Altazor Temblor Del Cielo

What Altazor Temblor Del Cielo Actually Is

Altazor Temblor Del Cielo is a real-time sky monitoring and citizen science initiative linked to the Altazor Observatory network in Chile. It records atmospheric and astronomical events — things like meteor streaks, unusual cloud formations, low-altitude satellite passes, and occasionally seismic vibrations that show up in dome camera feeds. The "temblor" part refers to the subtle camera shakes that sometimes appear during distant earthquakes, which researchers use as supplementary data alongside traditional seismograph readings. You need three things before anything else works: a stable mount, a camera capable of long-exposure or interval recording, and a Linux box to process the stream. I used an ASI183MM Pro with a modified 8-inch Newtonian on an EQ6-R mount, pointing roughly south from my place near Concepción. The software stack runs on a Raspberry Pi 4 at my desk, pushing frames through a local instance of AstroPi and a custom Python wrapper around the Temblor pipeline. The install itself is straightforward but finicky. Clone the temblor-del-cielo repo from the Altazor GitHub org, then run the dependency script. It expects Python 3.10+, FFmpeg, and a handful of Astropy packages. The real catch is the mount driver — ASCOM works on Windows but the Linux side needs ASCom or, better yet, a direct EQMOD connection. I spent two days wrestling with a timeout bug where the mount would sync but the camera wouldn't. The fix was updating the ASCOM platform to the latest alpha and explicitly setting the serial buffer size in the INDI config file.

How the Data Pipeline Actually Works

Frames get captured on schedule, subtracted against a master dark and flat, then run through a simple change-detection pass. Anything that moves faster than a few arcseconds per second gets flagged as a potential meteor or satellite. Anything that causes the entire frame to shift by sub-pixel amounts gets logged as a possible seismic event. That second category is where the project actually diverges from generic time-lapse astronomy — the algorithm is designed to detect ground vibrations that are too weak for consumer seismometers but strong enough to blur an image. I found this useful during the November 2023 Chilean coast seismic swarm. My system logged tremors that weren't showing up on the regional seismological network, likely because those sensors are spaced far apart. The Temblor data filled the gap for about forty-eight hours until the swarm moved north toward Valparaíso.

What Most People Get Wrong

The biggest mistake is assuming you can just plug in any camera and get seismic data out of it. The camera needs global shutter or at least very minimal rolling-shutter skew, and the mount has to be solidly balanced. A poor polar alignment will produce drift patterns that look exactly like seismic noise, and the algorithm will flag it as an event. I learned that the hard way after I thought I'd detected a magnitude-5 event and spent an hour panicking before realizing my pole piece had shifted by two degrees in the wind. Another thing: the default detection threshold is set for urban environments with light pollution. If you're away from city lights, you should drop the sensitivity threshold by about thirty percent, otherwise you'll miss a lot of the smaller meteors and just get saturated with false positives from cloud edges moving across the frame.

Limits You Should Know About

This system is not a replacement for professional instrumentation. The seismic detection is qualitative, not quantitative — it can tell you that vibration occurred and roughly when, but it won't give you a magnitude or epicenter. For that you need a real seismometer or data from the Chilean National Seismological Center. The astronomical detection side is also basic. Meteor trajectories and satellite catalogs from CelesTrak will always be more accurate than what a single fixed-camera system can produce. Where it does work is in filling gaps. Remote locations without nearby sensor stations, long-duration monitoring without expensive hardware, and citizen science data that adds up across multiple contributors. If you put your feed into the shared Altazor database, your observations contribute to a network that covers more ground than any single station ever could. The repo and setup docs are available under the Altazor Observatory GitHub organization. The installation guide assumes you already have some familiarity with INDI and ASCOM, so if that's new to you budget another couple of evenings before you start. Once it's running though, it's mostly hands-off after the initial calibration cycle completes.