A New Appreciation for Remote Geospatial Research

While I was in graduate school I didn’t understand why people got master’s degrees in geospatial analysis. Well, I guess I understood it, but I thought it looked like a miserable job.   I would come back from a field excursion with dirt covering me from eyebrows to boot tips, a month’s worth of lab samples in my backpack, happy as can be.   I felt sorry for the geospatial people staggering out from their computer-heated cave.  Now I have become one of those people; one of those sore-eyed, computer-staring people but I’ve discovered a new appreciation for remote sensing-based research.

Field work is fantastic for localized research, especially if that research is something that happens on a very fine scale. Field work can be undertaken on a huge scale, and sometimes it is: someone went into the mountains all over this country and mapped geologic formations. Teams of surveyors went out and stood in the roads and fields to get elevation data for us to plug into maps and databases. Field work is important; data needs to be collected and collected accurately. It’s just expensive. In academia it is not uncommon for some university departments to have millions of dollars coming in as research funding. Coincidentally, those university faculty have summers off for month-long research trips. They can also take semester or year-long sabbaticals and enlist free labor in the form of undergraduate students eager for practical experience. This kind of funding and set-aside research time often produces robust databases of fresh, fine-scale information.

Those resources and research breaks are not available to the commercial industry. It isn’t practical or affordable so frequently a remote based approach is used. Think about it: in order to get the similar data via field work a team would have to work more hours overall to complete the project. The team needs to get to the location so there would be travel costs. Equipment needs to be purchased or rented. For companies with profit margins and deadlines more concrete than, “Eh, we can publish it by the summer of 2019” extensive field data collection usually isn’t feasible. What I have learned to appreciate is that we don’t always need field work.

A “need” to create my own new and accurate database was my big hang-up formerly preventing me from getting on board with research done predominantly through remote sensing techniques. In field and lab research, most teams have extensive chain of custody procedures to track samples and data from field collection through lab analysis through the formation of a database. This is to ensure that variables are being measured in the same way, that the samples have been preserved, stored, and handled properly, and to have a defendable record of the data’s veracity. This is a good policy.  Geospatial analysts are almost always using a database collected by a stranger, which is then reformatted to fit whatever program is being used in analysis. Sure, metadata describing the database is usually available, but it typically does not go into great detail on data collection methods. Remember the game “telephone” we played as kids? Sometimes it ends up like that: addresses that belong to waterfront marinas end up four blocks inland, the scale isn’t accurately recorded in the database description, and sometimes whole variables get corrupted or go missing. With some extra work most of those issues can be fixed.

I’m currently working on a government transportation project. We had to field verify about 100 sites and it took two people 12 hours. That’s 24 man hours just on field verification. Remotely I can accurately review about 300 sites in an eight hour workday.  That’s about 4 times as fast.

Ultimately geospatial analysts do some field verification and field scientists use ArcMap to display and analyze their data. These things are not opposites; remote sensing and field research techniques are both tools used to answer questions about the world around us.  Field scientists are often able to create dense, detailed datasets because they have set aside time for research built into their jobs, sources of cheap labor, and access to academic research grants. Geospatial analysts are able to quickly determine temporal and spatial relationships across a given area with a much smaller budget than that of a field team assigned to the same task.   Both approaches have an important role in getting the most accurate data in the most time and cost-effective manner.

Post was written by Christine.

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