2026-10-14T20:03:54Z https://www.scidb.cn/oai

10.57760/sciencedb.17702 2024-08-16T11:33:42Z

2024-08-16 CloudSEN12+: The largest collection of expert-labeled pixels for cloud and cloud shadow detection in Sentinel-2 doi:10.57760/sciencedb.17702 en Detecting and screening clouds is the first step in any optical remote sensing (RS) analysis. Cloud formation is diverse, presenting many shapes, thicknesses, and altitudes. This variety poses a significant challenge to developing effective cloud detection algorithms since most datasets shortfall an unbiased representation. To address this issue, we have built CloudSEN12+, a significant expansion of the CloudSEN12 dataset. This new dataset doubles the expert-labeled pixels, making it the largest cloud detection dataset for Sentinel-2 imagery up to date. We have carefully reviewed and refined previous human labels in this new release to ensure maximum trustworthiness. We hope CloudSEN12+ will be a valuable resource for the cloud detection research community. Sentinel-2; thin cloud; cloud shadow; IRIS; U-Net; global dataset; cloud detection Cesar Aybar Lesly Bautista Julio Contreras Fernando Prudencio Daryl Ayala David Montero Jhomira Loja Luis Ysuhuaylas Fernando Herrera Karen Gonzales Jeanett Valladares Lucy A. Flores Evelin Mamani Maria Quiñonez Rai Fajardo Wendy Espinoza Antonio Limas Roy Yali Bram Willems Raúl Loayza-Muro Martín Leyva Alejandro Alcántara Gonzalo Mateo-García Luis Gómez-Chova PUBLIC https://creativecommons.org/publicdomain/zero/1.0/ dataset Science Data Bank