Terrestrial Oil Spill Detection and Environmental Impact Monitoring using Multi-Source Earth Observation Data
利用多源地球观测数据进行陆地溢油检测和环境影响监测
基本信息
- 批准号:RGPIN-2015-05027
- 负责人:
- 金额:$ 1.11万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2017
- 资助国家:加拿大
- 起止时间:2017-01-01 至 2018-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Concerns about terrestrial or land-based oil and waste water spills have increased considerably in the past several years in the areas such as Alberta, Canada. For example, in spring 2012, a pipeline leaked 9.5 million liters of industrial waste water, the North America’s biggest spill in recent history, about 20 kilometres of Northeast of Zama City in Northern Alberta [1]. Many ecologically important ecosystems including rivers, lakes, wetlands and vegetation areas are threatened by such spills. With increasing establishment of pipelines and shipment of oil by other means such as rail (Railway Association of Canada) and higher possibility of oil spills, there is an immediate need to develop methods for early detection of spill, extraction and delineation of impacted areas, and monitoring the effectiveness of remediation process. Remote sensing is a rapid and cost effective technology that can be utilized for oil spill detection and environmental impact monitoring.
在过去几年中,在加拿大阿尔伯塔省等地区,对陆地或陆上石油和废水泄漏的担忧大大增加。例如,2012年春天,一条管道泄漏了950万升工业废水,这是北美近代史上最大的泄漏事件,发生在阿尔伯塔省北部扎马市东北约20公里处。许多具有重要生态意义的生态系统,包括河流、湖泊、湿地和植被区,都受到这种泄漏的威胁。随着管道的建立和石油通过铁路等其他方式运输的增加(加拿大铁路协会)以及石油泄漏的可能性增加,迫切需要开发早期检测泄漏,提取和划定受影响区域的方法,并监测补救过程的有效性。遥感是一种快速和成本效益高的技术,可用于溢油探测和环境影响监测。
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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Salehi, Bahram其他文献
Spectral analysis of wetlands using multi-source optical satellite imagery
- DOI:
10.1016/j.isprsjprs.2018.07.005 - 发表时间:
2018-10-01 - 期刊:
- 影响因子:12.7
- 作者:
Amani, Meisam;Salehi, Bahram;Brisco, Brian - 通讯作者:
Brisco, Brian
A new fully convolutional neural network for semantic segmentation of polarimetric SAR imagery in complex land cover ecosystem
- DOI:
10.1016/j.isprsjprs.2019.03.015 - 发表时间:
2019-05-01 - 期刊:
- 影响因子:12.7
- 作者:
Mohammadimanesh, Fariba;Salehi, Bahram;Molinier, Matthieu - 通讯作者:
Molinier, Matthieu
Temperature-Vegetation-soil Moisture Dryness Index (TVMDI)
- DOI:
10.1016/j.rse.2017.05.026 - 发表时间:
2017-08-01 - 期刊:
- 影响因子:13.5
- 作者:
Amani, Meisam;Salehi, Bahram;Dehnavi, Sahar - 通讯作者:
Dehnavi, Sahar
Automatic Moving Vehicles Information Extraction From Single-Pass WorldView-2 Imagery
- DOI:
10.1109/jstars.2012.2183117 - 发表时间:
2012-02-01 - 期刊:
- 影响因子:5.5
- 作者:
Salehi, Bahram;Zhang, Yun;Zhong, Ming - 通讯作者:
Zhong, Ming
Random forest wetland classification using ALOS-2 L-band, RADARSAT-2 C-band, and TerraSAR-X imagery
- DOI:
10.1016/j.isprsjprs.2017.05.010 - 发表时间:
2017-08-01 - 期刊:
- 影响因子:12.7
- 作者:
Mandianpari, Masoud;Salehi, Bahram;Motagh, Mandi - 通讯作者:
Motagh, Mandi
Salehi, Bahram的其他文献
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{{ truncateString('Salehi, Bahram', 18)}}的其他基金
Terrestrial Oil Spill Detection and Environmental Impact Monitoring using Multi-Source Earth Observation Data
利用多源地球观测数据进行陆地溢油检测和环境影响监测
- 批准号:
RGPIN-2015-05027 - 财政年份:2018
- 资助金额:
$ 1.11万 - 项目类别:
Discovery Grants Program - Individual
Terrestrial Oil Spill Detection and Environmental Impact Monitoring using Multi-Source Earth Observation Data
利用多源地球观测数据进行陆地溢油检测和环境影响监测
- 批准号:
RGPIN-2015-05027 - 财政年份:2016
- 资助金额:
$ 1.11万 - 项目类别:
Discovery Grants Program - Individual
Terrestrial Oil Spill Detection and Environmental Impact Monitoring using Multi-Source Earth Observation Data
利用多源地球观测数据进行陆地溢油检测和环境影响监测
- 批准号:
RGPIN-2015-05027 - 财政年份:2015
- 资助金额:
$ 1.11万 - 项目类别:
Discovery Grants Program - Individual
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%20创新%20油%20溢出%20清理%20产品%20使用%20微生物%20酶%20处理%20%20将%20最小化%20环境%20损害%20和%20减少%20清理%20成本%20by%2050%%20或%20更多
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