Low graze angle imaging

A city seen from a satellite through an orthographic camera. Drag to pan. With an instrument selected, scroll or pinch magnifies the image like an imagery viewer; resolution is set by the optics and the slant range. Moving the angle sliders takes manual control.

Satellite pass

Pass time

Playback speed

Orbit altitude

Peak graze angle

Ground track heading

Circular orbit over a spherical earth, earth rotation ignored. The sensor stays pointed at the scene. Pass limits are where the graze angle drops to 8°.

Sensor geometry

Graze angle

View azimuth

Traffic

Density, cars per lane-km

Tracking boxes on moving vehicles and ships

Tracks from

The detector runs twice a second. Each vehicle is found with a probability set by its size in sensor pixels, the blur, and its contrast against the road; positions carry sub-pixel to pixel noise. A track is confirmed after 3 detections in 5 frames, coasts (dashed) through misses and is dropped after 4 in a row; a reacquired vehicle gets a new id.

Cars follow the road network in real time, keep a gap to the car ahead, stop at red signals and brake before turns so sideways acceleration stays near 2.5 m/s². The button also pauses the moving ship.

Sun

Sun elevation

Sun azimuth

Skylight in shadows

In optical imagery, shadow length depends on sun elevation, not on the sensor graze angle.

Image chain

Instrument

Colour is pan-sharpened the way commercial products are: red, green and blue bands with 4× the pan pixel are fused with the pan band, so colour bleeds slightly past sharp edges.

Display zoom, screen pixels per sensor pixel

Exposure

Contrast

Sharpening (MTFC)

Sensor noise

Atmospheric haze

Haze scales with the slant path length, 1/sin(graze).

Rendering

Supersampling per axis

noahdemar

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Noah Demar

NowAccrete AI
BeforeThe Aerospace Corporation
SchoolNorthwestern University, BS/MS ×2

LinkedIn · Projects (plain text)