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X-WR-CALNAME:eo science for society
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X-WR-CALDESC:Events for eo science for society
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DTSTART:20230326T010000
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DTSTART;VALUE=DATE:20230404
DTEND;VALUE=DATE:20230412
DTSTAMP:20260604T103706
CREATED:20230220T130238Z
LAST-MODIFIED:20240219T094300Z
UID:21805-1680566400-1681257599@eo4society.esa.int
SUMMARY:Agriculture Remote Sensing Webinar: Crop Mapping using Synthetic Aperture Radar (SAR) and Optical Remote Sensing
DESCRIPTION:Monitoring crop growth is important for assessing food production\, enabling optimal use of the landscape\, and contributing to agricultural policy. Remote sensing methods based on optical and/or radar sensors have become an important means of extracting information related to crops. \nOptical data is related to the chemical properties of the vegetation\, while radar data is related to vegetation structure and moisture. Radar can also image the Earth’s surface regardless of almost any type of weather condition. \nThis three-part\, advanced training built on previous ARSET agricultural trainings. \nHere we presented more advanced radar remote sensing techniques using polarimetry and a canopy structure dynamic model to monitor crop growth. The training covered how to apply machine learning methods to classify crop type using a time series of Sentinel-1 & Sentinel-2 imagery.  \nThis series included practical exercises using the Sentinel Application Platform (SNAP) and Python code written in Python Jupyter Notebooks\, a web-based interactive development environment for scientific computing and machine learning. \nThis webinar series is a collaboration between NASA ARSET\, Agriculture and Agri-Food Canada (AAFC)\, European Space Agency (ESA)\, University of Stirling\, University of Ljubljana\, and the CEOS Working Group on Capacity Building & Data Democracy (WGCapD). \nObjectives:\n\nBy the end of this training attendees are able to: \n\nMonitor crop growth with polarimetric time series SAR data from Sentinel-1\nExamine crop growth using a canopy structure dynamic model and time series of Sentinel-1 imagery\nClassify crop type using a time series of radar and optical imagery (Sentinel-1 & Sentinel-2)\n\n\nAudience:\n\nThis webinar series was intended for local\, regional\, federal\, and non-governmental organizations from agriculture and food security related agencies to use radar and optical remote sensing applications in the domain of agriculture for crop mapping and monitoring. \nCourse Format:\n\n\nApril 4-11th\, 2023\nThree\, 2.5-hour sessions\nThe morning session will be presented in English: 10:00 AM – 12:30 PM ET (16:00 – 18:30 CEST)\nThe afternoon session will be presented in Spanish: 13:00 – 15:30 PM ET (19:00 – 21:30 CEST)\n\n\n\nThe sessions were: \n\nPart 1: Crop Classification with Time Series of Polarimetric SAR Data (Armando Marino)\n\n\nTuesday\, April 4\, 2023\n\n\n\nPart 2: Crop Classification with Time Series Optical and Radar Data (Krištof Oštir\, Matej Račič)\n\n\nThursday\, April 6\, 2023\n\n\n\nPart 3: Monitoring Crop Growth Through SAR-Derived Crop Structural Parameters (Heather McNairn\, Emily Lindsay\, Xianfeng Jiao)\n\n\nTuesday\, April 11\, 2023\n\n\n\n\nFor information on course training see the ARSET course page. Lecture recordings and materials are available here. \n \n  \nNote that the course is also available in Spanish. \n
URL:https://eo4society.esa.int/event/2023-arset-agriculture-webinar/
LOCATION:Online
CATEGORIES:Training/Education
ATTACH;FMTTYPE=image/jpeg:https://eo4society.esa.int/wp-content/uploads/2023/02/ARSET-webinar-header.jpg
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