Integration of aerial image


Definition of space visual

Space visualization is a digital image of a phenomenon taken by an electronic pickup that records the energy reflected or emitted from ground targets and is expensive to carry the pickup on aircraft in the atmosphere, and the digital image is kept in a file recorded on electronic storage devices dealing directly with the computer.

This file containing the digital image may be displayed on the display, and what we see on this screen is an image similar to any other image taken by cameras.

The difference, however, is that this image displayed on the screen is basically digital and has been transformed into an analogue body similar to the aerial image of this aerial image consisting of a large set of numbers distributed in the form of a matrix with horizontal and vertical axes and a horizontal axis called X, and vertical called Y, and each number is called a pixel cell.

So the image consists of a matrix of cells divided into two axes, one horizontal and the other vertical, and the horizontal matrix called rows, either vertical, called columns, and usually selects points starting with a first row meeting and the first column at the far left top corner of the image, so that the last row meets the last column at the far right bottom corner of the image.

The image and if we want to identify a cell on the image we identify it by looking at its location from rows and columns, the space video is the images that are taken by sensors installed on satellite devices, the camera when photographing a landscape that captures light through the lens inside this camera to the sensor behind the CCD lens, the lens receives this light and cuts it into millions of small squares called pixels, each square stores this light in the form of a amount of Energy (electromagnetic field).

Integration of aerial image ranges from The Sentinel satellite

(Sentinel band combination):

We use domain groups to better understand the features in the images,

by rearranging the available channels in a different order,

where using domain groups we can extract specific information from the image.

For example, there are clusters of ranges that highlight geological,

agricultural or plant features in the form of a sentinel satellite. 

 (B2,B3,B4) By combining these ranges gives the natural color and its purpose is to display the image in the same way as you see our eyes,

as in the following picture:

Integration of aerial image

(B8,B4,B3) By combining these bands,

the color of infrared radiation and its purpose give emphasis on healthy and unhealthy vegetation

, as seen in the following picture:

Integration of aerial image

(B12,B8A,B4) By combining these bands gives a short-wave infrared color

where this compound shows vegetation in different degrees of green, as in the following picture:

Integration of aerial image

B11,B8,B2) By combining these bands (agricultural ranges) they are often used to monitor crop health because of how it is used for short waves and near infrared, as pictured:

Integration of aerial image

(B4,B3,B1) By combining these bands, depths can be measured (the pathometer range is good for coastal studies), as in the following picture:

Integration of aerial image
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