Geostatistical software for merging multivariate data with various spatial supports
用于将多元数据与各种空间支持合并的地统计软件
基本信息
- 批准号:10006357
- 负责人:
- 金额:$ 22.49万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-05-15 至 2021-04-30
- 项目状态:已结题
- 来源:
- 关键词:AirAir PollutionAreaCategoriesCensusesCitiesCommunitiesComputer softwareDataData AnalysesData SetDevelopmentDimensionsEnvironmentEnvironmental EpidemiologyEpidemiologistEvaluationGeographyGeologyHealthHealth SciencesHealth StatusImageryIndividualInvestigationLeadLead levelsLinear ModelsLiteratureLocationMalignant NeoplasmsMeasurementMeasuresMeteorologyMethodsModelingMonitorOutcomePerformancePhaseProtocols documentationRadonRecordsResearchSamplingScienceServicesSmall Business Innovation Research GrantSoilSourceSpace ModelsTechniquesTechnologyTest ResultTestingTimeUncertaintyUnited States National Institutes of HealthValidationVariantVisualizationWaterbasecostdensitydesignimprovedinnovationland useprototypereconstructionremote sensingsimulationtheoriestoolusabilityuser-friendly
项目摘要
7. Project Summary/Abstract
A key component in any investigation of association and/or cause-effect relationships between the
environment and health outcomes is the availability of accurate models of exposure. Because the cost of
collecting field data is often prohibitive, it is critical to incorporate any source of secondary information available
to supplement sparse datasets. Secondary data can take many forms (e.g., continuous or categorical
measurement scale), display various sampling densities (e.g., data available everywhere or at specific
locations), and be recorded over different spatial supports (e.g., point observations, census tracts, rasters).
Surprisingly, there is currently no commercial software for the geostatistical treatment of multivariate space-
time data, including the merging of data layers measured on different spatial supports.
This SBIR project is developing the first commercial software to offer tools for geostatistical multivariate ST
interpolation and modeling of uncertainty. The research product will be a stand-alone module into the desktop
space-time visualization core developed by BioMedware, an Esri partner. These tools will be suited for the
analysis of data outside health sciences, such as in remote sensing, geochemistry or soil science, broadening
significantly the commercial market for the end product. This project will accomplish three aims:
Review the main spatial coregionalization models available in the geostatistical literature (i.e., traditional vs
extended, intrinsic) and compare their performances (i.e., prediction accuracy) and user-friendliness (i.e.,
ease of inference) for multivariate spatial interpolation through the cross-validation analysis of 4 datasets
dealing with mapping of water lead levels, radon, meteorological and geochemical data. The comparison
will include various cokriging types (i.e., one or several unbiasedness constraints) and other tools used by
environmental epidemiologists, such as nearest monitors, inverse distance or purely spatial kriging.
Develop and test a prototype module that will guide non-expert users through the fitting of a linear model of
coregionalization (LMC) and selection of an appropriate multivariate interpolation method (e.g., cokriging,
kriging with an external drift, regression kriging), followed by the spatial interpolation based on
BioMedware’s space-time visualization and analysis technology.
Conduct a usability study and identify additional methods and tools to consider in Phase II.
These technologic, scientific and commercial innovations will enhance our ability to model geostatistically
multivariate space-time phenomena and compute estimates and the associated uncertainty at the scale (e.g.
point location, census-tract level) the most relevant for environmental epidemiology.
7. 项目总结/文摘
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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PIERRE E GOOVAERTS其他文献
PIERRE E GOOVAERTS的其他文献
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{{ truncateString('PIERRE E GOOVAERTS', 18)}}的其他基金
Geostatistical Software for Non-Parametric Geostatistical Modeling of Uncertainty
用于不确定性非参数地统计建模的地统计软件
- 批准号:
10697081 - 财政年份:2023
- 资助金额:
$ 22.49万 - 项目类别:
Geostatistical software for merging multivariate data with various spatial supports
用于将多元数据与各种空间支持合并的地统计软件
- 批准号:
10468323 - 财政年份:2020
- 资助金额:
$ 22.49万 - 项目类别:
Geostatistical software for merging multivariate data with various spatial supports
用于将多元数据与各种空间支持合并的地统计软件
- 批准号:
10323718 - 财政年份:2020
- 资助金额:
$ 22.49万 - 项目类别:
Geostatistical software for spatial and multi-dimensional joinpoint regression analysis of time series of health outcomes
用于健康结果时间序列的空间和多维连接点回归分析的地统计软件
- 批准号:
9047005 - 财政年份:2016
- 资助金额:
$ 22.49万 - 项目类别:
Geostatistical software for space-time interpolation and uncertainty modeling
用于时空插值和不确定性建模的地统计软件
- 批准号:
9138888 - 财政年份:2013
- 资助金额:
$ 22.49万 - 项目类别:
Geostatistical software for space-time interpolation and uncertainty modeling
用于时空插值和不确定性建模的地统计软件
- 批准号:
8523583 - 财政年份:2013
- 资助金额:
$ 22.49万 - 项目类别:
A geostatistical framework for the multi-scale boundary analysis of space-time tr
时空TR多尺度边界分析的地统计框架
- 批准号:
8588323 - 财政年份:2012
- 资助金额:
$ 22.49万 - 项目类别:
A geostatistical framework for the multi-scale boundary analysis of space-time tr
时空TR多尺度边界分析的地统计框架
- 批准号:
8444188 - 财政年份:2012
- 资助金额:
$ 22.49万 - 项目类别:
Three-dimensional visualization, interactive analysis and contextual mapping of s
三维可视化、交互式分析和上下文映射
- 批准号:
7908050 - 财政年份:2010
- 资助金额:
$ 22.49万 - 项目类别:
SBIR PHASE II- TOPIC 234- AUTOMATED PATTERN RECOGNITION IN SATELLITE IMAGERY
SBIR 第二阶段 - 主题 234 - 卫星图像中的自动模式识别
- 批准号:
7952599 - 财政年份:2009
- 资助金额:
$ 22.49万 - 项目类别:
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