I. Introduction
Unifying multitask interpretation in the remote sensing (RS) domain is crucial in practical application as real-world scenarios often demand comprehensive analyses to make informed decisions. Although deep learning methods in RS have been successful in RS visual analysis tasks [1], [2], [3], current methods mainly follow a one-task-one-architecture paradigm which limits their ability to handle multisensor RS images, multiple tasks, and generalize to open-set reasoning.