BioSpace: Using space-enabled remote sensing to deliver long term sustainable growth of biopesticide use

病虫害在世界各地造成农作物的重大损失，是对粮食安全的重大威胁。在中国，飞蝗影响了200多万公顷的农田，而在老挝，黄刺竹蝗在老挝北部的9个地区广泛分布，2019年破坏了5,000多公顷的农作物。一种新的入侵害虫，秋军虫正在东南亚和中国流行。它已在中国22个省被发现，并影响了老挝35，000公顷的玉米。非洲的经验表明，它可能导致几乎全部作物损失。由于缺乏关于作物风险最大之处的详细信息，使用不适当或无效的控制措施，以及害虫种群对化学农药的抗药性，管理害虫造成的损害可能很困难。此外，过度使用化学农药造成环境损害，其形式是生物多样性丧失，并在环境中，特别是在水道中留下化学残留物。在这个项目中，我们将利用地球观测和气象数据提供信息，帮助农民和农业当局更可持续地管理虫害风险。利用地球观测图像，我们将绘制风险地图，确定蝗虫和秋粘虫最有可能建立种群的栖息地。利用卫星表面温度数据，我们将开发和运行预测i）昆虫种群增长和ii）生物控制方法有效性的模型。这些模型将提供信息，以帮助备灾，并指导生物农药的施用时间。该项目将在中国东北已经开展的工作的基础上，将其应用于中国南部的海南省和老挝。我们将提供风险基础地图和信息产品，帮助选择干预的方法和时机。我们将与中国和老挝的农业管理当局合作，提供使用信息的培训。

Pests and diseases cause significant losses of crops around the world and is a significant threat to food security. In China the migratory locust affects over 2 million hectares of agricultural land, while in Laos the yellow spined bamboo locust which is widespread across the 9 districts of Norther Laos and damaged over 5,000 hectares of crops in 2019. A new invasive pest, the Fall Army Worm is becoming prevalent in Southeast Asia and China. It has been found in 22 provinces in China and affected 35,000 hectares of maize in Laos. Experience from Africa shows it can cause almost total crop losses. Managing the damage from pests can be difficult due to lack of detailed information on where risks to crops are greatest, use of inappropriate or ineffective control measures, and build of resistance in pest populations to chemical pesticides. In addition overuse of chemical pesticides causes environmental damage in the form of loss of biodiversity and through chemical residues left in the environment, particularly in waterways. In this project we will use Earth observation and meteorological data to provide information that will help farmers and agricultural authorities manage pest risk more sustainably. Using Earth observation imagery we will prepare risk maps that identify habitats where locusts and fall armyworm are most likely to establish populations. Using satellite data on surface temperature we will develop and run models that predict i) the growth of insect populations and ii) the effectiveness of biological control methods. The models will provide information to help preparedness and to guide the timing of application of biopesticides. The project will build upon work already undertaken in North-East China and apply it in the Southern Chinese province of Hainan, and in Laos. We will provide risk base maps and information products that help chose the method and timing of interventions. We will work with agricultural management authorities in China and Laos, providing training in the use of the information.