Life Sciences Commons^™

A Review Of Landcover Classification With Very-High Resolution Remotely Sensed Optical Images—Analysis Unit, Model Scalability And Transferability, Rongjun Qin, Tao Liu

Michigan Tech Publications

As an important application in remote sensing, landcover classification remains one of the most challenging tasks in very-high-resolution (VHR) image analysis. As the rapidly increasing number of Deep Learning (DL) based landcover methods and training strategies are claimed to be the state-of-the-art, the already fragmented technical landscape of landcover mapping methods has been further complicated. Although there exists a plethora of literature review work attempting to guide researchers in making an informed choice of landcover mapping methods, the articles either focus on the review of applications in a specific area or revolve around general deep learning models, which lack a …