Advanced Machine Learning and Deep Learning Approaches for Remote Sensing.

Remote sensing has dramatically increased the available quantity of marine data, and artificial intelligence technologies have demonstrated the ability to process big data and derive meaningful insights from them. Unlike field observation or field sensing, remote sensing is the process of obtaining information about an object or phenomenon without making physical contact. To this end, a two-step convolutional neural network is used to extract cloud transparency information and then generate ground surface information for thin cloud regions. Measured LFMC data, MODIS, Landsat-8, and Sentinel-1 remote sensing data and auxiliary data, such as canopy height and land cover in wildfire-prone areas in the western United States, are selected as study subjects. [Extracted from the article]