Welcome to
Koschny's NEO space!


Table of contents

Introduction
Lecture at TU Munich "NEOs for engineers and physicists"
Python routines - not only related to the lecture
"Star density" - data and Python routines to find the number of background stars in the sky
Other relevant presentations related to NEOs
Disclaimer


Introduction

This page provides some resources related to Planetary Defence and NEOs. No fance shiny web pages, just some text and links... But better this than nothing. Read the table of contents to jump to the relevant section on this page. Before using anything, read the disclaimer.


Lecture at TU Munich: "NEOs for engineers and physicists"

Here you will find the lecture viewgraphs from the previous year. The field is changing quickly, so things are changing - if you participate in a currently ongoing lecture, use the latest viewgraphs available on the TUM (Technical University of Munich) web portal "Moodle". You will know where to find it.


Python routines - not only related to the lecture

Some super-simple Python routines to compute different things related to NEOs - asteroid.py Download
A simple example using the JPL SPICE library - spice_demo.py Download



"Star density" - data and Python routines to find the number of background stars on the sky

Searching for asteroids gets more difficult, the more background stars there are. Here I provide data for the number of stars down to roughly about magnitude 21, for different positions in the sky. JSON-formatted files are given listing the number of stars per square degree as a function of celestial coordinates (RA, Dec). There is also a routine to read this into a Python 2-D array. You can retrieve the number of stars very efficiently by just reading the correct subscript of the array.

Here the data and reading routine for 1-degree steps in RA and Dec (yes this isn't really needed close to the poles - but it makes the look-up table straight forward):

star_densities_1_deg.json - Working on it...
star_density_read_1_deg.py - Working on it...

To identify dark clouds in the middle of the Milky Way, steps of 1 deg are too coarse. I am in the process of generating a look-up table in steps of 1/10 deg (6'). Generating the table takes time, so check back later for the result. The Python routine to generate the look-up table is here: star_density_1_deg.py. This downloads star data using the astroquery vo-conesearch routine. The routine is for one single RA value only. I run the routine via batch file with all RA values as a parameter. This makes it easier to recover in case of network or other issues. I combine all resulting files with star_densities_combine.py.


Other relevant presentations related to NEOs

SMPAG and IAWN history - background on the formation of these UN-endorsed groups (pdf) - To come


Disclaimer

All the information I make available on this page may be freely used - kindly refer to "Koschny 2021" when doing it. But note that you use everything on your own risk - everything is provided on a best-effort basis, I cannot guarantee correctness! I will not be liable for anything that happens to you because of using the information or code provided here.


Last update 04 Apr 2021, dvk