Brendan Collins chatted with Jeffrey Meyerson for episode 1250 of Software Engineering Daily. You can listen to the full podcast and access the transcript here.
Software Engineering Daily is a hub for tech leaders to keep up with current and emerging trends in the industry. Through articles and daily podcasts, Software Engineering Daily spotlights how technology is influencing different disciplines and provides deep dives into tech niches such as open source, blockchain and cloud engineering.
Some Key Questions Answered
Why is Geospatial data important today?
Brendan talked about the importance of geospatial data and its intersection with many industries, especially when it comes to questions that are influenced by location-based data for which the matter of “WHERE” is crucial.
People think a lot about the capture, storage, analysis and visualization of data. These steps advance at different rates. You may start out with a remote sensor which is collecting a certain amount of data at a specific time, but that data has to be stored somewhere and eventually analyzed to derive useful information.
An emerging trend is the increase in use of open, transparent tools and the building of communities around open source GIS tools for geospatial analysis, such as GeoPandas and GDAL.
At makepath, we focus more on the analysis of geospatial data and create open source tools for analyzing increasingly large and growing data sets. The goal is to create tools that can handle planetary-sized questions and make existing algorithms faster, more accessible and extendible.
What are some high-level application domains in need of geospatial analytics?
Epidemiology: An original use case of geospatial analysis is John Snow’s cholera outbreak map in London in the mid-19th century, looking at the relationship between wells, drinking water and cholera outbreaks. More recently, with the COVID-19 pandemic, the question of “WHERE” has been really important, for use cases such as contact tracing.
Finance: A current use case could be an analysis to determine the downstream effects, geographically and financially, of a vessel getting stuck in the Suez Canal. How do you quantify that? This can be done through analysis of ship trajectories, where we try to understand where these ships are going and the implied costs of unforeseen delays.
Natural Resource Management: We recently worked on a project that aims to quantify the amount of carbon in a stand of forest, in order to attribute a dollar value to the standing wood and capture an externality that is the storage of carbon.
What is makepath? How do you empower your customers?
makepath is a services firm with a focus on spatial data science and open source. We use open source tools to solve spatial data problems. We also create open source software tools and communities, such as Xarray-Spatial, a spatial extension for the Xarray library.
We take tools from general data science, such as Numpy, Pandas, Dask and Numba, and implement the core spatial algorithms needed to analyze geospatial data, using lingo and functions that geospatial analysts understand.
Filling in the gaps with Open Source Tools
What changes do you think are coming?
Increased focus on storytelling
With the increasing amount of data companies are generating, it can be difficult to synthesize it to tell an impactful story. How are companies communicating data so those insights pop out? The ability to tell a story will remain fundamental. An increased focus on visualizations speaks to that.
To tell the right story with data and scale analysis to larger data problems, it helps to be able to see the relationships between the dimensions in your data, to find outliers and to understand the relationships between variables. With open source libraries like Datashader, users can analyze points on the order of trillions with reproducible tools that allow them to visualize things without having to go in and make tweaks specifically for that data set.
Open source Geo in the public sector
State and local governments are finding open source tools to be increasingly reliable and easy to use. This is an asset in settings with high-turnover, need for continuity between different groups, redundancy between organizations and expensive license fees. This is especially helpful to public entities that do not plan to invest in expensive proprietary software solely geared towards geospatial applications.
Have any questions about the increasing importance of geospatial data analysis or any topics covered in the podcast? Let us know in the comments section below or drop us a line at email@example.com.