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On the Earth we rely on to survive, changes are happening every day. From large-scale natural landscape changes like earthquakes, landslides, and floods to relatively small-scale man-made landscape changes like building constructions, artificial lakes, and artificial islands, these transformations profoundly affect people's lives. Optical remote sensing satellites, as the core technology for modern Earth observation, provide us with the convenience of observing the Earth from space thanks to their "high-resolution imaging" and "what you see is what you get" capabilities. They also offer indispensable data support for numerous scientific fields.
If we liken optical remote sensing satellites to humans, then space optical cameras are the "eyes" of these satellites. In ophthalmology, terms like "myopia" and "astigmatism" are used to describe human vision. So, what indicators do we use to describe the "vision" of satellites? And what criteria are used to determine if their "vision" meets detection requirements?
"Resolution" and "Modulation Transfer Function" are the two most crucial indicators for measuring the performance of space cameras. The quality of these indicators directly determines the accuracy and usability of remote sensing data.
When people use the "God's perspective" from space to observe the Earth with the "eyes" of satellites, we can intuitively feel the differences in resolution through images. The higher the resolution, the sharper the satellite's "eyes" and the clearer the images.
In the field of space optical remote sensing, resolution includes two concepts: Ground Sample Distance (GSD) and spatial resolution.
The calculation of Ground Sample Distance (GSD) usually involves factors such as satellite orbit altitude, camera focal length, pixel size, and off-nadir angle. With the continuous development of remote sensing technology, the GSD of optical remote sensing satellites is shrinking, allowing us to obtain higher resolution remote sensing images.
Spatial Resolution (Ground Resolution Distance, or GRD) refers to the smallest unit size of ground objects that can be distinguished in remote sensing images, usually expressed in meters. Unlike GSD, GRD focuses more on the distinguishability between objects in the image rather than the ground size covered by a single pixel. GRD reflects the ability of remote sensing images to express details of ground features. Its value depends on various factors, including the satellite's orbit altitude, camera performance, and data processing methods.
The Modulation Transfer Function (MTF) is defined as the ratio of contrast between the image and the object at different spatial frequencies. It reflects the contrast changes between image and object across the detectable spatial frequency range. MTF is currently recognized as the most comprehensive and quantitative indicator that fully reflects the practical imaging quality of a system. It quantitatively shows the combined effects of diffraction and aberration caused by the optical system.
To improve imaging quality, one approach is to opt for large-aperture optical systems as much as possible. Additionally, in the design phase, optical systems need to optimize geometric aberrations to achieve "clear images, similar likeness between object and image, and minimal distortion." For optical remote sensing satellites, the design must also optimize thermal design of space cameras, structural stability, and the unified thermal deformation design of platform-camera to strictly control optical system aberrations and ensure imaging quality.
Resolution and Modulation Transfer Function (MTF) are the two most crucial indicators for measuring the performance of space cameras, and they are fundamentally interrelated. Both are aimed at describing the satellite's "detail resolution capability." Although there are three criteria for satellite optical system resolution—Rayleigh criterion, Dawes criterion, and Sparrow criterion—they can all be uniformly represented using MTF.
In designing and optimizing optical remote sensing satellites, it is critical to comprehensively consider both resolution and MTF to ensure that high-quality, high-clarity remote sensing images can be provided, thus becoming the "eye in the sky" that records magnificent landscapes.