Assessment of soil water conditions using microwave remote sensing data

利用微波遥感数据评估土壤水状况

• 批准号: RGPIN-2017-05533
• 负责人: Magagi, Ramata
• 金额: $ 2.33万
• 依托单位: Université de Sherbrooke
• 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: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=633952
• 关键词: Assessment; soil; water; conditions; using

Soil water conditions affect directly the processes (infiltration, runoff, evaporation, etc.) governing the water and energy cycles. Several environmental domains such as agriculture, hydrology, meteorology, are closely related to soil water conditions. However, despite its importance, the understanding of the spatial and temporal variability in soil water conditions still remains a challenge. The general objective of the proposed research program is to improve the access to frequent spatial and temporal distributions of soil water conditions for a better understanding of the water cycle. It will be achieved through the following specific objectives: a) Develop and analyze a multifrequency passive and active microwave soil moisture retrieval method; b) Estimate and analyze a multitemporal fine-scale soil moisture content; and c) Characterize the saturated areas over agricultural fields in Quebec. The focus is on the extraction and the analysis of surface soil moisture, soil moisture profiles and the depth of saturated soils with respect to the characteristics of passive/active microwave data (frequency, spatial resolution) and the changes in both soil roughness and vegetation. The research program will benefit from the huge dataset of SMAPVEX16-MB field campaign that took place in Manitoba in the summer 2016 (http://smapvex16-mb.espaceweb.usherbrooke.ca/). It is composed of ground measurements of soil (moisture, temperature and roughness) and vegetation (types, height, water content, etc.) characteristics which were collected quasi-simultaneously with spaceborne passive and active microwave data (SMOS, SMAP, RADARSAT-2, Sentinel-1, TerraSAR-X, and ALOS-PALSAR), airborne measurements of PALS (Passive/Active L-band Sensor), and ground microwave radiometer measurements. The proposed methodology includes: inversion of passive and active microwave models, adaptation of an existing soil moisture disaggregation method, synergistic studies for soil moisture estimation at different scales, and the combination of radar model/soil model/assimilation model for the characterisation of saturated agricultural fields at both the soil surfaces and along a certain depth. Results will be validated using ground measurements. They will be very useful for the early detection of droughts, floods, and fires and for the development of warning systems. In addition, with the use of Sentinel-1 high temporal frequency synthetic aperture radar data, the proposed research program presents interesting examples of using the future RADARSAT Constellation Mission (launch date scheduled for July 2018) data for operational applications.

土壤水分条件直接影响控制水和能量循环的过程（入渗、径流、蒸发等）。农业、水文、气象等几个环境领域都与土壤水分状况密切相关。然而，尽管它很重要，但对土壤水分条件时空变化的理解仍然是一个挑战。提出的研究计划的总体目标是改善对土壤水分条件的频繁时空分布的获取，以便更好地了解水循环。具体目标如下：a)开发和分析一种多频被动和主动微波土壤水分反演方法；b)估算和分析多时相精细尺度土壤含水量；c)描绘魁北克农田上空饱和区域的特征。重点是根据被动/主动微波数据的特征（频率、空间分辨率）提取和分析表层土壤水分、土壤水分剖面和饱和土壤深度，以及土壤粗糙度和植被的变化。该研究项目将受益于2016年夏天在马尼托巴省进行的SMAPVEX16-MB现场活动的庞大数据集（http://smapvex16-mb.espaceweb.usherbrooke.ca/）。它由与星载被动和主动微波数据（SMOS、SMAP、RADARSAT-2、Sentinel-1、TerraSAR-X和ALOS-PALSAR）准同步采集的土壤（湿度、温度和粗糙度）和植被（类型、高度、含水量等）特征、机载pal（被动/主动l波段传感器）测量数据和地面微波辐射计测量数据组成。提出的方法包括：被动和主动微波模型的反演，现有土壤水分分解方法的改进，不同尺度土壤水分估算的协同研究，以及雷达模型/土壤模型/同化模型在土壤表面和一定深度上的饱和农田特征的组合。结果将通过地面测量进行验证。它们将对早期发现干旱、洪水和火灾以及发展预警系统非常有用。此外，通过使用Sentinel-1高时间频率合成孔径雷达数据，拟议的研究计划提供了将未来RADARSAT星座任务（发射日期定于2018年7月）数据用于作战应用的有趣示例。