Development of a methodology to fill gaps in MODIS LST data for Antarctica

• Main Author: Alasawedah, Mohammad Hussein Mohammad
• Other Authors: Meyer, Hanna, Valdes, Maite Lezama, Guerrero, Ignacio
• Format: Master Thesis
• Language: English
• Published: 2021
• Subjects: Convolutional Neural Networks; Extreme learning machine; Gam; Antarc*; Antarctica
• Online Access: http://hdl.handle.net/10362/113760

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies Land Surface Temperature (LST) is an essential parameter for analyzing many environmental questions. Lack of high spatio-temporal resolution of LST data in Antarctica limit...