I-Corps: Using Remote Sensing and Geospatial Data for Informed Climate Adaptation, Mitigation, Resiliency, and Environmentally Friendly Solutions

I-Corps:利用遥感和地理空间数据提供明智的气候适应、减缓、恢复和环境友好解决方案

基本信息

项目摘要

The broader impact/commercial potential of this I-Corps project is the development of advancements in geophysics and engineering using environmental and geospatial solutions by utilizing models based on remote sensing and other spatial data. This project may impact areas such as urban sustainability, water quality and quantity monitoring, and risk analyses based on natural and climate change. Nowadays, with significant satellite remote sensing observations availability and advances in machine learning and cloud computing, new analyses could inform various stakeholders and policy makers. Satellite data are advantageous because of their spatial (from local up to global scale) and temporal coverage (some from decades ago) which could significantly lower the costs of alternative, ground-based, data collection and processing. Particular topics such as water quality monitoring (including Harmful Algal Bloom (HAB) detection) and identifying a resilient solution for pedestrians during heatwaves using satellite data are among the technology and services to be explored in this project.This I-Corps project is based on the development of high spatial and temporal resolution satellite data products using data processing, machine learning, and validation efforts. The project defines the existing gaps that could be filled with remote sensing and data processing technologies such as: algorithms to statistically develop a high spatio-temporal resolution downscaled satellite data; models to identify cool corridors and open street paths as a resilient solution and response to urban heat islands (UHIs) which will mitigate the adverse health impacts of UHIs; and algorithms for small water-bodies and lakes water quality monitoring using fine resolution satellite imageries.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
这个I-Corps项目更广泛的影响/商业潜力是,通过利用基于遥感和其他空间数据的模型,利用环境和地理空间解决方案,在地球物理学和工程学方面取得进展。该项目可能影响城市可持续性、水质和水量监测以及基于自然和气候变化的风险分析等领域。如今,随着大量卫星遥感观测的可用性以及机器学习和云计算的进步,新的分析可以为各种利益攸关方和政策制定者提供信息。卫星数据的优势在于其空间(从地方到全球范围)和时间(有些是几十年前的)覆盖面,这可以大大降低替代性地面数据收集和处理的成本。该项目将探讨的技术和服务包括水质监测(包括有害藻类水华(HAB)检测)和使用卫星数据为热浪期间的行人确定弹性解决方案等特定主题。该I-Corps项目基于使用数据处理、机器学习和验证工作开发高空间和时间分辨率卫星数据产品。该项目确定了可以用遥感和数据处理技术填补的现有空白,例如:在统计上开发高时空分辨率缩小尺度的卫星数据的算法;确定凉爽走廊和开放街道的模型,作为对城市热岛的弹性解决方案和应对措施,这将减轻城市热岛对健康的不利影响;该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

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)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Hamidreza Norouzi其他文献

Seasonal Lake Surface Temperature Trends in the Adirondacks via Remote Sensing
通过遥感观测阿迪朗达克山脉季节性湖泊表面温度趋势
Using Remote Sensing to Catalyze Urban Climate Studies in Underserved Communities
利用遥感促进服务不足社区的城市气候研究

Hamidreza Norouzi的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

相似国自然基金

Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data
  • 批准号:
    31070748
  • 批准年份:
    2010
  • 资助金额:
    34.0 万元
  • 项目类别:
    面上项目

相似海外基金

Next generation forest dynamics modelling using remote sensing data
使用遥感数据的下一代森林动力学建模
  • 批准号:
    MR/Y033981/1
  • 财政年份:
    2024
  • 资助金额:
    $ 5万
  • 项目类别:
    Fellowship
Feasibility study of remote exposure therapy using wearable devices
使用可穿戴设备进行远程暴露疗法的可行性研究
  • 批准号:
    23K02929
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Evaluation of countermeasures against heat illness from both hardware and software perspectives using satellite remote sensing and human flow data
利用卫星遥感和人流数据从硬件和软件角度评估中暑对策
  • 批准号:
    23K13457
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
Remote Intravascular Pressure Sensing using Ultrasound
使用超声波进行远程血管内压力传感
  • 批准号:
    10648240
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
Assessing the interplay between stress, health, behavior, and inflammatory gene expression response to wildfire smoke exposures using community engaged and remote sampling approaches - Brown Div Supp
使用社区参与和远程采样方法评估压力、健康、行为和炎症基因表达对野火烟雾暴露的反应之间的相互作用 - Brown Div Supp
  • 批准号:
    10707654
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
Remote sensing of river flow using uncrewed aerial systems (UAS) and satellite platforms
使用无人航空系统(UAS)和卫星平台遥感河流流量
  • 批准号:
    2882137
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Studentship
A novel method for remote assessment of exercise capacity using a telehealth platform and a wearable medical device
使用远程医疗平台和可穿戴医疗设备远程评估运动能力的新方法
  • 批准号:
    10052835
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Collaborative R&D
Development of Architectural Educational Reference Tools in Remote and Asynchronous Environments using Object VR
使用对象 VR 在远程和异步环境中开发建筑教育参考工具
  • 批准号:
    23K02643
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Partners IN CONTROL: Using Remote MonitorINg teChnology with cOmmuNity healTh woRkers to support hypertensiOn management for Latinx patients
控制合作伙伴:与社区卫生工作者一起使用远程监测技术来支持拉丁裔患者的高血压管理
  • 批准号:
    10669469
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
Using remote sensing and machine learning to explore the spatial patterning of poverty and inequality
利用遥感和机器学习探索贫困和不平等的空间格局
  • 批准号:
    2883392
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Studentship
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了