Camera Images Ceiling and Visibility (CICV) database
The purpose of this database is to be able to provide a constant, real-time/up-to-date set of data points which will then be used to train a Machine Learning (ML) algorithm that can produce it's own real-time cloud ceiling data along with the ability to forecast ceiling heights.
Documentation and information is provided below; related to the collection of Camera Images and Ceiling (CIC) data and creation of a database for a ML algorithm which will be trained on the combined data from three types of data sites within a given geographical area available for the public:
- Surface CAM images (by extracting images and features from CAM imagery such as weather cameras, road cameras, etc),
- Ceilometers (by processing data and numbers from METAR, ASOS, AWOS, etc)
Public Ceiling and Visibility Datasets
Public Camera Image Sets
Creating the Database
Once downloaded, they will be documented and paired with metadata such as:
- Location
- Date
- Camera Location
- METAR/ASOS Features
This categorization and metadata pairing will allow for organized and structured access to the ceiling data within the CIC database.
Methods
The following link provides a step-by-step run down on how research for this project is conducted and how data is obtained.