Phone astrophotography

 Phone cameras have come a long way and are inching closer to the capabilities of DSLR and mirrorless cameras when it comes to astrophotography. Improvements in sensor technology and built in post processing features such as HDR, stacking and star alignment being have made them into a useful backup or even a viable replacement for traditional cameras, especially when used with a tripod. These days, I find myself using my phone more than my DSLR for milky way photography.

The photos that follow are some of my favorite shots of the milky way and landscapes taken using an iPhone 14 pro, on tripod with the maximum 30s exposure in the built-in camera app, and later edited in Lightroom mobile. 

The above was taken at Lerderberg State Park Victoria aiming directly at the zenith around the end of winter. 

These two photos were taken in Point Lonsdale lighthouse. The red light from the lighthouse lit up the surrounding rock formations in red as seen in the top image. What is also interesting is that the second image would not have been possible on a single exposure on a DSLR, as the light from the lighthouse would have washed out the image. It appears that the phone has automatically stacked images of various exposures to create a composite image.

These images were taken at the Gravity Observatory in Perth. While a lot of stars are visible the image contains a lot of noise highlighted during the edits, possibly showing the limits of phone night photography.

The first two phots above were taken at Lake Tyrell, and third at the town of Sea Lake. In the second image, the moon illuminated the surroundings and overpowered the stars, but I was able to capture the reflections of a few stars on lake's calm surface. 

 

These two images are the latest ones taken at Aireys Inlet beach. The last one is my favorite so far since it highlights the details of the milky way as well as the rock formation. I used the flashlight from another phone to briefly light up the rocks while the image was being exposed for 30s, and in my opinion it resulted in perfect exposure of both landscape and the stars. 

While phone cameras have made impressive improvements and deliver impressive results, DSLR and mirrorless systems continue to advance in their own right. Still, smartphones offer unmatched accessibility and portability - and as the saying goes, "the best camera is the one you have with you".

Another web app to estimate the soil water retention curve

I created another simple web application to estimate the soil water retention curve from basic particle size distribution data. I used the equations developed by Zapata et al. (2000). The water retention curve can be exported as before and the previous app can be used to estimate hydraulic conductivity and oxygen diffusion coefficient of the soil after fitting to the vanGenuchten model.

Link : https://rukshan-azoor-psd.anvil.app/

I have also embedded the app below:  

Building a web app with nothing but (a bit of) Python

My knowledge of Python (the programming language) is not extensive. I have used it a few times to streamline some of my research activities that include data handling and processing. I find Python easy to get into without much programming experience and sources like Stack Overflow help very much to do this. So when I came across a web platform called Anvil that claims to let you build fully functional web apps with nothing but Python, I decided to give it a try. I was pleasantly surprised, and happy with the web application that I was able to build with a relatively basic knowledge of Python and nothing else. My code may not be the most efficient, but it gets the job done.

I decided to build an app within my area of research. It is an app to estimate soil hydraulic properties and oxygen diffusion coefficients at different degrees of saturation, based on water retention properties of the soil. I used equations from literature and those developed in my own research to do this. Two water retention curve parameters (van Genuchten α and n) and the soil porosity are used as inputs and the hydraulic conductivity function and oxygen diffusion coefficient characteristic are generated using the equations. I used the Plotly library built into Anvil to generate three plots for the generated functions and the water retention curve. I also built in an option to export the generated data as a text file that can be used for further analysis.

I was able to do this with the free plan that Anvil offers. Anvil also has a paid subscription plan that has more Python libraries and more options for development support and deployment. I believe it is a great product with exciting capabilities.

My first web app can be accessed at :  https://rukshan-azoor-wrc.anvil.app/