Better Birds, Birders and Birding Through Data (Singapore Edition)

This article examines how birders can use photo metadata to analyze birding trends and peak migratory seasons in Singapore. By leveraging image data, photographers can identify optimal locations and times for sightings, providing a data-driven alternative to traditional birding wisdom and large-scale observation platforms.

Introduction Ask any experienced birder in Singapore about what’s the best and busiest month for birding and you’ll hear either October or November mentioned. After all, migratory birds are coming in fast and furious during this period. One must therefore ask the question, “Are there any studies done to establish whether these two months are indeed the best month for birding?” And if such a study exist, is it October, November or some other months? Now is as good a time as any to have find out. Before that, let’s have two other interesting questions that are often asked. “Where are the best places for birding?”, “What’s the best time to photograph/observe birds?”. Almost everyone has thoughtful answers for them, based on their own experience and what have been passed on as common wisdom from more experienced birders. It’ll be good if we can get some hard data to confirm these as well. Birding observation platforms like eBird or iNaturalist may provide some answers to these questions through the sheer amount of data they accumulate from birders over the years. I expect Raghav (our resident data wrangler) to provide some answers and more to these questions sooner or later, using his amazing number crunching skill. In the meantime, playing the role of a citizen scientist, I am presenting another method here. Not as good, but simpler and tailored for photographers willing to undertake similar projects. Most photos these days are taken with additional data (metadata) that reveals for example where and when the photo was taken. They also include what sort of camera settings that used to take these photos. When a smartphone is used to take photos, companies like Google and Apple make use of these metadata to customize and remind users of life events like past birthdays and anniversary photos for example (based on date and time encoded in photos), or maybe organize all photos taken on an overseas trip (based on location data encoded in photos) on their virtual album for the users to peruse through. Using the same type of metadata on bird photos taken using camera gear specialized for that purpose, accumulating enough of them, and cataloging these photos and supplementing these with additional data (when necessary), one can build a mini database of information that allows more definite answers to the questions that were posed at the start of this article. Methodology (briefly) The base photos for this particular analysis located in a photo album posted online at https://fryap.com/photos/index/category/singapore-birds The album contains representative photos of all the Singapore bird species I have photographed and curated over 12 years of bird photography. At the time of analysis, there are 1248 photos over 368 species. To be clear, these are non-random photo selections based on my preferences and birding habits. Photo aesthetics and other technical considerations influenced the final photo set as well. The program/app called EXIFTool (https://exiftool.org/) is used to extract metadata of all the photos mentioned above and subsequently written to one XML file. The resulting XML file is imported into a database and through some SQL queries, tables and charts are prepared for presentation. The second step can be done in different ways. I am just outlining my general approach. Time and date-centred queries to the raw data from the photos were pared down to 11 full years starting from October 1, 2011 to September 30, 2022. The first year or so of birding wasn’t the most productive nor the most insightful, as lack of experience and a lot of trial and error on the author’s part probably distorted the data in that earlier timeframe. Full disclosure: There are 5 photos with the wrong EXIF data information due to new camera misconfiguration. These were taken in November 2014 but the EXIF information showed October 2014. Those have been manually reassigned for the graph. The possibility always exist that human error can result in wrong interpretation of data. Luckily these errors were known ahead of time. Results and analysis (with apologies to serious data scientist) Best months for birding A plot of month of the year vs number of photos. Click to see larger chart Let’s start with the assumption that bird and birding activity is correlated with the number of bird photographs posted in the album. Extracting and compiling the data on the date in which each photo was taken, we have the chart above. Mid-year seems to have the least amount of activity locally, as migrant bird species are absent. It is a good time for birders to consider going overseas for birding. Activity start picking up during autumn migration from the north starting from July/August and reach its peak in the month of October. Hence the answer to the first question posed is October. November and December are still active months for birding, but action tend to slow down in the new year. A modest rise in activity in March can be attributed to peak spring...