Skip to main content

On satellite imagery and sand mafia

The cost of launching satellites is going down, be it in the US or in India. Smaller and easier to develop micro-satellites are the latest trend, usually developed with a specific goal in mind e.g. satellite imagery. These, and a lot of other factors, have contributed to an increase in the number of satellites hovering over earth in the recent years, a number which is bound to only keep increasing.

ISRO recently put 88 (micro) satellites belonging to Planet Labs, satellites which Planet Labs will use to image the Earth everyday. ISRO and other government space organizations themselves have satellites that image the Earth and/or their respective countries on a regular basis. And a number of these organizations are releasing their data publicly.

With that context, I realized a while back that daily imagery will help identify and possibly curb sand mafia, specifically in India. The boom in infrastructure, specifically housing and office construction in India, was one of the reasons why the sand mafia exists. A number of people have died trying to uncover and expose the sand mafia, given the amount of money involved in the infrastructure and construction business. So, I thought that it'd be safer, and scalable, to use satellite imagery instead of being on the ground.

Maybe some weekend I'll sit down and look for satellite imagery available in the public domain, specifically of rivers in India, and understand if this is possible and how it can be done.

Popular posts from this blog

Animation using GNUPlot

Animation using GNUPlotI've been trying to create an animation depicting a quasar spectrum moving across the 5 SDSS pass bands with respect to redshift. It is important to visualise what emission lines are moving in and out of bands to be able to understand the color-redshift plots and the changes in it.
I've tried doing this using the animate function in matplotlib, python but i wasn't able to make it work - meaning i worked on it for a couple of days and then i gave up, not having found solutions for my problems on the internet.
And then i came across this site, where the gunn-peterson trough and the lyman alpha forest have been depicted - in a beautiful manner. And this got me interested in using js and d3 to do the animations and make it dynamic - using sliders etc.
In the meanwhile, i thought i'd look up and see if there was a way to create animations in gnuplot and whoopdedoo, what do i find but nirvana!

In the image, you see 5 static curves and one dynam…

Pandas download statistics, PyPI and Google BigQuery - Daily downloads and downloads by latest version

Inspired by this blog post : https://langui.sh/2016/12/09/data-driven-decisions/, I wanted to play around with Google BigQuery myself. And the blog post is pretty awesome because it has sample queries. I mix and matched the examples mentioned on the blog post, intent on answering two questions - 
1. How many people download the Pandas library on a daily basis? Actually, if you think about it, it's more of a question of how many times was the pandas library downloaded in a single day, because the same person could've downloaded multiple times. Or a bot could've.
This was just a fun first query/question.
2. What is the adoption rate of different versions of the Pandas library? You might have come across similar graphs which show the adoption rate of various versions of Windows.
Answering this question is actually important because the developers should have an idea of what the most popular versions are, see whether or not users are adopting new features/changes they provide…

Adaptive step size Runge-Kutta method

I am still trying to implement an adaptive step size RK routine. So far, I've been able to implement the step-halving method but not the RK-Fehlberg. I am not able to figure out how to increase the step size after reducing it initially.

To give some background on the topic, Runge-Kutta methods are used to solve ordinary differential equations, of any order. For example, in a first order differential equation, it uses the derivative of the function to predict what the function value at the next step should be. Euler's method is a rudimentary implementation of RK. Adaptive step size RK is changing the step size depending on how fastly or slowly the function is changing. If a function is rapidly rising or falling, it is in a region that we should sample carefully and therefore, we reduce the step size and if the rate of change of the function is small, we can increase the step size. I've been able to implement a way to reduce the step size depending on the rate of change of …