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--- atmos:camera_images_and_ceiling_cic_database:home [2023/06/27 17:38] – kaito.kanazawa
+++ atmos:camera_images_and_ceiling_cic_database:home [2024/04/15 20:15] (current) – rebecca.jacoby
@@ Line 1: / Line 1: @@
-**Camera Images and Ceiling (CIC) database**
+**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 will then be used to train Machine Learning (ML) algorithm that can produce it's own real-time cloud ceiling data along with the ability to forecast ceiling heights.
+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) and
+  - Ceilometers (by processing data and numbers from METAR, ASOS, AWOS, etc)
-  - Satellite (by extracting images and features from Satellite imagery such as cloud top height).
-The resulting training based on the publicly available real time data should provide sufficient data points for the ML Algorithm to create it's own real time ceiling data which can be cross referenced with ceilometers.
+**Public Ceiling and Visibility Datasets**
-For example, the UND Dept. of Atmospheric Sciences Skycam images, KGFK METAR, and GOES Satellite imagery can be utilized to determine cloud ceilings in the Grand Forks City area. The ML algorithm will be trained using regularly updated images and data points, enabling it to provide real-time ceiling figures more frequently than the hourly intervals provided by METAR and then produce a set of forecast data points for the location.
-**Public Datasets**
   * [[ARM Data Center]]
@@ Line 20: / Line 15: @@
   * [[Iowa State University ASOS-AWOS-METAR Data]]
+**Public Camera Image Sets**
+  * [[ARM Data Center]]
-**Creating the Database**
+  * [[FAA WeatherCams]]
-Data and information retrieved from publicly available databases will be grouped under where they fit within the three basic ceiling categories below:
+  * [[WeatherBug]]
-  * Ceiling < 200ft AGL
-  * 200 < Ceiling < 400ft AGL
-  * Ceiling > 4000ft AGL
-Once classified, they will be documented and paired with metadata such as:
+**Creating the Database**
+Once downloaded, they will be documented and paired with metadata such as:
   * Location
   * Date
   * Camera Location
-  * Camera Features
   * METAR/ASOS Features
-  * Ceiling
 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.
+  * [[Methodology]]