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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=684179
• 关键词: Assessment; soil; water; conditions; using

Summary***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.

* 土壤水分状况直接影响各种过程（渗透、径流、蒸发等）。控制着水和能量的循环农业、水文、气象等环境领域都与土壤水分状况密切相关。然而，尽管其重要性，在土壤水分条件的空间和时间变异的理解仍然是一个挑战。拟议的研究计划的总体目标是改善获得频繁的空间和时间分布的土壤水分条件，更好地了解水循环。它将通过以下具体目标来实现：a）开发和分析多频被动和主动微波土壤水分反演方法; B）估计和分析多时精细尺度土壤水分含量;和c）描述魁北克农田饱和区的特征。重点是提取和分析表层土壤水分、土壤水分剖面和饱和土壤的深度，并考虑到被动/主动微波数据的特性（频率、空间分辨率）以及土壤粗糙度和植被的变化。该研究计划将受益于2016年夏天在马尼托巴进行的SMAPVEX 16-MB现场活动的巨大数据集（http：//smapvex16-mb.espaceweb.usherbrooke.ca/）。它由土壤（湿度、温度和粗糙度）和植被（类型、高度、含水量等）的地面测量组成。这些数据是与星载无源和有源微波数据（SMOS、SMAP、RADARSAT-2、Sentinel-1、TerraSAR-X和ALOS-PALSAR）、帕尔斯（无源/有源L波段传感器）的机载测量和地面微波辐射计测量准同时收集的。拟议的方法包括：被动和主动微波模型的反演，现有土壤水分分解方法的调整，不同尺度土壤水分估计的协同研究，以及雷达模型/土壤模型/同化模型的组合，用于表征土壤表面和沿着一定深度的饱和农田。结果将使用地面测量进行验证。它们对于及早发现干旱、洪水和火灾以及发展预警系统将非常有用。此外，通过使用哨兵-1高时间频率合成孔径雷达数据，拟议的研究方案提供了将未来雷达卫星星座使命（发射日期定于2018年7月）数据用于业务应用的有趣实例。