Many people depend upon a digital terrain model for a number of different reasons. Elevation measurement of the earth’s surface is an integral piece of information. Flood mapping depends upon correct elevation data. It helps us to understand where rising water levels will appear and provides valuable information for emergency planning and response. Knowing the elevation supports determination of aspect (north-south-east-west) of a given point, thus knowing where the sun will shine or not, the wind will occur mostly, as well as the suitability of a particular land use — particularly for agricultural, construction or transport. Obviously trains cannot run up or down fifty degree slopes, for example.
The same principle applies to aerial sensing for photogrammetry purposes whereby flight planning often entails determining flight lines (where the aircraft will fly) to avoid excessive overlap (sidelap, endlap) and boundaries.
Thus flight lines are interpreted similarly to ground transect lines with information gathered along them using either GPS on the ground or aerial cameras from an airplane — two different techniques and approaches.
On the other hand, satellite In the case of GPS, advanced techniques are often used and this may include GPS networks. For example, the Ordnance Survey in the UK operates a GPS network across the country — as do many other countries. The results of measurements using GPS techniques can often be better than half a meter and may approach centimeters in most cases. This is also true for aerial gathered data using digital photogrammetry techniques. Satellite sensors can also acquire elevation data with a high level of accuracy and precision.
But can we separate one technology from another for a given application? For national or broad regional questions that demand similar data across long distances, it is often impractical to start building a gridded network of GPS points. If the points are widely separated, then the derived terrain model may not represent undulations and changes occurring between measured points accurately.
Conversely, aerial or satellite generated DTM information may include costs that are prohibitive to their use, particularly for small and intermediate sized companies. I have heard this stated many times.
But the fact is, people do not use DTM’s alone. They are usually coupling them to other goals and purposes associated in their projects. It is not uncommon to see other sensors, often expensive and demanding a high degree of knowledge for their operation and can be used together with topography. In some instances sensors that measure radiance, salinity, aerosols, traffic and other application types may include spatial processing that is dependent upon topography.
Did you know that about 18% of top US farm producers are producing about 72% of that countries corn? These are the alpha or early adopters in the agri-food production cycle. While the geospatial has at times dismissed the agricultural community for more lucrative waters, the fact remains, this core group (and they exist around the world), base their decisions on science, knowledge and new tools. They achieve efficiencies and aim for them, and they benefit from the returns.
This group of people understand that food production is a series of processes, much like constructing a building, and they couple topography into quite a few of these processes, from seeding to management to distribution and marketing. They are pursuing ‘whole plant system agriculture’ that effectively ties 3D into the production cycle as they develop sustainable agricultural systems.
These systems are complex, but the drift towards simplicity is enabling these changes while maintaining the real complexity under-the-hood.
This poses unique challenges for the GPS industry in agriculture, since laser remote sensing and radar can effectively provide a more densely measured topographic network. However, the role of GPS is about to change and become more tightly coupled to secondary sensors and other technologies that support the digital farm and whole plant agriculture in 3D. That 18% or alpha group is leading the way in terms of technology use and application. They are found in areas like wines, grains, hay, beans and fruit production. Their work will lead towards higher traceability, greater food security, more efficient processes for production and include distribution and economic networks linked directly to banking and finance.
Is aerial sensing or GPS more effective for topography applications? In many ways topography is a key element that will play a major role in the upcoming 3D agriculture future. Imaging sensors will monitor production and also provide valuable information. I suspect that the sweet spot in all of this will be the point where GPS and topographic technologies converge to support agricultural processes more effectively. This is different than providing technology alone, it requires an understanding of how the early adopter agricultural community really see agriculture in the future.
While the 3D building environment is pursuing 3D BIM and other applications, an analogy can be drawn, closely, to what farmers are thinking about underground in terms of roots and how they gauge land tenure, operations, production and maintenance over the sustainability cycle.
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Jeff Thurston is editor and co-founder of V1 Magazine. He is based in Berlin.