From 23d59729cf2e121a3c2a768b88b2e75be7f8ea16 Mon Sep 17 00:00:00 2001 From: matthieumm Date: Fri, 5 May 2023 00:15:34 +0300 Subject: [PATCH] Update README.md Added WHUS2-CD+ dataset in ## Cloud datasets, under cloudsen12 (grouped with other Sentinel-2 cloud datasets) --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 4d2690e..cd17c7d 100644 --- a/README.md +++ b/README.md @@ -348,6 +348,7 @@ Since there is a whole community around GEE I will not reproduce it here but lis * [The Azavea Cloud Dataset](https://www.azavea.com/blog/2021/08/02/the-azavea-cloud-dataset/) which is used to train this [cloud-model](https://github.com/azavea/cloud-model) * [Sentinel-2 Cloud Cover Segmentation Dataset](https://mlhub.earth/data/ref_cloud_cover_detection_challenge_v1) on Radiant mlhub * [cloudsen12](https://cloudsen12.github.io/) -> see [video](https://youtu.be/GhQwnVhJ1wo) +* [WHUS2-CD+](https://zenodo.org/record/5511793) -> 36 manually labeled cloud masks at 10m resolution and corresponding Sentinel-2 images evenly distributed over China mainland, and used to train CD-FM3SF [cloud-model] (https://github.com/Neooolee/WHUS2-CD) * [HRC_WHU](https://github.com/dr-lizhiwei/HRC_WHU) -> High-Resolution Cloud Detection Dataset comprising 150 RGB images and a resolution varying from 0.5 to 15 m in different global regions * [AIR-CD](https://github.com/AICyberTeam/AIR-CD) -> a challenging cloud detection data set called AIR-CD, with higher spatial resolution and more representative landcover types * [Landsat 8 Cloud Cover Assessment Validation Data](https://landsat.usgs.gov/landsat-8-cloud-cover-assessment-validation-data) @@ -741,4 +742,4 @@ Competitions are an excellent source for accessing clean, ready-to-use satellite * https://spaceml.org/repo/project/60002402f5647f00129f7287 -> lightning and extreme weather * https://spaceml.org/repo/project/6025107d79c197001219c481/true -> ~1TB dataset for precipitation forecasting * https://spaceml.org/repo/project/61c0a1b9ff8868000dfb79e1/true -> Sentinel-2 image super-resolution -