Multi-sensor remote sensing of wetland change

湿地变化多传感器遥感

• 批准号: RGPIN-2022-04874
• 负责人: Millard, Koreen
• 金额: $ 1.89万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=754913
• 关键词: Multi; sensor; remote; sensing; wetland

This research will examine interactions between disturbances and peatland ecosystem change. There are three main objectives. 1) Develop methods to use remotely-sensed imagery and field data measurements to create accurate maps that can be updated regularly, and that capture peatland locations, vegetation and hydrologic conditions (e.g. wetness): Many areas of research (e.g. climate, weather and hydrological models), policy development and international agreements (e.g. UNFCCC, Paris agreement) require peatland maps. Previous research has largely focused on producing static data products at specific time intervals. This research will integrate time series analysis techniques, enabling the creation of timely maps that reflect natural and human induced impacts on peatland ecohydrological characteristics. 2) Develop methods to identify and characterize drought conditions in peatlands and to spatially model the susceptibility of wildfire occurrence using remotely-sensed imagery: Hydrology and surface water in peatlands is largely controlled by precipitation, which is monitored sparsely throughout boreal peatlands. Landscape-level hydrological precursors to wildfire in these systems are poorly studied and there exists no maps/data products of peatland wildfire likelihood. Accelerated burning in boreal peatlands will lead to a drastic increase in carbon emissions, yet the ability to predict peatland susceptibility to wildfire is limited. Through this research, remote-sensing methods will be developed to identify and characterize drought conditions in peatlands and to spatially model the susceptibility of wildfire occurrence. 3) Examine spatio-temporal variability of carbon losses from wildfire and other disturbances: Peatlands store and sequester more carbon than any other landscape, yet natural and anthropogenic disturbances can cause shifts in hydrologic and fire regimes, vegetation assemblages, and thawing permafrost, leading to changes in peatland carbon storage potential. Using remote sensing techniques coupled with intense field monitoring at selected known disturbed and undisturbed sites, this research objective will link disturbances to changes in carbon storage and carbon loss. Pre- and post-fire surface measurements derived from remote sensing will be used to model carbon loss. This research will lead to advances in peatland ecohydrology, remote sensing and fire science by developing methods of fire susceptibility mapping, ensuring quicker fire response and advanced warning for potential large fires and smoldering, enhancing the safety and security of Canadians. Novel remote sensing techniques will be developed, resulting in improved mapping products that will contribute to earth systems and climate models, and inform the development of nature-based climate solutions. It will also contribute to critically needed advancements in understanding the effects of natural and anthropogenic disturbances on these carbon rich environments.

本研究将探讨干扰与泥炭地生态系统变化之间的相互作用。有三个主要目标。1)开发使用遥感图像和实地数据测量的方法，以创建可定期更新的精确地图，并捕获泥炭地位置、植被和水文条件（如湿度）：许多研究领域（如气候、天气和水文模型）、政策制定和国际协议（如《联合国气候变化框架公约》、《巴黎协定》）都需要泥炭地地图。以前的研究主要集中在特定时间间隔产生静态数据产品。这项研究将整合时间序列分析技术，使及时绘制反映自然和人为对泥炭地生态水文特征影响的地图成为可能。2)开发识别和表征泥炭地干旱条件的方法，并利用遥感图像对野火发生的易感性进行空间模拟：泥炭地的水文和地表水主要受降水控制，而降水在整个北方泥炭地都很少监测。这些系统中野火的景观级水文前兆研究很少，并且没有泥炭地野火可能性的地图/数据产品。北方泥炭地的加速燃烧将导致碳排放量急剧增加，但预测泥炭地对野火的易感性的能力是有限的。通过这项研究，将开发遥感方法来识别和表征泥炭地的干旱条件，并建立野火发生易感性的空间模型。3)研究野火和其他干扰造成的碳损失的时空变异性：泥炭地储存和封存的碳比任何其他景观都多，但自然和人为干扰可能导致水文和火灾制度、植被组合和永久冻土融化的变化，从而导致泥炭地碳储存潜力的变化。利用遥感技术加上在选定的已知受干扰和未受干扰地点进行密集的实地监测，本研究目标将把干扰与碳储存和碳损失的变化联系起来。从遥感得到的火灾前和火灾后的地表测量数据将用于模拟碳损失。这项研究将通过开发火灾易感性测绘方法，促进泥炭地生态水文、遥感和火灾科学的发展，确保更快的火灾响应和对潜在的大火和阴燃的提前预警，增强加拿大人的安全和保障。将开发新的遥感技术，从而改进制图产品，为地球系统和气候模型作出贡献，并为制定基于自然的气候解决方案提供信息。它还将有助于在了解自然和人为干扰对这些富含碳的环境的影响方面取得迫切需要的进展。