一种自动广义机器学习方法来绘制熔岩流图

2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI:10.1109/CNNA49188.2021.9610813

C. Corradino, E. Amato, F. Torrisi, C. Negro

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引用次数: 2

摘要

与火山有关的重铺过程可以通过雷达和光学传感器的互补来监测。将这两种数据源与机器学习(ML)方法相结合是自动提取火山相关特征的基础。本文在谷歌Earth Engine (GEE)中开发了一种广义ML方法，用于在近实时(NRT)和非时间临界(NTC)时间尺度上绘制熔岩流。提出了一种用于新熔岩流自动映射的广义分类方法的首次尝试。

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Towards an automatic generalized machine learning approach to map lava flows

Volcano-related resurfacing processes can be monitored by complementary using radar and optical sensors. Combining both data sources with machine learning (ML) approaches is fundamental to automatically extract volcano-related features. Here, a generalized ML approach is developed in Google Earth Engine (GEE) to map lava flows in both near-real time (NRT) and no-time critical (NTC) time scales. A first attempt towards a generalized classification to automatically map new lava flows is proposed.

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来源期刊

2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)

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