One of the neat things about working in environmental monitoring is the sheer range of tools available to use, and the rate at which they’re evolving. One example that’s rapidly changing monitoring science is the technology around remote environmental sensing—things like detailed satellite imagery of the planet.
The expanding array of Earth observation (EO) data is a goldmine of information. But it’s also a challenge: how do you integrate so much info from so many new and different sources into something cohesive and useful? Over the past year, the ABMI’s Geospatial Centre has been working on this in developing its new Advanced Landcover Prediction and Habitat Assessment (ALPHA) program.
With ALPHA, we’ve tried to approach a range of questions of interest to our data users by integrating input data from three distinct categories: static, real-time, and historical. Using these input data sets, we can get new info for all of Alberta every 3–4 days and can even look back in time to monitor historical landcover trends.
This approach gives easier access to large-scale (provincial to national and even global) data, and it offers uniquely consistent, seamless, repeated data collection for basically any study area (even daily revisits in some cases). And it’s especially useful for remote areas such as northern Alberta, since consistent field data collection and acquisition of airborne photography can be challenging. The different input data types naturally give rise to different output data products, which can be used to ask and answer questions like: Where are all of the wetlands in Alberta? How often does this particular prairie pothole flood? What year was this harvest area cut?
Like all ABMI data, data sets resulting from the ALPHA project are available for free from our website. We’ve included URLs for each, in case you want to check them out—just copy and paste into your browser. We’ve also developed a short case study using ALPHA data sets and methods to explore a disturbed wetland/fen complex in northern Alberta.