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遥感在数据科学农业应用中的机遇与挑战

Opportunities and Challenges for Remote Sensing in Agricultural Applications of Data Science
课程网址: https://videolectures.net/videos/kdd2016_crawford_data_science  
主讲教师: Melba Crawford
开课单位: KDD 2016研讨会
开课时间: 2025-02-04
课程语种: 英语
中文简介:
全球人口的增长,加上气候变化的挑战,需要开发技术来支持从植物育种到农产品交付的整个供应链中粮食产量的增加。天基、机载和近端传感平台的遥感发展,加上计算平台和数据分析的先进能力,为解决与粮食、能源和水有关的重大挑战提供了新的机会。携带新型主动和被动传感器的星载平台正从复杂的多用途任务转向成本较低、特定于测量的小型卫星星座。材料的进步导致传感器和配套仪器的小型化和大规模生产,从而实现了经济实惠的自动驾驶汽车的先进传感。正在开发新的算法,以利用海量的多模态数据集,并为从表型到作物测绘和监测的农业应用提供可操作的信息。将概述数据科学在多时相、多尺度多传感器遥感数据分析方面的最新贡献以及机遇和挑战。
课程简介: Increases in global population, coupled with challenges of climate change require development of technologies to support increased food production throughout the entire supply chain – from plant breeding to delivery of agricultural products. Developments in remote sensing from space-based, airborne, and proximal sensing platforms, coupled with advanced capabilities in computational platforms and data analytics, are providing new opportunities for contributing solutions to address grand challenges related to food, energy, and water. Spaceborne platforms carrying new active and passive sensors are moving from complex, multi-purpose missions to lower cost, measurement specific constellations of small satellites. Advances in materials are leading to miniaturization and mass production of sensors and supporting instrumentation, resulting in advanced sensing from affordable autonomous vehicles. New algorithms to exploit the massive, multi-modality data sets and provide actionable information for agricultural applications from phenotyping to crop mapping and monitoring are being developed. An overview of recent contributions, as well opportunities and challenges for data science in analysis of multi-temporal, multi-scale multi-sensor remotely sensed data will be presented.
关 键 词: 数据科学; 农业应用; 机遇与挑战
课程来源: 视频讲座网
数据采集: 2025-02-27:liyq
最后编审: 2025-02-27:liyq
阅读次数: 4