Clouds-1000

Clouds-1000 is a dataset of 1000 sky images captured with cameras directed towards the horizon in the north and south directions in an area with a good view of the sky in the UFSC Photovoltaic Laboratory at the Federal University of Santa Catarina, in the city of Florianópolis/SC-Brazil. The images were collected every minute over the period of March–October of 2021. Each image was annotated with a polygon tool and classified using 4 cloud types: Cirriform, Cumuliform, Stratiform, and Stratocumuliform, and 1 class representing trees and buildings. This classification is based on the solar radiation absorption characteristics of clouds. For the task of image annotation, our research team was divided into 3 Data Analysts responsible for analyzing and labeling the images, and 2 meteorologists responsible for supervision and validation. Sylvio Mantelli is a PhD from INPE, working on our research team and helped with data labeling mentoring and several analysis throughout development of the dataset. Maurici Amantino Monteiro, professor and currently climatologist at Aqueris Engenharia e Soluções Ambientais. With several years of experience in synoptic observation, he helped us to understand the nature of clouds and associate them with their corresponding classes. The annotations were handmade using the Supervisely tool. The tool was created for image annotation and data management in which it's possible to create the annotations via interface available, similar to other image editors. Each image was annotated with the polygon tool and classified using 4 cloud types: Cirriform, Cumuliform, Stratiform, Stratocumuliform and 1 class representing trees and buildings. This classification is based on solar radiation absorption characteristics. Due to the humid climate of the region, the Cumulonimbus (Cb) cloud seldom forms. This type of cloud usually form in dryer regions, thus we won't find any occurrence of this cloud in the dataset. The dataset faced several validations and during an inspection we found 4 images that were either partially annotated or missing annotation entirely. Therefore, the latest and current version of the Clouds-1000 dataset is composed of 996 fully hand-annotated images. For more information see the github repository.

Clouds-1000是一个包含1000张天空图像的数据集，所有图像均由安装于巴西圣卡塔琳娜州弗洛里亚诺波利斯市圣卡塔琳娜联邦大学（UFSC）光伏实验室的相机拍摄，拍摄方向朝向南北地平线，该实验室拥有极佳的天空观测视野。图像采集于2021年3月至10月期间，采集频率为每分钟一张。
每张图像均通过多边形标注工具完成标注，共分为5个类别：4种云类（卷云型（Cirriform）、积云型（Cumuliform）、层云型（Stratiform）、层积云型（Stratocumuliform））以及1个代表树木与建筑的地物类别，该分类体系基于各类云对太阳辐射的吸收特性。
本研究团队分为3名数据分析专员负责图像分析与标注，以及2名气象学家负责监督与验证。其中来自巴西国家空间研究院（INPE）的西尔维奥·曼泰利（Sylvio Mantelli）博士参与本团队，为数据集构建过程中的标注指导与多项分析工作提供了支持。此外，现任职于Aqueris Engenharia e Soluções Ambientais的气候学家、教授毛里西·阿曼蒂诺·蒙特罗（Maurici Amantino Monteiro）拥有多年天气观测经验，协助团队理解云的自然属性并匹配对应类别。
标注工作通过Supervisely工具手工完成，该工具专为图像标注与数据管理开发，可通过类似其他图像编辑器的可视化界面完成标注操作。每张图像均通过多边形标注工具完成标注，并采用前述的4类云与1类地物的分类体系，分类依据仍为云对太阳辐射的吸收特性。
由于该区域气候湿润，积雨云（Cumulonimbus，Cb）极少形成——这类云通常多见于干旱地区，因此本数据集未收录该类云的样本。该数据集曾经过多轮验证，在一次巡检中发现有4张图像存在标注不全或完全未标注的问题。因此，当前最新版的Clouds-1000数据集共包含996张完整手工标注的图像。更多信息可查阅其GitHub仓库。