How do we process satellite imagery so that customer can operate with Ready-to-use Data
Posted on 06 Aug 2018
By: Anton Sonyushkin
Lead Data Science Engineer, OpenWeather.
Key Account Manager, OpenWeather.
1. Satellite data search
1.1. Selection of suppliers or distributors of satellite data
1.2. Data search in archives. Search is based on the following criteria: - date of satellite imagery, percet of cloud coverage, type of satellite imagery system, level of data preprocessing, geographical area of interest (AOI)
2. Downloading data from supplier servers
3. Data processing
3.1. Convert pixel values of satellite images from DN to physical units (ToA)
Typically, pixel values of satellite images are presented as dimensionless integer units – Digital numbers (DN). Their values range depending on the type of satellite imaging system and the mode of its operation (gain exposure like in photography), illumination conditions and imaging geometry, etc., which in turn hinders the joint analysis of data obtained from various systems.
To simplify the subsequent data analysis, we apply correction of all obtained satellite images and convert pixel values to the reflectance properties of the Earth's surface (albedo) measured by a space-based sensor flying higher than the Earth's atmosphere (Top of atmosphere reflectance - TOA). This type of correction is performed considering the illumination conditions and imaging geometry at the scene acquisition time.
3.2. Convert satellite images data to a single (unified) cartographic projection and cutting into tiles.
Generally, satellite images displayed using the Universal Transverse Mercator (UTM). In this projection, the globe is divided into zones 6 degrees wide by longitude, separate for the Northern and Southern hemispheres. In total, this is 120 cartographic projections with different mathematical descriptions and with different coordinate values accordingly.
We use a single projection for the entire territory of the globe - the Cylindrical Projection widely used for building of cartographic web-services (web Mercator), which allows working with images in a single system of cartographic coordinates.
As a data storage unit, we use a square segment (tile) with the size of 256x256 pixels. The images are cut into tiles according to the standard scheme, which ensures compatibility of our data with such popular services as OSM, Google, Bings and with popular libraries for the development of cartographic web-services, such as Leaflet, OpenLayers, etc.
Each tile is accompanied by additional meta information, such as:
percentage of the useful area of the image within the limits of the tile
matrix of image location within the tile (in the case of incomplete coverage of the tile image - in which part of the tile the image is present)
percent of cloud coverage within the tile
sun azimuth and elevation angles
information about the available spectral channels
Obviously, one of the main conditions for choosing a satellite image is the percent of cloud coverage. This information is usually provided by the data provider but as a rule for the entire image. It is often difficult to assess whether the object of interest will be closed by cloud or atmospheric haze. Our API users can obtain localized information about the cloud presence within the limits of the tile that greatly simplifies the subsequent analysis of data.
We store in our database:
Images converted to single units of brightness and a single projection in the form of tiles compatible with popular web-services and metadata of these tiles.
We provide users with the following basic information products:
* A satellite image in the form of a tile service, or an image generated within a specified polygon area, in PNG format. The user can choose a combination of spectral channels and carry out color correction of the images at his discretion.
* A satellite image with brightness converted to ToA, in a web-mercator projection in GeoTIFF Uint-16 format, as tiles, or generated within a specified polygon area.
* Popular derived indicators (indices) in the form of a tile service, or a satellite image formed within a given polygon area, in PNG format. The user can choose a combination of spectral channels and perform color correction of the images at his discretion.
* Popular derived indicators (indices) in the GeoTIFF Float-32 format, in the form of tiles, or formed within a given polygon area.
* Basic statistical information calculated within a given polygon area, from the original image or derived index, in JSON format.
* Information about the value of one of the indicators (weather, soil moisture, UV, etc.) at a point with a specified latitude and longitude
Using our API, the user saves on:
Equipment + Software + Expert
We provide ready-to-use data