Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240729T094659Z)

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_20240729T094659/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).本数据集包含由机器学习模型输出得到的估算海表温度（sea surface temperature, SST）。本次模型训练采用监督机器学习框架，训练数据涵盖欧盟哥白尼计划（Copernicus programme）Sentinel-3任务获取的热红外数据，以及UNIGE-DISTAV与ENEA的同行提供的现场海温真值实测数据。完整元数据：https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T094659/index.html本数据集为RAISE Spoke 3项目成果的组成部分。RAISE是由意大利大学与研究部依据国家恢复与韧性计划（National Recovery and Resilience Plan, NRRP，任务4、组件2、投资1.5）资助的创新生态系统。