Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20221028T093930Z)

The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework Full metadata: https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930/index.htmlThis dataset is part of the RAISE Spoke 3 project outcomes. RAISE is an innovation ecosystem funded by the Ministry of University and Research under the National Recovery and Resilience Plan (NRRP, Mission 4, Component 2, Investment 1.5).本数据集收录了通过机器学习模型输出得到的估算海表温度（Sea Surface Temperature, SST）。本次建模的训练数据包含欧盟哥白尼计划（Copernicus Programme）哨兵3号（Sentinel-3）任务获取的热红外数据，以及由日内瓦大学DISTAV部门（UNIGE-DISTAV）与意大利国家新技术、能源与可持续经济发展署（ENEA）的同仁提供的原位海温实测数据，模型训练在监督式机器学习框架下完成。完整元数据：https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930/index.html。本数据集属于RAISE Spoke 3项目的成果之一。RAISE是由意大利大学与研究部依据国家复苏与韧性计划（National Recovery and Resilience Plan, NRRP，使命4、组件2、投资1.5）资助的创新生态系统。