A year after the introductory post to my “All tied up” series I am actually releasing my next post. In the intervening year terms have, if anything, become even more interwoven with many of us often going to the now de facto ‘geospatial technologies’ to explain the wealth of technologies and data that we pull out of the toolbox and database for any given project. The term that has most been hidden by this (in my opinion, with no easy way to back it up) is Remote Sensing. By Remote Sensing I refer to what Lillesand and Keifer define as “The science and art of obtaining information…acquired by a device that is not in contact with the object…”.
This is a very broad definition and it captures all of the ways in which remotely sensed information is captured, but here I will narrow it down to those raster-based data (and occasionally point cloud data) that are captured from a distance. We can easily include photogrammetry (planes, balloons, etc) and satellite remote sensing capturing everything from panchromatic to hyperspectral images.
While we are on ‘what it is’ I will include what may get lumped in occasionally. Remote sensing is not all sensor data from remote locations. While the term is not incorrectly used, it is not always the same since some of these sensors are in direct contact with what they are measuring (stream gauges, temperature sensors, etc). So in a Venn diagram there is a large overlap between sensors located remotely and remote sensing instruments, but they are not completely overlapping sets. Kind of an aside, but I wanted to make a Venn diagram.
Getting back to remote sensing, there are two ways to look at the term. One is that it isn’t so much tied up, but largely absent in the industry today. In many areas, imagery has become the term of choice and, of course, the backdrop in our web maps, cartographic products, etc. In these projects and products we talk about imagery, but its source has become an almost unimportant aspect of some work. The other way we look at remote sensing is definitely one that is tied up in GIS. Many, many moons ago you had raster software and vector software and much of that raster geospatial software was driven by remote sensing activities, but that has changed (I think we can agree, for the better) in the GIS space as vector and raster has come together. As discussions with some of the leading remote sensing software vendors on the podcast have shown they are inline with, or even making tools available directly within, GIS software packages. We have lost the divide between GIS and Remote Sensing which having to switch between applications gave us. The separation continues to fade in terms of the software arena.
What does standout in terms of Remote Sensing, not tangled up if you will, is the hardware used to capture imagery (from satellite to helicopter to kite to drone…) and the data itself. This content continues to push our industry forward as we can collect both broad swath information that pushes science forward (e.g. moderate resolution data) and we continue to create sensors with ever-finer resolution and higher accuracy and precision (e.g. lidar). These data, as mentioned, are seen now more than ever with web maps and virtual globes, but it is the analytical potential that they offer, whether resulting in time series, human/environment processes, or finding archaeological sites, that are the strength of our investment in remote sensing platforms and data.
We will cut the strings there, as raster analysis is another set of terms that have been tied together as well. But keep in mind as you are doing your research or projects that your imagery is the result of over a century of research in capturing and manipulating images from a distance. While we have begun to take the technologies for granted in some cases, remote sensing remains an integral part of many areas of the industry.