Drone operators have a strong incentive to choose the equipment that will help them run their business most efficiently and profitably. This means balancing the upfront and ongoing cost of equipment with the productivity their solution will deliver for its intended application. Over time, the cost of labor usually means that a system that can deliver more acres per hour of data is a better choice.  In this document, we’ll look at the factors that drive the primary measure of drone productivity – the number of acres that can be surveyed per hour, and we’ll show how the new 6X sensor can drive productivity for your business.

What drives area coverage?

When planning an aerial multispectral survey, there are typically operational parameters that must be achieved to provide data that’s suitable for the intended end application.

Ground Sample Distance (resolution) of the imagery

Ground sample distance (GSD) represents the dimensions of the land each pixel covers. Typically, larger GSDs (lower resolution) are used for basic vegetative index mapping and smaller GSDs (higher resolution) may be required for advanced analytics such as plant counting, weed detection, and digital phenotyping.  Generally, at the same GSD, the more pixels the camera is equipped with, the larger area that can be covered while maintaining an equivalent GSD, although other factors, such as lens quality and angle of incidence requirements can also affect suitability.

Overlap and sidelap

When planning the mission, the operator must consider sidelap and overlap.  As the drone flies “lanes” back and forth to cover a field, sidelap is the percentage of overlap of the images taken from adjacent lanes.  Lower sidelap means higher productivity.  Typical sidelap requirements for image stitching software are 60-75%.

Overlap is the amount of common content in two adjacent photos taken in the same lane.  Like sidelap, overlap requirements will be driven by the end application for the imagery, but it is common that drone missions are planned with 75% overlap in order to accommodate stitching the photos into orthomosaic usage tools such as Pix4D or Agisoft.

The design of the drone and sensor can have a significant effect on how efficiently the system can produce data with the required GSD, overlap, and sidelap.

Maximum effective ground speed, the rate at which the drone can pass over the survey area, directly impacts this number.  Often, this figure is limited by the capture rate of the camera, the speed at which the camera can collect images.  To achieve the required overlap between successive images using a “slow” camera requires the drone to slow down so that overlap is preserved.

Most multispectral sensors available today deliver only around a 1 frame per second (1 Hz) capture rate. This limits how fast users can fly their drone and therefore, reduces the number of acres covered in any given period of time.

Determining maximum flight speed

The equation below shows how to determine the allowable flight speed for your particular mission.

Ground Speed = GSD * Vertical Pixels * (1 – Overlap) * Capture Rate

A typical multispectral sensor application is shown below. In this scenario, a sensor operates at 1Hz capture rate and is equipped with 1.2MP cameras measuring 960 pixels in the vertical direction.  The target GSD is 4cm GSD, with 75% overlap and sidelap.

Ground Speed = 2.5 cm/pixel * 960 pixels * (1 – 0.75) * 1 Hz = 600 cm/s = 6.00 m/s

In this case, the drone is restricted to 6 meters per second (about 13 mph) in order to maintain the desired overlap. Given that a DJI M200, for example, is capable of flight speeds of 17 m/s (about 38 mph), a notional M200-based system with this equiment is achieving only about 1/3 third of its potential coverage rate, simply due to speed limitations. The operator will spend literally 3 times longer in flight than necessary to collect the same data – wasting time and money.  In truth, because of added battery swaps and resulting time on the ground and transiting back to the operator, results will be even worse.

The 6X difference

The 6X uses a very high-speed onboard processing engine, engineered by Sentera specifically to support high-rate data capture.  6X effectively eliminates the need to calculate allowable ground speed based on capture rate, maximizing the potential coverage of an aerial drone system equipped with the 6X.

Instead of 1 image every second, 6X can capture 5 frames per second, simultaneously, across all 5 3.2MP multispectral bands and the 20MP RGB band.  High-quality optical components and focal array components deliver excellent accompanying blur and image quality, even at maximum rate.

The difference is clear.  Here’s the same potential throughput using 6X:

Ground Speed = 2.5 cm/pixel * 1542 pixels * (1 – 0.75) * 5 Hz = 4819 cm/s = 48 m/s

48m/s or 108mph is faster than any practical drone platform, but clearly, an operator using an M200 or Inspire-class product can operate at the system’s full speed – realizing a true tripling of acres covered per hour.  Capture rate is not a flight planning consideration.

What This Means for Land Coverage

With the 6X, operators can fly as fast as the system allows. The plot below shows how many acres can be realistically imaged in a 30-minute flight at various GSDs. These assume 75% overlap for a stitched orthomosaic end product.

This plot shows how the coverage of the Sentera 6X installed on a DJI M200 (green curve) compares to other multispectral camera systems. Whereas the coverage for the other cameras is driven by the frame rate of the camera, 6X is limited only by maximum drone transit speed.

Of additional note is the dotted green line which illustrates how much coverage the system could be capable of were it not limited by the maximum airspeed of the aircraft. Clearly, the Sentera 6X multispectral system has significant margin to accommodate faster aircraft or significant tail winds without capture rate ever becoming a concern. Meanwhile, coverage rates for the competitive products listed are limited by the sensor capture rate. These curves allow no margin and would require the proper calculations to be performed to determine allowable ground speed before flight.

Written by Ryan Nelson, Chief Mechanical Engineer