Time series classification for new-generation Earth observation satellites

新一代对地观测卫星时间序列分类

• 批准号: DE170100037
• 负责人: Dr Francois Petitjean
• 金额: $ 22.47万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2017
• 资助国家: 澳大利亚
• 起止时间: 2017-06-01 至 2020-06-01
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE170100037
• 关键词: Time; series; classification; new; generation

This project aims to develop time series classification methods for satellite images, to produce accurate temporal land-cover maps. Latest generation satellites have just begun imaging Earth frequently, completely, in high-resolution, and at no charge to end-users – an unprecedented opportunity to monitor the flux of our planet's systems. However, time series classification techniques do not scale to handle such wealth of data. The project anticipates its time series technologies will be applicable in agriculture planning, fire prevention, and disaster mapping, and that substantially greater value can be derived from significant investments into Earth Observation programmes.

该项目旨在开发卫星图像的时间序列分类方法，以制作准确的时间土地覆盖图。最新一代的卫星刚刚开始频繁地、完全地、高分辨率地对地球进行成像，并且对最终用户免费--这是监测我们星球系统通量的前所未有的机会。然而，时间序列分类技术不能扩展以处理如此丰富的数据。该项目预计其时间序列技术将适用于农业规划、防火和灾害绘图，对地球观测方案的重大投资可产生更大的价值。