Dual-Polarisation Weather Radar for Advanced Monitoring of Aerial Biodiversity (BioDAR)

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项目编号	NE/S001298/1
	Dual-Polarisation Weather Radar for Advanced Monitoring of Aerial Biodiversity (BioDAR)
	Christopher Hassall
主持机构	University of Leeds
项目开始年	2019
	2019
项目结束日期	2021-06-30
资助机构	UK-NERC
项目类别	Research Grant
项目经费	607143(GBP)
国家	英国
语种	英语
英文摘要	The BioDAR Project will revolutionise the way in which we record the abundance and diversity of animals that live in the air, by harnessing the power of next generation weather radar. Weather radar scan the entirety of the UK every 5 minutes, and similar types of radar are used around the world for the same purpose. These radar routinely detect bees and other insects, but since animals are not of interest to meteorologists, they are discarded as unwanted "noise". That "noise" is a veritable treasure trove of information on insect diversity and abundance, but what is required is a way to link what a radar sees to the insects that we wish to monitor. The BioDAR Project brings together leading ecologists and radar scientists to collaborate on a programme of work that will produce, test, and disseminate computer algorithms to turn radar noise into high quality biological data with the potential to produce a step change in the way in which we monitor the environment. In the first phase of the project, we will use computer scanning techniques that can image objects 1/10th the width of a human hair to produce high resolution 3D models of a range of 60 different insects of different shapes. Using software techniques from physics, we can simulate what the radar might see when each of those animals passes through the radar beam. The results of those simulations will be used to produce algorithms that can classify results from the radar data into different kinds of insects based on their shape, as well as quantifying the diversity and number of insects passing through the beam. In the second phase of the project, we will then test the classification algorithms by comparing our radar predictions against three different datasets. First, we will look at three existing datasets that have used (i) special radar called "vertical looking radar" to scan small areas of sky, (ii) a network of 18 suction traps that capture insects every day, and (iii) a network of 83 light traps that catch nocturnal moths. Next, we will conduct our own insect sampling using nets at a range of heights from 12m to 1km attached to balloons. Finally, we will attempt to produce our own insect assemblage in the radar beam using lab-reared bluebottle flies to saturate the air in different locations around the radar. These three tests will help us to understand how our algorithms perform in the field. In the third phase of the project, we will combine the lessons learned about our classification algorithms in the first and second phases to produce a national map of aerial insect biodiversity and abundance. This map will be used to investigate a pressing issue in conservation: the effect of human modification of the landscape on insects. We will examine this issue in three ways, by looking at the impacts of light pollution, urbanisation, and agri-environment schemes (which are designed to help nature on farmland). We would expect lower insect biodiversity and abundance near areas with high nocturnal light pollution, higher intensity of urbanisation, and in the absence of agri-environment schemes. The final part of the project will take everything that we have learned (the classification algorithms from phase 1, the validation studies in phase 2, and the national mapping data from phase 3, and make them available to all researchers and the general public. We will make all of our data and analysis transparent so that any researcher can replicate the work, which we hope will enable other countries to make use of our findings to apply the BioDAR approach to their own weather radar networks. The data will also be turned into an online portal which can be accessed by the general public to see insect biodiversity and abundance in an interface similar to a weather forecast. The final datasets will be of great interest to a range of end users, including local and national governments, farmers, and conservation groups.
来源学科分类	Natural Environment Research
文献类型	项目
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/87553
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	Christopher Hassall.Dual-Polarisation Weather Radar for Advanced Monitoring of Aerial Biodiversity (BioDAR).2019.