Synthesis of remote sensing and novel ground truth sensors to develop high resolution soil moisture forecasts in China and the UK

综合遥感和新型地面实况传感器，开发中国和英国的高分辨率土壤湿度预报

• 批准号: ST/N006836/1
• 负责人: Simon Pearson
• 金额: $ 125.81万
• 依托单位: University of Lincoln
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FN006836%2F1
• 关键词: Synthesis; remote; sensing; novel; ground

The availability of water is a key driver of agricultural productivity. It directly impacts plant growth, and in many countries and locations it is in short or over supply. The impact of water availability on global food production is seen as a key global risk and challenge. Water availability is a hugely contentious international issue, and global climate change, potentially driving increased droughts and flooding, is considered a compounding factor. This projects seeks to develop agri-tech solutions to help alleviate the issue of water in agriculture, and for producers to ultimately drive water use efficiency. Soil moisture directly impacts crop growth, it drives irrigation systems and once a soil has reached its holding capacity excess water rapidly runs into the drainage system, potentially impacting flood risk and system drainage capacity. One of the most significant challenges within the water debate is that there are few simple and reliable systems to measure soil moisture. It is difficult to accurately measure. Techniques developed include spot THD capacitance sensors, the use of neutron probes and more recently the use of remote sensing techniques. Currently, there is no system to measure soil moisture distribution accurately across a field, and the resolution of remote sensing has not been sufficient for agricultural application, or local water management to reduce flood risk. In this project we will bring together a suite of new technologies which increase the resolution of soil moisture measurement to render it applicable for agricultural application on a field, as well as, landscape scale.The project will deploy two new sensors (one static, one mobile) within China that measures soil moisture content as a function of the albedo of cosmically generated fast neutrons (Cosmos sensor, designed by Hydroinova, US). The static sensor measures soil moisture within a field up to a 200m radius from the measurement point. A mesh of static sensors will be deployed within Henan and Hebei province (which produces 40% wheat of China), China. The mobile sensor will be deployed on a bespoke autonomous vehicle or rover to measure soil moisture variation within a field. The vehicle will be developed within the project and will be the first autonomous deployment of this sensor technology. Data from the soil moisture sensors will be used to calibrate the InSARS sensor on the Sentinel-1 satellite to monitor soil moisture within China to within a 500m x 500m resolution. This is a 5-fold improvement on current resolution from SARS. Ultimately, the technology will enable near real time forecasts of soil moisture at a field scale. This information will be invaluable to agricultural producers and for flood risk forecasting, including key insights to improve water use efficiency, irrigation practices, land drainage and the implementation of precision agricultural techniques. This is an ambitious multi disciplinary project. The project coordinates the expertise of four key groups, the University of Lincoln (robotics, mapping and deployment of autonomous vehicles), the Institute of Ecology and Agrometeorology (IEAM) of Chinese Academy of Meteorological Sciences, University of Information Science &Technology, the Centre for Ecology and Hydrology (Wallingford) and the School of Geography and Earth Sciences, The University of Aberystwth. Considerable focus is placed on knowledge exchange, not just with the agricultural and hydrological communities, but also between international partners within the project. We anticipate that the UK will benefit from understanding the challenges of developing sensor networks in China, with significant differences in scale and environment. The Chinese team will spend considerable periods embedded with the UK academics to learn new skills in remote sensing, sensor deployment and autonomous vehicles.

水的可用性是农业生产力的关键驱动因素。它直接影响植物生长，在许多国家和地区，它供不应求。水资源供应对全球粮食生产的影响被视为一项关键的全球风险和挑战。水资源供应是一个极具争议的国际问题，全球气候变化可能导致干旱和洪水增加，被认为是一个复合因素。该项目旨在开发农业技术解决方案，以帮助缓解农业用水问题，并帮助生产者最终提高用水效率。土壤湿度直接影响作物生长，它驱动灌溉系统，一旦土壤达到其承载能力，多余的水就会迅速流入排水系统，潜在地影响洪水风险和系统排水能力。关于水的争论中最重要的挑战之一是，很少有简单可靠的系统来测量土壤湿度。很难精确测量。所开发的技术包括现场THD电容传感器、中子探针的使用以及最近使用的遥感技术。目前，还没有准确测量农田土壤水分分布的系统，遥感分辨率还不足以用于农业应用或当地水资源管理以降低洪水风险。在这个项目中，我们将汇集一套新技术，提高土壤湿度测量的分辨率，使其适用于农田农业应用，以及景观规模。该项目将在中国部署两个新的传感器（一个静态的，一个移动的），测量土壤水分含量作为宇宙产生的快中子反照率的函数（Cosmos传感器，由Hydroinova公司设计，美国）。静态传感器测量距测量点半径200m范围内的土壤湿度。静态传感器网将部署在中国河南省和河北省（占中国小麦产量的40%）。移动传感器将部署在定制的自动驾驶汽车或漫游车上，以测量田地内的土壤湿度变化。该车辆将在该项目中开发，并将成为该传感器技术的第一辆自动部署车辆。来自土壤湿度传感器的数据将用于校准Sentinel-1卫星上的InSARS传感器，以监测中国境内500米× 500米分辨率的土壤湿度。这比SARS目前的分辨率提高了5倍。最终，该技术将实现近乎实时的田间土壤湿度预测。这些信息对农业生产者和洪水风险预测将是无价的，包括提高用水效率、灌溉做法、土地排水和实施精准农业技术的关键见解。这是一个雄心勃勃的多学科项目。该项目协调了四个关键小组的专业知识，林肯大学（机器人、测绘和自动驾驶汽车的部署）、中国气象科学院生态与农业气象研究所（IEAM）、信息科学与技术大学、生态与水文中心（沃林福德）和阿伯里斯特斯大学地理与地球科学学院。相当多的重点放在知识交流上，不仅与农业和水文界交流，而且与项目内的国际伙伴交流。我们预计，英国将从了解中国在规模和环境上的巨大差异中发展传感器网络的挑战中受益。中国团队将花相当长的时间与英国学者一起学习遥感、传感器部署和自动驾驶汽车方面的新技能。

项目成果

Using Additional Moderator to Control the Footprint of a COSMOS Rover for Soil Moisture Measurement

• DOI: 10.1029/2020wr028478
• 发表时间: 2021-05
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: A. Badiee;J. Wallbank;J. P. Fentanes;E. Trill;Pete Scarlet;Yongchao Zhu;Grzegorz Cielniak;Hollie M. Coop

Kriging-based robotic exploration for soil moisture mapping using a cosmic-ray sensor

使用宇宙射线传感器进行基于克里金法的土壤湿度测绘机器人探索

• DOI: 10.1002/rob.21914
• 发表时间: 2019
• 期刊: Journal of Field Robotics
• 影响因子: 8.3
• 作者: Pulido Fentanes J

3D Soil Compaction Mapping through Kriging-based Exploration with a Mobile Robot

使用移动机器人通过基于克里金法的探索绘制 3D 土壤压实图

• DOI: 10.48550/arxiv.1803.08069
• 发表时间: 2018
• 作者: Fentanes J

Complex systems modelling of UK winter wheat yield

• DOI: 10.1016/j.compag.2023.107855
• 发表时间: 2023-04-27
• 期刊: COMPUTERS AND ELECTRONICS IN AGRICULTURE
• 影响因子: 8.3
• 作者: Hall，R. J.;Wei，H. -L.;Hanna，E.
• 通讯作者: Hanna，E.

3-D Soil Compaction Mapping Through Kriging-Based Exploration With a Mobile Robot

使用移动机器人通过基于克里金法的勘探绘制 3D 土壤压实图

• DOI: 10.1109/lra.2018.2849567
• 发表时间: 2018
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Fentanes J