.

2009-12-01

This paper reports recent efforts by the Department of Environmental, Earth and Geospatial Sciences faculty at North Carolina Central University (NCCU) to develop a leading geospatial sciences program that will be considered a model for other Historically Black College/University (HBCU) peers nationally. NCCU was established in 1909 and is the nation’s first state supported public liberal arts college funded for African Americans. In the most recent annual ranking of America’s best black colleges by the US News and World Report (Best Colleges 2010), NCCU was ranked 10th in the nation. As one of only two HBCUs in the southeast offering an undergraduate degree in Geography (McKee, J.O. and C. V. Dixon. Geography in Historically Black Colleges/ Universities in the Southeast, in The Role of the South in Making of American Geography: Centennial of the AAG, 2004), NCCU is uniquely positioned to positively affect talent and diversity of the geospatial discipline in the future. Therefore, successful creation of research and internship pathways for NCCU students has national implications because it will increase the number of minority students joining the workforce and applying to PhD programs. Several related efforts will be described, including research and internship projects with Fugro EarthData Inc., Center for Remote Sensing and Mapping Science at the University of Georgia, Center for Earthquake Research and Information at the University of Memphis and the City of Durham. The authors will also outline requirements and recent successes of ASPRS Provisional Certification Program, developed and pioneered as collaborative effort between ASPRS and NCCU. This certificate program allows graduating students majoring in geospatial technologies and allied fields to become provisionally certified by passing peer-review and taking the certification exam. At NCCU, projects and certification are conducted under the aegis of the Geospatial Research, Innovative Teaching and Service (GRITS) Center housed in the Department of Environmental, Earth and Geospatial Sciences. The GRITS center was established in 2006 with funding from the National Science Foundation to promote the learning and application of geospatial technologies. Since then GRITS has been a hub for Geographical Information Science (GIS) curriculum development, faculty and professional GIS workshops, grant writing and outreach efforts. The Center also serves as a contact point for partnerships with other universities, national organizations and businesses in the geospatial arena - and as a result, opens doors to the professional world for our graduate and undergraduate students.

EPA GEOSPATIAL QUALITY COUNCIL

EPA Science Inventory

The EPA Geospatial Quality Council (previously known as the EPA GIS-QA Team - EPA/600/R-00/009 was created to fill the gap between the EPA Quality Assurance (QA) and Geospatial communities. All EPA Offices and Regions were invited to participate. Currently, the EPA Geospatial Q...

Geospatial Thinking of Information Professionals

ERIC Educational Resources Information Center

Bishop, Bradley Wade; Johnston, Melissa P.

2013-01-01

Geospatial thinking skills inform a host of library decisions including planning and managing facilities, analyzing service area populations, facility site location, library outlet and service point closures, as well as assisting users with their own geospatial needs. Geospatial thinking includes spatial cognition, spatial reasoning, and knowledge…

Data and Tools | NREL

Science.gov Websites

Data and Tools Data and Tools NREL develops data sets, maps, models, and tools for the analysis of , models, and tools in the alphabetical listing. Popular Resources PVWatts Calculator Geospatial Data

Implementing Extreme Value Analysis in a Geospatial Workflow for Storm Surge Hazard Assessment

NASA Astrophysics Data System (ADS)

Catelli, J.; Nong, S.

2014-12-01

Gridded data of 100-yr (1%) and 500-yr (0.2%) storm surge flood elevations for the United States, Gulf of Mexico, and East Coast are critical to understanding this natural hazard. Storm surge heights were calculated across the study area utilizing SLOSH (Sea, Lake, and Overland Surges from Hurricanes) model data for thousands of synthetic US landfalling hurricanes. Based on the results derived from SLOSH, a series of interpolations were performed using spatial analysis in a geographic information system (GIS) at both the SLOSH basin and the synthetic event levels. The result was a single grid of maximum flood elevations for each synthetic event. This project addresses the need to utilize extreme value theory in a geospatial environment to analyze coincident cells across multiple synthetic events. The results are 100-yr (1%) and 500-yr (0.2%) values for each grid cell in the study area. This talk details a geospatial approach to move raster data to SciPy's NumPy Array structure using the Python programming language. The data are then connected through a Python library to an outside statistical package like R to fit cell values to extreme value theory distributions and return values for specified recurrence intervals. While this is not a new process, the value behind this work is the ability to keep this process in a single geospatial environment and be able to easily replicate this process for other natural hazard applications and extreme event modeling.

EPA Geospatial Quality Council Strategic and Implementation Plan 2010 to 2015

EPA Science Inventory

The EPA Geospatial Quality Council (GQC) was created to promote and provide Quality Assurance guidance for the development, use, and products of geospatial science. The GQC was created when the gap between the EPA Quality Assurance (QA) and Geospatial communities was recognized. ...

US EPA GEOSPATIAL QUALITY COUNCIL: ENSURING QUALITY GEOSPATIAL SOLUTIONS

EPA Science Inventory

This presentation will discuss the history, strategy, products, and future plans of the EPA Geospatial Quality Council (GQC). A topical review of GQC products will be presented including:

o Guidance for Geospatial Data Quality Assurance Project Plans.

o GPS - Tec...

A big data geospatial analytics platform - Physical Analytics Integrated Repository and Services (PAIRS)

NASA Astrophysics Data System (ADS)

Hamann, H.; Jimenez Marianno, F.; Klein, L.; Albrecht, C.; Freitag, M.; Hinds, N.; Lu, S.

2015-12-01

A big data geospatial analytics platform:Physical Analytics Information Repository and Services (PAIRS)Fernando Marianno, Levente Klein, Siyuan Lu, Conrad Albrecht, Marcus Freitag, Nigel Hinds, Hendrik HamannIBM TJ Watson Research Center, Yorktown Heights, NY 10598A major challenge in leveraging big geospatial data sets is the ability to quickly integrate multiple data sources into physical and statistical models and be run these models in real time. A geospatial data platform called Physical Analytics Information and Services (PAIRS) is developed on top of open source hardware and software stack to manage Terabyte of data. A new data interpolation and re gridding is implemented where any geospatial data layers can be associated with a set of global grid where the grid resolutions is doubling for consecutive layers. Each pixel on the PAIRS grid have an index that is a combination of locations and time stamp. The indexing allow quick access to data sets that are part of a global data layers and allowing to retrieve only the data of interest. PAIRS takes advantages of parallel processing framework (Hadoop) in a cloud environment to digest, curate, and analyze the data sets while being very robust and stable. The data is stored on a distributed no-SQL database (Hbase) across multiple server, data upload and retrieval is parallelized where the original analytics task is broken up is smaller areas/volume, analyzed independently, and then reassembled for the original geographical area. The differentiating aspect of PAIRS is the ability to accelerate model development across large geographical regions and spatial resolution ranging from 0.1 m up to hundreds of kilometer. System performance is benchmarked on real time automated data ingestion and retrieval of Modis and Landsat data layers. The data layers are curated for sensor error, verified for correctness, and analyzed statistically to detect local anomalies. Multi-layer query enable PAIRS to filter different data layers based on specific conditions (e.g analyze flooding risk of a property based on topography, soil ability to hold water, and forecasted precipitation) or retrieve information about locations that share similar weather and vegetation patterns during extreme weather events like heat wave.

A Graphical-User Interface for the U. S. Geological Survey's SUTRA Code using Argus ONE (for simulation of variable-density saturated-unsaturated ground-water flow with solute or energy transport)

USGS Publications Warehouse

Voss, Clifford I.; Boldt, David; Shapiro, Allen M.

1997-01-01

This report describes a Graphical-User Interface (GUI) for SUTRA, the U.S. Geological Survey (USGS) model for saturated-unsaturated variable-fluid-density ground-water flow with solute or energy transport,which combines a USGS-developed code that interfaces SUTRA with Argus ONE, a commercial software product developed by Argus Interware. This product, known as Argus Open Numerical Environments (Argus ONETM), is a programmable system with geographic-information-system-like (GIS-like) functionality that includes automated gridding and meshing capabilities for linking geospatial information with finite-difference and finite-element numerical model discretizations. The GUI for SUTRA is based on a public-domain Plug-In Extension (PIE) to Argus ONE that automates the use of ArgusONE to: automatically create the appropriate geospatial information coverages (information layers) for SUTRA, provide menus and dialogs for inputting geospatial information and simulation control parameters for SUTRA, and allow visualization of SUTRA simulation results. Following simulation control data and geospatial data input bythe user through the GUI, ArgusONE creates text files in a format required for normal input to SUTRA,and SUTRA can be executed within the Argus ONE environment. Then, hydraulic head, pressure, solute concentration, temperature, saturation and velocity results from the SUTRA simulation may be visualized. Although the GUI for SUTRA discussed in this report provides all of the graphical pre- and post-processor functions required for running SUTRA, it is also possible for advanced users to apply programmable features within Argus ONE to modify the GUI to meet the unique demands of particular ground-water modeling projects.

Searching and exploitation of distributed geospatial data sources via the Naval Research Lab's Geospatial Information Database (GIDB) Portal System

NASA Astrophysics Data System (ADS)

McCreedy, Frank P.; Sample, John T.; Ladd, William P.; Thomas, Michael L.; Shaw, Kevin B.

2005-05-01

The Naval Research Laboratory"s Geospatial Information Database (GIDBTM) Portal System has been extended to now include an extensive geospatial search functionality. The GIDB Portal System interconnects over 600 distributed geospatial data sources via the Internet with a thick client, thin client and a PDA client. As the GIDB Portal System has rapidly grown over the last two years (adding hundreds of geospatial sources), the obvious requirement has arisen to more effectively mine the interconnected sources in near real-time. How the GIDB Search addresses this issue is the prime focus of this paper.

The National Geospatial Technical Operations Center

USGS Publications Warehouse

Craun, Kari J.; Constance, Eric W.; Donnelly, Jay; Newell, Mark R.

2009-01-01

The United States Geological Survey (USGS) National Geospatial Technical Operations Center (NGTOC) provides geospatial technical expertise in support of the National Geospatial Program in its development of The National Map, National Atlas of the United States, and implementation of key components of the National Spatial Data Infrastructure (NSDI).

Bridging the Gap between NASA Hydrological Data and the Geospatial Community

NASA Technical Reports Server (NTRS)

Rui, Hualan; Teng, Bill; Vollmer, Bruce; Mocko, David M.; Beaudoing, Hiroko K.; Nigro, Joseph; Gary, Mark; Maidment, David; Hooper, Richard

2011-01-01

There is a vast and ever increasing amount of data on the Earth interconnected energy and hydrological systems, available from NASA remote sensing and modeling systems, and yet, one challenge persists: increasing the usefulness of these data for, and thus their use by, the geospatial communities. The Hydrology Data and Information Services Center (HDISC), part of the Goddard Earth Sciences DISC, has continually worked to better understand the hydrological data needs of the geospatial end users, to thus better able to bridge the gap between NASA data and the geospatial communities. This paper will cover some of the hydrological data sets available from HDISC, and the various tools and services developed for data searching, data subletting ; format conversion. online visualization and analysis; interoperable access; etc.; to facilitate the integration of NASA hydrological data by end users. The NASA Goddard data analysis and visualization system, Giovanni, is described. Two case examples of user-customized data services are given, involving the EPA BASINS (Better Assessment Science Integrating point & Non-point Sources) project and the CUAHSI Hydrologic Information System, with the common requirement of on-the-fly retrieval of long duration time series for a geographical point

New directions in valuing geospatial information - how to value goespatial information for policy and business decisioins in the future

NASA Astrophysics Data System (ADS)

Smart, A. C.

2014-12-01

Governments are increasingly asking for more evidence of the benefits of investing in geospatial data and infrastructure before investing. They are looking for a clearer articulation of the economic, environmental and social benefits than has been possble in the past. Development of techniques has accelerated in the past five years as governments and industry become more involved in the capture and use of geospatial data. However evaluation practitioners have struggled to answer these emerging questions. The paper explores the types of questions that decision makers are asking and discusses the different approaches and methods that have been used recently to answer them. It explores the need for better buisness case models. The emerging approaches are then discussed and their attributes reviewed. These include methods of analysing tengible economic benefits, intangible benefits and societal benefits. The paper explores the use of value chain analysis and real options analysis to better articulate the impacts on international competitiveness and how to value the potential benefits of innovations enabled by the geospatial data that is produced. The paper concludes by illustrating the potential for these techniques in current and future decision making.

TopoLens: Building a cyberGIS community data service for enhancing the usability of high-resolution National Topographic datasets

USGS Publications Warehouse

Hu, Hao; Hong, Xingchen; Terstriep, Jeff; Liu, Yan; Finn, Michael P.; Rush, Johnathan; Wendel, Jeffrey; Wang, Shaowen

2016-01-01

Geospatial data, often embedded with geographic references, are important to many application and science domains, and represent a major type of big data. The increased volume and diversity of geospatial data have caused serious usability issues for researchers in various scientific domains, which call for innovative cyberGIS solutions. To address these issues, this paper describes a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. Through the collaboration between the CyberGIS Center at the University of Illinois at Urbana-Champaign (UIUC) and the U.S. Geological Survey (USGS), a community data service for accessing, customizing, and sharing digital elevation model (DEM) and its derived datasets from the 10-meter national elevation dataset, namely TopoLens, is created to demonstrate the workflow integration of geospatial big data sources, computation, analysis needed for customizing the original dataset for end user needs, and a friendly online user environment. TopoLens provides online access to precomputed and on-demand computed high-resolution elevation data by exploiting the ROGER supercomputer. The usability of this prototype service has been acknowledged in community evaluation.

Impacts of Geospatial Information for Decision Making

NASA Astrophysics Data System (ADS)

Pearlman, F.; Coote, A.; Friedl, L.; Stewart, M.

2012-12-01

Geospatial information contributes to decisions by both societal and individual decision-makers. More effective use of this information is essential as issues are increasingly complex and consequences can be critical for future economic and social development. To address this, a workshop brought together analysts, communicators, officials, and researchers from academia, government, non-governmental organizations, and the private sector. A range of policy issues, management needs, and resource requirements were discussed and a wide array of analyses, geospatial data, methods of analysis, and metrics were presented for assessing and communicating the value of geospatial information. It is clear that there are many opportunities for integrating science and engineering disciplines with the social sciences for addressing societal issues that would benefit from using geospatial information and earth observations. However, these collaborations must have outcomes that can be easily communicated to decision makers. This generally requires either succinct quantitative statements of value based on rigorous models and/or user testimonials of actual applications that save real money. An outcome of the workshop is to pursue the development of a community of practice or society that encompasses a wide range of scientific, social, management, and communication disciplines and fosters collaboration across specialties, helping to build trust across social and science aspects. A resource base is also necessary. This presentation will address approaches for creating a shared knowledge database, containing a glossary of terms, reference materials and examples of case studies and the potential applications for benefit analyses.

Geospatial analysis of spaceborne remote sensing data for assessing disaster impacts and modeling surface runoff in the built-environment

NASA Astrophysics Data System (ADS)

Wodajo, Bikila Teklu

Every year, coastal disasters such as hurricanes and floods claim hundreds of lives and severely damage homes, businesses, and lifeline infrastructure. This research was motivated by the 2005 Hurricane Katrina disaster, which devastated the Mississippi and Louisiana Gulf Coast. The primary objective was to develop a geospatial decision-support system for extracting built-up surfaces and estimating disaster impacts using spaceborne remote sensing satellite imagery. Pre-Katrina 1-m Ikonos imagery of a 5km x 10km area of Gulfport, Mississippi, was used as source data to develop the built-up area and natural surfaces or BANS classification methodology. Autocorrelation of 0.6 or higher values related to spectral reflectance values of groundtruth pixels were used to select spectral bands and establish the BANS decision criteria of unique ranges of reflectance values. Surface classification results using GeoMedia Pro geospatial analysis for Gulfport sample areas, based on BANS criteria and manually drawn polygons, were within +/-7% of the groundtruth. The difference between the BANS results and the groundtruth was statistically not significant. BANS is a significant improvement over other supervised classification methods, which showed only 50% correctly classified pixels. The storm debris and erosion estimation or SDE methodology was developed from analysis of pre- and post-Katrina surface classification results of Gulfport samples. The SDE severity level criteria considered hurricane and flood damages and vulnerability of inhabited built-environment. A linear regression model, with +0.93 Pearson R-value, was developed for predicting SDE as a function of pre-disaster percent built-up area. SDE predictions for Gulfport sample areas, used for validation, were within +/-4% of calculated values. The damage cost model considered maintenance, rehabilitation and reconstruction costs related to infrastructure damage and community impacts of Hurricane Katrina. The developed models were implemented for a study area along I-10 considering the predominantly flood-induced damages in New Orleans. The BANS methodology was calibrated for 0.6-m QuickBird2 multispectral imagery of Karachi Port area in Pakistan. The results were accurate within +/-6% of the groundtruth. Due to its computational simplicity, the unit hydrograph method is recommended for geospatial visualization of surface runoff in the built-environment using BANS surface classification maps and elevations data. Key words. geospatial analysis, satellite imagery, built-environment, hurricane, disaster impacts, runoff.

Applying Geospatial Technologies for International Development and Public Health: The USAID/NASA SERVIR Program

NASA Technical Reports Server (NTRS)

Hemmings, Sarah; Limaye, Ashutosh; Irwin, Dan

2011-01-01

Background: SERVIR -- the Regional Visualization and Monitoring System -- helps people use Earth observations and predictive models based on data from orbiting satellites to make timely decisions that benefit society. SERVIR operates through a network of regional hubs in Mesoamerica, East Africa, and the Hindu Kush-Himalayas. USAID and NASA support SERVIR, with the long-term goal of transferring SERVIR capabilities to the host countries. Objective/Purpose: The purpose of this presentation is to describe how the SERVIR system helps the SERVIR regions cope with eight areas of societal benefit identified by the Group on Earth Observations (GEO): health, disasters, ecosystems, biodiversity, weather, water, climate, and agriculture. This presentation will describe environmental health applications of data in the SERVIR system, as well as ongoing and future efforts to incorporate additional health applications into the SERVIR system. Methods: This presentation will discuss how the SERVIR Program makes environmental data available for use in environmental health applications. SERVIR accomplishes its mission by providing member nations with access to geospatial data and predictive models, information visualization, training and capacity building, and partnership development. SERVIR conducts needs assessments in partner regions, develops custom applications of Earth observation data, and makes NASA and partner data available through an online geospatial data portal at SERVIRglobal.net. Results: Decision makers use SERVIR to improve their ability to monitor air quality, extreme weather, biodiversity, and changes in land cover. In past several years, the system has been used over 50 times to respond to environmental threats such as wildfires, floods, landslides, and harmful algal blooms. Given that the SERVIR regions are experiencing increased stress under larger climate variability than historic observations, SERVIR provides information to support the development of adaptation strategies for nations affected by climate change. Conclusions: SERVIR is a platform for collaboration and cross-agency coordination, international partnerships, and delivery of web-based geospatial information services and applications. SERVIR makes a variety of geospatial data available for use in studies of environmental health outcomes.

Application of 3D Spatio-Temporal Data Modeling, Management, and Analysis in DB4GEO

NASA Astrophysics Data System (ADS)

Kuper, P. V.; Breunig, M.; Al-Doori, M.; Thomsen, A.

2016-10-01

Many of todaýs world wide challenges such as climate change, water supply and transport systems in cities or movements of crowds need spatio-temporal data to be examined in detail. Thus the number of examinations in 3D space dealing with geospatial objects moving in space and time or even changing their shapes in time will rapidly increase in the future. Prominent spatio-temporal applications are subsurface reservoir modeling, water supply after seawater desalination and the development of transport systems in mega cities. All of these applications generate large spatio-temporal data sets. However, the modeling, management and analysis of 3D geo-objects with changing shape and attributes in time still is a challenge for geospatial database architectures. In this article we describe the application of concepts for the modeling, management and analysis of 2.5D and 3D spatial plus 1D temporal objects implemented in DB4GeO, our service-oriented geospatial database architecture. An example application with spatio-temporal data of a landfill, near the city of Osnabrück in Germany demonstrates the usage of the concepts. Finally, an outlook on our future research focusing on new applications with big data analysis in three spatial plus one temporal dimension in the United Arab Emirates, especially the Dubai area, is given.

Solar and Wind Resource Assessments for Afghanistan and Pakistan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Renne, D. S.; Kelly, M.; Elliott, D.

2007-01-01

The U.S. National Renewable Energy Laboratory (NREL) has recently completed the production of high-resolution wind and solar energy resource maps and related data products for Afghanistan and Pakistan. The resource data have been incorporated into a geospatial toolkit (GsT), which allows the user to manipulate the resource information along with country-specific geospatial information such as highway networks, power facilities, transmission corridors, protected land areas, etc. The toolkit allows users to then transfer resource data for specific locations into NREL's micropower optimization model known as HOMER.

Geospatial Perspective: Toward a Visual Political Literacy Project in Education, Health, and Human Services

ERIC Educational Resources Information Center

Hogrebe, Mark C.; Tate, William F., IV

2012-01-01

In this chapter, "geospatial" refers to geographic space that includes location, distance, and the relative position of things on the earth's surface. Geospatial perspective calls for the addition of a geographic lens that focuses on place and space as important contextual variables. A geospatial view increases one's understanding of…

Geospatial Data Curation at the University of Idaho

ERIC Educational Resources Information Center

Kenyon, Jeremy; Godfrey, Bruce; Eckwright, Gail Z.

2012-01-01

The management and curation of digital geospatial data has become a central concern for many academic libraries. Geospatial data is a complex type of data critical to many different disciplines, and its use has become more expansive in the past decade. The University of Idaho Library maintains a geospatial data repository called the Interactive…

Geospatial Engineering

DTIC Science & Technology

2017-02-22

manages operations through guidance, policies, programs, and organizations. The NSG is designed to be a mutually supportive enterprise that...deliberate technical design and deliberate human actions. Geospatial engineer teams (GETs) within the geospatial intelligence cells are the day-to-day...standards working group and are designated by the AGC Geospatial Acquisition Support Directorate as required for interoperability. Applicable standards

Geospatial Modelling for Micro Zonation of Groundwater Regime in Western Assam, India

NASA Astrophysics Data System (ADS)

Singh, R. P.

2016-12-01

Water, most precious natural resource on earth, is vital to sustain the natural system and human civilisation on the earth. The Assam state located in north-eastern part of India has a relatively good source of ground water due to their geographic and physiographic location but there is problem deterioration of groundwater quality causing major health problem in the area. In this study, I tried a integrated study of remote sensing and GIS and chemical analysis of groundwater samples to throw a light over groundwater regime and provides information for decision makers to make sustainable water resource management. The geospatial modelling performed by integrating hydrogeomorphic features. Geomorphology, lineament, Drainage, Landuse/landcover layer were generated through visual interpretation on satellite image (LISS III) based on tone, texture, shape, size, and arrangement of the features. Slope layer was prepared by using SRTM DEM data set .The LULC of the area were categories in to 6 classes of Agricultural field, Forest area ,River, Settlement , Tree-clad area and Wetlands. The geospatial modelling performed through weightage and rank method in GIS, depending on the influence of the features on ground water regime. To Assess the ground water quality of the area 45 groundwater samples have been collected from the field and chemical analysis performed through the standard method in the laboratory. The overall assessment of the ground water quality of the area analyse through Water Quality Index and found that about 70% samples are not potable for drinking purposes due to higher concentration Arsenic, Fluoride and Iron. It appears that, source of all these pollutants geologically and geomorphologically derived. Interpolated layer of Water Quality Index and geospatial modelled Groundwater potential layer provides a holistic view of groundwater scenario and provide direction for better planning and groundwater resource management. Study will be discussed in details during the conference.

Urban growth and landscape connectivity threats assessment at Saguaro National Park, Arizona, USA

USGS Publications Warehouse

Perkl, Ryan; Norman, Laura M.; Mitchell, David; Feller, Mark R.; Smith, Garrett; Wilson, Natalie R.

2018-01-01

Urban and exurban expansion results in habitat and biodiversity loss globally. We hypothesize that a coupled-model approach could connect urban planning for future cities with landscape ecology to consider wildland habitat connectivity. Our work combines urban growth simulations with models of wildlife corridors to examine how species will be impacted by development to test this hypothesis. We leverage a land use change model (SLEUTH) with structural and functional landscape-connectivity modeling techniques to ascertain the spatial extent and locations of connectivity related threats to a national park in southern Arizona, USA, and describe how protected areas might be impacted by urban expansion. Results of projected growth significantly altered structural connectivity (80%) when compared to current (baseline) corridor conditions. Moreover, projected growth impacted functional connectivity differently amongst species, indicating resilience of some species and near-complete displacement of others. We propose that implementing a geospatial-design-based model will allow for a better understanding of the impacts management decisions have on wildlife populations. The application provides the potential to understand both human and environmental impacts of land-system dynamics, critical for long-term sustainability.

Modelling surface-water depression storage in a Prairie Pothole Region

USGS Publications Warehouse

Hay, Lauren E.; Norton, Parker A.; Viger, Roland; Markstrom, Steven; Regan, R. Steven; Vanderhoof, Melanie

2018-01-01

In this study, the Precipitation-Runoff Modelling System (PRMS) was used to simulate changes in surface-water depression storage in the 1,126-km2 Upper Pipestem Creek basin located within the Prairie Pothole Region of North Dakota, USA. The Prairie Pothole Region is characterized by millions of small water bodies (or surface-water depressions) that provide numerous ecosystem services and are considered an important contribution to the hydrologic cycle. The Upper Pipestem PRMS model was extracted from the U.S. Geological Survey's (USGS) National Hydrologic Model (NHM), developed to support consistent hydrologic modelling across the conterminous United States. The Geospatial Fabric database, created for the USGS NHM, contains hydrologic model parameter values derived from datasets that characterize the physical features of the entire conterminous United States for 109,951 hydrologic response units. Each hydrologic response unit in the Geospatial Fabric was parameterized using aggregated surface-water depression area derived from the National Hydrography Dataset Plus, an integrated suite of application-ready geospatial datasets. This paper presents a calibration strategy for the Upper Pipestem PRMS model that uses normalized lake elevation measurements to calibrate the parameters influencing simulated fractional surface-water depression storage. Results indicate that inclusion of measurements that give an indication of the change in surface-water depression storage in the calibration procedure resulted in accurate changes in surface-water depression storage in the water balance. Regionalized parameterization of the USGS NHM will require a proxy for change in surface-storage to accurately parameterize surface-water depression storage within the USGS NHM.

Raster Data Partitioning for Supporting Distributed GIS Processing

NASA Astrophysics Data System (ADS)

Nguyen Thai, B.; Olasz, A.

2015-08-01

In the geospatial sector big data concept also has already impact. Several studies facing originally computer science techniques applied in GIS processing of huge amount of geospatial data. In other research studies geospatial data is considered as it were always been big data (Lee and Kang, 2015). Nevertheless, we can prove data acquisition methods have been improved substantially not only the amount, but the resolution of raw data in spectral, spatial and temporal aspects as well. A significant portion of big data is geospatial data, and the size of such data is growing rapidly at least by 20% every year (Dasgupta, 2013). The produced increasing volume of raw data, in different format, representation and purpose the wealth of information derived from this data sets represents only valuable results. However, the computing capability and processing speed rather tackle with limitations, even if semi-automatic or automatic procedures are aimed on complex geospatial data (Kristóf et al., 2014). In late times, distributed computing has reached many interdisciplinary areas of computer science inclusive of remote sensing and geographic information processing approaches. Cloud computing even more requires appropriate processing algorithms to be distributed and handle geospatial big data. Map-Reduce programming model and distributed file systems have proven their capabilities to process non GIS big data. But sometimes it's inconvenient or inefficient to rewrite existing algorithms to Map-Reduce programming model, also GIS data can not be partitioned as text-based data by line or by bytes. Hence, we would like to find an alternative solution for data partitioning, data distribution and execution of existing algorithms without rewriting or with only minor modifications. This paper focuses on technical overview of currently available distributed computing environments, as well as GIS data (raster data) partitioning, distribution and distributed processing of GIS algorithms. A proof of concept implementation have been made for raster data partitioning, distribution and processing. The first results on performance have been compared against commercial software ERDAS IMAGINE 2011 and 2014. Partitioning methods heavily depend on application areas, therefore we may consider data partitioning as a preprocessing step before applying processing services on data. As a proof of concept we have implemented a simple tile-based partitioning method splitting an image into smaller grids (NxM tiles) and comparing the processing time to existing methods by NDVI calculation. The concept is demonstrated using own development open source processing framework.

An agent-based approach for modeling dynamics of contagious disease spread

PubMed Central

Perez, Liliana; Dragicevic, Suzana

2009-01-01

Background The propagation of communicable diseases through a population is an inherent spatial and temporal process of great importance for modern society. For this reason a spatially explicit epidemiologic model of infectious disease is proposed for a greater understanding of the disease's spatial diffusion through a network of human contacts. Objective The objective of this study is to develop an agent-based modelling approach the integrates geographic information systems (GIS) to simulate the spread of a communicable disease in an urban environment, as a result of individuals' interactions in a geospatial context. Methods The methodology for simulating spatiotemporal dynamics of communicable disease propagation is presented and the model is implemented using measles outbreak in an urban environment as a case study. Individuals in a closed population are explicitly represented by agents associated to places where they interact with other agents. They are endowed with mobility, through a transportation network allowing them to move between places within the urban environment, in order to represent the spatial heterogeneity and the complexity involved in infectious diseases diffusion. The model is implemented on georeferenced land use dataset from Metro Vancouver and makes use of census data sets from Statistics Canada for the municipality of Burnaby, BC, Canada study site. Results The results provide insights into the application of the model to calculate ratios of susceptible/infected in specific time frames and urban environments, due to its ability to depict the disease progression based on individuals' interactions. It is demonstrated that the dynamic spatial interactions within the population lead to high numbers of exposed individuals who perform stationary activities in areas after they have finished commuting. As a result, the sick individuals are concentrated in geographical locations like schools and universities. Conclusion The GIS-agent based model designed for this study can be easily customized to study the disease spread dynamics of any other communicable disease by simply adjusting the modeled disease timeline and/or the infection model and modifying the transmission process. This type of simulations can help to improve comprehension of disease spread dynamics and to take better steps towards the prevention and control of an epidemic outbreak. PMID:19656403

Ontology for Transforming Geo-Spatial Data for Discovery and Integration of Scientific Data

NASA Astrophysics Data System (ADS)

Nguyen, L.; Chee, T.; Minnis, P.

2013-12-01

Discovery and access to geo-spatial scientific data across heterogeneous repositories and multi-discipline datasets can present challenges for scientist. We propose to build a workflow for transforming geo-spatial datasets into semantic environment by using relationships to describe the resource using OWL Web Ontology, RDF, and a proposed geo-spatial vocabulary. We will present methods for transforming traditional scientific dataset, use of a semantic repository, and querying using SPARQL to integrate and access datasets. This unique repository will enable discovery of scientific data by geospatial bound or other criteria.

Geospatial Analysis and Seasonal Distribution of West Nile Virus Vectors (Diptera: Culicidae) in Southern Ontario, Canada

PubMed Central

Turner, Kevin W.; Hunter, Fiona F.

2018-01-01

The purpose of this study was to establish geospatial and seasonal distributions of West Nile virus vectors in southern Ontario, Canada using historical surveillance data from 2002 to 2014. We set out to produce mosquito abundance prediction surfaces for each of Ontario’s thirteen West Nile virus vectors. We also set out to determine whether elevation and proximity to conservation areas and provincial parks, wetlands, and population centres could be used to improve our model. Our results indicated that the data sets for Anopheles quadrimaculatus, Anopheles punctipennis, Anopheles walkeri, Culex salinarius, Culex tarsalis, Ochlerotatus stimulans, and Ochlerotatus triseriatus were not suitable for geospatial modelling because they are randomly distributed throughout Ontario. Spatial prediction surfaces were created for Aedes japonicus and proximity to wetlands, Aedes vexans and proximity to population centres, Culex pipiens/restuans and proximity to population centres, Ochlerotatus canadensis and elevation, and Ochlerotatus trivittatus and proximity to population centres using kriging. Seasonal distributions are presented for all thirteen species. We have identified both when and where vector species are most abundant in southern Ontario. These data have the potential to contribute to a more efficient and focused larvicide program and West Nile virus awareness campaigns. PMID:29597256

Mobile Geospatial Information Systems for Land Force Operations: Analysis of Operational Needs and Research Opportunities

DTIC Science & Technology

2010-03-01

Dynamics Itronix Duo-Touch II SmartPhones 1. Apple iPhone 2. Blackberry Smartphone 3. Cassiopeia E-105 4. Hewlett Packard (HP) iPAQ 910 Smartphone...Mobile GIS Page 2-39 Blackberry Smartphone Housekeeping Functions (internal device functionality, status, and security) 1 Maintain awareness of...sensor status and alarms SW (comments) 2 Plan storage SW 3 Development Environment Blackberry OS Can additional programmable

A geospatial search engine for discovering multi-format geospatial data across the web

Treesearch

Christopher Bone; Alan Ager; Ken Bunzel; Lauren Tierney

2014-01-01

The volume of publically available geospatial data on the web is rapidly increasing due to advances in server-based technologies and the ease at which data can now be created. However, challenges remain with connecting individuals searching for geospatial data with servers and websites where such data exist. The objective of this paper is to present a publically...

The Use of Geospatial Technologies Instruction within a Student/Teacher/Scientist Partnership: Increasing Students' Geospatial Skills and Atmospheric Concept Knowledge

ERIC Educational Resources Information Center

Hedley, Mikell Lynne; Templin, Mark A.; Czaljkowski, Kevin; Czerniak, Charlene

2013-01-01

Many 21st century careers rely on geospatial skills; yet, curricula and professional development lag behind in incorporating these skills. As a result, many teachers have limited experience or preparation for teaching geospatial skills. One strategy for overcoming such problems is the creation of a student/teacher/scientist (STS) partnership…

Bridging the Gap Between Surveyors and the Geo-Spatial Society

NASA Astrophysics Data System (ADS)

Müller, H.

2016-06-01

For many years FIG, the International Association of Surveyors, has been trying to bridge the gap between surveyors and the geospatial society as a whole, with the geospatial industries in particular. Traditionally the surveying profession contributed to the good of society by creating and maintaining highly precise and accurate geospatial data bases, based on an in-depth knowledge of spatial reference frameworks. Furthermore in many countries surveyors may be entitled to make decisions about land divisions and boundaries. By managing information spatially surveyors today develop into the role of geo-data managers, the longer the more. Job assignments in this context include data entry management, data and process quality management, design of formal and informal systems, information management, consultancy, land management, all that in close cooperation with many different stakeholders. Future tasks will include the integration of geospatial information into e-government and e-commerce systems. The list of professional tasks underpins the capabilities of surveyors to contribute to a high quality geospatial data and information management. In that way modern surveyors support the needs of a geo-spatial society. The paper discusses several approaches to define the role of the surveyor within the modern geospatial society.

Free and Open Source Software for Geospatial in the field of planetary science

NASA Astrophysics Data System (ADS)

Frigeri, A.

2012-12-01

Information technology applied to geospatial analyses has spread quickly in the last ten years. The availability of OpenData and data from collaborative mapping projects increased the interest on tools, procedures and methods to handle spatially-related information. Free Open Source Software projects devoted to geospatial data handling are gaining a good success as the use of interoperable formats and protocols allow the user to choose what pipeline of tools and libraries is needed to solve a particular task, adapting the software scene to his specific problem. In particular, the Free Open Source model of development mimics the scientific method very well, and researchers should be naturally encouraged to take part to the development process of these software projects, as this represent a very agile way to interact among several institutions. When it comes to planetary sciences, geospatial Free Open Source Software is gaining a key role in projects that commonly involve different subjects in an international scenario. Very popular software suites for processing scientific mission data (for example, ISIS) and for navigation/planning (SPICE) are being distributed along with the source code and the interaction between user and developer is often very strict, creating a continuum between these two figures. A very widely spread library for handling geospatial data (GDAL) has started to support planetary data from the Planetary Data System, and recent contributions enabled the support to other popular data formats used in planetary science, as the Vicar one. The use of Geographic Information System in planetary science is now diffused, and Free Open Source GIS, open GIS formats and network protocols allow to extend existing tools and methods developed to solve Earth based problems, also to the case of the study of solar system bodies. A day in the working life of a researcher using Free Open Source Software for geospatial will be presented, as well as benefits and solutions to possible detriments coming from the effort required by using, supporting and contributing.

KML Tours: A New Platform for Exploring and Sharing Geospatial Data

NASA Astrophysics Data System (ADS)

Barcay, D. P.; Weiss-Malik, M.

2009-12-01

Google Earth and other virtual globes have allowed millions of people to explore the world from their own home. This technology has also raised the bar for professional visualizations: enabling interactive 3D visualizations to be created from massive data-sets, and shared using the KML language. For academics and professionals alike, an engaging presentation of your geospatial data is generally expected and can be the most effective form of advertisement. To that end, we released 'Touring' in Google Earth 5.0: a new medium for cinematic expression, visualized in Google Earth and written as extensions to the KML language. In a KML tour, the author has fine-grained control over the entire visual experience: precisely moving the virtual camera through the world while dynamically modifying the content, style, position, and visibility of the displayed data. An author can synchronize audio to this experience, bringing further immersion to a visualization. KML tours can help engage a broad user-base and conveying subtle concepts that aren't immediately apparent in traditional geospatial content. Unlike a pre-rendered video, a KML Tour maintains the rich interactivity of Google Earth, allowing users to continue exploring your content, and to mash-up other content with your visualization. This session will include conceptual explanations of the Touring feature in Google Earth, the structure of the touring KML extensions, as well as examples of compelling tours.

Automated geospatial Web Services composition based on geodata quality requirements

NASA Astrophysics Data System (ADS)

Cruz, Sérgio A. B.; Monteiro, Antonio M. V.; Santos, Rafael

2012-10-01

Service-Oriented Architecture and Web Services technologies improve the performance of activities involved in geospatial analysis with a distributed computing architecture. However, the design of the geospatial analysis process on this platform, by combining component Web Services, presents some open issues. The automated construction of these compositions represents an important research topic. Some approaches to solving this problem are based on AI planning methods coupled with semantic service descriptions. This work presents a new approach using AI planning methods to improve the robustness of the produced geospatial Web Services composition. For this purpose, we use semantic descriptions of geospatial data quality requirements in a rule-based form. These rules allow the semantic annotation of geospatial data and, coupled with the conditional planning method, this approach represents more precisely the situations of nonconformities with geodata quality that may occur during the execution of the Web Service composition. The service compositions produced by this method are more robust, thus improving process reliability when working with a composition of chained geospatial Web Services.

Sensitivity of resource selection and connectivity models to landscape definition

Treesearch

Katherine A. Zeller; Kevin McGarigal; Samuel A. Cushman; Paul Beier; T. Winston Vickers; Walter M. Boyce

2017-01-01

Context: The definition of the geospatial landscape is the underlying basis for species-habitat models, yet sensitivity of habitat use inference, predicted probability surfaces, and connectivity models to landscape definition has received little attention. Objectives: We evaluated the sensitivity of resource selection and connectivity models to four landscape...

Optimization of Land Use Suitability for Agriculture Using Integrated Geospatial Model and Genetic Algorithms

NASA Astrophysics Data System (ADS)

Mansor, S. B.; Pormanafi, S.; Mahmud, A. R. B.; Pirasteh, S.

2012-08-01

In this study, a geospatial model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the infrastructural preference. The model was developed based on multi-agent genetic algorithm. The model was customized to accommodate the constraint set for the study area, namely the resource saving and environmental-friendly. The model was then applied to solve the practical multi-objective spatial optimization allocation problems of land use in the core region of Menderjan Basin in Iran. The first task was to study the dominant crops and economic suitability evaluation of land. Second task was to determine the fitness function for the genetic algorithms. The third objective was to optimize the land use map using economical benefits. The results has indicated that the proposed model has much better performance for solving complex multi-objective spatial optimization allocation problems and it is a promising method for generating land use alternatives for further consideration in spatial decision-making.

EPA National Geospatial Data Policy

EPA Pesticide Factsheets

National Geospatial Data Policy (NGDP) establishes principles, responsibilities, and requirements for collecting and managing geospatial data used by Federal environmental programs and projects within the jurisdiction of the U.S. EPA

Towards the Geospatial Web: Media Platforms for Managing Geotagged Knowledge Repositories

NASA Astrophysics Data System (ADS)

Scharl, Arno

International media have recognized the visual appeal of geo-browsers such as NASA World Wind and Google Earth, for example, when Web and television coverage on Hurricane Katrina used interactive geospatial projections to illustrate its path and the scale of destruction in August 2005. Yet these early applications only hint at the true potential of geospatial technology to build and maintain virtual communities and to revolutionize the production, distribution and consumption of media products. This chapter investigates this potential by reviewing the literature and discussing the integration of geospatial and semantic reference systems, with an emphasis on extracting geospatial context from unstructured text. A content analysis of news coverage based on a suite of text mining tools (webLyzard) sheds light on the popularity and adoption of geospatial platforms.

The Inter-American Geospatial Data Network— developing a Western Hemisphere geospatial data clearinghouse

USGS Publications Warehouse

Anthony, Michelle L.; Klaver, Jacqueline M.; Quenzer, Robert

1998-01-01

The US Geological Survey and US Agency for International Development are enhancing the geographic information infrastructure of the Western Hemisphere by establishing the Inter-American Geospatial Data Network (IGDN). In its efforts to strengthen the Western Hemisphere's information infrastructure, the IGDN is consistent with the goals of the Plan of Action that emerged from the 1994 Summit of the Americas. The IGDN is an on-line cooperative, or clearinghouse, of geospatial data. Internet technology is used to facilitate the discovery and access of Western Hemisphere geospatial data. It was established by using the standards and guidelines of the Federal Geographic Data Committee to provide a consistent data discovery mechanism that will help minimize geospatial data duplication, promote data availability, and coordinate data collection and research activities.

Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes.

PubMed

Hahus, Ian; Migliaccio, Kati; Douglas-Mankin, Kyle; Klarenberg, Geraldine; Muñoz-Carpena, Rafael

2018-04-27

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward's linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

EPA Geospatial Applications

EPA Pesticide Factsheets

EPA has developed many applications that allow users to explore and interact with geospatial data. This page highlights some of the flagship geospatial web applications but these represent only a fraction of the total.

The African Geospatial Sciences Institute (agsi): a New Approach to Geospatial Training in North Africa

NASA Astrophysics Data System (ADS)

Oeldenberger, S.; Khaled, K. B.

2012-07-01

The African Geospatial Sciences Institute (AGSI) is currently being established in Tunisia as a non-profit, non-governmental organization (NGO). Its objective is to accelerate the geospatial capacity development in North-Africa, providing the facilities for geospatial project and management training to regional government employees, university graduates, private individuals and companies. With typical course durations between one and six months, including part-time programs and long-term mentoring, its focus is on practical training, providing actual project execution experience. The AGSI will complement formal university education and will work closely with geospatial certification organizations and the geospatial industry. In the context of closer cooperation between neighboring North Africa and the European Community, the AGSI will be embedded in a network of several participating European and African universities, e. g. the ITC, and international organizations, such as the ISPRS, the ICA and the OGC. Through a close cooperation with African organizations, such as the AARSE, the RCMRD and RECTAS, the network and exchange of ideas, experiences, technology and capabilities will be extended to Saharan and sub-Saharan Africa. A board of trustees will be steering the AGSI operations and will ensure that practical training concepts and contents are certifiable and can be applied within a credit system to graduate and post-graduate education at European and African universities. The geospatial training activities of the AGSI are centered on a facility with approximately 30 part- and full-time general staff and lecturers in Tunis during the first year. The AGSI will operate a small aircraft with a medium-format aerial camera and compact LIDAR instrument for local, community-scale data capture. Surveying training, the photogrammetric processing of aerial images, GIS data capture and remote sensing training will be the main components of the practical training courses offered, to build geospatial capacity and ensure that AGSI graduates will have the appropriate skill-sets required for employment in the geospatial industry. Geospatial management courses and high-level seminars will be targeted at decision makers in government and industry to build awareness for geospatial applications and benefits. Online education will be developed together with international partners and internet-based activities will involve the public to familiarize them with geospatial data and its many applications.

Using AGWA and the KINEROS2 Model-to-Model Green Infrastructure in Two Typical Residential Lots in Prescott, AZ

EPA Science Inventory

The Automated Geospatial Watershed Assessment (AGWA) Urban tool provides a step-by-step process to model subdivisions using the KINEROS2 model, with and without Green Infrastructure (GI) practices. AGWA utilizes the Kinematic Runoff and Erosion (KINEROS2) model, an event driven, ...

Geospatial Data Science Analysis | Geospatial Data Science | NREL

Science.gov Websites

different levels of technology maturity. Photo of a man taking field measurements. Geospatial analysis energy for different technologies across the nation? Featured Analysis Products Renewable Energy

Geospatial Information is the Cornerstone of Effective Hazards Response

USGS Publications Warehouse

Newell, Mark

2008-01-01

Every day there are hundreds of natural disasters world-wide. Some are dramatic, whereas others are barely noticeable. A natural disaster is commonly defined as a natural event with catastrophic consequences for living things in the vicinity. Those events include earthquakes, floods, hurricanes, landslides, tsunami, volcanoes, and wildfires. Man-made disasters are events that are caused by man either intentionally or by accident, and that directly or indirectly threaten public health and well-being. These occurrences span the spectrum from terrorist attacks to accidental oil spills. To assist in responding to natural and potential man-made disasters, the U.S. Geological Survey (USGS) has established the Geospatial Information Response Team (GIRT) (http://www.usgs.gov/emergency/). The primary purpose of the GIRT is to ensure rapid coordination and availability of geospatial information for effective response by emergency responders, and land and resource managers, and for scientific analysis. The GIRT is responsible for establishing monitoring procedures for geospatial data acquisition, processing, and archiving; discovery, access, and delivery of data; anticipating geospatial needs; and providing relevant geospatial products and services. The GIRT is focused on supporting programs, offices, other agencies, and the public in mission response to hazards. The GIRT will leverage the USGS Geospatial Liaison Network and partnerships with the Department of Homeland Security (DHS), National Geospatial-Intelligence Agency (NGA), and Northern Command (NORTHCOM) to coordinate the provisioning and deployment of USGS geospatial data, products, services, and equipment. The USGS geospatial liaisons will coordinate geospatial information sharing with State, local, and tribal governments, and ensure geospatial liaison back-up support procedures are in place. The GIRT will coordinate disposition of USGS staff in support of DHS response center activities as requested by DHS. The GIRT is a standing team that is available during all hazard events and is on high alert during the hurricane season from June through November each year. To track all of the requirements and data acquisitions processed through the team, the GIRT will use the new Emergency Request Track (ER Track) tool. Currently, the ER Track is only available to USGS personnel.

Elkhorn Slough: Detecting Eutrophication through Geospatial Modeling Applications

NASA Astrophysics Data System (ADS)

Caraballo Álvarez, I. O.; Childs, A.; Jurich, K.

2016-12-01

Elkhorn Slough in Monterey, California, has experienced substantial nutrient loading and eutrophication over the past 21 years as a result of fertilizer-rich runoff from nearby agricultural fields. This study seeks to identify and track spatial patterns of eutrophication hotspots and the correlation to land use changes, possible nutrient sources, and general climatic trends using remotely sensed and in situ data. Threats of rising sea level, subsiding marshes, and increased eutrophication hotspots demonstrate the necessity to analyze the effects of increasing nutrient loads, relative sea level changes, and sedimentation within Elkhorn Slough. The Soil & Water Assessment Tool (SWAT) model integrates specified inputs to assess nutrient and sediment loading and their sources. TerrSet's Land Change Modeler forecasts the future potential of land change transitions for various land cover classes around the slough as a result of nutrient loading, eutrophication, and increased sedimentation. TerrSet's Earth Trends Modeler provides a comprehensive analysis of image time series to rapidly assess long term eutrophication trends and detect spatial patterns of known hotspots. Results from this study will inform future coastal management practices and provide greater spatial and temporal insight into Elkhorn Slough eutrophication dynamics.

Generation of Multiple Metadata Formats from a Geospatial Data Repository

NASA Astrophysics Data System (ADS)

Hudspeth, W. B.; Benedict, K. K.; Scott, S.

2012-12-01

The Earth Data Analysis Center (EDAC) at the University of New Mexico is partnering with the CYBERShARE and Environmental Health Group from the Center for Environmental Resource Management (CERM), located at the University of Texas, El Paso (UTEP), the Biodiversity Institute at the University of Kansas (KU), and the New Mexico Geo- Epidemiology Research Network (GERN) to provide a technical infrastructure that enables investigation of a variety of climate-driven human/environmental systems. Two significant goals of this NASA-funded project are: a) to increase the use of NASA Earth observational data at EDAC by various modeling communities through enabling better discovery, access, and use of relevant information, and b) to expose these communities to the benefits of provenance for improving understanding and usability of heterogeneous data sources and derived model products. To realize these goals, EDAC has leveraged the core capabilities of its Geographic Storage, Transformation, and Retrieval Engine (Gstore) platform, developed with support of the NSF EPSCoR Program. The Gstore geospatial services platform provides general purpose web services based upon the REST service model, and is capable of data discovery, access, and publication functions, metadata delivery functions, data transformation, and auto-generated OGC services for those data products that can support those services. Central to the NASA ACCESS project is the delivery of geospatial metadata in a variety of formats, including ISO 19115-2/19139, FGDC CSDGM, and the Proof Markup Language (PML). This presentation details the extraction and persistence of relevant metadata in the Gstore data store, and their transformation into multiple metadata formats that are increasingly utilized by the geospatial community to document not only core library catalog elements (e.g. title, abstract, publication data, geographic extent, projection information, and database elements), but also the processing steps used to generate derived modeling products. In particular, we discuss the generation and service delivery of provenance, or trace of data sources and analytical methods used in a scientific analysis, for archived data. We discuss the workflows developed by EDAC to capture end-to-end provenance, the storage model for those data in a delivery format independent data structure, and delivery of PML, ISO, and FGDC documents to clients requesting those products.

Ecosystem Services Provided by Agricultural Land as Modeled by Broad Scale Geospatial Analysis

NASA Astrophysics Data System (ADS)

Kokkinidis, Ioannis

Agricultural ecosystems provide multiple services including food and fiber provision, nutrient cycling, soil retention and water regulation. Objectives of the study were to identify and quantify a selection of ecosystem services provided by agricultural land, using existing geospatial tools and preferably free and open source data, such as the Virginia Land Use Evaluation System (VALUES), the North Carolina Realistic Yield Expectations (RYE) database, and the land cover datasets NLCD and CDL. Furthermore I sought to model tradeoffs between provisioning and other services. First I assessed the accuracy of agricultural land in NLCD and CDL over a four county area in eastern Virginia using cadastral parcels. I uncovered issues concerning the definition of agricultural land. The area and location of agriculture saw little change in the 19 years studied. Furthermore all datasets have significant errors of omission (11.3 to 95.1%) and commission (0 to 71.3%). Location of agriculture was used with spatial crop yield databases I created and combined with models I adapted to calculate baseline values for plant biomass, nutrient composition and requirements, land suitability for and potential production of biofuels and the economic impact of agriculture for the four counties. The study area was then broadened to cover 97 counties in eastern Virginia and North Carolina, investigating the potential for increased regional grain production through intensification and extensification of agriculture. Predicted yield from geospatial crop models was compared with produced yield from the NASS Survey of Agriculture. Area of most crops in CDL was similar to that in the Survey of Agriculture, but a yield gap is present for most years, partially due to weather, thus indicating potential for yield increase through intensification. Using simple criteria I quantified the potential to extend agriculture in high yield land in other uses and modeled the changes in erosion and runoff should conversion take place. While the quantity of wheat produced though extensification is equal to 4.2 times 2012 production, conversion will lead to large increases in runoff (4.1 to 39.4%) and erosion (6 times). This study advances the state of geospatial tools for quantification of ecosystem services.

A human-driven decline in global burned area

NASA Astrophysics Data System (ADS)

Andela, N.; Morton, D. C.; Chen, Y.; van der Werf, G.; Giglio, L.; Kasibhatla, P. S.; Randerson, J. T.

2016-12-01

Fire is an important and dynamic ecosystem process that influences many aspects of the global Earth system. Here, we used several different satellite datasets to assess trends in global burned area during 1998 to 2014. Global burned area decreased by about 21.6 ± 8.5% over the period from 1998-2014, with large regional declines observed in savanna and grassland ecosystems in northern Africa, Eurasia, and South America. The decrease in burned area remained robust after removing the influence of climate (16.0 ± 6.0%), implicating human activity as a likely driver. To further investigate the mechanisms contributing to regional and global trends, we conducted several kinds of analysis, including separation of burned area into ignition and fire size components and geospatial analysis of fire trends in relationship with demographic and land use variables. We found that fire number was a more important factor contributing to burned area trends than fire size, suggesting a reduction in the use of fire for management purposes. Concurrent decreases in fire size also contributed to the trend outside of North and South America, suggesting a role for greater landscape fragmentation. From our geospatial analysis, we developed a conceptual model that incorporates a range of drivers for human-driven changes in biomass burning that can be used to guide global fire models, currently unable to reproduce these large scale recent trends. Patterns of agricultural expansion and land use intensification are likely to further contribute to declining burned area trends in future decades, with important consequences for Earth system processes mediated by surface albedo, greenhouse gas emissions, and aerosols. Our results also highlight the vulnerability of savannas and grassland to land use changes with unprecedented global scale consequences for vegetation structure and the carbon cycle.

Impacts of Vegetation and Development on the Morphology of Coastal Sand Dunes Using Modern Geospatial Techniques: Jockey's Ridge Case Study

NASA Astrophysics Data System (ADS)

Weaver, K.; Mitasova, H.; Overton, M.

2011-12-01

LiDAR surveys acquired in the years 2007 and 2008, combined with previous LiDAR, topographic mapping and aerial imagery collected along the Outer Banks of North Carolina were used for comprehensive geospatial analysis of the largest sand dune on the eastern coast of the United States, Jockey's Ridge. The objective of the analysis was to evaluate whether the dune's evolution has continued as hypothesized in previous studies and whether an increase of development and vegetation has contributed to the dune's stabilization and overall loss of dune height. Geospatial analysis of the dune system evolution (1974 - 2008) was performed using time series of digital elevation models at one meter resolution. Image processing was conducted in order to analyze land cover change (1932 - 2009) using unsupervised classification to extract vegetation, development and sand in and around Jockey's Ridge State Park. The dune system evolution was then characterized using feature-based and raster-based metrics, including vertical and horizontal change of dune peaks, horizontal migration of dune crests, slip face geometry transformation and volume change analysis using the core and dynamic layer concept. Based on the evolutionary data studied, the volume of sand at Jockey's Ridge is consistent throughout time, composed of a stable core and a dynamically migrating layer that is not gaining or losing sand. Although the peak elevation of the Main Dune has decreased from 43m in 1953 to 22m in 2008, the analysis has shown that the sand is redistributed within the dune field. Today, the dune field peaks are increasing in elevation, and all of the dunes within the system are stabilizing at similar heights of 20-22m along with transformation of the dunes from unvegetated, crescentic to vegetated, parabolic dunes. The overall land cover trend indicates that since the 1930s vegetation and development have gradually increased over time, influencing the morphology of the dune field by stabilizing the area of sand that once fed the dunes, limiting aeolian sand transport and migration of the dune system. Not only are vegetation and development increasing around the Jockey's Ridge State Park, but vegetation is increasing inside the park boundaries with the majority of growth along the windward side of the dune system, blocking sand from feeding the dunes. Vegetation growth is also found to increase in front of the dune field, recently causing the migration of the dune to slow down.

Geospatial assessment of solar energy potential for utility scale parabolic trough collector power plant in Saudi Arabia

NASA Astrophysics Data System (ADS)

Ibarra, Mercedes; Gherboudj, Imen; Al Rished, Abdulaziz; Ghedira, Hosni

2017-06-01

Given ambitious plans to increase the amount of electricity production from renewable resources and the natural resources of the Kingdom of Saudi Arabia (KSA), solar energy stands as a technology with a great development potential in this country. In this work, the suitability of the territory is assess through a geospatial analysis, using a PTC performance model to account for the technical potential. As a result, a land suitability map is presented, where the North-West area of the country is identified as the one with more highly suitable area.

Multidimensional poverty in rural Mozambique: a new metric for evaluating public health interventions.

PubMed

Victor, Bart; Blevins, Meridith; Green, Ann F; Ndatimana, Elisée; González-Calvo, Lázaro; Fischer, Edward F; Vergara, Alfredo E; Vermund, Sten H; Olupona, Omo; Moon, Troy D

2014-01-01

Poverty is a multidimensional phenomenon and unidimensional measurements have proven inadequate to the challenge of assessing its dynamics. Dynamics between poverty and public health intervention is among the most difficult yet important problems faced in development. We sought to demonstrate how multidimensional poverty measures can be utilized in the evaluation of public health interventions; and to create geospatial maps of poverty deprivation to aid implementers in prioritizing program planning. Survey teams interviewed a representative sample of 3,749 female heads of household in 259 enumeration areas across Zambézia in August-September 2010. We estimated a multidimensional poverty index, which can be disaggregated into context-specific indicators. We produced an MPI comprised of 3 dimensions and 11 weighted indicators selected from the survey. Households were identified as "poor" if were deprived in >33% of indicators. Our MPI is an adjusted headcount, calculated by multiplying the proportion identified as poor (headcount) and the poverty gap (average deprivation). Geospatial visualizations of poverty deprivation were created as a contextual baseline for future evaluation. In our rural (96%) and urban (4%) interviewees, the 33% deprivation cut-off suggested 58.2% of households were poor (29.3% of urban vs. 59.5% of rural). Among the poor, households experienced an average deprivation of 46%; thus the MPI/adjusted headcount is 0.27 ( = 0.58×0.46). Of households where a local language was the primary language, 58.6% were considered poor versus Portuguese-speaking households where 73.5% were considered non-poor. Living standard is the dominant deprivation, followed by health, and then education. Multidimensional poverty measurement can be integrated into program design for public health interventions, and geospatial visualization helps examine the impact of intervention deployment within the context of distinct poverty conditions. Both permit program implementers to focus resources and critically explore linkages between poverty and its social determinants, thus deriving useful findings for evidence-based planning.

Multidimensional Poverty in Rural Mozambique: A New Metric for Evaluating Public Health Interventions

PubMed Central

Victor, Bart; Blevins, Meridith; Green, Ann F.; Ndatimana, Elisée; González-Calvo, Lázaro; Fischer, Edward F.; Vergara, Alfredo E.; Vermund, Sten H.; Olupona, Omo; Moon, Troy D.

2014-01-01

Background Poverty is a multidimensional phenomenon and unidimensional measurements have proven inadequate to the challenge of assessing its dynamics. Dynamics between poverty and public health intervention is among the most difficult yet important problems faced in development. We sought to demonstrate how multidimensional poverty measures can be utilized in the evaluation of public health interventions; and to create geospatial maps of poverty deprivation to aid implementers in prioritizing program planning. Methods Survey teams interviewed a representative sample of 3,749 female heads of household in 259 enumeration areas across Zambézia in August-September 2010. We estimated a multidimensional poverty index, which can be disaggregated into context-specific indicators. We produced an MPI comprised of 3 dimensions and 11 weighted indicators selected from the survey. Households were identified as “poor” if were deprived in >33% of indicators. Our MPI is an adjusted headcount, calculated by multiplying the proportion identified as poor (headcount) and the poverty gap (average deprivation). Geospatial visualizations of poverty deprivation were created as a contextual baseline for future evaluation. Results In our rural (96%) and urban (4%) interviewees, the 33% deprivation cut-off suggested 58.2% of households were poor (29.3% of urban vs. 59.5% of rural). Among the poor, households experienced an average deprivation of 46%; thus the MPI/adjusted headcount is 0.27 ( = 0.58×0.46). Of households where a local language was the primary language, 58.6% were considered poor versus Portuguese-speaking households where 73.5% were considered non-poor. Living standard is the dominant deprivation, followed by health, and then education. Conclusions Multidimensional poverty measurement can be integrated into program design for public health interventions, and geospatial visualization helps examine the impact of intervention deployment within the context of distinct poverty conditions. Both permit program implementers to focus resources and critically explore linkages between poverty and its social determinants, thus deriving useful findings for evidence-based planning. PMID:25268951

GEOSPATIAL QA

EPA Science Inventory

Geospatial Science is increasingly becoming an important tool in making Agency decisions. Quality Control and Quality Assurance are required to be integrated during the planning, implementation and assessment of geospatial databases, processes and products. In order to ensure Age...

The geospatial data quality REST API for primary biodiversity data

PubMed Central

Otegui, Javier; Guralnick, Robert P.

2016-01-01

Summary: We present a REST web service to assess the geospatial quality of primary biodiversity data. It enables access to basic and advanced functions to detect completeness and consistency issues as well as general errors in the provided record or set of records. The API uses JSON for data interchange and efficient parallelization techniques for fast assessments of large datasets. Availability and implementation: The Geospatial Data Quality API is part of the VertNet set of APIs. It can be accessed at http://api-geospatial.vertnet-portal.appspot.com/geospatial and is already implemented in the VertNet data portal for quality reporting. Source code is freely available under GPL license from http://www.github.com/vertnet/api-geospatial. Contact: javier.otegui@gmail.com or rguralnick@flmnh.ufl.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26833340

The geospatial data quality REST API for primary biodiversity data.

PubMed

Otegui, Javier; Guralnick, Robert P

2016-06-01

We present a REST web service to assess the geospatial quality of primary biodiversity data. It enables access to basic and advanced functions to detect completeness and consistency issues as well as general errors in the provided record or set of records. The API uses JSON for data interchange and efficient parallelization techniques for fast assessments of large datasets. The Geospatial Data Quality API is part of the VertNet set of APIs. It can be accessed at http://api-geospatial.vertnet-portal.appspot.com/geospatial and is already implemented in the VertNet data portal for quality reporting. Source code is freely available under GPL license from http://www.github.com/vertnet/api-geospatial javier.otegui@gmail.com or rguralnick@flmnh.ufl.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Automated Geospatial Watershed Assessment (AGWA) Tool for hydrologic modeling and watershed assessment

EPA Pesticide Factsheets

Using basic, easily attainable GIS data, AGWA provides a simple, direct, and repeatable methodology for hydrologic model setup, execution, and visualization. AGWA experiences activity from over 170 countries. It l has been downloaded over 11,000 times.

The AgESGUI geospatial simulation system for environmental model application and evaluation

USDA-ARS?s Scientific Manuscript database

Practical decision making in spatially-distributed environmental assessment and management is increasingly being based on environmental process-based models linked to geographical information systems (GIS). Furthermore, powerful computers and Internet-accessible assessment tools are providing much g...

OpenClimateGIS - A Web Service Providing Climate Model Data in Commonly Used Geospatial Formats

NASA Astrophysics Data System (ADS)

Erickson, T. A.; Koziol, B. W.; Rood, R. B.

2011-12-01

The goal of the OpenClimateGIS project is to make climate model datasets readily available in commonly used, modern geospatial formats used by GIS software, browser-based mapping tools, and virtual globes.The climate modeling community typically stores climate data in multidimensional gridded formats capable of efficiently storing large volumes of data (such as netCDF, grib) while the geospatial community typically uses flexible vector and raster formats that are capable of storing small volumes of data (relative to the multidimensional gridded formats). OpenClimateGIS seeks to address this difference in data formats by clipping climate data to user-specified vector geometries (i.e. areas of interest) and translating the gridded data on-the-fly into multiple vector formats. The OpenClimateGIS system does not store climate data archives locally, but rather works in conjunction with external climate archives that expose climate data via the OPeNDAP protocol. OpenClimateGIS provides a RESTful API web service for accessing climate data resources via HTTP, allowing a wide range of applications to access the climate data.The OpenClimateGIS system has been developed using open source development practices and the source code is publicly available. The project integrates libraries from several other open source projects (including Django, PostGIS, numpy, Shapely, and netcdf4-python).OpenClimateGIS development is supported by a grant from NOAA's Climate Program Office.

Purpose, Processes, Partnerships, and Products: 4Ps to advance Participatory Socio-Environmental Modeling

NASA Astrophysics Data System (ADS)

Gray, S. G.; Voinov, A. A.; Jordan, R.; Paolisso, M.

2016-12-01

Model-based reasoning is a basic part of human understanding, decision-making, and communication. Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding environmental change since stakeholders often hold valuable knowledge about socio-environmental dynamics and since collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four dimensional framework that includes reporting on dimensions of: (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of environmental changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of environmental policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

Model My Watershed and BiG CZ Data Portal: Interactive geospatial analysis and hydrological modeling web applications that leverage the Amazon cloud for scientists, resource managers and students

NASA Astrophysics Data System (ADS)

Aufdenkampe, A. K.; Mayorga, E.; Tarboton, D. G.; Sazib, N. S.; Horsburgh, J. S.; Cheetham, R.

2016-12-01

The Model My Watershed Web app (http://wikiwatershed.org/model/) was designed to enable citizens, conservation practitioners, municipal decision-makers, educators, and students to interactively select any area of interest anywhere in the continental USA to: (1) analyze real land use and soil data for that area; (2) model stormwater runoff and water-quality outcomes; and (3) compare how different conservation or development scenarios could modify runoff and water quality. The BiG CZ Data Portal is a web application for scientists for intuitive, high-performance map-based discovery, visualization, access and publication of diverse earth and environmental science data via a map-based interface that simultaneously performs geospatial analysis of selected GIS and satellite raster data for a selected area of interest. The two web applications share a common codebase (https://github.com/WikiWatershed and https://github.com/big-cz), high performance geospatial analysis engine (http://geotrellis.io/ and https://github.com/geotrellis) and deployment on the Amazon Web Services (AWS) cloud cyberinfrastructure. Users can use "on-the-fly" rapid watershed delineation over the national elevation model to select their watershed or catchment of interest. The two web applications also share the goal of enabling the scientists, resource managers and students alike to share data, analyses and model results. We will present these functioning web applications and their potential to substantially lower the bar for studying and understanding our water resources. We will also present work in progress, including a prototype system for enabling citizen-scientists to register open-source sensor stations (http://envirodiy.org/mayfly/) to stream data into these systems, so that they can be reshared using Water One Flow web services.

Leveraging geospatial data, technology, and methods for improving the health of communities: priorities and strategies from an expert panel convened by the CDC.

PubMed

Elmore, Kim; Flanagan, Barry; Jones, Nicholas F; Heitgerd, Janet L

2010-04-01

In 2008, CDC convened an expert panel to gather input on the use of geospatial science in surveillance, research and program activities focused on CDC's Healthy Communities Goal. The panel suggested six priorities: spatially enable and strengthen public health surveillance infrastructure; develop metrics for geospatial categorization of community health and health inequity; evaluate the feasibility and validity of standard metrics of community health and health inequities; support and develop GIScience and geospatial analysis; provide geospatial capacity building, training and education; and, engage non-traditional partners. Following the meeting, the strategies and action items suggested by the expert panel were reviewed by a CDC subcommittee to determine priorities relative to ongoing CDC geospatial activities, recognizing that many activities may need to occur either in parallel, or occur multiple times across phases. Phase A of the action items centers on developing leadership support. Phase B focuses on developing internal and external capacity in both physical (e.g., software and hardware) and intellectual infrastructure. Phase C of the action items plan concerns the development and integration of geospatial methods. In summary, the panel members provided critical input to the development of CDC's strategic thinking on integrating geospatial methods and research issues across program efforts in support of its Healthy Communities Goal.

Remote measurement methods for 3-D modeling purposes using BAE Systems' Software

NASA Astrophysics Data System (ADS)

Walker, Stewart; Pietrzak, Arleta

2015-06-01

Efficient, accurate data collection from imagery is the key to an economical generation of useful geospatial products. Incremental developments of traditional geospatial data collection and the arrival of new image data sources cause new software packages to be created and existing ones to be adjusted to enable such data to be processed. In the past, BAE Systems' digital photogrammetric workstation, SOCET SET®, met fin de siècle expectations in data processing and feature extraction. Its successor, SOCET GXP®, addresses today's photogrammetric requirements and new data sources. SOCET GXP is an advanced workstation for mapping and photogrammetric tasks, with automated functionality for triangulation, Digital Elevation Model (DEM) extraction, orthorectification and mosaicking, feature extraction and creation of 3-D models with texturing. BAE Systems continues to add sensor models to accommodate new image sources, in response to customer demand. New capabilities added in the latest version of SOCET GXP facilitate modeling, visualization and analysis of 3-D features.

Flexible Environmental Modeling with Python and Open - GIS

NASA Astrophysics Data System (ADS)

Pryet, Alexandre; Atteia, Olivier; Delottier, Hugo; Cousquer, Yohann

2015-04-01

Numerical modeling now represents a prominent task of environmental studies. During the last decades, numerous commercial programs have been made available to environmental modelers. These software applications offer user-friendly graphical user interfaces that allow an efficient management of many case studies. However, they suffer from a lack of flexibility and closed-source policies impede source code reviewing and enhancement for original studies. Advanced modeling studies require flexible tools capable of managing thousands of model runs for parameter optimization, uncertainty and sensitivity analysis. In addition, there is a growing need for the coupling of various numerical models associating, for instance, groundwater flow modeling to multi-species geochemical reactions. Researchers have produced hundreds of open-source powerful command line programs. However, there is a need for a flexible graphical user interface allowing an efficient processing of geospatial data that comes along any environmental study. Here, we present the advantages of using the free and open-source Qgis platform and the Python scripting language for conducting environmental modeling studies. The interactive graphical user interface is first used for the visualization and pre-processing of input geospatial datasets. Python scripting language is then employed for further input data processing, call to one or several models, and post-processing of model outputs. Model results are eventually sent back to the GIS program, processed and visualized. This approach combines the advantages of interactive graphical interfaces and the flexibility of Python scripting language for data processing and model calls. The numerous python modules available facilitate geospatial data processing and numerical analysis of model outputs. Once input data has been prepared with the graphical user interface, models may be run thousands of times from the command line with sequential or parallel calls. We illustrate this approach with several case studies in groundwater hydrology and geochemistry and provide links to several python libraries that facilitate pre- and post-processing operations.

GEOSPATIAL QUALITY COUNCIL

EPA Science Inventory

Geospatial Science is increasingly becoming an important tool in making Agency decisions. QualIty Control and Quality Assurance are required to be integrated during the planning, implementation and assessment of geospatial databases, processes and products. In order to ensure Age...

Advancements in Open Geospatial Standards for Photogrammetry and Remote Sensing from Ogc

NASA Astrophysics Data System (ADS)

Percivall, George; Simonis, Ingo

2016-06-01

The necessity of open standards for effective sharing and use of remote sensing continues to receive increasing emphasis in policies of agencies and projects around the world. Coordination on the development of open standards for geospatial information is a vital step to insure that the technical standards are ready to support the policy objectives. The mission of the Open Geospatial Consortium (OGC) is to advance development and use of international standards and supporting services that promote geospatial interoperability. To accomplish this mission, OGC serves as the global forum for the collaboration of geospatial data / solution providers and users. Photogrammetry and remote sensing are sources of the largest and most complex geospatial information. Some of the most mature OGC standards for remote sensing include the Sensor Web Enablement (SWE) standards, the Web Coverage Service (WCS) suite of standards, encodings such as NetCDF, GMLJP2 and GeoPackage, and the soon to be approved Discrete Global Grid Systems (DGGS) standard. In collaboration with ISPRS, OGC working with government, research and industrial organizations continue to advance the state of geospatial standards for full use of photogrammetry and remote sensing.

Increasing Diversity in Geosciences: Geospatial Initiatives at North Carolina Central University

NASA Astrophysics Data System (ADS)

Vlahovic, G.; Malhotra, R.; Renslow, M.; Harris, J.; Barnett, A.

2006-12-01

Two new initiatives funded by the NSF-GEO and NSF-HRD directorates have potential to advance the geospatial program at the North Carolina Central University (NCCU). As one of only two Historically Black Colleges and Universities (HBCUs) in the southeast offering Geography as a major, NCCU is establishing a GIS Research, Innovative Teaching, and Service (GRITS) Laboratory and has partnered with American Society for Photogrammetry and Remote Sensing (ASPRS) to offer GIS certification to Geography graduates. This presentation will focus on the role that GRITS and GIS certification will play in attracting students to the geoscience majors, the planned curriculum changes, and the emerging partnership with ASPRS to develop and offer "provisional certification" to NCCU students. In addition, authors would also like to describe plans to promote geospatial education in partnership with other educational institutions. NCCUs high minority enrollment (at the present approximately 90%) and quality and tradition of geoscience program make it an ideal incubator for accreditation and certification activities and possible role model for other HBCUs.

The Whole World In Your Hands: Using an Interactive Virtual Reality Sandbox for Geospatial Education and Outreach

NASA Astrophysics Data System (ADS)

Clucas, T.; Wirth, G. S.; Broderson, D.

2014-12-01

Traditional geospatial education tools such as maps and computer screens don't convey the rich topography present on Earth. Translating lines on a contour lines on a topo map to relief in a landscape can be a challenging concept to convey.A partnership between Alaska EPSCoR and the Geographic Information Network of Alaska has successfully constructed an Interactive Virtual Reality Sandbox, an education tool that in real-time projects and updates topographic contours on the surface of a sandbox. The sandbox has been successfully deployed at public science events as well as professional geospatial and geodesy conferences. Landscape change, precipitation, and evaporation can all be modeled, much to the delight of our enthusiasts, who range in age from 3 to 90. Visually, as well as haptically, demonstrating the effects of events (such as dragging a hand through the sand) on a landscape, as well as the intuitive realization of meaning of topographic contour lines, has proven to be engaging.

Geospatial Modelling Approach for 3d Urban Densification Developments

NASA Astrophysics Data System (ADS)

Koziatek, O.; Dragićević, S.; Li, S.

2016-06-01

With growing populations, economic pressures, and the need for sustainable practices, many urban regions are rapidly densifying developments in the vertical built dimension with mid- and high-rise buildings. The location of these buildings can be projected based on key factors that are attractive to urban planners, developers, and potential buyers. Current research in this area includes various modelling approaches, such as cellular automata and agent-based modelling, but the results are mostly linked to raster grids as the smallest spatial units that operate in two spatial dimensions. Therefore, the objective of this research is to develop a geospatial model that operates on irregular spatial tessellations to model mid- and high-rise buildings in three spatial dimensions (3D). The proposed model is based on the integration of GIS, fuzzy multi-criteria evaluation (MCE), and 3D GIS-based procedural modelling. Part of the City of Surrey, within the Metro Vancouver Region, Canada, has been used to present the simulations of the generated 3D building objects. The proposed 3D modelling approach was developed using ESRI's CityEngine software and the Computer Generated Architecture (CGA) language.

77 FR 67634 - Hydrographic Services Review Panel Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-13

... coastal observation systems for coastal protection and restoration programs and surge and inundation models to protect coastal populations; and (3) use of geospatial services and spatial reference systems...

Marine vessels as substitutes for heavy-duty trucks in Great Lakes freight transportation.

PubMed

Comer, Bryan; Corbett, James J; Hawker, J Scott; Korfmacher, Karl; Lee, Earl E; Prokop, Chris; Winebrake, James J

2010-07-01

This paper applies a geospatial network optimization model to explore environmental, economic, and time-of-delivery tradeoffs associated with the application of marine vessels as substitutes for heavy-duty trucks operating in the Great Lakes region. The geospatial model integrates U.S. and Canadian highway, rail, and waterway networks to create an intermodal network and characterizes this network using temporal, economic, and environmental attributes (including emissions of carbon dioxide, particulate matter, carbon monoxide, sulfur oxides, volatile organic compounds, and nitrogen oxides). A case study evaluates tradeoffs associated with containerized traffic flow in the Great Lakes region, demonstrating how choice of freight mode affects the environmental performance of movement of goods. These results suggest opportunities to improve the environmental performance of freight transport through infrastructure development, technology implementation, and economic incentives.

Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling

USGS Publications Warehouse

Gray, Steven; Voinov, Alexey; Paolisso, Michael; Jordan, Rebecca; BenDor, Todd; Bommel, Pierre; Glynn, Pierre D.; Hedelin, Beatrice; Hubacek, Klaus; Introne, Josh; Kolagani, Nagesh; Laursen, Bethany; Prell, Christina; Schmitt-Olabisi, Laura; Singer, Alison; Sterling, Eleanor J.; Zellner, Moira

2018-01-01

Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human–environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling.

PubMed

Gray, Steven; Voinov, Alexey; Paolisso, Michael; Jordan, Rebecca; BenDor, Todd; Bommel, Pierre; Glynn, Pierre; Hedelin, Beatrice; Hubacek, Klaus; Introne, Josh; Kolagani, Nagesh; Laursen, Bethany; Prell, Christina; Schmitt Olabisi, Laura; Singer, Alison; Sterling, Eleanor; Zellner, Moira

2018-01-01

Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM. © 2017 by the Ecological Society of America.

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT: A GIS-BASED HYDROLOGIC MODELING TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving toward complex, spatially explicit regional assessments. These problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extens...

Variable population exposure and distributed travel speeds in least-cost tsunami evacuation modelling

NASA Astrophysics Data System (ADS)

Fraser, S. A.; Wood, N. J.; Johnston, D. M.; Leonard, G. S.; Greening, P. D.; Rossetto, T.

2014-06-01

Evacuation of the population from a tsunami hazard zone is vital to reduce life-loss due to inundation. Geospatial least-cost distance modelling provides one approach to assessing tsunami evacuation potential. Previous models have generally used two static exposure scenarios and fixed travel speeds to represent population movement. Some analyses have assumed immediate evacuation departure time or assumed a common departure time for all exposed population. In this paper, a method is proposed to incorporate time-variable exposure, distributed travel speeds, and uncertain evacuation departure time into an existing anisotropic least-cost path distance framework. The model is demonstrated for a case study of local-source tsunami evacuation in Napier City, Hawke's Bay, New Zealand. There is significant diurnal variation in pedestrian evacuation potential at the suburb-level, although the total number of people unable to evacuate is stable across all scenarios. Whilst some fixed travel speeds can approximate a distributed speed approach, others may overestimate evacuation potential. The impact of evacuation departure time is a significant contributor to total evacuation time. This method improves least-cost modelling of evacuation dynamics for evacuation planning, casualty modelling, and development of emergency response training scenarios.

UASs for geospatial data

USDA-ARS?s Scientific Manuscript database

Increasingly, consumer organizations, businesses, and academic researchers are using UAS to gather geospatial, environmental data on natural and man-made phenomena. These data may be either remotely sensed or measured directly (e. g., sampling of atmospheric constituents). The term geospatial data r...

Predicting the spatial extent of liquefaction from geospatial and earthquake specific parameters

USGS Publications Warehouse

Zhu, Jing; Baise, Laurie G.; Thompson, Eric M.; Wald, David J.; Knudsen, Keith L.; Deodatis, George; Ellingwood, Bruce R.; Frangopol, Dan M.

2014-01-01

The spatially extensive damage from the 2010-2011 Christchurch, New Zealand earthquake events are a reminder of the need for liquefaction hazard maps for anticipating damage from future earthquakes. Liquefaction hazard mapping as traditionally relied on detailed geologic mapping and expensive site studies. These traditional techniques are difficult to apply globally for rapid response or loss estimation. We have developed a logistic regression model to predict the probability of liquefaction occurrence in coastal sedimentary areas as a function of simple and globally available geospatial features (e.g., derived from digital elevation models) and standard earthquake-specific intensity data (e.g., peak ground acceleration). Some of the geospatial explanatory variables that we consider are taken from the hydrology community, which has a long tradition of using remotely sensed data as proxies for subsurface parameters. As a result of using high resolution, remotely-sensed, and spatially continuous data as a proxy for important subsurface parameters such as soil density and soil saturation, and by using a probabilistic modeling framework, our liquefaction model inherently includes the natural spatial variability of liquefaction occurrence and provides an estimate of spatial extent of liquefaction for a given earthquake. To provide a quantitative check on how the predicted probabilities relate to spatial extent of liquefaction, we report the frequency of observed liquefaction features within a range of predicted probabilities. The percentage of liquefaction is the areal extent of observed liquefaction within a given probability contour. The regional model and the results show that there is a strong relationship between the predicted probability and the observed percentage of liquefaction. Visual inspection of the probability contours for each event also indicates that the pattern of liquefaction is well represented by the model.

Quality Assessment and Accessibility Applications of Crowdsourced Geospatial Data: A Report on the Development and Extension of the George Mason University Geocrowdsourcing Testbed

DTIC Science & Technology

2014-09-01

Approved for public release; distribution is unlimited. Prepared for Geospatial Research Laboratory U.S. Army Engineer Research and Development...Center U.S. Army Corps of Engineers Under Data Level Enterprise Tools Monitored by Geospatial Research Laboratory 7701 Telegraph Road...Engineer Research and Development Center (ERDC) ERDC Geospatial Research Laboratory 7701 Telegraph Road 11. SPONSOR/MONITOR’S REPORT Alexandria, VA 22135

An Institutional Community-Driven effort to Curate and Preserve Geospatial Data using GeoBlacklight

NASA Astrophysics Data System (ADS)

Petters, J.; Coleman, S.; Andrea, O.

2016-12-01

A variety of geospatial data is produced or collected by both academic researchers and non-academic groups in the Virginia Tech community. In an effort to preserve, curate and make this geospatial data discoverable, the University Libraries have been building a local implementation of GeoBlacklight, a multi-institutional open-source collaborative project to improve the discoverability and sharing of geospatial data. We will discuss the local implementation of Geoblacklight at Virginia Tech, focusing on the efforts necessary to make it a sustainable resource for the institution and local community going forward. This includes technical challenges such as the development of uniform workflows for geospatial data produced within and outside the course of research, but organizational and economic barriers must be overcome as well. In spearheading this GeoBlacklight effort the Libraries have partnered with University Facilities and University IT. The IT group manages the storage and backup of geospatial data, allowing our group to focus on geospatial data collection and curation. Both IT and University Facilities are in possession of localized geospatial data of interest to Viriginia Tech researchers that all parties agreed should be made discoverable and accessible. The interest and involvement of these and other university stakeholders is key to establishing the sustainability of the infrastructure and the capabilities it can provide to the Virginia Tech community and beyond.

A cross-sectional ecological analysis of international and sub-national health inequalities in commercial geospatial resource availability.

PubMed

Dotse-Gborgbortsi, Winfred; Wardrop, Nicola; Adewole, Ademola; Thomas, Mair L H; Wright, Jim

2018-05-23

Commercial geospatial data resources are frequently used to understand healthcare utilisation. Although there is widespread evidence of a digital divide for other digital resources and infra-structure, it is unclear how commercial geospatial data resources are distributed relative to health need. To examine the distribution of commercial geospatial data resources relative to health needs, we assembled coverage and quality metrics for commercial geocoding, neighbourhood characterisation, and travel time calculation resources for 183 countries. We developed a country-level, composite index of commercial geospatial data quality/availability and examined its distribution relative to age-standardised all-cause and cause specific (for three main causes of death) mortality using two inequality metrics, the slope index of inequality and relative concentration index. In two sub-national case studies, we also examined geocoding success rates versus area deprivation by district in Eastern Region, Ghana and Lagos State, Nigeria. Internationally, commercial geospatial data resources were inversely related to all-cause mortality. This relationship was more pronounced when examining mortality due to communicable diseases. Commercial geospatial data resources for calculating patient travel times were more equitably distributed relative to health need than resources for characterising neighbourhoods or geocoding patient addresses. Countries such as South Africa have comparatively high commercial geospatial data availability despite high mortality, whilst countries such as South Korea have comparatively low data availability and low mortality. Sub-nationally, evidence was mixed as to whether geocoding success was lowest in more deprived districts. To our knowledge, this is the first global analysis of commercial geospatial data resources in relation to health outcomes. In countries such as South Africa where there is high mortality but also comparatively rich commercial geospatial data, these data resources are a potential resource for examining healthcare utilisation that requires further evaluation. In countries such as Sierra Leone where there is high mortality but minimal commercial geospatial data, alternative approaches such as open data use are needed in quantifying patient travel times, geocoding patient addresses, and characterising patients' neighbourhoods.

Web catalog of oceanographic data using GeoNetwork

NASA Astrophysics Data System (ADS)

Marinova, Veselka; Stefanov, Asen

2017-04-01

Most of the data collected, analyzed and used by Bulgarian oceanographic data center (BgODC) from scientific cruises, argo floats, ferry boxes and real time operating systems are spatially oriented and need to be displayed on the map. The challenge is to make spatial information more accessible to users, decision makers and scientists. In order to meet this challenge, BgODC concentrate its efforts on improving dynamic and standardized access to their geospatial data as well as those from various related organizations and institutions. BgODC currently is implementing a project to create a geospatial portal for distributing metadata and search, exchange and harvesting spatial data. There are many open source software solutions able to create such spatial data infrastructure (SDI). Finally, the GeoNetwork open source is chosen, as it is already widespread. This software is free, effective and "cheap" solution for implementing SDI at organization level. It is platform independent and runs under many operating systems. Filling of the catalog goes through these practical steps: • Managing and storing data reliably within MS SQL spatial data base; • Registration of maps and data of various formats and sources in GeoServer (most popular open source geospatial server embedded with GeoNetwork) ; • Filling added meta data and publishing geospatial data at the desktop of GeoNetwork. GeoServer and GeoNetwork are based on Java so they require installing of a servlet engine like Tomcat. The experience gained from the use of GeoNetwork Open Source confirms that the catalog meets the requirements for data management and is flexible enough to customize. Building the catalog facilitates sustainable data exchange between end users. The catalog is a big step towards implementation of the INSPIRE directive due to availability of many features necessary for producing "INSPIRE compliant" metadata records. The catalog now contains all available GIS data provided by BgODC for Internet access. Searching data within the catalog is based upon geographic extent, theme type and free text search.

78 FR 69393 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-19

.... FOR FURTHER INFORMATION CONTACT: National Geospatial-Intelligence Agency (NGA), ATTN: Human...: Delete entry and replace with ``Human Development Directorate, National Geospatial-Intelligence Agency...; System of Records AGENCY: National Geospatial-Intelligence Agency, DoD. ACTION: Notice to alter a System...

77 FR 5820 - National Geospatial Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-06

... DEPARTMENT OF THE INTERIOR Office of the Secretary National Geospatial Advisory Committee AGENCY... that the Secretary of the Interior has renewed the National Geospatial Advisory Committee. The Committee will provide advice and recommendations to the Federal Geographic Data Committee (FGDC), through...

Information Fusion for Feature Extraction and the Development of Geospatial Information

DTIC Science & Technology

2004-07-01

of automated processing . 2. Requirements for Geospatial Information Accurate, timely geospatial information is critical for many military...this evaluation illustrates some of the difficulties in comparing manual and automated processing results (figure 5). The automated delineation of

Nick Grue | NREL

Science.gov Websites

geospatial data analysis using parallel processing High performance computing Renewable resource technical potential and supply curve analysis Spatial database utilization Rapid analysis of large geospatial datasets energy and geospatial analysis products Research Interests Rapid, web-based renewable resource analysis

Geospatial Information Best Practices

DTIC Science & Technology

2012-01-01

26 Spring - 2012 By MAJ Christopher Blais, CW2 Joshua Stratton and MSG Moise Danjoint The fact that Geospatial information can be codified and...Operation Iraqi Freedom V (2007-2008, and Operation New Dawn (2011). MSG Moise Danjoint is the noncommissioned officer in charge, Geospatial

Stakeholder-driven geospatial modeling for assessing tsunami vertical-evacuation strategies in the U.S. Pacific Northwest

NASA Astrophysics Data System (ADS)

Wood, N. J.; Schmidtlein, M.; Schelling, J.; Jones, J.; Ng, P.

2012-12-01

Recent tsunami disasters, such as the 2010 Chilean and 2011 Tohoku events, demonstrate the significant life loss that can occur from tsunamis. Many coastal communities in the world are threatened by near-field tsunami hazards that may inundate low-lying areas only minutes after a tsunami begins. Geospatial integration of demographic data and hazard zones has identified potential impacts on populations in communities susceptible to near-field tsunami threats. Pedestrian-evacuation models build on these geospatial analyses to determine if individuals in tsunami-prone areas will have sufficient time to reach high ground before tsunami-wave arrival. Areas where successful evacuations are unlikely may warrant vertical-evacuation (VE) strategies, such as berms or structures designed to aid evacuation. The decision of whether and where VE strategies are warranted is complex. Such decisions require an interdisciplinary understanding of tsunami hazards, land cover conditions, demography, community vulnerability, pedestrian-evacuation models, land-use and emergency-management policy, and decision science. Engagement with the at-risk population and local emergency managers in VE planning discussions is critical because resulting strategies include permanent structures within a community and their local ownership helps ensure long-term success. We present a summary of an interdisciplinary approach to assess VE options in communities along the southwest Washington coast (U.S.A.) that are threatened by near-field tsunami hazards generated by Cascadia subduction zone earthquakes. Pedestrian-evacuation models based on an anisotropic approach that uses path-distance algorithms were merged with population data to forecast the distribution of at-risk individuals within several communities as a function of travel time to safe locations. A series of community-based workshops helped identify potential VE options in these communities, collectively known as "Project Safe Haven" at the State of Washington Emergency Management Division. Models of the influence of stakeholder-driven VE options identified changes in the type and distribution of at-risk individuals. Insights from VE use and performance as an aid to evacuations from the 2011 Tohoku tsunami helped to inform the meetings and the analysis. We developed geospatial tools to automate parts of the pedestrian-evacuation models to support the iterative process of developing VE options and forecasting changes in population exposure. Our summary presents the interdisciplinary effort to forecast population impacts from near-field tsunami threats and to develop effective VE strategies to minimize fatalities in future events.

Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

NASA Astrophysics Data System (ADS)

Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

2013-12-01

Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it requires the use of additional software. In particular, there are at least three elements that are needed: a geospatially enabled database, a map server, and geoprocessing toolbox. We recommend a software stack for geospatial web application development comprising: MapServer, PostGIS, and 52 North with Python as the scripting language to tie them together. Another hurdle that must be cleared is managing the cloud-computing load. We are using HTCondor as a solution to this end. Finally, we are creating a scripting environment wherein developers will be able to create apps that use existing hydrologic models in our system with minimal effort. This capability will be accomplished by creating a plugin for a Python content management system called CKAN. We are currently developing cyberinfrastructure that utilizes this stack and greatly lowers the investment required to deploy cloud-based modeling apps. This material is based upon work supported by the National Science Foundation under Grant No. 1135482

Jupyter meets Earth: Creating Comprehensible and Reproducible Scientific Workflows with Jupyter Notebooks and Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T.

2016-12-01

Deriving actionable information from Earth observation data obtained from sensors or models can be quite complicated, and sharing those insights with others in a form that they can understand, reproduce, and improve upon is equally difficult. Journal articles, even if digital, commonly present just a summary of an analysis that cannot be understood in depth or reproduced without major effort on the part of the reader. Here we show a method of improving scientific literacy by pairing a recently developed scientific presentation technology (Jupyter Notebooks) with a petabyte-scale platform for accessing and analyzing Earth observation and model data (Google Earth Engine). Jupyter Notebooks are interactive web documents that mix live code with annotations such as rich-text markup, equations, images, videos, hyperlinks and dynamic output. Notebooks were first introduced as part of the IPython project in 2011, and have since gained wide acceptance in the scientific programming community, initially among Python programmers but later by a wide range of scientific programming languages. While Jupyter Notebooks have been widely adopted for general data analysis, data visualization, and machine learning, to date there have been relatively few examples of using Jupyter Notebooks to analyze geospatial datasets. Google Earth Engine is cloud-based platform for analyzing geospatial data, such as satellite remote sensing imagery and/or Earth system model output. Through its Python API, Earth Engine makes petabytes of Earth observation data accessible, and provides hundreds of algorithmic building blocks that can be chained together to produce high-level algorithms and outputs in real-time. We anticipate that this technology pairing will facilitate a better way of creating, documenting, and sharing complex analyses that derive information on our Earth that can be used to promote broader understanding of the complex issues that it faces. http://jupyter.orghttps://earthengine.google.com

GIS-and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Wei; Minnick, Matthew; Geza, Mengistu

2012-09-30

The Colorado School of Mines (CSM) was awarded a grant by the National Energy Technology Laboratory (NETL), Department of Energy (DOE) to conduct a research project en- titled GIS- and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development in October of 2008. The ultimate goal of this research project is to develop a water resource geo-spatial infrastructure that serves as “baseline data” for creating solutions on water resource management and for supporting decisions making on oil shale resource development. The project came to the end on September 30, 2012. This final project report will report the key findings frommore » the project activity, major accomplishments, and expected impacts of the research. At meantime, the gamma version (also known as Version 4.0) of the geodatabase as well as other various deliverables stored on digital storage media will be send to the program manager at NETL, DOE via express mail. The key findings from the project activity include the quantitative spatial and temporal distribution of the water resource throughout the Piceance Basin, water consumption with respect to oil shale production, and data gaps identified. Major accomplishments of this project include the creation of a relational geodatabase, automated data processing scripts (Matlab) for database link with surface water and geological model, ArcGIS Model for hydrogeologic data processing for groundwater model input, a 3D geological model, surface water/groundwater models, energy resource development systems model, as well as a web-based geo-spatial infrastructure for data exploration, visualization and dissemination. This research will have broad impacts of the devel- opment of the oil shale resources in the US. The geodatabase provides a “baseline” data for fur- ther study of the oil shale development and identification of further data collection needs. The 3D geological model provides better understanding through data interpolation and visualization techniques of the Piceance Basin structure spatial distribution of the oil shale resources. The sur- face water/groundwater models quantify the water shortage and better understanding the spatial distribution of the available water resources. The energy resource development systems model reveals the phase shift of water usage and the oil shale production, which will facilitate better planning for oil shale development. Detailed descriptions about the key findings from the project activity, major accomplishments, and expected impacts of the research will be given in the sec- tion of “ACCOMPLISHMENTS, RESULTS, AND DISCUSSION” of this report.« less

GIS-BASED HYDROLOGIC MODELING: THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving from simple, local scale problems toward complex, spatially explicit regional ones. Such problems have to be
addressed with distributed models that can compute runoff and erosion at different spatial a...

Web mapping system for complex processing and visualization of environmental geospatial datasets

NASA Astrophysics Data System (ADS)

Titov, Alexander; Gordov, Evgeny; Okladnikov, Igor

2016-04-01

Environmental geospatial datasets (meteorological observations, modeling and reanalysis results, etc.) are used in numerous research applications. Due to a number of objective reasons such as inherent heterogeneity of environmental datasets, big dataset volume, complexity of data models used, syntactic and semantic differences that complicate creation and use of unified terminology, the development of environmental geodata access, processing and visualization services as well as client applications turns out to be quite a sophisticated task. According to general INSPIRE requirements to data visualization geoportal web applications have to provide such standard functionality as data overview, image navigation, scrolling, scaling and graphical overlay, displaying map legends and corresponding metadata information. It should be noted that modern web mapping systems as integrated geoportal applications are developed based on the SOA and might be considered as complexes of interconnected software tools for working with geospatial data. In the report a complex web mapping system including GIS web client and corresponding OGC services for working with geospatial (NetCDF, PostGIS) dataset archive is presented. There are three basic tiers of the GIS web client in it: 1. Tier of geospatial metadata retrieved from central MySQL repository and represented in JSON format 2. Tier of JavaScript objects implementing methods handling: --- NetCDF metadata --- Task XML object for configuring user calculations, input and output formats --- OGC WMS/WFS cartographical services 3. Graphical user interface (GUI) tier representing JavaScript objects realizing web application business logic Metadata tier consists of a number of JSON objects containing technical information describing geospatial datasets (such as spatio-temporal resolution, meteorological parameters, valid processing methods, etc). The middleware tier of JavaScript objects implementing methods for handling geospatial metadata, task XML object, and WMS/WFS cartographical services interconnects metadata and GUI tiers. The methods include such procedures as JSON metadata downloading and update, launching and tracking of the calculation task running on the remote servers as well as working with WMS/WFS cartographical services including: obtaining the list of available layers, visualizing layers on the map, exporting layers in graphical (PNG, JPG, GeoTIFF), vector (KML, GML, Shape) and digital (NetCDF) formats. Graphical user interface tier is based on the bundle of JavaScript libraries (OpenLayers, GeoExt and ExtJS) and represents a set of software components implementing web mapping application business logic (complex menus, toolbars, wizards, event handlers, etc.). GUI provides two basic capabilities for the end user: configuring the task XML object functionality and cartographical information visualizing. The web interface developed is similar to the interface of such popular desktop GIS applications, as uDIG, QuantumGIS etc. Web mapping system developed has shown its effectiveness in the process of solving real climate change research problems and disseminating investigation results in cartographical form. The work is supported by SB RAS Basic Program Projects VIII.80.2.1 and IV.38.1.7.

Two Contrasting Approaches to Building High School Teacher Capacity to Teach About Local Climate Change Using Powerful Geospatial Data and Visualization Technology

NASA Astrophysics Data System (ADS)

Zalles, D. R.

2011-12-01

The presentation will compare and contrast two different place-based approaches to helping high school science teachers use geospatial data visualization technology to teach about climate change in their local regions. The approaches are being used in the development, piloting, and dissemination of two projects for high school science led by the author: the NASA-funded Data-enhanced Investigations for Climate Change Education (DICCE) and the NSF funded Studying Topography, Orographic Rainfall, and Ecosystems with Geospatial Information Technology (STORE). DICCE is bringing an extensive portal of Earth observation data, the Goddard Interactive Online Visualization and Analysis Infrastructure, to high school classrooms. STORE is making available data for viewing results of a particular IPCC-sanctioned climate change model in relation to recent data about average temperatures, precipitation, and land cover for study areas in central California and western New York State. Across the two projects, partner teachers of academically and ethnically diverse students from five states are participating in professional development and pilot testing. Powerful geospatial data representation technologies are difficult to implement in high school science because of challenges that teachers and students encounter navigating data access and making sense of data characteristics and nomenclature. Hence, on DICCE, the researchers are testing the theory that by providing a scaffolded technology-supported process for instructional design, starting from fundamental questions about the content domain, teachers will make better instructional decisions. Conversely, the STORE approach is rooted in the perspective that co-design of curricular materials among researchers and teacher partners that work off of "starter" lessons covering focal skills and understandings will lead to the most effective utilizations of the technology in the classroom. The projects' goals and strategies for student learning proceed from research suggesting that students will be more engaged and able to utilize prior knowledge better when seeing the local and hence personal relevance of climate change and other pressing contemporary science-related issues. In these projects, the students look for climate change trends in geospatial Earth System data layers from weather stations, satellites, and models in relation to global trends. They examine these data to (1) reify what they are learning in science class about meteorology, climate, and ecology, (2) build inquiry skills by posing and seeking answers to research questions, and (3) build data literacy skills through experience generating appropriate data queries and examining data output on different forms of geospatial representations such as maps, elevation profiles, and time series plots. Teachers also are given the opportunity to have their students look at geospatially represented census data from the tool Social Explorer (http://www.socialexplorer.com/pub/maps/home.aspx) in order to better understand demographic trends in relation to climate change-related trends in the Earth system. Early results will be reported about teacher professional development and student learning, gleaned from interviews and observations.

US EPA GEOSPATIAL QUALITY COUNCIL: ENSURING QUALITY IN GEOPSPATIAL SOLUTIONS

EPA Science Inventory

In 1999, the U.S. Environmental Protection Agency (EPA), Office of Research and Development, Environmental Sciences Division, created the EPA Geospatial Quality Council (GQC) to fill the gap between the EPA Quality Assurance (QA) and Geospatial communities. GQC participants inclu...

Searches over graphs representing geospatial-temporal remote sensing data

DOEpatents

Brost, Randolph; Perkins, David Nikolaus

2018-03-06

Various technologies pertaining to identifying objects of interest in remote sensing images by searching over geospatial-temporal graph representations are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Geospatial-temporal graph searches are made computationally efficient by taking advantage of characteristics of geospatial-temporal data in remote sensing images through the application of various graph search techniques.

Renewable Energy Deployment in Colorado and the West: A Modeling Sensitivity and GIS Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrows, Clayton; Mai, Trieu; Haase, Scott

2016-03-01

The Resource Planning Model is a capacity expansion model designed for a regional power system, such as a utility service territory, state, or balancing authority. We apply a geospatial analysis to Resource Planning Model renewable energy capacity expansion results to understand the likelihood of renewable development on various lands within Colorado.

Investigations of the gravity profile below the Tibetan plateau

NASA Astrophysics Data System (ADS)

Shen, W. B.; Han, J. C.

2012-04-01

Scientists pay great attention to the structure and dynamics of the Tibetan plateau due to the fact that it is a natural experiment site for geoscience studies. The gravity profiles below the Tibetan plateau with successive high-accuracy play more and more significant role in studying the structure and evolution of the Tibetan plateau. This study focuses on determining the inner gravity field of the Tibetan plateau until to the depth of D and interpret possible mechanism of the gravity profile below the Tibetan plateau, especially reinvestigating the isostasy problem (Pratt hypothesis and Airy hypothesis). The inner gravity field below the Tibetan plateau is determined based on a simple technique (i.e. a combination of Newtonian integral, downward continuation of gravity field, and "remove-restore" scheme) and the following datasets: the external Earth gravitational model EGM2008 and the digital topographic model DTM2006.0 released by NGA (National Geospatial-Intelligence Agency, USA), and the crust density distribution model CRUST2.0 released by NGS (National Geological Survey, USA). This study is supported by Natural Science Foundation China (grant No.40974015; No.41174011).

Introduction to This Special Issue on Geostatistics and Geospatial Techniques in Remote Sensing

NASA Technical Reports Server (NTRS)

Atkinson, Peter; Quattrochi, Dale A.; Goodman, H. Michael (Technical Monitor)

2000-01-01

The germination of this special Computers & Geosciences (C&G) issue began at the Royal Geographical Society (with the Institute of British Geographers) (RGS-IBG) annual meeting in January 1997 held at the University of Exeter, UK. The snow and cold of the English winter were tempered greatly by warm and cordial discussion of how to stimulate and enhance cooperation on geostatistical and geospatial research in remote sensing 'across the big pond' between UK and US researchers. It was decided that one way forward would be to hold parallel sessions in 1998 on geostatistical and geospatial research in remote sensing at appropriate venues in both the UK and the US. Selected papers given at these sessions would be published as special issues of C&G on the UK side and Photogrammetric Engineering and Remote Sensing (PE&RS) on the US side. These issues would highlight the commonality in research on geostatistical and geospatial research in remote sensing on both sides of the Atlantic Ocean. As a consequence, a session on "Geostatistics and Geospatial Techniques for Remote Sensing of Land Surface Processes" was held at the RGS-IBG annual meeting in Guildford, Surrey, UK in January 1998, organized by the Modeling and Advanced Techniques Special Interest Group (MAT SIG) of the Remote Sensing Society (RSS). A similar session was held at the Association of American Geographers (AAG) annual meeting in Boston, Massachusetts in March 1998, sponsored by the AAG's Remote Sensing Specialty Group (RSSG). The 10 papers that make up this issue of C&G, comprise 7 papers from the UK and 3 papers from the LIS. We are both co-editors of each of the journal special issues, with the lead editor of each journal issue being from their respective side of the Atlantic. The special issue of PE&RS (vol. 65) that constitutes the other half of this co-edited journal series was published in early 1999, comprising 6 papers by US authors. We are indebted to the International Association for Mathematical Geology for allowing us to use C&G as a vehicle to convey how geostatistics and geospatial techniques can be used to analyze remote sensing and other types of spatial data. We see this special issue of C&G. and its complementary issue of PE&RS. as a testament to the vitality and interest in the application of geostatistical and geospatial techniques in remote sensing. We also see these special journal issues as the beginning of a fruitful. and hopefully long-term relationship, between American and British geographers and other researchers interested in geostatistical and geospatial techniques applied to remote sensing and other spatial data.

NASA's Geospatial Interoperability Office(GIO)Program

NASA Technical Reports Server (NTRS)

Weir, Patricia

2004-01-01

NASA produces vast amounts of information about the Earth from satellites, supercomputer models, and other sources. These data are most useful when made easily accessible to NASA researchers and scientists, to NASA's partner Federal Agencies, and to society as a whole. A NASA goal is to apply its data for knowledge gain, decision support and understanding of Earth, and other planetary systems. The NASA Earth Science Enterprise (ESE) Geospatial Interoperability Office (GIO) Program leads the development, promotion and implementation of information technology standards that accelerate and expand the delivery of NASA's Earth system science research through integrated systems solutions. Our overarching goal is to make it easy for decision-makers, scientists and citizens to use NASA's science information. NASA's Federal partners currently participate with NASA and one another in the development and implementation of geospatial standards to ensure the most efficient and effective access to one another's data. Through the GIO, NASA participates with its Federal partners in implementing interoperability standards in support of E-Gov and the associated President's Management Agenda initiatives by collaborating on standards development. Through partnerships with government, private industry, education and communities the GIO works towards enhancing the ESE Applications Division in the area of National Applications and decision support systems. The GIO provides geospatial standards leadership within NASA, represents NASA on the Federal Geographic Data Committee (FGDC) Coordination Working Group and chairs the FGDC's Geospatial Applications and Interoperability Working Group (GAI) and supports development and implementation efforts such as Earth Science Gateway (ESG), Space Time Tool Kit and Web Map Services (WMS) Global Mosaic. The GIO supports NASA in the collection and dissemination of geospatial interoperability standards needs and progress throughout the agency including areas such as ESE Applications, the SEEDS Working Groups, the Facilities Engineering Division (Code JX) and NASA's Chief Information Offices (CIO). With these agency level requirements GIO leads, brokers and facilitates efforts to, develop, implement, influence and fully participate in standards development internationally, federally and locally. The GIO also represents NASA in the OpenGIS Consortium and ISO TC211. The OGC has made considerable progress in regards to relations with other open standards bodies; namely ISO, W3C and OASIS. ISO TC211 is the Geographic and Geomatics Information technical committee that works towards standardization in the field of digital geographic information. The GIO focuses on seamless access to data, applications of data, and enabling technologies furthering the interoperability of distributed data. Through teaming within the Applications Directorate and partnerships with government, private industry, education and communities, GIO works towards the data application goals of NASA, the ESE Applications Directorate, and our Federal partners by managing projects in four categories: Geospatial Standards and Leadership, Geospatial One Stop, Standards Development and Implementation, and National and NASA Activities.

International Maps | Geospatial Data Science | NREL

Science.gov Websites

International Maps International Maps This map collection provides examples of how geographic information system modeling is used in international resource analysis. The images below are samples of

Renewable Energy Deployment in Colorado and the West: Extended Policy Sensitivities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrows, Clayton P.; Stoll, Brady; Mooney, Meghan E.

The Resource Planning Model is a capacity expansion model designed for a regional power system, such as a utility service territory, state, or balancing authority. We apply a geospatial analysis to Resource Planning Model renewable energy capacity expansion results to understand the likelihood of renewable development on various lands within Colorado.

Variable population exposure and distributed travel speeds in least-cost tsunami evacuation modelling

NASA Astrophysics Data System (ADS)

Fraser, S. A.; Wood, N. J.; Johnston, D. M.; Leonard, G. S.; Greening, P. D.; Rossetto, T.

2014-11-01

Evacuation of the population from a tsunami hazard zone is vital to reduce life-loss due to inundation. Geospatial least-cost distance modelling provides one approach to assessing tsunami evacuation potential. Previous models have generally used two static exposure scenarios and fixed travel speeds to represent population movement. Some analyses have assumed immediate departure or a common evacuation departure time for all exposed population. Here, a method is proposed to incorporate time-variable exposure, distributed travel speeds, and uncertain evacuation departure time into an existing anisotropic least-cost path distance framework. The method is demonstrated for hypothetical local-source tsunami evacuation in Napier City, Hawke's Bay, New Zealand. There is significant diurnal variation in pedestrian evacuation potential at the suburb level, although the total number of people unable to evacuate is stable across all scenarios. Whilst some fixed travel speeds approximate a distributed speed approach, others may overestimate evacuation potential. The impact of evacuation departure time is a significant contributor to total evacuation time. This method improves least-cost modelling of evacuation dynamics for evacuation planning, casualty modelling, and development of emergency response training scenarios. However, it requires detailed exposure data, which may preclude its use in many situations.

Variable population exposure and distributed travel speeds in least-cost tsunami evacuation modelling

USGS Publications Warehouse

Fraser, Stuart A.; Wood, Nathan J.; Johnston, David A.; Leonard, Graham S.; Greening, Paul D.; Rossetto, Tiziana

2014-01-01

Evacuation of the population from a tsunami hazard zone is vital to reduce life-loss due to inundation. Geospatial least-cost distance modelling provides one approach to assessing tsunami evacuation potential. Previous models have generally used two static exposure scenarios and fixed travel speeds to represent population movement. Some analyses have assumed immediate departure or a common evacuation departure time for all exposed population. Here, a method is proposed to incorporate time-variable exposure, distributed travel speeds, and uncertain evacuation departure time into an existing anisotropic least-cost path distance framework. The method is demonstrated for hypothetical local-source tsunami evacuation in Napier City, Hawke's Bay, New Zealand. There is significant diurnal variation in pedestrian evacuation potential at the suburb level, although the total number of people unable to evacuate is stable across all scenarios. Whilst some fixed travel speeds approximate a distributed speed approach, others may overestimate evacuation potential. The impact of evacuation departure time is a significant contributor to total evacuation time. This method improves least-cost modelling of evacuation dynamics for evacuation planning, casualty modelling, and development of emergency response training scenarios. However, it requires detailed exposure data, which may preclude its use in many situations.

Adverse Impact of Electromagnetic Radiation on Urban Environment and Natural Resources using Optical Sensors

NASA Astrophysics Data System (ADS)

Kumar, Pawan; Katiyar, Swati; Rani, Meenu

2016-07-01

We are living in the age of a rapidly growing population and changing environmental conditions with an advance technical capacity.This has resulted in wide spread land cover change. One of the main causes for increasing urban heat is that more than half of the world's population lives in a rapidly growing urbanized environment. Satellite data can be highly useful to map change in land cover and other environmental phenomena with the passage of time. Among several human-induced environmental and urban thermal problems are reported to be negatively affecting urban residents in many ways. The built-up structures in urbanized areas considerably alter land cover thereby affecting thermal energy flow which leads to development of elevated surface and air temperature. The phenomenon Urban Heat Island implies 'island' of high temperature in cities, surrounded by relatively lower temperature in rural areas. The UHI for the temporal period is estimated using geospatial techniques which are then utilized for the impact assessment on climate of the surrounding regions and how it reduce the sustainability of the natural resources like air, vegetation. The present paper describes the methodology and resolution dynamic urban heat island change on climate using the geospatial approach. NDVI were generated using day time LANDSAT ETM+ image of 1990, 2000 and 2013. Temperature of various land use and land cover categories was estimated. Keywords: NDVI, Surface temperature, Dynamic changes.

78 FR 32635 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-31

...; System of Records AGENCY: National Geospatial-Intelligence Agency, DoD. ACTION: Notice to Add a New System of Records. SUMMARY: The National Geospatial-Intelligence Agency is establishing a new system of... information. FOR FURTHER INFORMATION CONTACT: National Geospatial-Intelligence Agency [[Page 32636

78 FR 35606 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-13

...; System of Records AGENCY: National Geospatial-Intelligence Agency, DoD. ACTION: Notice to alter a System of Records. SUMMARY: The National Geospatial-Intelligence Agency is altering a system of records in.... FOR FURTHER INFORMATION CONTACT: National Geospatial-Intelligence Agency (NGA), ATTN: Security...

Distributed Research Center for Analysis of Regional Climatic Changes and Their Impacts on Environment

NASA Astrophysics Data System (ADS)

Shiklomanov, A. I.; Okladnikov, I.; Gordov, E. P.; Proussevitch, A. A.; Titov, A. G.

2016-12-01

Presented is a collaborative project carrying out by joint team of researchers from the Institute of Monitoring of Climatic and Ecological Systems, Russia and Earth Systems Research Center, University of New Hampshire, USA. Its main objective is development of a hardware and software prototype of Distributed Research Center (DRC) for monitoring and projecting of regional climatic and and their impacts on the environment over the Northern extratropical areas. In the framework of the project new approaches to "cloud" processing and analysis of large geospatial datasets (big geospatial data) are being developed. It will be deployed on technical platforms of both institutions and applied in research of climate change and its consequences. Datasets available at NCEI and IMCES include multidimensional arrays of climatic, environmental, demographic, and socio-economic characteristics. The project is aimed at solving several major research and engineering tasks: 1) structure analysis of huge heterogeneous climate and environmental geospatial datasets used in the project, their preprocessing and unification; 2) development of a new distributed storage and processing model based on a "shared nothing" paradigm; 3) development of a dedicated database of metadata describing geospatial datasets used in the project; 4) development of a dedicated geoportal and a high-end graphical frontend providing intuitive user interface, internet-accessible online tools for analysis of geospatial data and web services for interoperability with other geoprocessing software packages. DRC will operate as a single access point to distributed archives of spatial data and online tools for their processing. Flexible modular computational engine running verified data processing routines will provide solid results of geospatial data analysis. "Cloud" data analysis and visualization approach will guarantee access to the DRC online tools and data from all over the world. Additionally, exporting of data processing results through WMS and WFS services will be used to provide their interoperability. Financial support of this activity by the RF Ministry of Education and Science under Agreement 14.613.21.0037 (RFMEFI61315X0037) and by the Iola Hubbard Climate Change Endowment is acknowledged.

SWOT analysis on National Common Geospatial Information Service Platform of China

NASA Astrophysics Data System (ADS)

Zheng, Xinyan; He, Biao

2010-11-01

Currently, the trend of International Surveying and Mapping is shifting from map production to integrated service of geospatial information, such as GOS of U.S. etc. Under this circumstance, the Surveying and Mapping of China is inevitably shifting from 4D product service to NCGISPC (National Common Geospatial Information Service Platform of China)-centered service. Although State Bureau of Surveying and Mapping of China has already provided a great quantity of geospatial information service to various lines of business, such as emergency and disaster management, transportation, water resource, agriculture etc. The shortcomings of the traditional service mode are more and more obvious, due to the highly emerging requirement of e-government construction, the remarkable development of IT technology and emerging online geospatial service demands of various lines of business. NCGISPC, which aimed to provide multiple authoritative online one-stop geospatial information service and API for further development to government, business and public, is now the strategic core of SBSM (State Bureau of Surveying and Mapping of China). This paper focuses on the paradigm shift that NCGISPC brings up by using SWOT (Strength, Weakness, Opportunity and Threat) analysis, compared to the service mode that based on 4D product. Though NCGISPC is still at its early stage, it represents the future service mode of geospatial information of China, and surely will have great impact not only on the construction of digital China, but also on the way that everyone uses geospatial information service.

A simplified regional-scale electromagnetic induction - Salinity calibration model using ANOCOVA modeling techniques

USDA-ARS?s Scientific Manuscript database

Directed soil sampling based on geospatial measurements of apparent soil electrical conductivity (ECa) is a potential means of characterizing the spatial variability of any soil property that influences ECa including soil salinity, water content, texture, bulk density, organic matter, and cation exc...

AN INTEGRATED LANDSCAPE AND HYDROLOGICAL ASSESSMENT FOR THE YANTRA RIVER BASIN, BULGARIA

EPA Science Inventory

Geospatial data and relationships derived there from are the cornerstone of the landscape sciences. This information is also of fundamental importance in deriving parameter inputs to watershed hydrologic models.

Updated logistic regression equations for the calculation of post-fire debris-flow likelihood in the western United States

USGS Publications Warehouse

Staley, Dennis M.; Negri, Jacquelyn A.; Kean, Jason W.; Laber, Jayme L.; Tillery, Anne C.; Youberg, Ann M.

2016-06-30

Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can generate dangerous flash floods and debris flows. To reduce public exposure to hazard, the U.S. Geological Survey produces post-fire debris-flow hazard assessments for select fires in the western United States. We use publicly available geospatial data describing basin morphology, burn severity, soil properties, and rainfall characteristics to estimate the statistical likelihood that debris flows will occur in response to a storm of a given rainfall intensity. Using an empirical database and refined geospatial analysis methods, we defined new equations for the prediction of debris-flow likelihood using logistic regression methods. We showed that the new logistic regression model outperformed previous models used to predict debris-flow likelihood.

The PANTHER User Experience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coram, Jamie L.; Morrow, James D.; Perkins, David Nikolaus

2015-09-01

This document describes the PANTHER R&D Application, a proof-of-concept user interface application developed under the PANTHER Grand Challenge LDRD. The purpose of the application is to explore interaction models for graph analytics, drive algorithmic improvements from an end-user point of view, and support demonstration of PANTHER technologies to potential customers. The R&D Application implements a graph-centric interaction model that exposes analysts to the algorithms contained within the GeoGraphy graph analytics library. Users define geospatial-temporal semantic graph queries by constructing search templates based on nodes, edges, and the constraints among them. Users then analyze the results of the queries using bothmore » geo-spatial and temporal visualizations. Development of this application has made user experience an explicit driver for project and algorithmic level decisions that will affect how analysts one day make use of PANTHER technologies.« less

River predisposition to ice jams: a simplified geospatial model

NASA Astrophysics Data System (ADS)

De Munck, Stéphane; Gauthier, Yves; Bernier, Monique; Chokmani, Karem; Légaré, Serge

2017-07-01

Floods resulting from river ice jams pose a great risk to many riverside municipalities in Canada. The location of an ice jam is mainly influenced by channel morphology. The goal of this work was therefore to develop a simplified geospatial model to estimate the predisposition of a river channel to ice jams. Rather than predicting the timing of river ice breakup, the main question here was to predict where the broken ice is susceptible to jam based on the river's geomorphological characteristics. Thus, six parameters referred to potential causes for ice jams in the literature were initially selected: presence of an island, narrowing of the channel, high sinuosity, presence of a bridge, confluence of rivers, and slope break. A GIS-based tool was used to generate the aforementioned factors over regular-spaced segments along the entire channel using available geospatial data. An ice jam predisposition index (IJPI) was calculated by combining the weighted optimal factors. Three Canadian rivers (province of Québec) were chosen as test sites. The resulting maps were assessed from historical observations and local knowledge. Results show that 77 % of the observed ice jam sites on record occurred in river sections that the model considered as having high or medium predisposition. This leaves 23 % of false negative errors (missed occurrence). Between 7 and 11 % of the highly predisposed river sections did not have an ice jam on record (false-positive cases). Results, limitations, and potential improvements are discussed.

Geospatial modeling approach to monument construction using Michigan from A.D. 1000-1600 as a case study.

PubMed

Howey, Meghan C L; Palace, Michael W; McMichael, Crystal H

2016-07-05

Building monuments was one way that past societies reconfigured their landscapes in response to shifting social and ecological factors. Understanding the connections between those factors and monument construction is critical, especially when multiple types of monuments were constructed across the same landscape. Geospatial technologies enable past cultural activities and environmental variables to be examined together at large scales. Many geospatial modeling approaches, however, are not designed for presence-only (occurrence) data, which can be limiting given that many archaeological site records are presence only. We use maximum entropy modeling (MaxEnt), which works with presence-only data, to predict the distribution of monuments across large landscapes, and we analyze MaxEnt output to quantify the contributions of spatioenvironmental variables to predicted distributions. We apply our approach to co-occurring Late Precontact (ca. A.D. 1000-1600) monuments in Michigan: (i) mounds and (ii) earthwork enclosures. Many of these features have been destroyed by modern development, and therefore, we conducted archival research to develop our monument occurrence database. We modeled each monument type separately using the same input variables. Analyzing variable contribution to MaxEnt output, we show that mound and enclosure landscape suitability was driven by contrasting variables. Proximity to inland lakes was key to mound placement, and proximity to rivers was key to sacred enclosures. This juxtaposition suggests that mounds met local needs for resource procurement success, whereas enclosures filled broader regional needs for intergroup exchange and shared ritual. Our study shows how MaxEnt can be used to develop sophisticated models of past cultural processes, including monument building, with imperfect, limited, presence-only data.

US EPA GLOBAL POSITIONING SYSTEMS - TECHNICAL IMPLEMENTATION GUIDANCE

EPA Science Inventory

The U.S. EPA Geospatial Quality Council (GQC) was formed in 1998 to provide Quality Assurance guidance for the development, use, and products of geospatial activities and research. The long-term goals of the GQC are expressed in a living document, currently the EPA Geospatial Qua...

Integration of Geospatial Science in Teacher Education

ERIC Educational Resources Information Center

Hauselt, Peggy; Helzer, Jennifer

2012-01-01

One of the primary missions of our university is to train future primary and secondary teachers. Geospatial sciences, including GIS, have long been excluded from teacher education curriculum. This article explains the curriculum revisions undertaken to increase the geospatial technology education of future teachers. A general education class…

75 FR 43497 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-26

...; System of Records AGENCY: National Geospatial-Intelligence Agency (NGA), DoD. ACTION: Notice to add a system of records. SUMMARY: The National Geospatial-Intelligence Agency (NGA) proposes to add a system of...-3808. SUPPLEMENTARY INFORMATION: The National Geospatial-Intelligence Agency notices for systems of...

Indigenous knowledges driving technological innovation

Treesearch

Lilian Alessa; Carlos Andrade; Phil Cash Cash; Christian P. Giardina; Matt Hamabata; Craig Hammer; Kai Henifin; Lee Joachim; Jay T. Johnson; Kekuhi Kealiikanakaoleohaililani; Deanna Kingston; Andrew Kliskey; Renee Pualani Louis; Amanda Lynch; Daryn McKenny; Chels Marshall; Mere Roberts; Taupouri Tangaro; Jyl Wheaton-Abraham; Everett Wingert

2011-01-01

This policy brief explores the use and expands the conversation on the ability of geospatial technologies to represent Indigenous cultural knowledge. Indigenous peoples' use of geospatial technologies has already proven to be a critical step for protecting tribal self-determination. However, the ontological frameworks and techniques of Western geospatial...

Modelling and mapping tick dynamics using volunteered observations.

PubMed

Garcia-Martí, Irene; Zurita-Milla, Raúl; van Vliet, Arnold J H; Takken, Willem

2017-11-14

Tick populations and tick-borne infections have steadily increased since the mid-1990s posing an ever-increasing risk to public health. Yet, modelling tick dynamics remains challenging because of the lack of data and knowledge on this complex phenomenon. Here we present an approach to model and map tick dynamics using volunteered data. This approach is illustrated with 9 years of data collected by a group of trained volunteers who sampled active questing ticks (AQT) on a monthly basis and for 15 locations in the Netherlands. We aimed at finding the main environmental drivers of AQT at multiple time-scales, and to devise daily AQT maps at the national level for 2014. Tick dynamics is a complex ecological problem driven by biotic (e.g. pathogens, wildlife, humans) and abiotic (e.g. weather, landscape) factors. We enriched the volunteered AQT collection with six types of weather variables (aggregated at 11 temporal scales), three types of satellite-derived vegetation indices, land cover, and mast years. Then, we applied a feature engineering process to derive a set of 101 features to characterize the conditions that yielded a particular count of AQT on a date and location. To devise models predicting the AQT, we use a time-aware Random Forest regression method, which is suitable to find non-linear relationships in complex ecological problems, and provides an estimation of the most important features to predict the AQT. We trained a model capable of fitting AQT with reduced statistical metrics. The multi-temporal study on the feature importance indicates that variables linked to water levels in the atmosphere (i.e. evapotranspiration, relative humidity) consistently showed a higher explanatory power than previous works using temperature. As a product of this study, we are able of mapping daily tick dynamics at the national level. This study paves the way towards the design of new applications in the fields of environmental research, nature management, and public health. It also illustrates how Citizen Science initiatives produce geospatial data collections that can support scientific analysis, thus enabling the monitoring of complex environmental phenomena.

Mapping the Future Today: The Community College of Baltimore County Geospatial Applications Program

ERIC Educational Resources Information Center

Jeffrey, Scott; Alvarez, Jaime

2010-01-01

The Geospatial Applications Program at the Community College of Baltimore County (CCBC), located five miles west of downtown Baltimore, Maryland, provides comprehensive instruction in geographic information systems (GIS), remote sensing and global positioning systems (GPS). Geospatial techniques, which include computer-based mapping and remote…

The Efficacy of Educative Curriculum Materials to Support Geospatial Science Pedagogical Content Knowledge

ERIC Educational Resources Information Center

Bodzin, Alec; Peffer, Tamara; Kulo, Violet

2012-01-01

Teaching and learning about geospatial aspects of energy resource issues requires that science teachers apply effective science pedagogical approaches to implement geospatial technologies into classroom instruction. To address this need, we designed educative curriculum materials as an integral part of a comprehensive middle school energy…

Strategizing Teacher Professional Development for Classroom Uses of Geospatial Data and Tools

ERIC Educational Resources Information Center

Zalles, Daniel R.; Manitakos, James

2016-01-01

Studying Topography, Orographic Rainfall, and Ecosystems with Geospatial Information Technology (STORE), a 4.5-year National Science Foundation funded project, explored the strategies that stimulate teacher commitment to the project's driving innovation: having students use geospatial information technology (GIT) to learn about weather, climate,…

Fostering 21st Century Learning with Geospatial Technologies

ERIC Educational Resources Information Center

Hagevik, Rita A.

2011-01-01

Global positioning systems (GPS) receivers and other geospatial tools can help teachers create engaging, hands-on activities in all content areas. This article provides a rationale for using geospatial technologies in the middle grades and describes classroom-tested activities in English language arts, science, mathematics, and social studies.…

EPA GEOSPATIAL QUALITY COUNCIL STRATEGY PLAN FY-02

EPA Science Inventory

The EPA Geospatial Quality Council (GQC), previously known as the EPA GIS-QA Team - EPA/600/R-00/009, was created to fill the gap between the EPA Quality Assurance (QA) and Geospatial communities. All EPA Offices and Regions were invited to participate. Currently, the EPA...

Mapping and monitoring potato cropping systems in Maine: geospatial methods and land use assessments

USDA-ARS?s Scientific Manuscript database

Geospatial frameworks and GIS-based approaches were used to assess current cropping practices in potato production systems in Maine. Results from the geospatial integration of remotely-sensed cropland layers (2008-2011) and soil datasets for Maine revealed a four-year potato systems footprint estima...

The Virginia Geocoin Adventure: An Experiential Geospatial Learning Activity

ERIC Educational Resources Information Center

Johnson, Laura; McGee, John; Campbell, James; Hays, Amy

2013-01-01

Geospatial technologies have become increasingly prevalent across our society. Educators at all levels have expressed a need for additional resources that can be easily adopted to support geospatial literacy and state standards of learning, while enhancing the overall learning experience. The Virginia Geocoin Adventure supports the needs of 4-H…

Geospatial Technology

ERIC Educational Resources Information Center

Reed, Philip A.; Ritz, John

2004-01-01

Geospatial technology refers to a system that is used to acquire, store, analyze, and output data in two or three dimensions. This data is referenced to the earth by some type of coordinate system, such as a map projection. Geospatial systems include thematic mapping, the Global Positioning System (GPS), remote sensing (RS), telemetry, and…

lawn: An R client for the Turf JavaScript Library for Geospatial Analysis

EPA Science Inventory

lawn is an R package to provide access to the geospatial analysis capabilities in the Turf javascript library. Turf expects data in GeoJSON format. Given that many datasets are now available natively in GeoJSON providing an easier method for conducting geospatial analyses on thes...

A Spatial Data Infrastructure to Share Earth and Space Science Data

NASA Astrophysics Data System (ADS)

Nativi, S.; Mazzetti, P.; Bigagli, L.; Cuomo, V.

2006-05-01

Spatial Data Infrastructure:SDI (also known as Geospatial Data Infrastructure) is fundamentally a mechanism to facilitate the sharing and exchange of geospatial data. SDI is a scheme necessary for the effective collection, management, access, delivery and utilization of geospatial data; it is important for: objective decision making and sound land based policy, support economic development and encourage socially and environmentally sustainable development. As far as data model and semantics are concerned, a valuable and effective SDI should be able to cross the boundaries between the Geographic Information System/Science (GIS) and Earth and Space Science (ESS) communities. Hence, SDI should be able to discover, access and share information and data produced and managed by both GIS and ESS communities, in an integrated way. In other terms, SDI must be built on a conceptual and technological framework which abstracts the nature and structure of shared dataset: feature-based data or Imagery, Gridded and Coverage Data (IGCD). ISO TC211 and the Open Geospatial Consortium provided important artifacts to build up this framework. In particular, the OGC Web Services (OWS) initiatives and several Interoperability Experiment (e.g. the GALEON IE) are extremely useful for this purpose. We present a SDI solution which is able to manage both GIS and ESS datasets. It is based on OWS and other well-accepted or promising technologies, such as: UNIDATA netCDF and CDM, ncML and ncML-GML. Moreover, it uses a specific technology to implement a distributed and federated system of catalogues: the GI-Cat. This technology performs data model mediation and protocol adaptation tasks. It is used to work out a metadata clearinghouse service, implementing a common (federal) catalogue model which is based on the ISO 19115 core metadata for geo-dataset. Nevertheless, other well- accepted or standard catalogue data models can be easily implemented as common view (e.g. OGC CS-W, the next coming INSPIRE discovery metadata model, etc.). The proposed solution has been conceived and developed for building up the "Lucan SDI". This is the SDI of the Italian Basilicata Region. It aims to connect the following data providers and users: the National River Basin Authority of Basilicata, the Regional Environmental Agency, the Land Management & Cadastre Regional Authorities, the Prefecture, the Regional Civil Protection Centers, the National Research Council Institutes in Basilicata, the Academia, several SMEs.

Model My Watershed - A Robust Online App to Enable Citizen Scientists to Model Watershed Hydrology and Water Quality at Regulatory-Level Standards

NASA Astrophysics Data System (ADS)

Daniels, M.; Kerlin, S.; Arscott, D.

2017-12-01

Citizen-based watershed monitoring has historically lacked scientific rigor and geographic scope due to limitation in access to watershed-level data and the high level skills and resources required to adequately model watershed dynamics. Public access to watershed information is currently routed through a variety of governmental data portals and often requires advanced geospatial skills to collect and present in useable forms. At the same time, tremendous financial resources are being invested in watershed restoration and management efforts, and often these resources pass through local stakeholder groups such as conservation NGO, watershed interest groups, and local municipalities without extensive hydrologic knowledge or access to sophisticated modeling resources. Even governmental agencies struggle to understand how to best steer or prioritize restoration investments. A new app, Model My Watershed, was built to improve access to watershed data and modeling capabilities in a fast, accessible, free web-app format. Working across the contiguous United States, the Model My Watershed app provides land cover, soils, aerial imagery and relief, watershed delineation, and stream network delineation. Users can model watersheds or areas of interest and create management scenarios to evaluate implementation of land cover changes and best management practice implementation with both hydrologic and water quality outputs that meet TMDL regulatory standards.

Factors affecting species distribution predictions: A simulation modeling experiment

Treesearch

Gordon C. Reese; Kenneth R. Wilson; Jennifer A. Hoeting; Curtis H. Flather

2005-01-01

Geospatial species sample data (e.g., records with location information from natural history museums or annual surveys) are rarely collected optimally, yet are increasingly used for decisions concerning our biological heritage. Using computer simulations, we examined factors that could affect the performance of autologistic regression (ALR) models that predict species...

Geospatial application of the Water Erosion Prediction Project (WEPP) model

USDA-ARS?s Scientific Manuscript database

At the hillslope profile and/or field scale, a simple Windows graphical user interface (GUI) is available to easily specify the slope, soil, and management inputs for application of the USDA Water Erosion Prediction Project (WEPP) model. Likewise, basic small watershed configurations of a few hillsl...

DOTAGWA: A CASE STUDY IN WEB-BASED ARCHITECTURES FOR CONNECTING SURFACE WATER MODELS TO SPATIALLY ENABLED WEB APPLICATIONS

EPA Science Inventory

The Automated Geospatial Watershed Assessment (AGWA) tool is a desktop application that uses widely available standardized spatial datasets to derive inputs for multi-scale hydrologic models (Miller et al., 2007). The required data sets include topography (DEM data), soils, clima...

MERGANSER - An Empirical Model to Predict Fish and Loon Mercury in New England Lakes

EPA Science Inventory

MERGANSER (MERcury Geo-spatial AssessmeNtS for the New England Region) is an empirical least-squares multiple regression model using mercury (Hg) deposition and readily obtainable lake and watershed features to predict fish (fillet) and common loon (blood) Hg in New England lakes...

Integrating Geo-Spatial Data for Regional Landslide Susceptibility Modeling in Consideration of Run-Out Signature

NASA Astrophysics Data System (ADS)

Lai, J.-S.; Tsai, F.; Chiang, S.-H.

2016-06-01

This study implements a data mining-based algorithm, the random forests classifier, with geo-spatial data to construct a regional and rainfall-induced landslide susceptibility model. The developed model also takes account of landslide regions (source, non-occurrence and run-out signatures) from the original landslide inventory in order to increase the reliability of the susceptibility modelling. A total of ten causative factors were collected and used in this study, including aspect, curvature, elevation, slope, faults, geology, NDVI (Normalized Difference Vegetation Index), rivers, roads and soil data. Consequently, this study transforms the landslide inventory and vector-based causative factors into the pixel-based format in order to overlay with other raster data for constructing the random forests based model. This study also uses original and edited topographic data in the analysis to understand their impacts to the susceptibility modeling. Experimental results demonstrate that after identifying the run-out signatures, the overall accuracy and Kappa coefficient have been reached to be become more than 85 % and 0.8, respectively. In addition, correcting unreasonable topographic feature of the digital terrain model also produces more reliable modelling results.

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal

Atmospheric Science Data Center

2018-03-01

The Prediction Of Worldwide Energy Resource (POWER) Project facilitates access to NASA's satellite and modeling analysis for Renewable Energy, Sustainable Buildings and Agroclimatology applications.  A   new ...

The influence of multi-season imagery on models of canopy cover: A case study

Treesearch

John W. Coulston; Dennis M. Jacobs; Chris R. King; Ivey C. Elmore

2013-01-01

Quantifying tree canopy cover in a spatially explicit fashion is important for broad-scale monitoring of ecosystems and for management of natural resources. Researchers have developed empirical models of tree canopy cover to produce geospatial products. For subpixel models, percent tree canopy cover estimates (derived from fine-scale imagery) serve as the response...

Modeling Alaska boreal forests with a controlled trend surface approach

Treesearch

Mo Zhou; Jingjing Liang

2012-01-01

An approach of Controlled Trend Surface was proposed to simultaneously take into consideration large-scale spatial trends and nonspatial effects. A geospatial model of the Alaska boreal forest was developed from 446 permanent sample plots, which addressed large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of...

Remote sensing applied to resource management

Treesearch

Henry M. Lachowski

1998-01-01

Effective management of forest resources requires access to current and consistent geospatial information that can be shared by resource managers and the public. Geospatial information describing our land and natural resources comes from many sources and is most effective when stored in a geospatial database and used in a geographic information system (GIS). The...

The Impact of a Geospatial Technology-Supported Energy Curriculum on Middle School Students' Science Achievement

ERIC Educational Resources Information Center

Kulo, Violet; Bodzin, Alec

2013-01-01

Geospatial technologies are increasingly being integrated in science classrooms to foster learning. This study examined whether a Web-enhanced science inquiry curriculum supported by geospatial technologies promoted urban middle school students' understanding of energy concepts. The participants included one science teacher and 108 eighth-grade…

Introduction to the Complex Geospatial Web in Geographical Education

ERIC Educational Resources Information Center

Papadimitriou, Fivos

2010-01-01

The Geospatial Web is emerging in the geographical education landscape in all its complexity. How will geographers and educators react? What are the most important facets of this development? After reviewing the possible impacts on geographical education, it can be conjectured that the Geospatial Web will eventually replace the usual geographical…

Examining the Enactment of Web GIS on Students' Geospatial Thinking and Reasoning and Tectonics Understandings

ERIC Educational Resources Information Center

Bodzin, Alec M.; Fu, Qiong; Bressler, Denise; Vallera, Farah L.

2015-01-01

Geospatially enabled learning technologies may enhance Earth science learning by placing emphasis on geographic space, visualization, scale, representation, and geospatial thinking and reasoning (GTR) skills. This study examined if and how a series of Web geographic information system investigations that the researchers developed improved urban…

The Impact of Professional Development in Natural Resource Investigations Using Geospatial Technologies

ERIC Educational Resources Information Center

Hanley, Carol D.; Davis, Hilarie B.; Davey, Bradford T.

2012-01-01

As use of geospatial technologies has increased in the workplace, so has interest in using these technologies in the K-12 classroom. Prior research has identified several reasons for using geospatial technologies in the classroom, such as developing spatial thinking, supporting local investigations, analyzing changes in the environment, and…

The Sky's the Limit: Integrating Geospatial Tools with Pre-College Youth Education

ERIC Educational Resources Information Center

McGee, John; Kirwan, Jeff

2010-01-01

Geospatial tools, which include global positioning systems (GPS), geographic information systems (GIS), and remote sensing, are increasingly driving a variety of applications. Local governments and private industry are embracing these tools, and the public is beginning to demand geospatial services. The U.S. Department of Labor (DOL) reported that…

Geospatial Services in Special Libraries: A Needs Assessment Perspective

ERIC Educational Resources Information Center

Barnes, Ilana

2013-01-01

Once limited to geographers and mapmakers, Geographic Information Systems (GIS) has taken a growing central role in information management and visualization. Geospatial services run a gamut of different products and services from Google maps to ArcGIS servers to Mobile development. Geospatial services are not new. Libraries have been writing about…

Analytical Hierarchy Process modeling for malaria risk zones in Vadodara district, Gujarat

NASA Astrophysics Data System (ADS)

Bhatt, B.; Joshi, J. P.

2014-11-01

Malaria epidemic is one of the complex spatial problems around the world. According to WHO, an estimated 6, 27, 000 deaths occurred due to malaria in 2012. In many developing nations with diverse ecological regions, it is still a large cause of human mortality. Owing to the incompleteness of epidemiological data and their spatial origin, the quantification of disease incidence burdening basic public health planning is a major constrain especially in developing countries. The present study focuses on the integrated Geospatial and Multi-Criteria Evaluation (AHP) technique to determine malaria risk zones. The study is conducted in Vadodara district, including 12 Taluka among which 4 Taluka are predominantly tribal. The influence of climatic and physical environmental factors viz., rainfall, hydro geomorphology; drainage, elevation, and land cover are used to score their share in the evaluation of malariogenic condition. This was synthesized on the basis of preference over each factor and the total weights of each data and data layer were computed and visualized. The district was divided into three viz., high, moderate and low risk zones .It was observed that a geographical area of 1885.2sq.km comprising 30.3% fall in high risk zone. The risk zones identified on the basis of these parameters and assigned weights shows a close resemblance with ground condition. As the API distribution for 2011overlaid corresponds to the risk zones identified. The study demonstrates the significance and prospect of integrating Geospatial tools and Analytical Hierarchy Process for malaria risk zones and dynamics of malaria transmission.

Using the Geospatial Web to Deliver and Teach Giscience Education Programs

NASA Astrophysics Data System (ADS)

Veenendaal, B.

2015-05-01

Geographic information science (GIScience) education has undergone enormous changes over the past years. One major factor influencing this change is the role of the geospatial web in GIScience. In addition to the use of the web for enabling and enhancing GIScience education, it is also used as the infrastructure for communicating and collaborating among geospatial data and users. The web becomes both the means and the content for a geospatial education program. However, the web does not replace the traditional face-to-face environment, but rather is a means to enhance it, expand it and enable an authentic and real world learning environment. This paper outlines the use of the web in both the delivery and content of the GIScience program at Curtin University. The teaching of the geospatial web, web and cloud based mapping, and geospatial web services are key components of the program, and the use of the web and online learning are important to deliver this program. Some examples of authentic and real world learning environments are provided including joint learning activities with partner universities.

Citing geospatial feature inventories with XML manifests

NASA Astrophysics Data System (ADS)

Bose, R.; McGarva, G.

2006-12-01

Today published scientific papers include a growing number of citations for online information sources that either complement or replace printed journals and books. We anticipate this same trend for cartographic citations used in the geosciences, following advances in web mapping and geographic feature-based services. Instead of using traditional libraries to resolve citations for print material, the geospatial citation life cycle will include requesting inventories of objects or geographic features from distributed geospatial data repositories. Using a case study from the UK Ordnance Survey MasterMap database, which is illustrative of geographic object-based products in general, we propose citing inventories of geographic objects using XML feature manifests. These manifests: (1) serve as a portable listing of sets of versioned features; (2) could be used as citations within the identification portion of an international geospatial metadata standard; (3) could be incorporated into geospatial data transfer formats such as GML; but (4) can be resolved only with comprehensive, curated repositories of current and historic data. This work has implications for any researcher who foresees the need to make or resolve references to online geospatial databases.

Mapping rice ecosystem dynamics and greenhouse gas emissions using multiscale imagery and biogeochemical models

NASA Astrophysics Data System (ADS)

Salas, W.; Torbick, N.

2017-12-01

Rice greenhouse gas (GHG) emissions in production hot spots have been mapped using multiscale satellite imagery and a processed-based biogeochemical model. The multiscale Synthetic Aperture Radar (SAR) and optical imagery were co-processed and fed into a machine leanring framework to map paddy attributes that are tuned using field observations and surveys. Geospatial maps of rice extent, crop calendar, hydroperiod, and cropping intensity were then used to parameterize the DeNitrification-DeComposition (DNDC) model to estimate emissions. Results, in the Red River Detla for example, show total methane emissions at 345.4 million kgCH4-C equivalent to 11.5 million tonnes CO2e (carbon dioxide equivalent). We further assessed the role of Alternative Wetting and Drying and the impact on GHG and yield across production hot spots with uncertainty estimates. The approach described in this research provides a framework for using SAR to derive maps of rice and landscape characteristics to drive process models like DNDC. These types of tools and approaches will support the next generation of Monitoring, Reporting, and Verification (MRV) to combat climate change and support ecosystem service markets.

Rethinking GIS Towards The Vision Of Smart Cities Through CityGML

NASA Astrophysics Data System (ADS)

Guney, C.

2016-10-01

Smart cities present a substantial growth opportunity in the coming years. The role of GIS in the smart city ecosystem is to integrate different data acquired by sensors in real time and provide better decisions, more efficiency and improved collaboration. Semantically enriched vision of GIS will help evolve smart cities into tomorrow's much smarter cities since geospatial/location data and applications may be recognized as a key ingredient of smart city vision. However, it is need for the Geospatial Information communities to debate on "Is 3D Web and mobile GIS technology ready for smart cities?" This research places an emphasis on the challenges of virtual 3D city models on the road to smarter cities.

Tsunami vertical-evacuation planning in the U.S. Pacific Northwest as a geospatial, multi-criteria decision problem

USGS Publications Warehouse

Wood, Nathan; Jones, Jeanne; Schelling, John; Schmidtlein, Mathew

2014-01-01

Tsunami vertical-evacuation (TVE) refuges can be effective risk-reduction options for coastal communities with local tsunami threats but no accessible high ground for evacuations. Deciding where to locate TVE refuges is a complex risk-management question, given the potential for conflicting stakeholder priorities and multiple, suitable sites. We use the coastal community of Ocean Shores (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, multi-criteria decision analysis for framing the locational problem of TVE siting. We demonstrate a mixed-methods approach that uses potential TVE sites identified at community workshops, geospatial analysis to model changes in pedestrian evacuation times for TVE options, and statistical analysis to develop metrics for comparing population tradeoffs and to examine influences in decision making. Results demonstrate that no one TVE site can save all at-risk individuals in the community and each site provides varying benefits to residents, employees, customers at local stores, tourists at public venues, children at schools, and other vulnerable populations. The benefit of some proposed sites varies depending on whether or not nearby bridges will be functioning after the preceding earthquake. Relative rankings of the TVE sites are fairly stable under various criteria-weighting scenarios but do vary considerably when comparing strategies to exclusively protect tourists or residents. The proposed geospatial framework can serve as an analytical foundation for future TVE siting discussions.

A method for examining the geospatial distribution of CO2 storage resources applied to the Pre-Punta Gorda Composite and Dollar Bay reservoirs of the South Florida Basin, U.S.A

USGS Publications Warehouse

Roberts-Ashby, Tina; Brandon N. Ashby,

2016-01-01

This paper demonstrates geospatial modification of the USGS methodology for assessing geologic CO2 storage resources, and was applied to the Pre-Punta Gorda Composite and Dollar Bay reservoirs of the South Florida Basin. The study provides detailed evaluation of porous intervals within these reservoirs and utilizes GIS to evaluate the potential spatial distribution of reservoir parameters and volume of CO2 that can be stored. This study also shows that incorporating spatial variation of parameters using detailed and robust datasets may improve estimates of storage resources when compared to applying uniform values across the study area derived from small datasets, like many assessment methodologies. Geospatially derived estimates of storage resources presented here (Pre-Punta Gorda Composite = 105,570 MtCO2; Dollar Bay = 24,760 MtCO2) were greater than previous assessments, which was largely attributed to the fact that detailed evaluation of these reservoirs resulted in higher estimates of porosity and net-porous thickness, and areas of high porosity and thick net-porous intervals were incorporated into the model, likely increasing the calculated volume of storage space available for CO2 sequestration. The geospatial method for evaluating CO2 storage resources also provides the ability to identify areas that potentially contain higher volumes of storage resources, as well as areas that might be less favorable.

Mobile Traffic Alert and Tourist Route Guidance System Design Using Geospatial Data

NASA Astrophysics Data System (ADS)

Bhattacharya, D.; Painho, M.; Mishra, S.; Gupta, A.

2017-09-01

The present study describes an integrated system for traffic data collection and alert warning. Geographical information based decision making related to traffic destinations and routes is proposed through the design. The system includes a geospatial database having profile relating to a user of a mobile device. The processing and understanding of scanned maps, other digital data input leads to route guidance. The system includes a server configured to receive traffic information relating to a route and location information relating to the mobile device. Server is configured to send a traffic alert to the mobile device when the traffic information and the location information indicate that the mobile device is traveling toward traffic congestion. Proposed system has geospatial and mobile data sets pertaining to Bangalore city in India. It is envisaged to be helpful for touristic purposes as a route guidance and alert relaying information system to tourists for proximity to sites worth seeing in a city they have entered into. The system is modular in architecture and the novelty lies in integration of different modules carrying different technologies for a complete traffic information system. Generic information processing and delivery system has been tested to be functional and speedy under test geospatial domains. In a restricted prototype model with geo-referenced route data required information has been delivered correctly over sustained trials to designated cell numbers, with average time frame of 27.5 seconds, maximum 50 and minimum 5 seconds. Traffic geo-data set trials testing is underway.

Establishment of the Northeast Coastal Watershed Geospatial Data Network (NECWGDN)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hannigan, Robyn

The goals of NECWGDN were to establish integrated geospatial databases that interfaced with existing open-source (water.html) environmental data server technologies (e.g., HydroDesktop) and included ecological and human data to enable evaluation, prediction, and adaptation in coastal environments to climate- and human-induced threats to the coastal marine resources within the Gulf of Maine. We have completed the development and testing of a "test bed" architecture that is compatible with HydroDesktop and have identified key metadata structures that will enable seamless integration and delivery of environmental, ecological, and human data as well as models to predict threats to end-users. Uniquely this databasemore » integrates point as well as model data and so offers capacities to end-users that are unique among databases. Future efforts will focus on the development of integrated environmental-human dimension models that can serve, in near real time, visualizations of threats to coastal resources and habitats.« less

Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology.

PubMed

VoPham, Trang; Hart, Jaime E; Laden, Francine; Chiang, Yao-Yi

2018-04-17

Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.

Introduction to geospatial semantics and technology workshop handbook

USGS Publications Warehouse

Varanka, Dalia E.

2012-01-01

The workshop is a tutorial on introductory geospatial semantics with hands-on exercises using standard Web browsers. The workshop is divided into two sections, general semantics on the Web and specific examples of geospatial semantics using data from The National Map of the U.S. Geological Survey and the Open Ontology Repository. The general semantics section includes information and access to publicly available semantic archives. The specific session includes information on geospatial semantics with access to semantically enhanced data for hydrography, transportation, boundaries, and names. The Open Ontology Repository offers open-source ontologies for public use.

Designing a two-rank acceptance sampling plan for quality inspection of geospatial data products

NASA Astrophysics Data System (ADS)

Tong, Xiaohua; Wang, Zhenhua; Xie, Huan; Liang, Dan; Jiang, Zuoqin; Li, Jinchao; Li, Jun

2011-10-01

To address the disadvantages of classical sampling plans designed for traditional industrial products, we originally propose a two-rank acceptance sampling plan (TRASP) for the inspection of geospatial data outputs based on the acceptance quality level (AQL). The first rank sampling plan is to inspect the lot consisting of map sheets, and the second is to inspect the lot consisting of features in an individual map sheet. The TRASP design is formulated as an optimization problem with respect to sample size and acceptance number, which covers two lot size cases. The first case is for a small lot size with nonconformities being modeled by a hypergeometric distribution function, and the second is for a larger lot size with nonconformities being modeled by a Poisson distribution function. The proposed TRASP is illustrated through two empirical case studies. Our analysis demonstrates that: (1) the proposed TRASP provides a general approach for quality inspection of geospatial data outputs consisting of non-uniform items and (2) the proposed acceptance sampling plan based on TRASP performs better than other classical sampling plans. It overcomes the drawbacks of percent sampling, i.e., "strictness for large lot size, toleration for small lot size," and those of a national standard used specifically for industrial outputs, i.e., "lots with different sizes corresponding to the same sampling plan."

THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT TOOL

EPA Science Inventory

A toolkit for distributed hydrologic modeling at multiple scales using a geographic information system is presented. This open-source, freely available software was developed through a collaborative endeavor involving two Universities and two government agencies. Called the Auto...

Geospatial wetlands impacts and mitigation forecasting models.

DOT National Transportation Integrated Search

2017-06-30

The South Carolina Department of Transportation (SCDOT) develops near (3-5 years) and long (15- 20 years) range plans for road widening, alignment, bridge replacement, and new road construction. Each road/bridge project may impact wetlands or streams...

The Value of Information - Accounting for a New Geospatial Paradigm

NASA Astrophysics Data System (ADS)

Pearlman, J.; Coote, A. M.

2014-12-01

A new frontier in consideration of socio-economic benefit is valuing information as an asset, often referred to as Infonomics. Conventional financial practice does not easily provide a mechanism for valuing information and yet clearly for many of the largest corporations, such as Google and Facebook, it is their principal asset. This is exacerbated for public sector organizations, as those that information-centric rather than information-enabled are relatively few - statistics, archiving and mapping agencies are perhaps the only examples - so it's not at the top of the agenda for Government. However, it is a hugely important issue when valuing Geospatial data and information. Geospatial data allows public institutions to operate, and facilitates the provision of essential services for emergency response and national defense. In this respect, geospatial data is strongly analogous to other types of public infrastructure, such as utilities and roads. The use of Geospatial data is widespread from companies in the transportation or construction sectors to individual planning for daily events. The categorization of geospatial data as infrastructure is critical to decisions related to investment in its management, maintenance and upgrade over time. Geospatial data depreciates in the same way that physical infrastructure depreciates. It needs to be maintained otherwise its functionality and value in use declines. We have coined the term geo-infonomics to encapsulate the concept. This presentation will develop the arguments around its importance and current avenues of research.

Understanding needs and barriers to using geospatial tools for public health policymaking in China.

PubMed

Kim, Dohyeong; Zhang, Yingyuan; Lee, Chang Kil

2018-05-07

Despite growing popularity of using geographical information systems and geospatial tools in public health fields, these tools are only rarely implemented in health policy management in China. This study examines the barriers that could prevent policy-makers from applying such tools to actual managerial processes related to public health problems that could be assisted by such approaches, e.g. evidence-based policy-making. A questionnaire-based survey of 127 health-related experts and other stakeholders in China revealed that there is a consensus on the needs and demands for the use of geospatial tools, which shows that there is a more unified opinion on the matter than so far reported. Respondents pointed to lack of communication and collaboration among stakeholders as the most significant barrier to the implementation of geospatial tools. Comparison of survey results to those emanating from a similar study in Bangladesh revealed different priorities concerning the use of geospatial tools between the two countries. In addition, the follow-up in-depth interviews highlighted the political culture specific to China as a critical barrier to adopting new tools in policy development. Other barriers included concerns over the limited awareness of the availability of advanced geospatial tools. Taken together, these findings can facilitate a better understanding among policy-makers and practitioners of the challenges and opportunities for widespread adoption and implementation of a geospatial approach to public health policy-making in China.

Brokered virtual hubs for facilitating access and use of geospatial Open Data

NASA Astrophysics Data System (ADS)

Mazzetti, Paolo; Latre, Miguel; Kamali, Nargess; Brumana, Raffaella; Braumann, Stefan; Nativi, Stefano

2016-04-01

Open Data is a major trend in current information technology scenario and it is often publicised as one of the pillars of the information society in the near future. In particular, geospatial Open Data have a huge potential also for Earth Sciences, through the enablement of innovative applications and services integrating heterogeneous information. However, open does not mean usable. As it was recognized at the very beginning of the Web revolution, many different degrees of openness exist: from simple sharing in a proprietary format to advanced sharing in standard formats and including semantic information. Therefore, to fully unleash the potential of geospatial Open Data, advanced infrastructures are needed to increase the data openness degree, enhancing their usability. In October 2014, the ENERGIC OD (European NEtwork for Redistributing Geospatial Information to user Communities - Open Data) project, funded by the European Union under the Competitiveness and Innovation framework Programme (CIP), has started. In response to the EU call, the general objective of the project is to "facilitate the use of open (freely available) geographic data from different sources for the creation of innovative applications and services through the creation of Virtual Hubs". The ENERGIC OD Virtual Hubs aim to facilitate the use of geospatial Open Data by lowering and possibly removing the main barriers which hampers geo-information (GI) usage by end-users and application developers. Data and services heterogeneity is recognized as one of the major barriers to Open Data (re-)use. It imposes end-users and developers to spend a lot of effort in accessing different infrastructures and harmonizing datasets. Such heterogeneity cannot be completely removed through the adoption of standard specifications for service interfaces, metadata and data models, since different infrastructures adopt different standards to answer to specific challenges and to address specific use-cases. Thus, beyond a certain extent, heterogeneity is irreducible especially in interdisciplinary contexts. ENERGIC OD Virtual Hubs address heterogeneity adopting a mediation and brokering approach: specific components (brokers) are dedicated to harmonize service interfaces, metadata and data models, enabling seamless discovery and access to heterogeneous infrastructures and datasets. As an innovation project, ENERGIC OD integrates several existing technologies to implement Virtual Hubs as single points of access to geospatial datasets provided by new or existing platforms and infrastructures, including INSPIRE-compliant systems and Copernicus services. A first version of the ENERGIC OD brokers has been implemented based on the GI-Suite Brokering Framework developed by CNR-IIA, and complemented with other tools under integration and development. It already enables mediated discovery and harmonized access to different geospatial Open Data sources. It is accessible by users as Software-as-a-Service through a browser. Moreover, open APIs and a Javascript library are available for application developers. Six ENERGIC OD Virtual Hubs have been currently deployed: one at regional level (Berlin metropolitan area) and five at national-level (in France, Germany, Italy, Poland and Spain). Each Virtual Hub manager decided the deployment strategy (local infrastructure or commercial Infrastructure-as-a-Service cloud), and the list of connected Open Data sources. The ENERGIC OD Virtual Hubs are under test and validation through the development of ten different mobile and Web applications.

Cyberspatial mechanics.

PubMed

Bayne, Jay S

2008-06-01

In support of a generalization of systems theory, this paper introduces a new approach in modeling complex distributed systems. It offers an analytic framework for describing the behavior of interactive cyberphysical systems (CPSs), which are networked stationary or mobile information systems responsible for the real-time governance of physical processes whose behaviors unfold in cyberspace. The framework is predicated on a cyberspace-time reference model comprising three spatial dimensions plus time. The spatial domains include geospatial, infospatial, and sociospatial references, the latter describing relationships among sovereign enterprises (rational agents) that choose voluntarily to organize and interoperate for individual and mutual benefit through geospatial (physical) and infospatial (logical) transactions. Of particular relevance to CPSs are notions of timeliness and value, particularly as they relate to the real-time governance of physical processes and engagements with other cooperating CPS. Our overarching interest, as with celestial mechanics, is in the formation and evolution of clusters of cyberspatial objects and the federated systems they form.

Delivery of Forecasted Atmospheric Ozone and Dust for the New Mexico Environmental Public Health Tracking System - An Open Source Geospatial Solution

NASA Astrophysics Data System (ADS)

Hudspeth, W. B.; Sanchez-Silva, R.; Cavner, J. A.

2010-12-01

New Mexico's Environmental Public Health Tracking System (EPHTS), funded by the Centers for Disease Control (CDC) Environmental Public Health Tracking Network (EPHTN), aims to improve health awareness and services by linking health effects data with levels and frequency of environmental exposure. As a public health decision-support system, EPHTS systems include: state-of-the-art statistical analysis tools; geospatial visualization tools; data discovery, extraction, and delivery tools; and environmental/public health linkage information. As part of its mandate, EPHTS issues public health advisories and forecasts of environmental conditions that have consequences for human health. Through a NASA-funded partnership between the University of New Mexico and the University of Arizona, NASA Earth Science results are fused into two existing models (the Dust Regional Atmospheric Model (DREAM) and the Community Multiscale Air Quality (CMAQ) model) in order to improve forecasts of atmospheric dust, ozone, and aerosols. The results and products derived from the outputs of these models are made available to an Open Source mapping component of the New Mexico EPHTS. In particular, these products are integrated into a Django content management system using GeoDjango, GeoAlchemy, and other OGC-compliant geospatial libraries written in the Python and C++ programming languages. Capabilities of the resultant mapping system include indicator-based thematic mapping, data delivery, and analytical capabilities. DREAM and CMAQ outputs can be inspected, via REST calls, through temporal and spatial subsetting of the atmospheric concentration data across analytical units employed by the public health community. This paper describes details of the architecture and integration of NASA Earth Science into the EPHTS decision-support system.

Prediction of fish and sediment mercury in streams using landscape variables and historical mining.

PubMed

Alpers, Charles N; Yee, Julie L; Ackerman, Joshua T; Orlando, James L; Slotton, Darrel G; Marvin-DiPasquale, Mark C

2016-11-15

Widespread mercury (Hg) contamination of aquatic systems in the Sierra Nevada of California, U.S., is associated with historical use to enhance gold (Au) recovery by amalgamation. In areas affected by historical Au mining operations, including the western slope of the Sierra Nevada and downstream areas in northern California, such as San Francisco Bay and the Sacramento River-San Joaquin River Delta, microbial conversion of Hg to methylmercury (MeHg) leads to bioaccumulation of MeHg in food webs, and increased risks to humans and wildlife. This study focused on developing a predictive model for THg in stream fish tissue based on geospatial data, including land use/land cover data, and the distribution of legacy Au mines. Data on total mercury (THg) and MeHg concentrations in fish tissue and streambed sediment collected during 1980-2012 from stream sites in the Sierra Nevada, California were combined with geospatial data to estimate fish THg concentrations across the landscape. THg concentrations of five fish species (Brown Trout, Rainbow Trout, Sacramento Pikeminnow, Sacramento Sucker, and Smallmouth Bass) within stream sections were predicted using multi-model inference based on Akaike Information Criteria, using geospatial data for mining history and landscape characteristics as well as fish species and length (r(2)=0.61, p<0.001). Including THg concentrations in streambed sediment did not improve the model's fit, however including MeHg concentrations in streambed sediment, organic content (loss on ignition), and sediment grain size resulted in an improved fit (r(2)=0.63, p<0.001). These models can be used to estimate THg concentrations in stream fish based on landscape variables in the Sierra Nevada in areas where direct measurements of THg concentration in fish are unavailable. Published by Elsevier B.V.

Prediction of fish and sediment mercury in streams using landscape variables and historical mining

USGS Publications Warehouse

Alpers, Charles N.; Yee, Julie L.; Ackerman, Joshua T.; Orlando, James L.; Slotton, Darrell G.; Marvin-DiPasquale, Mark C.

2016-01-01

Widespread mercury (Hg) contamination of aquatic systems in the Sierra Nevada of California, U.S., is associated with historical use to enhance gold (Au) recovery by amalgamation. In areas affected by historical Au mining operations, including the western slope of the Sierra Nevada and downstream areas in northern California, such as San Francisco Bay and the Sacramento River–San Joaquin River Delta, microbial conversion of Hg to methylmercury (MeHg) leads to bioaccumulation of MeHg in food webs, and increased risks to humans and wildlife. This study focused on developing a predictive model for THg in stream fish tissue based on geospatial data, including land use/land cover data, and the distribution of legacy Au mines. Data on total mercury (THg) and MeHg concentrations in fish tissue and streambed sediment collected during 1980–2012 from stream sites in the Sierra Nevada, California were combined with geospatial data to estimate fish THg concentrations across the landscape. THg concentrations of five fish species (Brown Trout, Rainbow Trout, Sacramento Pikeminnow, Sacramento Sucker, and Smallmouth Bass) within stream sections were predicted using multi-model inference based on Akaike Information Criteria, using geospatial data for mining history and landscape characteristics as well as fish species and length (r2 = 0.61, p < 0.001). Including THg concentrations in streambed sediment did not improve the model's fit, however including MeHg concentrations in streambed sediment, organic content (loss on ignition), and sediment grain size resulted in an improved fit (r2 = 0.63, p < 0.001). These models can be used to estimate THg concentrations in stream fish based on landscape variables in the Sierra Nevada in areas where direct measurements of THg concentration in fish are unavailable.

Ranking contributing areas of salt and selenium in the Lower Gunnison River Basin, Colorado, using multiple linear regression models

USGS Publications Warehouse

Linard, Joshua I.

2013-01-01

Mitigating the effects of salt and selenium on water quality in the Grand Valley and lower Gunnison River Basin in western Colorado is a major concern for land managers. Previous modeling indicated means to improve the models by including more detailed geospatial data and a more rigorous method for developing the models. After evaluating all possible combinations of geospatial variables, four multiple linear regression models resulted that could estimate irrigation-season salt yield, nonirrigation-season salt yield, irrigation-season selenium yield, and nonirrigation-season selenium yield. The adjusted r-squared and the residual standard error (in units of log-transformed yield) of the models were, respectively, 0.87 and 2.03 for the irrigation-season salt model, 0.90 and 1.25 for the nonirrigation-season salt model, 0.85 and 2.94 for the irrigation-season selenium model, and 0.93 and 1.75 for the nonirrigation-season selenium model. The four models were used to estimate yields and loads from contributing areas corresponding to 12-digit hydrologic unit codes in the lower Gunnison River Basin study area. Each of the 175 contributing areas was ranked according to its estimated mean seasonal yield of salt and selenium.

Measuring the Impact of a Pilot Geospatial Technology Apprenticeship Program for the Department of Labor

ERIC Educational Resources Information Center

Gaudet, Cyndi; Annulis, Heather; Kmiec, John

2010-01-01

The Geospatial Technology Apprenticeship Program (GTAP) pilot was designed as a replicable and sustainable program to enhance workforce skills in geospatial technologies to best leverage a $30 billion market potential. The purpose of evaluating GTAP was to ensure that investment in this high-growth industry was adding value. Findings from this…

Integrating geospatial data and cropping system simulation within a geographic information system to analyze spatial seed cotton yield, water use, and irrigation requirements

USDA-ARS?s Scientific Manuscript database

The development of sensors that provide geospatial information on crop and soil conditions has been a primary success for precision agriculture. However, further developments are needed to integrate geospatial data into computer algorithms that spatially optimize crop production while considering po...

Application of an imputation method for geospatial inventory of forest structural attributes across multiple spatial scales in the Lake States, U.S.A

NASA Astrophysics Data System (ADS)

Deo, Ram K.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

NASA Astrophysics Data System (ADS)

Song, M.; Li, W.; Zhou, X.

2014-12-01

In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.

Semantic Document Library: A Virtual Research Environment for Documents, Data and Workflows Sharing

NASA Astrophysics Data System (ADS)

Kotwani, K.; Liu, Y.; Myers, J.; Futrelle, J.

2008-12-01

The Semantic Document Library (SDL) was driven by use cases from the environmental observatory communities and is designed to provide conventional document repository features of uploading, downloading, editing and versioning of documents as well as value adding features of tagging, querying, sharing, annotating, ranking, provenance, social networking and geo-spatial mapping services. It allows users to organize a catalogue of watershed observation data, model output, workflows, as well publications and documents related to the same watershed study through the tagging capability. Users can tag all relevant materials using the same watershed name and find all of them easily later using this tag. The underpinning semantic content repository can store materials from other cyberenvironments such as workflow or simulation tools and SDL provides an effective interface to query and organize materials from various sources. Advanced features of the SDL allow users to visualize the provenance of the materials such as the source and how the output data is derived. Other novel features include visualizing all geo-referenced materials on a geospatial map. SDL as a component of a cyberenvironment portal (the NCSA Cybercollaboratory) has goal of efficient management of information and relationships between published artifacts (Validated models, vetted data, workflows, annotations, best practices, reviews and papers) produced from raw research artifacts (data, notes, plans etc.) through agents (people, sensors etc.). Tremendous scientific potential of artifacts is achieved through mechanisms of sharing, reuse and collaboration - empowering scientists to spread their knowledge and protocols and to benefit from the knowledge of others. SDL successfully implements web 2.0 technologies and design patterns along with semantic content management approach that enables use of multiple ontologies and dynamic evolution (e.g. folksonomies) of terminology. Scientific documents involved with many interconnected entities (artifacts or agents) are represented as RDF triples using semantic content repository middleware Tupelo in one or many data/metadata RDF stores. Queries to the RDF enables discovery of relations among data, process and people, digging out valuable aspects, making recommendations to users, such as what tools are typically used to answer certain kinds of questions or with certain types of dataset. This innovative concept brings out coherent information about entities from four different perspectives of the social context (Who-human relations and interactions), the casual context (Why - provenance and history), the geo-spatial context (Where - location or spatially referenced information) and the conceptual context (What - domain specific relations, ontologies etc.).

Analysis of Giga-size Earth Observation Data in Open Source GRASS GIS 7 - from Desktop to On-line Solutions.

NASA Astrophysics Data System (ADS)

Stepinski, T. F.; Mitasova, H.; Jasiewicz, J.; Neteler, M.; Gebbert, S.

2014-12-01

GRASS GIS is a leading open source GIS for geospatial analysis and modeling. In addition to being utilized as a desktop GIS it also serves as a processing engine for high performance geospatial computing for applications in diverse disciplines. The newly released GRASS GIS 7 supports big data analysis including temporal framework, image segmentation, watershed analysis, synchronized 2D/3D animations and many others. This presentation will focus on new GRASS GIS 7-powered tools for geoprocessing giga-size earth observation (EO) data using spatial pattern analysis. Pattern-based analysis connects to human visual perception of space as well as makes geoprocessing of giga-size EO data possible in an efficient and robust manner. GeoPAT is a collection of GRASS GIS 7 modules that fully integrates procedures for pattern representation of EO data and patterns similarity calculations with standard GIS tasks of mapping, maps overlay, segmentation, classification(Fig 1a), change detections etc. GeoPAT works very well on a desktop but it also underpins several GeoWeb applications (http://sil.uc.edu/ ) which allow users to do analysis on selected EO datasets without the need to download them. The GRASS GIS 7 temporal framework and high resolution visualizations will be illustrated using time series of giga-size, lidar-based digital elevation models representing the dynamics of North Carolina barrier islands over the past 15 years. The temporal framework supports efficient raster and vector data series analysis and simplifies data input for visual analysis of dynamic landscapes (Fig. 1b) allowing users to rapidly identify vulnerable locations, changes in built environment and eroding coastlines. Numerous improvements in GRASS GIS 7 were implemented to support terabyte size data processing for reconstruction of MODIS land surface temperature (LST) at 250m resolution using multiple regressions and PCA (Fig. 1c) . The new MODIS LST series (http://gis.cri.fmach.it/eurolst/) includes 4 maps per day since year 2000, provide improved data for the epidemiological predictions, viticulture, assessment of urban heat islands and numerous other applications. The presentation will conclude with outline of future development for big data interfaces to further enhance the web-based GRASS GIS data analysis.

E-DECIDER Disaster Response and Decision Support Cyberinfrastructure: Technology and Challenges

NASA Astrophysics Data System (ADS)

Glasscoe, M. T.; Parker, J. W.; Pierce, M. E.; Wang, J.; Eguchi, R. T.; Huyck, C. K.; Hu, Z.; Chen, Z.; Yoder, M. R.; Rundle, J. B.; Rosinski, A.

2014-12-01

Timely delivery of critical information to decision makers during a disaster is essential to response and damage assessment. Key issues to an efficient emergency response after a natural disaster include rapidly processing and delivering this critical information to emergency responders and reducing human intervention as much as possible. Essential elements of information necessary to achieve situational awareness are often generated by a wide array of organizations and disciplines, using any number of geospatial and non-geospatial technologies. A key challenge is the current state of practice does not easily support information sharing and technology interoperability. NASA E-DECIDER (Emergency Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response) has worked with the California Earthquake Clearinghouse and its partners to address these issues and challenges by adopting the XChangeCore Web Service Data Orchestration technology and participating in several earthquake response exercises. The E-DECIDER decision support system provides rapid delivery of advanced situational awareness data products to operations centers and emergency responders in the field. Remote sensing and hazard data, model-based map products, information from simulations, damage detection, and crowdsourcing is integrated into a single geospatial view and delivered through a service oriented architecture for improved decision-making and then directly to mobile devices of responders. By adopting a Service Oriented Architecture based on Open Geospatial Consortium standards, the system provides an extensible, comprehensive framework for geospatial data processing and distribution on Cloud platforms and other distributed environments. While the Clearinghouse and its partners are not first responders, they do support the emergency response community by providing information about the damaging effects earthquakes. It is critical for decision makers to maintain a situational awareness that is knowledgeable of potential and current conditions, possible impacts on populations and infrastructure, and other key information. E-DECIDER and the Clearinghouse have worked together to address many of these issues and challenges to deliver interoperable, authoritative decision support products.

Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method

USGS Publications Warehouse

Cheruvelil, Kendra Spence; Yuan, Shuai; Webster, Katherine E.; Tan, Pang-Ning; Lapierre, Jean-Francois; Collins, Sarah M.; Fergus, C. Emi; Scott, Caren E.; Norton Henry, Emily; Soranno, Patricia A.; Filstrup, Christopher T.; Wagner, Tyler

2017-01-01

Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question—How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km2); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation—approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.

Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method.

PubMed

Cheruvelil, Kendra Spence; Yuan, Shuai; Webster, Katherine E; Tan, Pang-Ning; Lapierre, Jean-François; Collins, Sarah M; Fergus, C Emi; Scott, Caren E; Henry, Emily Norton; Soranno, Patricia A; Filstrup, Christopher T; Wagner, Tyler

2017-05-01

Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question-How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km 2 ); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation-approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.

PANTHER. Pattern ANalytics To support High-performance Exploitation and Reasoning.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Czuchlewski, Kristina Rodriguez; Hart, William E.

Sandia has approached the analysis of big datasets with an integrated methodology that uses computer science, image processing, and human factors to exploit critical patterns and relationships in large datasets despite the variety and rapidity of information. The work is part of a three-year LDRD Grand Challenge called PANTHER (Pattern ANalytics To support High-performance Exploitation and Reasoning). To maximize data analysis capability, Sandia pursued scientific advances across three key technical domains: (1) geospatial-temporal feature extraction via image segmentation and classification; (2) geospatial-temporal analysis capabilities tailored to identify and process new signatures more efficiently; and (3) domain- relevant models of humanmore » perception and cognition informing the design of analytic systems. Our integrated results include advances in geographical information systems (GIS) in which we discover activity patterns in noisy, spatial-temporal datasets using geospatial-temporal semantic graphs. We employed computational geometry and machine learning to allow us to extract and predict spatial-temporal patterns and outliers from large aircraft and maritime trajectory datasets. We automatically extracted static and ephemeral features from real, noisy synthetic aperture radar imagery for ingestion into a geospatial-temporal semantic graph. We worked with analysts and investigated analytic workflows to (1) determine how experiential knowledge evolves and is deployed in high-demand, high-throughput visual search workflows, and (2) better understand visual search performance and attention. Through PANTHER, Sandia's fundamental rethinking of key aspects of geospatial data analysis permits the extraction of much richer information from large amounts of data. The project results enable analysts to examine mountains of historical and current data that would otherwise go untouched, while also gaining meaningful, measurable, and defensible insights into overlooked relationships and patterns. The capability is directly relevant to the nation's nonproliferation remote-sensing activities and has broad national security applications for military and intelligence- gathering organizations.« less

Progress of Interoperability in Planetary Research for Geospatial Data Analysis

NASA Astrophysics Data System (ADS)

Hare, T. M.; Gaddis, L. R.

2015-12-01

For nearly a decade there has been a push in the planetary science community to support interoperable methods of accessing and working with geospatial data. Common geospatial data products for planetary research include image mosaics, digital elevation or terrain models, geologic maps, geographic location databases (i.e., craters, volcanoes) or any data that can be tied to the surface of a planetary body (including moons, comets or asteroids). Several U.S. and international cartographic research institutions have converged on mapping standards that embrace standardized image formats that retain geographic information (e.g., GeoTiff, GeoJpeg2000), digital geologic mapping conventions, planetary extensions for symbols that comply with U.S. Federal Geographic Data Committee cartographic and geospatial metadata standards, and notably on-line mapping services as defined by the Open Geospatial Consortium (OGC). The latter includes defined standards such as the OGC Web Mapping Services (simple image maps), Web Feature Services (feature streaming), Web Coverage Services (rich scientific data streaming), and Catalog Services for the Web (data searching and discoverability). While these standards were developed for application to Earth-based data, they have been modified to support the planetary domain. The motivation to support common, interoperable data format and delivery standards is not only to improve access for higher-level products but also to address the increasingly distributed nature of the rapidly growing volumes of data. The strength of using an OGC approach is that it provides consistent access to data that are distributed across many facilities. While data-steaming standards are well-supported by both the more sophisticated tools used in Geographic Information System (GIS) and remote sensing industries, they are also supported by many light-weight browsers which facilitates large and small focused science applications and public use. Here we provide an overview of the interoperability initiatives that are currently ongoing in the planetary research community, examples of their successful application, and challenges that remain.

Geospatial Technology Strategic Plan 1997-2000

USGS Publications Warehouse

D'Erchia, Frank; D'Erchia, Terry D.; Getter, James; McNiff, Marcia; Root, Ralph; Stitt, Susan; White, Barbara

1997-01-01

Executive Summary -- Geospatial technology applications have been identified in many U.S. Geological Survey Biological Resources Division (BRD) proposals for grants awarded through internal and partnership programs. Because geospatial data and tools have become more sophisticated, accessible, and easy to use, BRD scientists frequently are using these tools and capabilities to enhance a broad spectrum of research activities. Bruce Babbitt, Secretary of the Interior, has acknowledged--and lauded--the important role of geospatial technology in natural resources management. In his keynote address to more than 5,500 people representing 87 countries at the Environmental Systems Research Institute Annual Conference (May 21, 1996), Secretary Babbitt stated, '. . .GIS [geographic information systems], if properly used, can provide a lot more than sets of data. Used effectively, it can help stakeholders to bring consensus out of conflict. And it can, by providing information, empower the participants to find new solutions to their problems.' This Geospatial Technology Strategic Plan addresses the use and application of geographic information systems, remote sensing, satellite positioning systems, image processing, and telemetry; describes methods of meeting national plans relating to geospatial data development, management, and serving; and provides guidance for sharing expertise and information. Goals are identified along with guidelines that focus on data sharing, training, and technology transfer. To measure success, critical performance indicators are included. The ability of the BRD to use and apply geospatial technology across all disciplines will greatly depend upon its success in transferring the technology to field biologists and researchers. The Geospatial Technology Strategic Planning Development Team coordinated and produced this document in the spirit of this premise. Individual Center and Program managers have the responsibility to implement the Strategic Plan by working within the policy and guidelines stated herein.

Geospatial cryptography: enabling researchers to access private, spatially referenced, human subjects data for cancer control and prevention.

PubMed

Jacquez, Geoffrey M; Essex, Aleksander; Curtis, Andrew; Kohler, Betsy; Sherman, Recinda; Emam, Khaled El; Shi, Chen; Kaufmann, Andy; Beale, Linda; Cusick, Thomas; Goldberg, Daniel; Goovaerts, Pierre

2017-07-01

As the volume, accuracy and precision of digital geographic information have increased, concerns regarding individual privacy and confidentiality have come to the forefront. Not only do these challenge a basic tenet underlying the advancement of science by posing substantial obstacles to the sharing of data to validate research results, but they are obstacles to conducting certain research projects in the first place. Geospatial cryptography involves the specification, design, implementation and application of cryptographic techniques to address privacy, confidentiality and security concerns for geographically referenced data. This article defines geospatial cryptography and demonstrates its application in cancer control and surveillance. Four use cases are considered: (1) national-level de-duplication among state or province-based cancer registries; (2) sharing of confidential data across cancer registries to support case aggregation across administrative geographies; (3) secure data linkage; and (4) cancer cluster investigation and surveillance. A secure multi-party system for geospatial cryptography is developed. Solutions under geospatial cryptography are presented and computation time is calculated. As services provided by cancer registries to the research community, de-duplication, case aggregation across administrative geographies and secure data linkage are often time-consuming and in some instances precluded by confidentiality and security concerns. Geospatial cryptography provides secure solutions that hold significant promise for addressing these concerns and for accelerating the pace of research with human subjects data residing in our nation's cancer registries. Pursuit of the research directions posed herein conceivably would lead to a geospatially encrypted geographic information system (GEGIS) designed specifically to promote the sharing and spatial analysis of confidential data. Geospatial cryptography holds substantial promise for accelerating the pace of research with spatially referenced human subjects data.

Brian Bush | NREL

Science.gov Websites

W Bush Photo of Brian Bush Brian Bush Researcher VI-Systems Engineering Brian.Bush@nrel.gov | 303 -384-7472 Orcid ID http://orcid.org/0000-0003-2864-7028 Brian W Bush is a member of the Systems Modeling team within the Systems Modeling & Geospatial Data Science Group in the Strategic Energy

Spatial discretization of large watersheds and its influence on the estimation of hillslope sediment yield

USDA-ARS?s Scientific Manuscript database

The combined use of water erosion models and geographic information systems (GIS) has facilitated soil loss estimation at the watershed scale. Tools such as the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP) model provide a convenient spatially distributed soil loss estimat...

Development and application of a geospatial wildfire exposure and risk calculation tool

Treesearch

Matthew P. Thompson; Jessica R. Haas; Julie W. Gilbertson-Day; Joe H. Scott; Paul Langowski; Elise Bowne; David E. Calkin

2015-01-01

Applying wildfire risk assessment models can inform investments in loss mitigation and landscape restoration, and can be used to monitor spatiotemporal trends in risk. Assessing wildfire risk entails the integration of fire modeling outputs, maps of highly valued resources and assets (HVRAs), characterization of fire effects, and articulation of relative importance...

National Geospatial Program

USGS Publications Warehouse

Carswell, William J.

2011-01-01

increases the efficiency of the Nation's geospatial community by improving communications about geospatial data, products, services, projects, needs, standards, and best practices. The NGP comprises seven major components (described below), that are managed as a unified set. For example, The National Map establishes data standards and identifies geographic areas where specific types of geospatial data need to be incorporated into The National Map. Partnership Network Liaisons work with Federal, State, local, and tribal partners to help acquire the data. Geospatial technical operations ensure the quality control, integration, and availability to the public of the data acquired. The Emergency Operations Office provides the requirements to The National Map and, during emergencies and natural disasters, provides rapid dissemination of information and data targeted to the needs of emergency responders. The National Atlas uses data from The National Map and other sources to make small-scale maps and multimedia articles about the maps.

Revelation of `Hidden' Balinese Geospatial Heritage on A Map

NASA Astrophysics Data System (ADS)

Soeria Atmadja, Dicky A. S.; Wikantika, Ketut; Budi Harto, Agung; Putra, Daffa Gifary M.

2018-05-01

Bali is not just about beautiful nature. It also has a unique and interesting cultural heritage, including `hidden' geospatial heritage. Tri Hita Karana is a Hinduism concept of life consisting of human relation to God, to other humans and to the nature (Parahiyangan, Pawongan and Palemahan), Based on it, - in term of geospatial aspect - the Balinese derived its spatial orientation, spatial planning & lay out, measurement as well as color and typography. Introducing these particular heritage would be a very interesting contribution to Bali tourism. As a respond to these issues, a question arise on how to reveal these unique and highly valuable geospatial heritage on a map which can be used to introduce and disseminate them to the tourists. Symbols (patterns & colors), orientation, distance, scale, layout and toponimy have been well known as elements of a map. There is an chance to apply Balinese geospatial heritage in representing these map elements.

USGS Geospatial Fabric and Geo Data Portal for Continental Scale Hydrology Simulations

NASA Astrophysics Data System (ADS)

Sampson, K. M.; Newman, A. J.; Blodgett, D. L.; Viger, R.; Hay, L.; Clark, M. P.

2013-12-01

This presentation describes use of United States Geological Survey (USGS) data products and server-based resources for continental-scale hydrologic simulations. The USGS Modeling of Watershed Systems (MoWS) group provides a consistent national geospatial fabric built on NHDPlus. They have defined more than 100,000 hydrologic response units (HRUs) over the continental United States based on points of interest (POIs) and split into left and right bank based on the corresponding stream segment. Geophysical attributes are calculated for each HRU that can be used to define parameters in hydrologic and land-surface models. The Geo Data Portal (GDP) project at the USGS Center for Integrated Data Analytics (CIDA) provides access to downscaled climate datasets and processing services via web-interface and python modules for creating forcing datasets for any polygon (such as an HRU). These resources greatly reduce the labor required for creating model-ready data in-house, contributing to efficient and effective modeling applications. We will present an application of this USGS cyber-infrastructure for assessments of impacts of climate change on hydrology over the continental United States.

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT ...

EPA Pesticide Factsheets

The Automated Geospatial Watershed Assessment tool (AGWA) is a GIS interface jointly developed by the USDA Agricultural Research Service, the U.S. Environmental Protection Agency, the University of Arizona, and the University of Wyoming to automate the parameterization and execution of the Soil Water Assessment Tool (SWAT) and KINEmatic Runoff and EROSion (KINEROS2) hydrologic models. The application of these two models allows AGWA to conduct hydrologic modeling and watershed assessments at multiple temporal and spatial scales. AGWA’s current outputs are runoff (volumes and peaks) and sediment yield, plus nitrogen and phosphorus with the SWAT model. AGWA uses commonly available GIS data layers to fully parameterize, execute, and visualize results from both models. Through an intuitive interface the user selects an outlet from which AGWA delineates and discretizes the watershed using a Digital Elevation Model (DEM) based on the individual model requirements. The watershed model elements are then intersected with soils and land cover data layers to derive the requisite model input parameters. The chosen model is then executed, and the results are imported back into AGWA for visualization. This allows managers to identify potential problem areas where additional monitoring can be undertaken or mitigation activities can be focused. AGWA also has tools to apply an array of best management practices. There are currently two versions of AGWA available; AGWA 1.5 for

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests

Treesearch

Bernard R. Parresol; Joe H. Scott; Anne Andreu; Susan Prichard; Laurie Kurth

2012-01-01

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or...

A model to predict stream water temperature across the conterminous USA

Treesearch

Catalina Segura; Peter Caldwell; Ge Sun; Steve McNulty; Yang Zhang

2014-01-01

Stream water temperature (ts) is a critical water quality parameter for aquatic ecosystems. However, ts records are sparse or nonexistent in many river systems. In this work, we present an empirical model to predict ts at the site scale across the USA. The model, derived using data from 171 reference sites selected from the Geospatial Attributes of Gages for Evaluating...

The Future of Geospatial Standards

NASA Astrophysics Data System (ADS)

Bermudez, L. E.; Simonis, I.

2016-12-01

The OGC is an international not-for-profit standards development organization (SDO) committed to making quality standards for the geospatial community. A community of more than 500 member organizations with more than 6,000 people registered at the OGC communication platform drives the development of standards that are freely available for anyone to use and to improve sharing of the world's geospatial data. OGC standards are applied in a variety of application domains including Environment, Defense and Intelligence, Smart Cities, Aviation, Disaster Management, Agriculture, Business Development and Decision Support, and Meteorology. Profiles help to apply information models to different communities, thus adapting to particular needs of that community while ensuring interoperability by using common base models and appropriate support services. Other standards address orthogonal aspects such as handling of Big Data, Crowd-sourced information, Geosemantics, or container for offline data usage. Like most SDOs, the OGC develops and maintains standards through a formal consensus process under the OGC Standards Program (OGC-SP) wherein requirements and use cases are discussed in forums generally open to the public (Domain Working Groups, or DWGs), and Standards Working Groups (SWGs) are established to create standards. However, OGC is unique among SDOs in that it also operates the OGC Interoperability Program (OGC-IP) to provide real-world testing of existing and proposed standards. The OGC-IP is considered the experimental playground, where new technologies are researched and developed in a user-driven process. Its goal is to prototype, test, demonstrate, and promote OGC Standards in a structured environment. Results from the OGC-IP often become requirements for new OGC standards or identify deficiencies in existing OGC standards that can be addressed. This presentation will provide an analysis of the work advanced in the OGC consortium including standards and testbeds, where we can extract a trend for the future of geospatial standards. We see a number of key elements in focus, but simultaneously a broadening of standards to address particular communities' needs.

Establishing Accurate and Sustainable Geospatial Reference Layers in Developing Countries

NASA Astrophysics Data System (ADS)

Seaman, V. Y.

2017-12-01

Accurate geospatial reference layers (settlement names & locations, administrative boundaries, and population) are not readily available for most developing countries. This critical information gap makes it challenging for governments to efficiently plan, allocate resources, and provide basic services. It also hampers international agencies' response to natural disasters, humanitarian crises, and other emergencies. The current work involves a recent successful effort, led by the Bill & Melinda Gates Foundation and the Government of Nigeria, to obtain such data. The data collection began in 2013, with local teams collecting names, coordinates, and administrative attributes for over 100,000 settlements using ODK-enabled smartphones. A settlement feature layer extracted from satellite imagery was used to ensure all settlements were included. Administrative boundaries (Ward, LGA) were created using the settlement attributes. These "new" boundary layers were much more accurate than existing shapefiles used by the government and international organizations. The resulting data sets helped Nigeria eradicate polio from all areas except in the extreme northeast, where security issues limited access and vaccination activities. In addition to the settlement and boundary layers, a GIS-based population model was developed, in partnership with Oak Ridge National Laboratories and Flowminder), that used the extracted settlement areas and characteristics, along with targeted microcensus data. This model provides population and demographics estimates independent of census or other administrative data, at a resolution of 90 meters. These robust geospatial data layers found many other uses, including establishing catchment area settlements and populations for health facilities, validating denominators for population-based surveys, and applications across a variety of government sectors. Based on the success of the Nigeria effort, a partnership between DfID and the Bill & Melinda Gates Foundation was formed in 2017 to help other developing countries collect these geospatial reference layers, and to build capacity within the host governments to manage, use, and sustain them. This work will support, wherever possible, a national geo-referenced census, from which the reference layers can be extracted.

Forest cover change prediction using hybrid methodology of geoinformatics and Markov chain model: A case study on sub-Himalayan town Gangtok, India

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Anirban; Mondal, Arun; Mukherjee, Sandip; Khatua, Dipam; Ghosh, Subhajit; Mitra, Debasish; Ghosh, Tuhin

2014-08-01

In the Himalayan states of India, with increasing population and activities, large areas of forested land are being converted into other land-use features. There is a definite cause and effect relationship between changing practice for development and changes in land use. So, an estimation of land use dynamics and a futuristic trend pattern is essential. A combination of geospatial and statistical techniques were applied to assess the present and future land use/land cover scenario of Gangtok, the subHimalayan capital of Sikkim. Multi-temporal satellite imageries of the Landsat series were used to map the changes in land use of Gangtok from 1990 to 2010. Only three major land use classes (built-up area and bare land, step cultivated area, and forest) were considered as the most dynamic land use practices of Gangtok. The conventional supervised classification, and spectral indices-based thresholding using NDVI (Normalized Difference Vegetation Index) and SAVI (Soil Adjusted Vegetation Index) were applied along with the accuracy assessments. Markov modelling was applied for prediction of land use/land cover change and was validated. SAVI provides the most accurate estimate, i.e., the difference between predicted and actual data is minimal. Finally, a combination of Markov modelling and SAVI was used to predict the probable land-use scenario in Gangtok in 2020 AD, which indicted that more forest areas will be converted for step cultivation by the year 2020.

GIS-based Geospatial Infrastructure of Water Resource Assessment for Supporting Oil Shale Development in Piceance Basin of Northwestern Colorado

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Wei; Minnick, Matthew D; Mattson, Earl D

Oil shale deposits of the Green River Formation (GRF) in Northwestern Colorado, Southwestern Wyoming, and Northeastern Utah may become one of the first oil shale deposits to be developed in the U.S. because of their richness, accessibility, and extensive prior characterization. Oil shale is an organic-rich fine-grained sedimentary rock that contains significant amounts of kerogen from which liquid hydrocarbons can be produced. Water is needed to retort or extract oil shale at an approximate rate of three volumes of water for every volume of oil produced. Concerns have been raised over the demand and availability of water to produce oilmore » shale, particularly in semiarid regions where water consumption must be limited and optimized to meet demands from other sectors. The economic benefit of oil shale development in this region may have tradeoffs within the local and regional environment. Due to these potential environmental impacts of oil shale development, water usage issues need to be further studied. A basin-wide baseline for oil shale and water resource data is the foundation of the study. This paper focuses on the design and construction of a centralized geospatial infrastructure for managing a large amount of oil shale and water resource related baseline data, and for setting up the frameworks for analytical and numerical models including but not limited to three-dimensional (3D) geologic, energy resource development systems, and surface water models. Such a centralized geospatial infrastructure made it possible to directly generate model inputs from the same database and to indirectly couple the different models through inputs/outputs. Thus ensures consistency of analyses conducted by researchers from different institutions, and help decision makers to balance water budget based on the spatial distribution of the oil shale and water resources, and the spatial variations of geologic, topographic, and hydrogeological Characterization of the basin. This endeavor encountered many technical challenging and hasn't been done in the past for any oil shale basin. The database built during this study remains valuable for any other future studies involving oil shale and water resource management in the Piceance Basin. The methodology applied in the development of the GIS based Geospatial Infrastructure can be readily adapted for other professionals to develop database structure for other similar basins.« less

GEO Label Web Services for Dynamic and Effective Communication of Geospatial Metadata Quality

NASA Astrophysics Data System (ADS)

Lush, Victoria; Nüst, Daniel; Bastin, Lucy; Masó, Joan; Lumsden, Jo

2014-05-01

We present demonstrations of the GEO label Web services and their integration into a prototype extension of the GEOSS portal (http://scgeoviqua.sapienzaconsulting.com/web/guest/geo_home), the GMU portal (http://gis.csiss.gmu.edu/GADMFS/) and a GeoNetwork catalog application (http://uncertdata.aston.ac.uk:8080/geonetwork/srv/eng/main.home). The GEO label is designed to communicate, and facilitate interrogation of, geospatial quality information with a view to supporting efficient and effective dataset selection on the basis of quality, trustworthiness and fitness for use. The GEO label which we propose was developed and evaluated according to a user-centred design (UCD) approach in order to maximise the likelihood of user acceptance once deployed. The resulting label is dynamically generated from producer metadata in ISO or FDGC format, and incorporates user feedback on dataset usage, ratings and discovered issues, in order to supply a highly informative summary of metadata completeness and quality. The label was easily incorporated into a community portal as part of the GEO Architecture Implementation Programme (AIP-6) and has been successfully integrated into a prototype extension of the GEOSS portal, as well as the popular metadata catalog and editor, GeoNetwork. The design of the GEO label was based on 4 user studies conducted to: (1) elicit initial user requirements; (2) investigate initial user views on the concept of a GEO label and its potential role; (3) evaluate prototype label visualizations; and (4) evaluate and validate physical GEO label prototypes. The results of these studies indicated that users and producers support the concept of a label with drill-down interrogation facility, combining eight geospatial data informational aspects, namely: producer profile, producer comments, lineage information, standards compliance, quality information, user feedback, expert reviews, and citations information. These are delivered as eight facets of a wheel-like label, which are coloured according to metadata availability and are clickable to allow a user to engage with the original metadata and explore specific aspects in more detail. To support this graphical representation and allow for wider deployment architectures we have implemented two Web services, a PHP and a Java implementation, that generate GEO label representations by combining producer metadata (from standard catalogues or other published locations) with structured user feedback. Both services accept encoded URLs of publicly available metadata documents or metadata XML files as HTTP POST and GET requests and apply XPath and XSLT mappings to transform producer and feedback XML documents into clickable SVG GEO label representations. The label and services are underpinned by two XML-based quality models. The first is a producer model that extends ISO 19115 and 19157 to allow fuller citation of reference data, presentation of pixel- and dataset- level statistical quality information, and encoding of 'traceability' information on the lineage of an actual quality assessment. The second is a user quality model (realised as a feedback server and client) which allows reporting and query of ratings, usage reports, citations, comments and other domain knowledge. Both services are Open Source and are available on GitHub at https://github.com/lushv/geolabel-service and https://github.com/52North/GEO-label-java. The functionality of these services can be tested using our GEO label generation demos, available online at http://www.geolabel.net/demo.html and http://geoviqua.dev.52north.org/glbservice/index.jsf.

Visualization and Ontology of Geospatial Intelligence

NASA Astrophysics Data System (ADS)

Chan, Yupo

Recent events have deepened our conviction that many human endeavors are best described in a geospatial context. This is evidenced in the prevalence of location-based services, as afforded by the ubiquitous cell phone usage. It is also manifested by the popularity of such internet engines as Google Earth. As we commute to work, travel on business or pleasure, we make decisions based on the geospatial information provided by such location-based services. When corporations devise their business plans, they also rely heavily on such geospatial data. By definition, local, state and federal governments provide services according to geographic boundaries. One estimate suggests that 85 percent of data contain spatial attributes.

Intelligent services for discovery of complex geospatial features from remote sensing imagery

NASA Astrophysics Data System (ADS)

Yue, Peng; Di, Liping; Wei, Yaxing; Han, Weiguo

2013-09-01

Remote sensing imagery has been commonly used by intelligence analysts to discover geospatial features, including complex ones. The overwhelming volume of routine image acquisition requires automated methods or systems for feature discovery instead of manual image interpretation. The methods of extraction of elementary ground features such as buildings and roads from remote sensing imagery have been studied extensively. The discovery of complex geospatial features, however, is still rather understudied. A complex feature, such as a Weapon of Mass Destruction (WMD) proliferation facility, is spatially composed of elementary features (e.g., buildings for hosting fuel concentration machines, cooling towers, transportation roads, and fences). Such spatial semantics, together with thematic semantics of feature types, can be used to discover complex geospatial features. This paper proposes a workflow-based approach for discovery of complex geospatial features that uses geospatial semantics and services. The elementary features extracted from imagery are archived in distributed Web Feature Services (WFSs) and discoverable from a catalogue service. Using spatial semantics among elementary features and thematic semantics among feature types, workflow-based service chains can be constructed to locate semantically-related complex features in imagery. The workflows are reusable and can provide on-demand discovery of complex features in a distributed environment.

Finding geospatial pattern of unstructured data by clustering routes

NASA Astrophysics Data System (ADS)

Boustani, M.; Mattmann, C. A.; Ramirez, P.; Burke, W.

2016-12-01

Today the majority of data generated has a geospatial context to it. Either in attribute form as a latitude or longitude, or name of location or cross referenceable using other means such as an external gazetteer or location service. Our research is interested in exploiting geospatial location and context in unstructured data such as that found on the web in HTML pages, images, videos, documents, and other areas, and in structured information repositories found on intranets, in scientific environments, and otherwise. We are working together on the DARPA MEMEX project to exploit open source software tools such as the Lucene Geo Gazetteer, Apache Tika, Apache Lucene, and Apache OpenNLP, to automatically extract, and make meaning out of geospatial information. In particular, we are interested in unstructured descriptors e.g., a phone number, or a named entity, and the ability to automatically learn geospatial paths related to these descriptors. For example, a particular phone number may represent an entity that travels on a monthly basis, according to easily identifiable and somes more difficult to track patterns. We will present a set of automatic techniques to extract descriptors, and then to geospatially infer their paths across unstructured data.

BPELPower—A BPEL execution engine for geospatial web services

NASA Astrophysics Data System (ADS)

Yu, Genong (Eugene); Zhao, Peisheng; Di, Liping; Chen, Aijun; Deng, Meixia; Bai, Yuqi

2012-10-01

The Business Process Execution Language (BPEL) has become a popular choice for orchestrating and executing workflows in the Web environment. As one special kind of scientific workflow, geospatial Web processing workflows are data-intensive, deal with complex structures in data and geographic features, and execute automatically with limited human intervention. To enable the proper execution and coordination of geospatial workflows, a specially enhanced BPEL execution engine is required. BPELPower was designed, developed, and implemented as a generic BPEL execution engine with enhancements for executing geospatial workflows. The enhancements are especially in its capabilities in handling Geography Markup Language (GML) and standard geospatial Web services, such as the Web Processing Service (WPS) and the Web Feature Service (WFS). BPELPower has been used in several demonstrations over the decade. Two scenarios were discussed in detail to demonstrate the capabilities of BPELPower. That study showed a standard-compliant, Web-based approach for properly supporting geospatial processing, with the only enhancement at the implementation level. Pattern-based evaluation and performance improvement of the engine are discussed: BPELPower directly supports 22 workflow control patterns and 17 workflow data patterns. In the future, the engine will be enhanced with high performance parallel processing and broad Web paradigms.

A bioavailable strontium isoscape for Western Europe: A machine learning approach

PubMed Central

von Holstein, Isabella C. C.; Laffoon, Jason E.; Willmes, Malte; Liu, Xiao-Ming; Davies, Gareth R.

2018-01-01

Strontium isotope ratios (87Sr/86Sr) are gaining considerable interest as a geolocation tool and are now widely applied in archaeology, ecology, and forensic research. However, their application for provenance requires the development of baseline models predicting surficial 87Sr/86Sr variations (“isoscapes”). A variety of empirically-based and process-based models have been proposed to build terrestrial 87Sr/86Sr isoscapes but, in their current forms, those models are not mature enough to be integrated with continuous-probability surface models used in geographic assignment. In this study, we aim to overcome those limitations and to predict 87Sr/86Sr variations across Western Europe by combining process-based models and a series of remote-sensing geospatial products into a regression framework. We find that random forest regression significantly outperforms other commonly used regression and interpolation methods, and efficiently predicts the multi-scale patterning of 87Sr/86Sr variations by accounting for geological, geomorphological and atmospheric controls. Random forest regression also provides an easily interpretable and flexible framework to integrate different types of environmental auxiliary variables required to model the multi-scale patterning of 87Sr/86Sr variability. The method is transferable to different scales and resolutions and can be applied to the large collection of geospatial data available at local and global levels. The isoscape generated in this study provides the most accurate 87Sr/86Sr predictions in bioavailable strontium for Western Europe (R2 = 0.58 and RMSE = 0.0023) to date, as well as a conservative estimate of spatial uncertainty by applying quantile regression forest. We anticipate that the method presented in this study combined with the growing numbers of bioavailable 87Sr/86Sr data and satellite geospatial products will extend the applicability of the 87Sr/86Sr geo-profiling tool in provenance applications. PMID:29847595

Strengthened IAEA Safeguards-Imagery Analysis: Geospatial Tools for Nonproliferation Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pabian, Frank V

2012-08-14

This slide presentation focuses on the growing role and importance of imagery analysis for IAEA safeguards applications and how commercial satellite imagery, together with the newly available geospatial tools, can be used to promote 'all-source synergy.' As additional sources of openly available information, satellite imagery in conjunction with the geospatial tools can be used to significantly augment and enhance existing information gathering techniques, procedures, and analyses in the remote detection and assessment of nonproliferation relevant activities, facilities, and programs. Foremost of the geospatial tools are the 'Digital Virtual Globes' (i.e., GoogleEarth, Virtual Earth, etc.) that are far better than previouslymore » used simple 2-D plan-view line drawings for visualization of known and suspected facilities of interest which can be critical to: (1) Site familiarization and true geospatial context awareness; (2) Pre-inspection planning; (3) Onsite orientation and navigation; (4) Post-inspection reporting; (5) Site monitoring over time for changes; (6) Verification of states site declarations and for input to State Evaluation reports; and (7) A common basis for discussions among all interested parties (Member States). Additionally, as an 'open-source', such virtual globes can also provide a new, essentially free, means to conduct broad area search for undeclared nuclear sites and activities - either alleged through open source leads; identified on internet BLOGS and WIKI Layers, with input from a 'free' cadre of global browsers and/or by knowledgeable local citizens (a.k.a.: 'crowdsourcing'), that can include ground photos and maps; or by other initiatives based on existing information and in-house country knowledge. They also provide a means to acquire ground photography taken by locals, hobbyists, and tourists of the surrounding locales that can be useful in identifying and discriminating between relevant and non-relevant facilities and their associated infrastructure. The digital globes also provide highly accurate terrain mapping for better geospatial context and allow detailed 3-D perspectives of all sites or areas of interest. 3-D modeling software (i.e., Google's SketchUp6 newly available in 2007) when used in conjunction with these digital globes can significantly enhance individual building characterization and visualization (including interiors), allowing for better assessments including walk-arounds or fly-arounds and perhaps better decision making on multiple levels (e.g., the best placement for International Atomic Energy Agency (IAEA) video monitoring cameras).« less

Geospatial Data Combined With The Automated Geospatial Watershed Assessment (AGWA) Tool For Rapid Post-Fire Watershed Assessments

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Clifford, T. J.; Guertin, D. P.; Sheppard, B. S.; Barlow, J. E.; Korgaonkar, Y.; Burns, I. S.; Unkrich, C. C.

2016-12-01

Wildfires disasters are common throughout the western US. While many feel fire suppression is the largest cost of wildfires, case studies note rehabilitation costs often equal or greatly exceed suppression costs. Using geospatial data sets, and post-fire burn severity products, coupled with the Automated Geospatial Watershed Assessment tool (AGWA - www.tucson.ars.ag.gov/agwa), the Dept. of Interior, Burned Area Emergency Response (BAER) teams can rapidly analyze and identify at-risk areas to target rehabilitation efforts. AGWA employs nationally available geospatial elevation, soils, and land cover data to parameterize the KINEROS2 hydrology and erosion model. A pre-fire watershed simulation can be done prior to BAER deployment using design storms. As soon as the satellite-derived Burned Area Reflectance Classification (BARC) map is obtained, a post-fire watershed simulation using the same storm is conducted. The pre- and post-fire simulations can be spatially differenced in the GIS for rapid identification of high at-risk areas of erosion or flooding. This difference map is used by BAER teams to prioritize field observations and in-turn produce a final burn severity map that is used in AGWA/KINEROS2 simulations to provide report ready results. The 2013 Elk Wildfire Complex that burned over 52,600 ha east of Boise, Idaho provides a tangible example of how BAER experts combined AGWA and geospatial data that resulted in substantial rehabilitation cost savings. The BAER team initially, they identified approximately 6,500 burned ha for rehabilitation. The team then used the AGWA pre- and post-fire watershed simulation results, accessibility constraints, and land slope conditions in an interactive process to locate burned areas that posed the greatest threat to downstream values-at-risk. The group combined the treatable area, field observations, and the spatial results from AGWA to target seed and mulch treatments that most effectively reduced the threats. Using this process, the BAER Team reduced the treatable acres from the original 16,000 ha to between 800 and 1,600 ha depending on the selected alternative. The final awarded contract amounted to about 1,480/ha, therefore, a total savings of 7.2 - $8.4 million was realized for mulch treatment alone.

Fundamental structures of dynamic social networks.

PubMed

Sekara, Vedran; Stopczynski, Arkadiusz; Lehmann, Sune

2016-09-06

Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection unnecessary. Starting from 5-min time slices, we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision.

Fundamental structures of dynamic social networks

PubMed Central

Sekara, Vedran; Stopczynski, Arkadiusz; Lehmann, Sune

2016-01-01

Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection unnecessary. Starting from 5-min time slices, we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision. PMID:27555584

Mapping a Difference: The Power of Geospatial Visualization

NASA Astrophysics Data System (ADS)

Kolvoord, B.

2015-12-01

Geospatial Technologies (GST), such as GIS, GPS and remote sensing, offer students and teachers the opportunity to study the "why" of where. By making maps and collecting location-based data, students can pursue authentic problems using sophisticated tools. The proliferation of web- and cloud-based tools has made these technologies broadly accessible to schools. In addition, strong spatial thinking skills have been shown to be a key factor in supporting students that want to study science, technology, engineering, and mathematics (STEM) disciplines (Wai, Lubinski and Benbow) and pursue STEM careers. Geospatial technologies strongly scaffold the development of these spatial thinking skills. For the last ten years, the Geospatial Semester, a unique dual-enrollment partnership between James Madison University and Virginia high schools, has provided students with the opportunity to use GST's to hone their spatial thinking skills and to do extended projects of local interest, including environmental, geological and ecological studies. Along with strong spatial thinking skills, these students have also shown strong problem solving skills, often beyond those of fellow students in AP classes. Programs like the Geospatial Semester are scalable and within the reach of many college and university departments, allowing strong engagement with K-12 schools. In this presentation, we'll share details of the Geospatial Semester and research results on the impact of the use of these technologies on students' spatial thinking skills, and discuss the success and challenges of developing K-12 partnerships centered on geospatial visualization.

Temporal Dynamics and Spatial Patterns of Aedes aegypti Breeding Sites, in the Context of a Dengue Control Program in Tartagal (Salta Province, Argentina).

PubMed

Espinosa, Manuel; Weinberg, Diego; Rotela, Camilo H; Polop, Francisco; Abril, Marcelo; Scavuzzo, Carlos Marcelo

2016-05-01

Since 2009, Fundación Mundo Sano has implemented an Aedes aegypti Surveillance and Control Program in Tartagal city (Salta Province, Argentina). The purpose of this study was to analyze temporal dynamics of Ae. aegypti breeding sites spatial distribution, during five years of samplings, and the effect of control actions over vector population dynamics. Seasonal entomological (larval) samplings were conducted in 17,815 fixed sites in Tartagal urban area between 2009 and 2014. Based on information of breeding sites abundance, from satellite remote sensing data (RS), and by the use of Geographic Information Systems (GIS), spatial analysis (hotspots and cluster analysis) and predictive model (MaxEnt) were performed. Spatial analysis showed a distribution pattern with the highest breeding densities registered in city outskirts. The model indicated that 75% of Ae. aegypti distribution is explained by 3 variables: bare soil coverage percentage (44.9%), urbanization coverage percentage(13.5%) and water distribution (11.6%). This results have called attention to the way entomological field data and information from geospatial origin (RS/GIS) are used to infer scenarios which could then be applied in epidemiological surveillance programs and in the determination of dengue control strategies. Predictive maps development constructed with Ae. aegypti systematic spatiotemporal data, in Tartagal city, would allow public health workers to identify and target high-risk areas with appropriate and timely control measures. These tools could help decision-makers to improve health system responses and preventive measures related to vector control.

Temporal Dynamics and Spatial Patterns of Aedes aegypti Breeding Sites, in the Context of a Dengue Control Program in Tartagal (Salta Province, Argentina)

PubMed Central

Espinosa, Manuel; Weinberg, Diego; Rotela, Camilo H.; Polop, Francisco; Abril, Marcelo; Scavuzzo, Carlos Marcelo

2016-01-01

Background Since 2009, Fundación Mundo Sano has implemented an Aedes aegypti Surveillance and Control Program in Tartagal city (Salta Province, Argentina). The purpose of this study was to analyze temporal dynamics of Ae. aegypti breeding sites spatial distribution, during five years of samplings, and the effect of control actions over vector population dynamics. Methodology/Principal Findings Seasonal entomological (larval) samplings were conducted in 17,815 fixed sites in Tartagal urban area between 2009 and 2014. Based on information of breeding sites abundance, from satellite remote sensing data (RS), and by the use of Geographic Information Systems (GIS), spatial analysis (hotspots and cluster analysis) and predictive model (MaxEnt) were performed. Spatial analysis showed a distribution pattern with the highest breeding densities registered in city outskirts. The model indicated that 75% of Ae. aegypti distribution is explained by 3 variables: bare soil coverage percentage (44.9%), urbanization coverage percentage(13.5%) and water distribution (11.6%). Conclusions/Significance This results have called attention to the way entomological field data and information from geospatial origin (RS/GIS) are used to infer scenarios which could then be applied in epidemiological surveillance programs and in the determination of dengue control strategies. Predictive maps development constructed with Ae. aegypti systematic spatiotemporal data, in Tartagal city, would allow public health workers to identify and target high-risk areas with appropriate and timely control measures. These tools could help decision-makers to improve health system responses and preventive measures related to vector control. PMID:27223693

Building unified geospatial data for land-change modeling—A case study in the area of Richmond, Virginia

USGS Publications Warehouse

Donato, David I.; Shapiro, Jason L.

2016-12-13

An effort to build a unified collection of geospatial data for use in land-change modeling (LCM) led to new insights into the requirements and challenges of building an LCM data infrastructure. A case study of data compilation and unification for the Richmond, Va., Metropolitan Statistical Area (MSA) delineated the problems of combining and unifying heterogeneous data from many independent localities such as counties and cities. The study also produced conclusions and recommendations for use by the national LCM community, emphasizing the critical need for simple, practical data standards and conventions for use by localities. This report contributes an uncopyrighted core glossary and a much needed operational definition of data unification.

Geospatial Authentication

NASA Technical Reports Server (NTRS)

Lyle, Stacey D.

2009-01-01

A software package that has been designed to allow authentication for determining if the rover(s) is/are within a set of boundaries or a specific area to access critical geospatial information by using GPS signal structures as a means to authenticate mobile devices into a network wirelessly and in real-time. The advantage lies in that the system only allows those with designated geospatial boundaries or areas into the server.

Geospatial Data Availability for Haiti: An Aid in the Development of GIS-Based Natural Resource Assessments for Conservation Planning.

Treesearch

Maya Quinones; William Gould; Carlos D. Rodriguez-Pedraza

2007-01-01

This report documents the type and source of geospatial data available for Haiti. It was compiled to serve as a resource for geographic information system (GIS)-based land management and planning. It will be useful for conservation planning, reforestation efforts, and agricultural extension projects. Our study indicates that there is a great deal of geospatial...

Supporting Timely Humanitarian Assistance/Disaster Relief (HA/DR) Decisions Through Geospatial Intelligence (GEOINT) and Geographical Information Systems (GIS) Tools

DTIC Science & Technology

2014-05-22

attempted to respond to the advances in technology and the growing power of geographical information system (GIS) tools. However, the doctrine...Geospatial intelligence (GEOINT), Geographical information systems (GIS) tools, Humanitarian Assistance/Disaster Relief (HA/DR), 2010 Haiti Earthquake...Humanitarian Assistance/Disaster Relief (HA/DR) Decisions Through Geospatial Intelligence (GEOINT) and Geographical Information Systems (GIS) Tools

Geospatial Information and Geographic Information Systems (GIS): Current Issues and Future Challenges

DTIC Science & Technology

2009-06-08

CRS Report for Congress Prepared for Members and Committees of Congress Geospatial Information and Geographic Information Systems (GIS...Geographic Information Systems (GIS): Current Issues and Future Challenges 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Geospatial Information and Geographic Information Systems (GIS

Incorporating Resilience into Transportation Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Connelly, Elizabeth; Melaina, Marc

To aid decision making for developing transportation infrastructure, the National Renewable Energy Laboratory has developed the Scenario Evaluation, Regionalization and Analysis (SERA) model. The SERA model is a geospatially and temporally oriented model that has been applied to determine optimal production and delivery scenarios for hydrogen, given resource availability and technology cost and performance, for use in fuel cell vehicles. In addition, the SERA model has been applied to plug-in electric vehicles.

Application of geo-spatial technology in schistosomiasis modelling in Africa: a review.

PubMed

Manyangadze, Tawanda; Chimbari, Moses John; Gebreslasie, Michael; Mukaratirwa, Samson

2015-11-04

Schistosomiasis continues to impact socio-economic development negatively in sub-Saharan Africa. The advent of spatial technologies, including geographic information systems (GIS), Earth observation (EO) and global positioning systems (GPS) assist modelling efforts. However, there is increasing concern regarding the accuracy and precision of the current spatial models. This paper reviews the literature regarding the progress and challenges in the development and utilization of spatial technology with special reference to predictive models for schistosomiasis in Africa. Peer-reviewed papers identified through a PubMed search using the following keywords: geo-spatial analysis OR remote sensing OR modelling OR earth observation OR geographic information systems OR prediction OR mapping AND schistosomiasis AND Africa were used. Statistical uncertainty, low spatial and temporal resolution satellite data and poor validation were identified as some of the factors that compromise the precision and accuracy of the existing predictive models. The need for high spatial resolution of remote sensing data in conjunction with ancillary data viz. ground-measured climatic and environmental information, local presence/absence intermediate host snail surveys as well as prevalence and intensity of human infection for model calibration and validation are discussed. The importance of a multidisciplinary approach in developing robust, spatial data capturing, modelling techniques and products applicable in epidemiology is highlighted.

Geospatial interface and model for predicting potential seagrass habitat

EPA Science Inventory

Restoration of ecosystem services provided by seagrass habitats in estuaries requires a clear understanding of the modes of action of multiple interacting stressors including nutrients, climate change, coastal land-use change, and habitat modification. We have developed a geos...

Disaster protection of transport infrastructure and mobility using flood risk modeling and geospatial visualization.

DOT National Transportation Integrated Search

2015-05-01

infrastructure networks are essential to sustain our economy, society and quality of life. Natural disasters cost lives, infrastructure destruction, and economic losses. In 2013 over 28 million people were displaced worldwide by natural disasters wit...

Understanding the Role of Muscle and Body Composition in Studies of Cancer Risk and Prognosis in Cancer Survivors

Cancer.gov

The purpose of this conference is to bring together a community of researchers across the cancer control continuum using geospatial tools, models and approaches to address cancer prevention and control.

A linear geospatial streamflow modeling system for data sparse environments

USGS Publications Warehouse

Asante, Kwabena O.; Arlan, Guleid A.; Pervez, Md Shahriar; Rowland, James

2008-01-01

In many river basins around the world, inaccessibility of flow data is a major obstacle to water resource studies and operational monitoring. This paper describes a geospatial streamflow modeling system which is parameterized with global terrain, soils and land cover data and run operationally with satellite‐derived precipitation and evapotranspiration datasets. Simple linear methods transfer water through the subsurface, overland and river flow phases, and the resulting flows are expressed in terms of standard deviations from mean annual flow. In sample applications, the modeling system was used to simulate flow variations in the Congo, Niger, Nile, Zambezi, Orange and Lake Chad basins between 1998 and 2005, and the resulting flows were compared with mean monthly values from the open‐access Global River Discharge Database. While the uncalibrated model cannot predict the absolute magnitude of flow, it can quantify flow anomalies in terms of relative departures from mean flow. Most of the severe flood events identified in the flow anomalies were independently verified by the Dartmouth Flood Observatory (DFO) and the Emergency Disaster Database (EM‐DAT). Despite its limitations, the modeling system is valuable for rapid characterization of the relative magnitude of flood hazards and seasonal flow changes in data sparse settings.

Operational Monitoring of Volcanoes Using Keyhole Markup Language

NASA Astrophysics Data System (ADS)

Dehn, J.; Bailey, J. E.; Webley, P.

2007-12-01

Volcanoes are some of the most geologically powerful, dynamic, visually appealing structures on the Earth's landscape. Volcanic eruptions are hard to predict, difficult to quantify and impossible to prevent, making effective monitoring a difficult proposition. In Alaska, volcanoes are an intrinsic part of the culture, with over 100 volcanoes and volcanic fields that have been active in historic time monitored by the Alaska Volcano Observatory (AVO). Observations and research are performed using a suite of methods and tools in the fields of remote sensing, seismology, geodesy and geology, producing large volumes of geospatial data. Keyhole Markup Language (KML) offers a context in which these different, and in the past disparate, data can be displayed simultaneously. Dynamic links keep these data current, allowing it to be used in an operational capacity. KML is used to display information from the aviation color codes and activity alert levels for volcanoes to locations of thermal anomalies, earthquake locations and ash plume modeling. The dynamic refresh and time primitive are used to display volcano webcam and satellite image overlays in near real-time. In addition a virtual globe browser using KML, such as Google Earth, provides an interface to further information using the hyperlink, rich- text and flash-embedding abilities supported within object description balloons. By merging these data sets in an easy to use interface, a virtual globe browser provides a better tool for scientists and emergency managers alike to mitigate volcanic crises.

Development of Geospatial Map Based Election Portal

NASA Astrophysics Data System (ADS)

Gupta, A. Kumar Chandra; Kumar, P.; Vasanth Kumar, N.

2014-11-01

The Geospatial Delhi Limited (GSDL), a Govt. of NCT of Delhi Company formed in order to provide the geospatial information of National Capital Territory of Delhi (NCTD) to the Government of National Capital Territory of Delhi (GNCTD) and its organs such as DDA, MCD, DJB, State Election Department, DMRC etc., for the benefit of all citizens of Government of National Capital Territory of Delhi (GNCTD). This paper describes the development of Geospatial Map based Election portal (GMEP) of NCT of Delhi. The portal has been developed as a map based spatial decision support system (SDSS) for pertain to planning and management of Department of Chief Electoral Officer, and as an election related information searching tools (Polling Station, Assembly and parliamentary constituency etc.,) for the citizens of NCTD. The GMEP is based on Client-Server architecture model. It has been developed using ArcGIS Server 10.0 with J2EE front-end on Microsoft Windows environment. The GMEP is scalable to enterprise SDSS with enterprise Geo Database & Virtual Private Network (VPN) connectivity. Spatial data to GMEP includes delimited precinct area boundaries of Voters Area of Polling stations, Assembly Constituency, Parliamentary Constituency, Election District, Landmark locations of Polling Stations & basic amenities (Police Stations, Hospitals, Schools and Fire Stations etc.). GMEP could help achieve not only the desired transparency and easiness in planning process but also facilitates through efficient & effective tools for management of elections. It enables a faster response to the changing ground realities in the development planning, owing to its in-built scientific approach and open-ended design.

Improving the Slum Planning Through Geospatial Decision Support System

NASA Astrophysics Data System (ADS)

Shekhar, S.

2014-11-01

In India, a number of schemes and programmes have been launched from time to time in order to promote integrated city development and to enable the slum dwellers to gain access to the basic services. Despite the use of geospatial technologies in planning, the local, state and central governments have only been partially successful in dealing with these problems. The study on existing policies and programmes also proved that when the government is the sole provider or mediator, GIS can become a tool of coercion rather than participatory decision-making. It has also been observed that local level administrators who have adopted Geospatial technology for local planning continue to base decision-making on existing political processes. In this juncture, geospatial decision support system (GSDSS) can provide a framework for integrating database management systems with analytical models, graphical display, tabular reporting capabilities and the expert knowledge of decision makers. This assists decision-makers to generate and evaluate alternative solutions to spatial problems. During this process, decision-makers undertake a process of decision research - producing a large number of possible decision alternatives and provide opportunities to involve the community in decision making. The objective is to help decision makers and planners to find solutions through a quantitative spatial evaluation and verification process. The study investigates the options for slum development in a formal framework of RAY (Rajiv Awas Yojana), an ambitious program of Indian Government for slum development. The software modules for realizing the GSDSS were developed using the ArcGIS and Community -VIZ software for Gulbarga city.

GeoProMT: A Collaborative Platform Supporting Natural Hazards Project Management From Assessment to Resilience

NASA Astrophysics Data System (ADS)

Renschler, C.; Sheridan, M. F.; Patra, A. K.

2008-05-01

The impact and consequences of extreme geophysical events (hurricanes, floods, wildfires, volcanic flows, mudflows, etc.) on properties and processes should be continuously assessed by a well-coordinated interdisciplinary research and outreach approach addressing risk assessment and resilience. Communication between various involved disciplines and stakeholders is the key to a successful implementation of an integrated risk management plan. These issues become apparent at the level of decision support tools for extreme events/disaster management in natural and managed environments. The Geospatial Project Management Tool (GeoProMT) is a collaborative platform for research and training to document and communicate the fundamental steps in transforming information for extreme events at various scales for analysis and management. GeoProMT is an internet-based interface for the management of shared geo-spatial and multi-temporal information such as measurements, remotely sensed images, and other GIS data. This tool enhances collaborative research activities and the ability to assimilate data from diverse sources by integrating information management. This facilitates a better understanding of natural processes and enhances the integrated assessment of resilience against both the slow and fast onset of hazard risks. Fundamental to understanding and communicating complex natural processes are: (a) representation of spatiotemporal variability, extremes, and uncertainty of environmental properties and processes in the digital domain, (b) transformation of their spatiotemporal representation across scales (e.g. interpolation, aggregation, disaggregation.) during data processing and modeling in the digital domain, and designing and developing tools for (c) geo-spatial data management, and (d) geo-spatial process modeling and effective implementation, and (e) supporting decision- and policy-making in natural resources and hazard management at various spatial and temporal scales of interest. GeoProMT is useful for researchers, practitioners, and decision-makers, because it provides an integrated environmental system assessment and data management approach that considers the spatial and temporal scales and variability in natural processes. Particularly in the occurrence or onset of extreme events it can utilize the latest data sources that are available at variable scales, combine them with existing information, and update assessment products such as risk and vulnerability assessment maps. Because integrated geo-spatial assessment requires careful consideration of all the steps in utilizing data, modeling and decision-making formats, each step in the sequence must be assessed in terms of how information is being scaled. At the process scale various geophysical models (e.g. TITAN, LAHARZ, or many other examples) are appropriate for incorporation in the tool. Some examples that illustrate our approach include: 1) coastal parishes impacted by Hurricane Rita (Southwestern Louisiana), 2) a watershed affected by extreme rainfall induced debris-flows (Madison County, Virginia; Panabaj, Guatemala; Casita, Nicaragua), and 3) the potential for pyroclastic flows to threaten a city (Tungurahua, Ecuador). This research was supported by the National Science Foundation.

Broad-Scale Assessment of Fuel Treatment Opportunities

Treesearch

Patrick D. Miles; Kenneth E. Skog; Wayne D. Shepperd; Elizabeth D. Reinhardt; Roger D. Fight

2006-01-01

The Forest Inventory and Analysis (FIA) program has produced estimates of the extent and composition of the Nation?s forests for several decades. FIA data have been used with a flexible silvicultural thinning option, a fire hazard model for preharvest and postharvest fire hazard assessment, a harvest economics model, and geospatial data to produce a Web-based tool to...

Geospatial application of the Water Erosion Prediction Project (WEPP) Model

Treesearch

D. C. Flanagan; J. R. Frankenberger; T. A. Cochrane; C. S. Renschler; W. J. Elliot

2011-01-01

The Water Erosion Prediction Project (WEPP) model is a process-based technology for prediction of soil erosion by water at hillslope profile, field, and small watershed scales. In particular, WEPP utilizes observed or generated daily climate inputs to drive the surface hydrology processes (infiltration, runoff, ET) component, which subsequently impacts the rest of the...

Geospatial application of the Water Erosion Prediction Project (WEPP) model

Treesearch

D. C. Flanagan; J. R. Frankenberger; T. A. Cochrane; C. S. Renschler; W. J. Elliot

2013-01-01

At the hillslope profile and/or field scale, a simple Windows graphical user interface (GUI) is available to easily specify the slope, soil, and management inputs for application of the USDA Water Erosion Prediction Project (WEPP) model. Likewise, basic small watershed configurations of a few hillslopes and channels can be created and simulated with this GUI. However,...

Newspaper archives + text mining = rich sources of historical geo-spatial data

NASA Astrophysics Data System (ADS)

Yzaguirre, A.; Smit, M.; Warren, R.

2016-04-01

Newspaper archives are rich sources of cultural, social, and historical information. These archives, even when digitized, are typically unstructured and organized by date rather than by subject or location, and require substantial manual effort to analyze. The effort of journalists to be accurate and precise means that there is often rich geo-spatial data embedded in the text, alongside text describing events that editors considered to be of sufficient importance to the region or the world to merit column inches. A regional newspaper can add over 100,000 articles to its database each year, and extracting information from this data for even a single country would pose a substantial Big Data challenge. In this paper, we describe a pilot study on the construction of a database of historical flood events (location(s), date, cause, magnitude) to be used in flood assessment projects, for example to calibrate models, estimate frequency, establish high water marks, or plan for future events in contexts ranging from urban planning to climate change adaptation. We then present a vision for extracting and using the rich geospatial data available in unstructured text archives, and suggest future avenues of research.

A novel algorithm for fully automated mapping of geospatial ontologies

NASA Astrophysics Data System (ADS)

Chaabane, Sana; Jaziri, Wassim

2018-01-01

Geospatial information is collected from different sources thus making spatial ontologies, built for the same geographic domain, heterogeneous; therefore, different and heterogeneous conceptualizations may coexist. Ontology integrating helps creating a common repository of the geospatial ontology and allows removing the heterogeneities between the existing ontologies. Ontology mapping is a process used in ontologies integrating and consists in finding correspondences between the source ontologies. This paper deals with the "mapping" process of geospatial ontologies which consist in applying an automated algorithm in finding the correspondences between concepts referring to the definitions of matching relationships. The proposed algorithm called "geographic ontologies mapping algorithm" defines three types of mapping: semantic, topological and spatial.

Data to Decisions: Valuing the Societal Benefit of Geospatial Information

NASA Astrophysics Data System (ADS)

Pearlman, F.; Kain, D.

2016-12-01

The March 10-11, 2016 GEOValue workshop on "Data to Decisions" was aimed at creating a framework for identification and implementation of best practices that capture the societal value of geospatial information for both public and private uses. The end-to-end information flow starts with the earth observation and data acquisition systems, includes the full range of processes from geospatial information to decisions support systems, and concludes with the end user. Case studies, which will be described in this presentation, were identified for a range of applications. The goal was to demonstrate and compare approaches to valuation of geospatial information and forge a path forward for research that leads to standards of practice.

Allometric Scaling and Resource Limitations Model of Total Aboveground Biomass in Forest Stands: Site-scale Test of Model

NASA Astrophysics Data System (ADS)

CHOI, S.; Shi, Y.; Ni, X.; Simard, M.; Myneni, R. B.

2013-12-01

Sparseness in in-situ observations has precluded the spatially explicit and accurate mapping of forest biomass. The need for large-scale maps has raised various approaches implementing conjugations between forest biomass and geospatial predictors such as climate, forest type, soil property, and topography. Despite the improved modeling techniques (e.g., machine learning and spatial statistics), a common limitation is that biophysical mechanisms governing tree growth are neglected in these black-box type models. The absence of a priori knowledge may lead to false interpretation of modeled results or unexplainable shifts in outputs due to the inconsistent training samples or study sites. Here, we present a gray-box approach combining known biophysical processes and geospatial predictors through parametric optimizations (inversion of reference measures). Total aboveground biomass in forest stands is estimated by incorporating the Forest Inventory and Analysis (FIA) and Parameter-elevation Regressions on Independent Slopes Model (PRISM). Two main premises of this research are: (a) The Allometric Scaling and Resource Limitations (ASRL) theory can provide a relationship between tree geometry and local resource availability constrained by environmental conditions; and (b) The zeroth order theory (size-frequency distribution) can expand individual tree allometry into total aboveground biomass at the forest stand level. In addition to the FIA estimates, two reference maps from the National Biomass and Carbon Dataset (NBCD) and U.S. Forest Service (USFS) were produced to evaluate the model. This research focuses on a site-scale test of the biomass model to explore the robustness of predictors, and to potentially improve models using additional geospatial predictors such as climatic variables, vegetation indices, soil properties, and lidar-/radar-derived altimetry products (or existing forest canopy height maps). As results, the optimized ASRL estimates satisfactorily resemble the FIA aboveground biomass in terms of data distribution, overall agreement, and spatial similarity across scales. Uncertainties are quantified (ranged from 0.2 to 0.4) by taking into account the spatial mismatch (FIA plot vs. PRISM grid), heterogeneity (species composition), and an example bias scenario (= 0.2) in the root system extents.

Geospatial Indicators of Space and Place: A Review of Multilevel Studies of HIV Prevention and Care Outcomes Among Young Men Who Have Sex With Men in the United States.

PubMed

Bauermeister, José A; Connochie, Daniel; Eaton, Lisa; Demers, Michele; Stephenson, Rob

Young men who have sex with men (YMSM), particularly YMSM who are racial/ethnic minorities, are disproportionately affected by the human immunodeficiency virus (HIV) epidemic in the United States. These HIV disparities have been linked to demographic, social, and physical geospatial characteristics. The objective of this scoping review was to summarize the existing evidence from multilevel studies examining how geospatial characteristics are associated with HIV prevention and care outcomes among YMSM populations. Our literature search uncovered 126 peer-reviewed articles, of which 17 were eligible for inclusion based on our review criteria. Nine studies examined geospatial characteristics as predictors of HIV prevention outcomes. Nine of the 17 studies reported HIV care outcomes. From the synthesis regarding the current state of research around geospatial correlates of behavioral and biological HIV risk, we propose strategies to move the field forward in order to inform the design of future multilevel research and intervention studies for this population.

MapFactory - Towards a mapping design pattern for big geospatial data

NASA Astrophysics Data System (ADS)

Rautenbach, Victoria; Coetzee, Serena

2018-05-01

With big geospatial data emerging, cartographers and geographic information scientists have to find new ways of dealing with the volume, variety, velocity, and veracity (4Vs) of the data. This requires the development of tools that allow processing, filtering, analysing, and visualising of big data through multidisciplinary collaboration. In this paper, we present the MapFactory design pattern that will be used for the creation of different maps according to the (input) design specification for big geospatial data. The design specification is based on elements from ISO19115-1:2014 Geographic information - Metadata - Part 1: Fundamentals that would guide the design and development of the map or set of maps to be produced. The results of the exploratory research suggest that the MapFactory design pattern will help with software reuse and communication. The MapFactory design pattern will aid software developers to build the tools that are required to automate map making with big geospatial data. The resulting maps would assist cartographers and others to make sense of big geospatial data.

Lessons from Providing Professional Development in Remote Sensing for Community College Instructors

NASA Astrophysics Data System (ADS)

Allen, J. E.

2014-12-01

Two-year colleges and Tribal colleges are important centers for workforce education and training. A professional development program funded by the National Science Foundation's Advanced Technological Education Program, 2007-2011 and 2012-2015, is providing the resources needed by instructors at those colleges to develop courses and programs in remote sensing. The highly successful program, "Integrated Geospatial Education and Technology Training-Remote Sensing (iGETT-RS)" will complete its currently funded work in May 2015. 76 instructors of Geographic Information Systems (GIS) from all over the country will have been served. Each of them will have spent 18 months on the project, participating in two Summer Institutes at NASA and USGS and in monthly webinars on science and technology of remote sensing. iGETT-RS participants have created their own exercises and "concept modules" for the classroom, and many have created new courses and new programs across the country. As the external evaluator for iGETT-RS expressed it, the impact on project participants can "only be described as transformational." Viewers of this presentation will learn about the iGETT-RS project design and approach; successes, failures and lessons learned by the staff; and how to access the workshop materials and participant-authored classroom resources. Viewers will also learn about the Geospatial Technology Competency Model at the US Department of Labor, and about specifications for the Remote Sensing Model Course recently developed by the National Geospatial Technology Center to provide invaluable frameworks for faculty, students, administrators and employers.

Geospatial Data Standards for Indian Water Resources Systems

NASA Astrophysics Data System (ADS)

Goyal, A.; Tyagi, H.; Gosain, A. K.; Khosa, R.

2016-12-01

Sustainable management of water resources is fundamental to the socio-economic development of any nation. There is an increasing degree of dependency on digital geographical data for monitoring, planning, managing and preserving the water resources and environmental quality. But the rising sophistication associated with the sharing of geospatial data among organizations or users, demands development of data standards for seamless information exchange among collaborators. Therefore, due to the realization that these datasets are vital for efficient use of Geographical Information Systems, there is a growing emphasis on data standards for modeling, encoding and communicating spatial data. Real world hydrologic interactions represented in a digital framework requires geospatial standards that may vary in contexts like: governance, resource inventory, cultural diversity, identifiers, role and scale. Though the prevalent standards for the hydrology data facilitate a particular need in a particular context but they lack a holistic approach. However, several worldwide initiatives such as Consortium for the Advancement of Hydrologic Sciences Inc. (USA), Infrastructure for Spatial Information in the European Community (Europe), Australian Water Resources Information System, etc., endeavour to address this issue of hydrology specific spatial data standards in a wholesome manner. But unfortunately there is no such provision for hydrology data exchange within the Indian community. Moreover, these standards somehow fail in providing powerful communication of the spatial hydrologic data. This study thus investigates the shortcomings of the existing industry standards for the hydrologic data models and then demonstrates a set of requirements for effective exchange of the hydrologic information in the Indian scenario.

Results of an Experimental Exploration of Advanced Automated Geospatial Tools: Agility in Complex Planning

DTIC Science & Technology

2009-06-01

AUTOMATED GEOSPATIAL TOOLS : AGILITY IN COMPLEX PLANNING Primary Topic: Track 5 – Experimentation and Analysis Walter A. Powell [STUDENT] - GMU...TITLE AND SUBTITLE Results of an Experimental Exploration of Advanced Automated Geospatial Tools : Agility in Complex Planning 5a. CONTRACT NUMBER...Std Z39-18 Abstract Typically, the development of tools and systems for the military is requirement driven; systems are developed to meet

Architecture of the local spatial data infrastructure for regional climate change research

NASA Astrophysics Data System (ADS)

Titov, Alexander; Gordov, Evgeny

2013-04-01

Georeferenced datasets (meteorological databases, modeling and reanalysis results, etc.) are actively used in modeling and analysis of climate change for various spatial and temporal scales. Due to inherent heterogeneity of environmental datasets as well as their size which might constitute up to tens terabytes for a single dataset studies in the area of climate and environmental change require a special software support based on SDI approach. A dedicated architecture of the local spatial data infrastructure aiming at regional climate change analysis using modern web mapping technologies is presented. Geoportal is a key element of any SDI, allowing searching of geoinformation resources (datasets and services) using metadata catalogs, producing geospatial data selections by their parameters (data access functionality) as well as managing services and applications of cartographical visualization. It should be noted that due to objective reasons such as big dataset volume, complexity of data models used, syntactic and semantic differences of various datasets, the development of environmental geodata access, processing and visualization services turns out to be quite a complex task. Those circumstances were taken into account while developing architecture of the local spatial data infrastructure as a universal framework providing geodata services. So that, the architecture presented includes: 1. Effective in terms of search, access, retrieval and subsequent statistical processing, model of storing big sets of regional georeferenced data, allowing in particular to store frequently used values (like monthly and annual climate change indices, etc.), thus providing different temporal views of the datasets 2. General architecture of the corresponding software components handling geospatial datasets within the storage model 3. Metadata catalog describing in detail using ISO 19115 and CF-convention standards datasets used in climate researches as a basic element of the spatial data infrastructure as well as its publication according to OGC CSW (Catalog Service Web) specification 4. Computational and mapping web services to work with geospatial datasets based on OWS (OGC Web Services) standards: WMS, WFS, WPS 5. Geoportal as a key element of thematic regional spatial data infrastructure providing also software framework for dedicated web applications development To realize web mapping services Geoserver software is used since it provides natural WPS implementation as a separate software module. To provide geospatial metadata services GeoNetwork Opensource (http://geonetwork-opensource.org) product is planned to be used for it supports ISO 19115/ISO 19119/ISO 19139 metadata standards as well as ISO CSW 2.0 profile for both client and server. To implement thematic applications based on geospatial web services within the framework of local SDI geoportal the following open source software have been selected: 1. OpenLayers JavaScript library, providing basic web mapping functionality for the thin client such as web browser 2. GeoExt/ExtJS JavaScript libraries for building client-side web applications working with geodata services. The web interface developed will be similar to the interface of such popular desktop GIS applications, as uDIG, QuantumGIS etc. The work is partially supported by RF Ministry of Education and Science grant 8345, SB RAS Program VIII.80.2.1 and IP 131.

RockFall analyst: A GIS extension for three-dimensional and spatially distributed rockfall hazard modeling

NASA Astrophysics Data System (ADS)

Lan, Hengxing; Derek Martin, C.; Lim, C. H.

2007-02-01

Geographic information system (GIS) modeling is used in combination with three-dimensional (3D) rockfall process modeling to assess rockfall hazards. A GIS extension, RockFall Analyst (RA), which is capable of effectively handling large amounts of geospatial information relative to rockfall behaviors, has been developed in ArcGIS using ArcObjects and C#. The 3D rockfall model considers dynamic processes on a cell plane basis. It uses inputs of distributed parameters in terms of raster and polygon features created in GIS. Two major components are included in RA: particle-based rockfall process modeling and geostatistics-based rockfall raster modeling. Rockfall process simulation results, 3D rockfall trajectories and their velocity features either for point seeders or polyline seeders are stored in 3D shape files. Distributed raster modeling, based on 3D rockfall trajectories and a spatial geostatistical technique, represents the distribution of spatial frequency, the flying and/or bouncing height, and the kinetic energy of falling rocks. A distribution of rockfall hazard can be created by taking these rockfall characteristics into account. A barrier analysis tool is also provided in RA to aid barrier design. An application of these modeling techniques to a case study is provided. The RA has been tested in ArcGIS 8.2, 8.3, 9.0 and 9.1.

Short note: the experimental geopotential model XGM2016

NASA Astrophysics Data System (ADS)

Pail, R.; Fecher, T.; Barnes, D.; Factor, J. F.; Holmes, S. A.; Gruber, T.; Zingerle, P.

2018-04-01

As a precursor study for the upcoming combined Earth Gravitational Model 2020 (EGM2020), the Experimental Gravity Field Model XGM2016, parameterized as a spherical harmonic series up to degree and order 719, is computed. XGM2016 shares the same combination methodology as its predecessor model GOCO05c (Fecher et al. in Surv Geophys 38(3): 571-590, 2017. doi: 10.1007/s10712-016-9406-y). The main difference between these models is that XGM2016 is supported by an improved terrestrial data set of 15^' × 15^' gravity anomaly area-means provided by the United States National Geospatial-Intelligence Agency (NGA), resulting in significant upgrades compared to existing combined gravity field models, especially in continental areas such as South America, Africa, parts of Asia, and Antarctica. A combination strategy of relative regional weighting provides for improved performance in near-coastal ocean regions, including regions where the altimetric data are mostly unchanged from previous models. Comparing cumulative height anomalies, from both EGM2008 and XGM2016 at degree/order 719, yields differences of 26 cm in Africa and 40 cm in South America. These differences result from including additional information of satellite data, as well as from the improved ground data in these regions. XGM2016 also yields a smoother Mean Dynamic Topography with significantly reduced artifacts, which indicates an improved modeling of the ocean areas.

Mapping and Analysis of Forest and Land Fire Potential Using Geospatial Technology and Mathematical Modeling

NASA Astrophysics Data System (ADS)

Suliman, M. D. H.; Mahmud, M.; Reba, M. N. M.; S, L. W.

2014-02-01

Forest and land fire can cause negative implications for forest ecosystems, biodiversity, air quality and soil structure. However, the implications involved can be minimized through effective disaster management system. Effective disaster management mechanisms can be developed through appropriate early warning system as well as an efficient delivery system. This study tried to focus on two aspects, namely by mapping the potential of forest fire and land as well as the delivery of information to users through WebGIS application. Geospatial technology and mathematical modeling used in this study for identifying, classifying and mapping the potential area for burning. Mathematical models used is the Analytical Hierarchy Process (AHP), while Geospatial technologies involved include remote sensing, Geographic Information System (GIS) and digital field data collection. The entire Selangor state was chosen as our study area based on a number of cases have been reported over the last two decades. AHP modeling to assess the comparison between the three main criteria of fuel, topography and human factors design. Contributions of experts directly involved in forest fire fighting operations and land comprising officials from the Fire and Rescue Department Malaysia also evaluated in this model. The study found that about 32.83 square kilometers of the total area of Selangor state are the extreme potential for fire. Extreme potential areas identified are in Bestari Jaya and Kuala Langat High Ulu. Continuity of information and terrestrial forest fire potential was displayed in WebGIS applications on the internet. Display information through WebGIS applications is a better approach to help the decision-making process at a high level of confidence and approximate real conditions. Agencies involved in disaster management such as Jawatankuasa Pengurusan Dan Bantuan Bencana (JPBB) of District, State and the National under the National Security Division and the Fire and Rescue Department Malaysia can use the end result of this study in preparation for the land and forest fires in the future.

One map policy (OMP) implementation strategy to accelerate mapping of regional spatial planing (RTRW) in Indonesia

NASA Astrophysics Data System (ADS)

Hasyim, Fuad; Subagio, Habib; Darmawan, Mulyanto

2016-06-01

A preparation of spatial planning documents require basic geospatial information and thematic accuracies. Recently these issues become important because spatial planning maps are impartial attachment of the regional act draft on spatial planning (PERDA). The needs of geospatial information in the preparation of spatial planning maps preparation can be divided into two major groups: (i). basic geospatial information (IGD), consist of of Indonesia Topographic maps (RBI), coastal and marine environmental maps (LPI), and geodetic control network and (ii). Thematic Geospatial Information (IGT). Currently, mostly local goverment in Indonesia have not finished their regulation draft on spatial planning due to some constrain including technical aspect. Some constrain in mapping of spatial planning are as follows: the availability of large scale ofbasic geospatial information, the availability of mapping guidelines, and human resources. Ideal conditions to be achieved for spatial planning maps are: (i) the availability of updated geospatial information in accordance with the scale needed for spatial planning maps, (ii) the guideline of mapping for spatial planning to support local government in completion their PERDA, and (iii) capacity building of local goverment human resources to completed spatial planning maps. The OMP strategies formulated to achieve these conditions are: (i) accelerating of IGD at scale of 1:50,000, 1: 25,000 and 1: 5,000, (ii) to accelerate mapping and integration of Thematic Geospatial Information (IGT) through stocktaking availability and mapping guidelines, (iii) the development of mapping guidelines and dissemination of spatial utilization and (iv) training of human resource on mapping technology.

An Automated End-To Multi-Agent Qos Based Architecture for Selection of Geospatial Web Services

NASA Astrophysics Data System (ADS)

Shah, M.; Verma, Y.; Nandakumar, R.

2012-07-01

Over the past decade, Service-Oriented Architecture (SOA) and Web services have gained wide popularity and acceptance from researchers and industries all over the world. SOA makes it easy to build business applications with common services, and it provides like: reduced integration expense, better asset reuse, higher business agility, and reduction of business risk. Building of framework for acquiring useful geospatial information for potential users is a crucial problem faced by the GIS domain. Geospatial Web services solve this problem. With the help of web service technology, geospatial web services can provide useful geospatial information to potential users in a better way than traditional geographic information system (GIS). A geospatial Web service is a modular application designed to enable the discovery, access, and chaining of geospatial information and services across the web that are often both computation and data-intensive that involve diverse sources of data and complex processing functions. With the proliferation of web services published over the internet, multiple web services may provide similar functionality, but with different non-functional properties. Thus, Quality of Service (QoS) offers a metric to differentiate the services and their service providers. In a quality-driven selection of web services, it is important to consider non-functional properties of the web service so as to satisfy the constraints or requirements of the end users. The main intent of this paper is to build an automated end-to-end multi-agent based solution to provide the best-fit web service to service requester based on QoS.

Next Generation Emission Measurements for Fugitive, Area Source, and Fence Line Applications?

EPA Science Inventory

Next generation emissions measurements (NGEM) is an EPA term for the rapidly advancing field of air pollutant sensor technologies, data integration concepts, and associated geospatial modeling strategies for source emissions measurements. Ranging from low coat sensors to satelli...

Next Generation Air Measurements for Fugitive, Area Source, and Fence Line Applications

EPA Science Inventory

Next generation air measurements (NGAM) is an EPA term for the advancing field of air pollutant sensor technologies, data integration concepts, and geospatial modeling strategies. Ranging from personal sensors to satellite remote sensing, NGAM systems may provide revolutionary n...

Geospatial Data Management Platform for Urban Groundwater

NASA Astrophysics Data System (ADS)

Gaitanaru, D.; Priceputu, A.; Gogu, C. R.

2012-04-01

Due to the large amount of civil work projects and research studies, large quantities of geo-data are produced for the urban environments. These data are usually redundant as well as they are spread in different institutions or private companies. Time consuming operations like data processing and information harmonisation represents the main reason to systematically avoid the re-use of data. The urban groundwater data shows the same complex situation. The underground structures (subway lines, deep foundations, underground parkings, and others), the urban facility networks (sewer systems, water supply networks, heating conduits, etc), the drainage systems, the surface water works and many others modify continuously. As consequence, their influence on groundwater changes systematically. However, these activities provide a large quantity of data, aquifers modelling and then behaviour prediction can be done using monitored quantitative and qualitative parameters. Due to the rapid evolution of technology in the past few years, transferring large amounts of information through internet has now become a feasible solution for sharing geoscience data. Furthermore, standard platform-independent means to do this have been developed (specific mark-up languages like: GML, GeoSciML, WaterML, GWML, CityML). They allow easily large geospatial databases updating and sharing through internet, even between different companies or between research centres that do not necessarily use the same database structures. For Bucharest City (Romania) an integrated platform for groundwater geospatial data management is developed under the framework of a national research project - "Sedimentary media modeling platform for groundwater management in urban areas" (SIMPA) financed by the National Authority for Scientific Research of Romania. The platform architecture is based on three components: a geospatial database, a desktop application (a complex set of hydrogeological and geological analysis tools) and a front-end geoportal service. The SIMPA platform makes use of mark-up transfer standards to provide a user-friendly application that can be accessed through internet to query, analyse, and visualise geospatial data related to urban groundwater. The platform holds the information within the local groundwater geospatial databases and the user is able to access this data through a geoportal service. The database architecture allows storing accurate and very detailed geological, hydrogeological, and infrastructure information that can be straightforwardly generalized and further upscaled. The geoportal service offers the possibility of querying a dataset from the spatial database. The query is coded in a standard mark-up language, and sent to the server through a standard Hyper Text Transfer Protocol (http) to be processed by the local application. After the validation of the query, the results are sent back to the user to be displayed by the geoportal application. The main advantage of the SIMPA platform is that it offers to the user the possibility to make a primary multi-criteria query, which results in a smaller set of data to be analysed afterwards. This improves both the transfer process parameters and the user's means of creating the desired query.

Development and deployment of a water-crop-nutrient simulation model embedded in a web application

NASA Astrophysics Data System (ADS)

Langella, Giuliano; Basile, Angelo; Coppola, Antonio; Manna, Piero; Orefice, Nadia; Terribile, Fabio

2016-04-01

It is long time by now that scientific research on environmental and agricultural issues spent large effort in the development and application of models for prediction and simulation in spatial and temporal domains. This is fulfilled by studying and observing natural processes (e.g. rainfall, water and chemicals transport in soils, crop growth) whose spatiotemporal behavior can be reproduced for instance to predict irrigation and fertilizer requirements and yield quantities/qualities. In this work a mechanistic model to simulate water flow and solute transport in the soil-plant-atmosphere continuum is presented. This desktop computer program was written according to the specific requirement of developing web applications. The model is capable to solve the following issues all together: (a) water balance and (b) solute transport; (c) crop modelling; (d) GIS-interoperability; (e) embedability in web-based geospatial Decision Support Systems (DSS); (f) adaptability at different scales of application; and (g) ease of code modification. We maintained the desktop characteristic in order to further develop (e.g. integrate novel features) and run the key program modules for testing and validation purporses, but we also developed a middleware component to allow the model run the simulations directly over the web, without software to be installed. The GIS capabilities allows the web application to make simulations in a user-defined region of interest (delimited over a geographical map) without the need to specify the proper combination of model parameters. It is possible since the geospatial database collects information on pedology, climate, crop parameters and soil hydraulic characteristics. Pedological attributes include the spatial distribution of key soil data such as soil profile horizons and texture. Further, hydrological parameters are selected according to the knowledge about the spatial distribution of soils. The availability and definition in the geospatial domain of these attributes allow the simulation outputs at a different spatial scale. Two different applications were implemented using the same framework but with different configurations of the software pieces making the physically based modelling chain: an irrigation tool simulating water requirements and their dates and a fertilization tool for optimizing in particular mineral nitrogen adds.

Uncertainty analysis in geospatial merit matrix–based hydropower resource assessment

DOE PAGES

Pasha, M. Fayzul K.; Yeasmin, Dilruba; Saetern, Sen; ...

2016-03-30

Hydraulic head and mean annual streamflow, two main input parameters in hydropower resource assessment, are not measured at every point along the stream. Translation and interpolation are used to derive these parameters, resulting in uncertainties. This study estimates the uncertainties and their effects on model output parameters: the total potential power and the number of potential locations (stream-reach). These parameters are quantified through Monte Carlo Simulation (MCS) linking with a geospatial merit matrix based hydropower resource assessment (GMM-HRA) Model. The methodology is applied to flat, mild, and steep terrains. Results show that the uncertainty associated with the hydraulic head ismore » within 20% for mild and steep terrains, and the uncertainty associated with streamflow is around 16% for all three terrains. Output uncertainty increases as input uncertainty increases. However, output uncertainty is around 10% to 20% of the input uncertainty, demonstrating the robustness of the GMM-HRA model. Hydraulic head is more sensitive to output parameters in steep terrain than in flat and mild terrains. Furthermore, mean annual streamflow is more sensitive to output parameters in flat terrain.« less

Gate-violation behavior at highway-rail grade crossings and the consequences: Using geo-Spatial modeling integrated with path analysis.

PubMed

Liu, Jun; Khattak, Asad J

2017-12-01

Drivers undertaking risky behaviors at highway-rail grade crossings are often severely injured in collisions with trains. Among these behaviors, gate-violation (referring to driving around or through the gates that were activated and lowered by an approaching train) seems to be one of the most dangerous actions a driver might take at a gated crossing; it may compromise the intended safety improvement made by adding gates at crossings. This study develops a nuanced conceptual framework that uses path analysis to explore the contributing factors to gate-violation behaviors and the correlation between gate-violation behaviors and the crash consequence - the driver injury severity. Further, using geo-spatial modeling techniques, this study explores whether the correlates of gate-violation behaviors and their associations with injury severity are stationary across diverse geographic contexts of the United States. Geo-spatial modeling shows that the correlates of gate-violation and its associations with injury severity vary substantially across the United States. Spatial variations in correlates of gate-violation and injury severity are mapped by estimating geographically weighted regressions; the maps can serve as an instrument for screening safety improvements and help identify regions that need safety improvements. For example, the results show that two-quadrant gates are more likely to have gate-violation crashes than four-quadrant gates in Iowa, Illinois, Wisconsin and Minnesota. These states may need to receive more attentions on the enforcement of inhibiting gate-violation at crossings with two-quadrant gates or have the priority over other states to upgrade these crossings to four-quadrant gates if financially feasible. Copyright © 2017. Published by Elsevier Ltd.

GPU based framework for geospatial analyses

NASA Astrophysics Data System (ADS)

Cosmin Sandric, Ionut; Ionita, Cristian; Dardala, Marian; Furtuna, Titus

2017-04-01

Parallel processing on multiple CPU cores is already used at large scale in geocomputing, but parallel processing on graphics cards is just at the beginning. Being able to use an simple laptop with a dedicated graphics card for advanced and very fast geocomputation is an advantage that each scientist wants to have. The necessity to have high speed computation in geosciences has increased in the last 10 years, mostly due to the increase in the available datasets. These datasets are becoming more and more detailed and hence they require more space to store and more time to process. Distributed computation on multicore CPU's and GPU's plays an important role by processing one by one small parts from these big datasets. These way of computations allows to speed up the process, because instead of using just one process for each dataset, the user can use all the cores from a CPU or up to hundreds of cores from GPU The framework provide to the end user a standalone tools for morphometry analyses at multiscale level. An important part of the framework is dedicated to uncertainty propagation in geospatial analyses. The uncertainty may come from the data collection or may be induced by the model or may have an infinite sources. These uncertainties plays important roles when a spatial delineation of the phenomena is modelled. Uncertainty propagation is implemented inside the GPU framework using Monte Carlo simulations. The GPU framework with the standalone tools proved to be a reliable tool for modelling complex natural phenomena The framework is based on NVidia Cuda technology and is written in C++ programming language. The code source will be available on github at https://github.com/sandricionut/GeoRsGPU Acknowledgement: GPU framework for geospatial analysis, Young Researchers Grant (ICUB-University of Bucharest) 2016, director Ionut Sandric

Impact of Drought on Groundwater and Soil Moisture - A Geospatial Tool for Water Resource Management

NASA Astrophysics Data System (ADS)

Ziolkowska, J. R.; Reyes, R.

2016-12-01

For many decades, recurring droughts in different regions in the US have been negatively impacting ecosystems and economic sectors. Oklahoma and Texas have been suffering from exceptional and extreme droughts in 2011-2014, with almost 95% of the state areas being affected (Drought Monitor, 2015). Accordingly, in 2011 alone, around 1.6 billion were lost in the agricultural sector alone as a result of drought in Oklahoma (Stotts 2011), and 7.6 billion in Texas agriculture (Fannin 2012). While surface water is among the instant indicators of drought conditions, it does not translate directly to groundwater resources that are the main source of irrigation water. Both surface water and groundwater are susceptible to drought, while groundwater depletion is a long-term process and might not show immediately. However, understanding groundwater availability is crucial for designing water management strategies and sustainable water use in the agricultural sector and other economic sectors. This paper presents an interactive geospatially weighted evaluation model and a tool at the same time to analyze groundwater resources that can be used for decision support in water management. The tool combines both groundwater and soil moisture changes in Oklahoma and Texas in 2003-2014, thus representing the most important indicators of agricultural and hydrological drought. The model allows for analyzing temporal and geospatial long-term drought at the county level. It can be expanded to other regions in the US and the world. The model has been validated with the Palmer Drought Index Severity Index to account for other indicators of meteorological drought. It can serve as a basis for an upcoming socio-economic and environmental analysis of drought events in the short and long-term in different geographic regions.

How bicycle level of traffic stress correlate with reported cyclist accidents injury severities: A geospatial and mixed logit analysis.

PubMed

Chen, Chen; Anderson, Jason C; Wang, Haizhong; Wang, Yinhai; Vogt, Rachel; Hernandez, Salvador

2017-11-01

Transportation agencies need efficient methods to determine how to reduce bicycle accidents while promoting cycling activities and prioritizing safety improvement investments. Many studies have used standalone methods, such as level of traffic stress (LTS) and bicycle level of service (BLOS), to better understand bicycle mode share and network connectivity for a region. However, in most cases, other studies rely on crash severity models to explain what variables contribute to the severity of bicycle related crashes. This research uniquely correlates bicycle LTS with reported bicycle crash locations for four cities in New Hampshire through geospatial mapping. LTS measurements and crash locations are compared visually using a GIS framework. Next, a bicycle injury severity model, that incorporates LTS measurements, is created through a mixed logit modeling framework. Results of the visual analysis show some geospatial correlation between higher LTS roads and "Injury" type bicycle crashes. It was determined, statistically, that LTS has an effect on the severity level of bicycle crashes and high LTS can have varying effects on severity outcome. However, it is recommended that further analyses be conducted to better understand the statistical significance and effect of LTS on injury severity. As such, this research will validate the use of LTS as a proxy for safety risk regardless of the recorded bicycle crash history. This research will help identify the clustering patterns of bicycle crashes on high-risk corridors and, therefore, assist with bicycle route planning and policy making. This paper also suggests low-cost countermeasures or treatments that can be implemented to address high-risk areas. Specifically, with the goal of providing safer routes for cyclists, such countermeasures or treatments have the potential to substantially reduce the number of fatalities and severe injuries. Published by Elsevier Ltd.

Using Watershed Boundaries to Map Adverse Health Outcomes: Examples From Nebraska, USA

PubMed Central

Corley, Brittany; Bartelt-Hunt, Shannon; Rogan, Eleanor; Coulter, Donald; Sparks, John; Baccaglini, Lorena; Howell, Madeline; Liaquat, Sidra; Commack, Rex; Kolok, Alan S

2018-01-01

In 2009, a paper was published suggesting that watersheds provide a geospatial platform for establishing linkages between aquatic contaminants, the health of the environment, and human health. This article is a follow-up to that original article. From an environmental perspective, watersheds segregate landscapes into geospatial units that may be relevant to human health outcomes. From an epidemiologic perspective, the watershed concept places anthropogenic health data into a geospatial framework that has environmental relevance. Research discussed in this article includes information gathered from the literature, as well as recent data collected and analyzed by this research group. It is our contention that the use of watersheds to stratify geospatial information may be both environmentally and epidemiologically valuable. PMID:29398918

Interoperability And Value Added To Earth Observation Data

NASA Astrophysics Data System (ADS)

Gasperi, J.

2012-04-01

Geospatial web services technology has provided a new means for geospatial data interoperability. Open Geospatial Consortium (OGC) services such as Web Map Service (WMS) to request maps on the Internet, Web Feature Service (WFS) to exchange vectors or Catalog Service for the Web (CSW) to search for geospatialized data have been widely adopted in the Geosciences community in general and in the remote sensing community in particular. These services make Earth Observation data available to a wider range of public users than ever before. The mapshup web client offers an innovative and efficient user interface that takes advantage of the power of interoperability. This presentation will demonstrate how mapshup can be effectively used in the context of natural disasters management.

United States Geological Survey (USGS) Natural Hazards Response

USGS Publications Warehouse

Lamb, Rynn M.; Jones, Brenda K.

2012-01-01

The primary goal of U.S. Geological Survey (USGS) Natural Hazards Response is to ensure that the disaster response community has access to timely, accurate, and relevant geospatial products, imagery, and services during and after an emergency event. To accomplish this goal, products and services provided by the National Geospatial Program (NGP) and Land Remote Sensing (LRS) Program serve as a geospatial framework for mapping activities of the emergency response community. Post-event imagery and analysis can provide important and timely information about the extent and severity of an event. USGS Natural Hazards Response will also support the coordination of remotely sensed data acquisitions, image distribution, and authoritative geospatial information production as required for use in disaster preparedness, response, and recovery operations.

Designing Crop Simulation Web Service with Service Oriented Architecture Principle

NASA Astrophysics Data System (ADS)

Chinnachodteeranun, R.; Hung, N. D.; Honda, K.

2015-12-01

Crop simulation models are efficient tools for simulating crop growth processes and yield. Running crop models requires data from various sources as well as time-consuming data processing, such as data quality checking and data formatting, before those data can be inputted to the model. It makes the use of crop modeling limited only to crop modelers. We aim to make running crop models convenient for various users so that the utilization of crop models will be expanded, which will directly improve agricultural applications. As the first step, we had developed a prototype that runs DSSAT on Web called as Tomorrow's Rice (v. 1). It predicts rice yields based on a planting date, rice's variety and soil characteristics using DSSAT crop model. A user only needs to select a planting location on the Web GUI then the system queried historical weather data from available sources and expected yield is returned. Currently, we are working on weather data connection via Sensor Observation Service (SOS) interface defined by Open Geospatial Consortium (OGC). Weather data can be automatically connected to a weather generator for generating weather scenarios for running the crop model. In order to expand these services further, we are designing a web service framework consisting of layers of web services to support compositions and executions for running crop simulations. This framework allows a third party application to call and cascade each service as it needs for data preparation and running DSSAT model using a dynamic web service mechanism. The framework has a module to manage data format conversion, which means users do not need to spend their time curating the data inputs. Dynamic linking of data sources and services are implemented using the Service Component Architecture (SCA). This agriculture web service platform demonstrates interoperability of weather data using SOS interface, convenient connections between weather data sources and weather generator, and connecting various services for running crop models for decision support.

Model of Higher GIS Education

ERIC Educational Resources Information Center

Jakab, Imrich; Ševcík, Michal; Grežo, Henrich

2017-01-01

The methods of geospatial data processing are being continually innovated, and universities that are focused on educating experts in Environmental Science should reflect this reality with an elaborate and purpose-built modernization of the education process, education content, as well as learning conditions. Geographic Information Systems (GIS)…

Business models for implementing geospatial technologies in transportation decision-making : GIS-T symposium, April 8, 2009.

DOT National Transportation Integrated Search

2009-04-08

In 2005 and 2006, the Federal Highway Administration (FHWA) Office of Interstate and Border Planning (HEPI), along with several state transportation executives, conducted a series of site visits to transportation agencies and GIS vendors to identify ...

National Geospatial-Intelligence Agency (NGA) Calibration Target Placements during HI-SCALE (Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems)

DOE Data Explorer

Kalukin, Andrew; Endo, Satashi

2016-08-30

Test the feasibility of incorporating atmospheric models to improve simulation algorithms of image collection, developed at NGA. Various calibration objects will be used to compare simulated image products with real image products.

USING REMORE SENSING AND LANDSCAPE ECOLOGY TO ASSESS THE CONDITION OF GREAT LAKES WETLANDS

EPA Science Inventory

Geospatial modeling approaches are being used to locate and assess the condition of natural resources (particularly wetland ecosystems) in the Great Lakes Basin. These assessments involve measuring landscape characteristics at multiple scales, primarily focusing

on surface...

Integrated web system of geospatial data services for climate research

NASA Astrophysics Data System (ADS)

Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander

2016-04-01

Georeferenced datasets are currently actively used for modeling, interpretation and forecasting of climatic and ecosystem changes on different spatial and temporal scales. Due to inherent heterogeneity of environmental datasets as well as their huge size (up to tens terabytes for a single dataset) a special software supporting studies in the climate and environmental change areas is required. An approach for integrated analysis of georefernced climatological data sets based on combination of web and GIS technologies in the framework of spatial data infrastructure paradigm is presented. According to this approach a dedicated data-processing web system for integrated analysis of heterogeneous georeferenced climatological and meteorological data is being developed. It is based on Open Geospatial Consortium (OGC) standards and involves many modern solutions such as object-oriented programming model, modular composition, and JavaScript libraries based on GeoExt library, ExtJS Framework and OpenLayers software. This work is supported by the Ministry of Education and Science of the Russian Federation, Agreement #14.613.21.0037.

A program for handling map projections of small-scale geospatial raster data

USGS Publications Warehouse

Finn, Michael P.; Steinwand, Daniel R.; Trent, Jason R.; Buehler, Robert A.; Mattli, David M.; Yamamoto, Kristina H.

2012-01-01

Scientists routinely accomplish small-scale geospatial modeling using raster datasets of global extent. Such use often requires the projection of global raster datasets onto a map or the reprojection from a given map projection associated with a dataset. The distortion characteristics of these projection transformations can have significant effects on modeling results. Distortions associated with the reprojection of global data are generally greater than distortions associated with reprojections of larger-scale, localized areas. The accuracy of areas in projected raster datasets of global extent is dependent on spatial resolution. To address these problems of projection and the associated resampling that accompanies it, methods for framing the transformation space, direct point-to-point transformations rather than gridded transformation spaces, a solution to the wrap-around problem, and an approach to alternative resampling methods are presented. The implementations of these methods are provided in an open-source software package called MapImage (or mapIMG, for short), which is designed to function on a variety of computer architectures.

Creating a Coastal National Elevation Database (CoNED) for science and conservation applications

USGS Publications Warehouse

Thatcher, Cindy A.; Brock, John C.; Danielson, Jeffrey J.; Poppenga, Sandra K.; Gesch, Dean B.; Palaseanu-Lovejoy, Monica; Barras, John; Evans, Gayla A.; Gibbs, Ann

2016-01-01

The U.S. Geological Survey is creating the Coastal National Elevation Database, an expanding set of topobathymetric elevation models that extend seamlessly across coastal regions of high societal or ecological significance in the United States that are undergoing rapid change or are threatened by inundation hazards. Topobathymetric elevation models are raster datasets useful for inundation prediction and other earth science applications, such as the development of sediment-transport and storm surge models. These topobathymetric elevation models are being constructed by the broad regional assimilation of numerous topographic and bathymetric datasets, and are intended to fulfill the pressing needs of decision makers establishing policies for hazard mitigation and emergency preparedness, coastal managers tasked with coastal planning compatible with predictions of inundation due to sea-level rise, and scientists investigating processes of coastal geomorphic change. A key priority of this coastal elevation mapping effort is to foster collaborative lidar acquisitions that meet the standards of the USGS National Geospatial Program's 3D Elevation Program, a nationwide initiative to systematically collect high-quality elevation data. The focus regions are located in highly dynamic environments, for example in areas subject to shoreline change, rapid wetland loss, hurricane impacts such as overwash and wave scouring, and/or human-induced changes to coastal topography.

77 FR 67831 - Announcement of National Geospatial Advisory Committee Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-14

... from governmental, private sector, non-profit, and academic organizations, has been established to... Dialogue --National Address Database --Geospatial Priorities --NGAC Subcommittee Activities --FGDC Update...

Borderless Geospatial Web (bolegweb)

NASA Astrophysics Data System (ADS)

Cetl, V.; Kliment, T.; Kliment, M.

2016-06-01

The effective access and use of geospatial information (GI) resources acquires a critical value of importance in modern knowledge based society. Standard web services defined by Open Geospatial Consortium (OGC) are frequently used within the implementations of spatial data infrastructures (SDIs) to facilitate discovery and use of geospatial data. This data is stored in databases located in a layer, called the invisible web, thus are ignored by search engines. SDI uses a catalogue (discovery) service for the web as a gateway to the GI world through the metadata defined by ISO standards, which are structurally diverse to OGC metadata. Therefore, a crosswalk needs to be implemented to bridge the OGC resources discovered on mainstream web with those documented by metadata in an SDI to enrich its information extent. A public global wide and user friendly portal of OGC resources available on the web ensures and enhances the use of GI within a multidisciplinary context and bridges the geospatial web from the end-user perspective, thus opens its borders to everybody. Project "Crosswalking the layers of geospatial information resources to enable a borderless geospatial web" with the acronym BOLEGWEB is ongoing as a postdoctoral research project at the Faculty of Geodesy, University of Zagreb in Croatia (http://bolegweb.geof.unizg.hr/). The research leading to the results of the project has received funding from the European Union Seventh Framework Programme (FP7 2007-2013) under Marie Curie FP7-PEOPLE-2011-COFUND. The project started in the November 2014 and is planned to be finished by the end of 2016. This paper provides an overview of the project, research questions and methodology, so far achieved results and future steps.

Making geospatial data in ASF archive readily accessible

NASA Astrophysics Data System (ADS)

Gens, R.; Hogenson, K.; Wolf, V. G.; Drew, L.; Stern, T.; Stoner, M.; Shapran, M.

2015-12-01

The way geospatial data is searched, managed, processed and used has changed significantly in recent years. A data archive such as the one at the Alaska Satellite Facility (ASF), one of NASA's twelve interlinked Distributed Active Archive Centers (DAACs), used to be searched solely via user interfaces that were specifically developed for its particular archive and data sets. ASF then moved to using an application programming interface (API) that defined a set of routines, protocols, and tools for distributing the geospatial information stored in the database in real time. This provided a more flexible access to the geospatial data. Yet, it was up to user to develop the tools to get a more tailored access to the data they needed. We present two new approaches for serving data to users. In response to the recent Nepal earthquake we developed a data feed for distributing ESA's Sentinel data. Users can subscribe to the data feed and are provided with the relevant metadata the moment a new data set is available for download. The second approach was an Open Geospatial Consortium (OGC) web feature service (WFS). The WFS hosts the metadata along with a direct link from which the data can be downloaded. It uses the open-source GeoServer software (Youngblood and Iacovella, 2013) and provides an interface to include the geospatial information in the archive directly into the user's geographic information system (GIS) as an additional data layer. Both services are run on top of a geospatial PostGIS database, an open-source geographic extension for the PostgreSQL object-relational database (Marquez, 2015). Marquez, A., 2015. PostGIS essentials. Packt Publishing, 198 p. Youngblood, B. and Iacovella, S., 2013. GeoServer Beginner's Guide, Packt Publishing, 350 p.

Geospatial Information Response Team

USGS Publications Warehouse

Witt, Emitt C.

2010-01-01

Extreme emergency events of national significance that include manmade and natural disasters seem to have become more frequent during the past two decades. The Nation is becoming more resilient to these emergencies through better preparedness, reduced duplication, and establishing better communications so every response and recovery effort saves lives and mitigates the long-term social and economic impacts on the Nation. The National Response Framework (NRF) (http://www.fema.gov/NRF) was developed to provide the guiding principles that enable all response partners to prepare for and provide a unified national response to disasters and emergencies. The NRF provides five key principles for better preparation, coordination, and response: 1) engaged partnerships, 2) a tiered response, 3) scalable, flexible, and adaptable operations, 4) unity of effort, and 5) readiness to act. The NRF also describes how communities, tribes, States, Federal Government, privatesector, and non-governmental partners apply these principles for a coordinated, effective national response. The U.S. Geological Survey (USGS) has adopted the NRF doctrine by establishing several earth-sciences, discipline-level teams to ensure that USGS science, data, and individual expertise are readily available during emergencies. The Geospatial Information Response Team (GIRT) is one of these teams. The USGS established the GIRT to facilitate the effective collection, storage, and dissemination of geospatial data information and products during an emergency. The GIRT ensures that timely geospatial data are available for use by emergency responders, land and resource managers, and for scientific analysis. In an emergency and response capacity, the GIRT is responsible for establishing procedures for geospatial data acquisition, processing, and archiving; discovery, access, and delivery of data; anticipating geospatial needs; and providing coordinated products and services utilizing the USGS' exceptional pool of geospatial experts and equipment.

Geospatial resources for the geologic community: The USGS National Map

USGS Publications Warehouse

Witt, Emitt C.

2015-01-01

Geospatial data are a key component of investigating, interpreting, and communicating the geological sciences. Locating geospatial data can be time-consuming, which detracts from time spent on a study because these data are not obviously placed in central locations or are served from many disparate databases. The National Map of the US Geological Survey is a publicly available resource for accessing the geospatial base map data needs of the geological community from a central location. The National Map data are available through a viewer and download platform providing access to eight primary data themes, plus the US Topo and scanned historical topographic maps. The eight themes are elevation, orthoimagery, hydrography, geographic names, boundaries, transportation, structures, and land cover, and they are being offered for download as predefined tiles in formats supported by leading geographic information system software. Data tiles are periodically refreshed to capture the most current content and are an efficient method for disseminating and receiving geospatial information. Elevation data, for example, are offered as a download from the National Map as 1° × 1° tiles for the 10- and 30- m products and as 15′ × 15′ tiles for the higher-resolution 3-m product. Vector data sets with smaller file sizes are offered at several tile sizes and formats. Partial tiles are not a download option—any prestaged data that intersect the requesting bounding box will be, in their entirety, part of the download order. While there are many options for accessing geospatial data via the Web, the National Map represents authoritative sources of data that are documented and can be referenced for citation and inclusion in scientific publications. Therefore, National Map products and services should be part of a geologist’s first stop for geospatial information and data.

Mercury Concentrations in Fish and Sediment within Streams are Influenced by Watershed and Landscape Variables including Historical Gold Mining in the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Alpers, C. N.; Yee, J. L.; Ackerman, J. T.; Orlando, J. L.; Slotton, D. G.; Marvin-DiPasquale, M. C.

2015-12-01

We compiled available data on total mercury (THg) and methylmercury (MeHg) concentrations in fish tissue and streambed sediment from stream sites in the Sierra Nevada, California, to assess whether spatial data, including information on historical mining, can be used to make robust predictions of fish fillet tissue THg concentrations. A total of 1,271 fish from five species collected at 103 sites during 1980-2012 were used for the modeling effort: 210 brown trout, 710 rainbow trout, 79 Sacramento pikeminnow, 93 Sacramento sucker, and 179 smallmouth bass. Sediment data were used from 73 sites, including 106 analyses of THg and 77 analyses of MeHg. The dataset included 391 fish (mostly rainbow trout) and 28 sediment samples collected explicitly for this study during 2011-12. Spatial data on historical mining included the USGS Mineral Resources Data System and publicly available maps and satellite photos showing the areas of hydraulic mine pits and other placer mines. Modeling was done using multivariate linear regression and multi-model inference using Akaike Information Criteria. Results indicate that fish THg, accounting for species and length, can be predicted using geospatial data on mining history together with other landscape characteristics including land use/land cover. A model requiring only geospatial data, with an R2 value of 0.61, predicted fish THg correctly with respect to over-or-under 0.2 μg/g wet weight (a California regulatory threshold) for 108 of 121 (89 %) size-species combinations tested. Data for THg in streambed sediment did not improve the geospatial-only model. However, data for sediment MeHg, loss on ignition (organic content), and percent of sediment less than 0.063 mm resulted in a slightly improved model, with an R2 value of 0.63. It is anticipated that these models will be useful to the State of California and others to predict areas where mercury concentrations in fish are likely to exceed regulatory criteria.

Installation Mapping Enables Many Missions: The Benefits of and Barriers to Sharing Geospatial Data Assets

DTIC Science & Technology

2007-01-01

software applications and rely on the installations to supply them with the basic I&E geospatial data - sets for those applications. Such...spatial data in geospatially based tools to help track military supplies and materials all over the world. For instance, SDDCTEA developed IRRIS, a...regional offices or individual installations to supply the data and perform QA/QC in the process. The IVT program office worked with the installations and

Issues on Building Kazakhstan Geospatial Portal to Implement E-Government

NASA Astrophysics Data System (ADS)

Sagadiyev, K.; Kang, H. K.; Li, K. J.

2016-06-01

A main issue in developing e-government is about how to integrate and organize many complicated processes and different stakeholders. Interestingly geospatial information provides an efficient framework to integrate and organized them. In particular, it is very useful to integrate the process of land management in e-government with geospatial information framework, since most of land management tasks are related with geospatial properties. In this paper, we present a use-case on the e-government project in Kazakhstan for land management. We develop a geoportal to connect many tasks and different users via geospatial information framework. This geoportal is based on open source geospatial software including GeoServer, PostGIS, and OpenLayers. With this geoportal, we expect three achievements as follows. First we establish a transparent governmental process, which is one of main goal of e-government. Every stakeholder monitors what is happening in land management process. Second, we can significantly reduce the time and efforts in the government process. For example, a grant procedure for a building construction has taken more than one year with more than 50 steps. It is expected that this procedure would be reduced to 2 weeks by the geoportal framework. Third we provide a collaborative environment between different governmental structures via the geoportal, while many conflicts and mismatches have been a critical issue of governmental administration processes.