Design Considerations For Long Range, Light Logistics Drones

Earlier this year, WeRobotics, in association with Peru Flying Labs, completed medical cargo delivery trials in the Peruvian Amazon. They released a very thorough report on their experiences, which can be found here. Event 38 participated in the trials by customizing aircraft for longer endurance flights, higher gross weights, and dual R/C control capability, though we were not able to participate in the direct operation of the aircraft. Cargo deliveries by drone are still a very new application with little field experience available from which to draw new development upon. I applaud WeRobotics for undertaking such a challenging project and for documenting their experiences so thoroughly. Cargo delivery missions are very different from mapping missions, and so demand a different set of equipment and processes. There are many options and performance tradeoffs to consider for any group looking to make cargo deliveries over relatively long distances. Considering specifically the type of cargo deliveries made by WeRobotics, I’ll address some of the options for such a mission profile and make recommendations for what features an operator should look for when selecting an aircraft. Each of the following phases of the mission must be considered: Launch, Transit, Delivery and Recovery.



The aircraft must be powerful enough to accelerate to a safe airspeed then climb quickly to avoid obstacles, even at relatively high takeoff weight. Taking off without launching equipment limits the maximum takeoff weight to whatever the operator can carry and requires the aircraft to accelerate more quickly to safely ascend. Fortunately, oversized electric powertrains do not have the same penalty that a similar gas engine would have, so electric aircraft can easily be powerful enough to accomplish this at even moderately high gross weight, up to about 12 pounds.  At low airspeeds, the propeller may be stalled, reducing the thrust output at the most critical stage of flight, so it is important to select the propellers carefully for takeoff thrust and efficiency in cruise.

Adding an extra motor is another way to address low takeoff thrust, but flying with two motors or more reduces efficiency for the rest of the flight. Direct failure of a motor is rare, but having an extra could theoretically improve reliability as long as the electronics are able to isolate a failure of one from the other. The autopilot also need to be able to safely fly the aircraft on one motor, something that is notoriously dangerous for human pilots. Using launch equipment on the other hand requires bulky equipment and increases investment and transportation costs. For a delivery program based out of designated locations though, it can increase the maximum payload significantly.

VTOL aircraft can certainly simplify the launch and recovery procedures, but come at a significant cost in terms of equipment, maintenance, and risk. VTOL aircraft by their nature require 5 times as many motors, ESCs and propellers as other aircraft, each of which must be maintained and checked for each flight, and each of which poses an additional failure risk. VTOL capability also adds relatively significant weight to a plane and typically are fixed externally, increasing drag and decreasing lift over the nearby wing section. With the right value of goods and mission profile, VTOL can and will excel in the future, but such opportunities may not be widely available today.



Because mapping aircraft usually fly equally with and against the wind, they can recover some lost energy by traversing downwind segments in less time. A cargo aircraft must be designed to operate an entire flight completely upwind if necessary. For such missions, the aircraft must be able to optimize forward progress instead of time aloft. To do this, it must balance groundspeed against aerodynamic drag, which increases with the square of airspeed. An example of this type of feature is the Wind Resist function on the E384-LR.

Wind speeds at flight altitude also tend to be stronger than on the ground. Operators must take this into account when planning missions. I’ve found to be a helpful tool for planning higher flights as it shows estimated wind speeds at various altitudes, but any such forecast has only limited accuracy. Wind poses a major risk to aircraft flying BLOS and out of communications range because conditions can quickly change during flight and local terrain may amplify prevailing winds to the point where they exceed the maximum speed of the aircraft. If operators are unable to maintain a telemetry link with the aircraft for the entire flight, the aircraft needs the capability to determine whether or not it can reach its primary landing zone and to automatically reroute to alternative LZs if not.

For any flight covering more than a few kilometers, it becomes necessary to use terrain following in order to safely maintain the planned altitude above ground level. For cargo drones this not only protects them from colliding with terrain, but it also helps maintain the lowest wind speed possible at lower altitudes and keeps them free from endangering other aircraft assuming proper permissions have been arranged.



The only two realistic delivery mechanisms for logistics drones at this time are landing the aircraft or dropping the cargo from the air with a parachute. Landing completely has the benefit of reducing aircraft range requirements by half, which also significantly reduces aircraft cost. It will increase operating and infrastructure cost however, and requires personnel at both the sending and receiving end of a delivery mission. Setting up a system in which the aircraft can land at all locations also opens the possibility of 2-way deliveries, something which is mentioned as a need for isolated communities. An aircraft capable of out and back flights for the longer distances described in the WeRobotics report will likely require larger launch equipment, more space to land, and a much larger investment.



Aircraft recovery in the WeRobotics trials was performed manually using specially outfitted aircraft to be operable by two separate R/C remote controllers. This method worked well for trials but may be difficult to scale and over time will have some added level of risk associated with human operators. It also requires a skilled operator to be present and ready for the arriving aircraft. Two other methods should be considered for aircraft recovery, auto-landing and parachute recovery. The former would likely require RTK GPS for accuracy and even then would still require a relatively large open space, something which was not conveniently located in all the Peruvian trial locations. This would increase infrastructure costs and may still pose some technical challenges with the aircraft switching between RTK base stations mid-flight. The last option, parachute recovery, is likely the best choice for cargo deliveries such as those performed by WeRobotics. It would have a payload or range penalty associated with it, but it significantly reduces the level of expertise needed by remote airfield operators. Aircraft could be landed automatically, and no operator would need to be immediately present. The parachute can also act as a safety device to improve the survivability of the aircraft if any other failure occurs during flight. Event 38 is continuing to test parachute recovery options, but some commercially available ejection mechanisms have serious drawbacks such as unreliable deployments or packing difficulty that need to be overcome.


Recommended Setup

Based on the WeRobotics cargo delivery mission profile and the desired capabilities and budget, I would recommend the following configuration for further testing. The aircraft should use a single, forward mounted motor and large propeller optimized for hand-launches and flight speeds up to 16m/s. Due to the high expected utilization, high temperatures, humidity, and difficulty of obtaining spare parts, an investment should be made into higher spec components including servos, motor controllers, and auxiliary power supplies. The aircraft mission software should be configured primarily for one-way flights, to include a ground advancement optimization, terrain following, and automatic mission abort based on estimated energy remaining. The aircraft should use a parachute for recovery, with an additional form of protection for the bottom of the aircraft in case of landing in brush.

Most of these features are commercially available although not necessarily all in the same aircraft. Event 38 has recently made some of these features standard, like Wind Resist, terrain following, and adding further safety margin to certain components like servos and power supplies. Ultimately, it is possible to achieve reliable operation of cargo drones within the requirements of a humanitarian mission operating in remote areas. A drone outfitted with the equipment described here has the best chance of success, while balancing simplicity and cost. I’m excited by the progress WeRobotics has made already. I hope to support their and other teams’ future efforts in building links to remote rivers and trails by taking to the sky.

Mapping with the new Event 38 Companion Computer

The companion computer is a fully integrated solution for streamlining the mapping and geotagging process on the E384 and E386. It allows users to completely bypass the normal geotagging post-processing step. This relieves a burden on operators running frequent missions, and improves the geotag accuracy of those missions at the same time. That can lead to faster and more accurate orthomosaic stitching, too.

Here’s how it works. The Companion Computer connects directly to both your Sony QX1 camera and the Pixhawk autopilot. When you power on the aircraft, the camera automatically powers up and connects to the Companion Computer. When ready, it displays a green LED.

In flight, the Companion Computer verifies directly with the camera that each picture was taken as expected. As each picture is taken, the Companion Computer transfers the image from the QX1 in real time to its own, easily accessible thumb drive. As each picture is saved, its geotags are added directly into its EXIF data as part of the same file and also written to a text log. The images with EXIF data can be imported directly into almost any post-processing software without further handling, but the logs are always there for reference.

If the camera is taking images too quickly for each one to be transferred in real time, Companion Computer will attempt to catch up when the camera is less busy. For large, low altitude missions especially, images may still be processing after the aircraft lands. In this case, the solid red LED will let you know to wait until the process is complete before powering down the aircraft or removing the thumb drive.

When you leave the field, just pull out the thumb drive from the Companion Computer and bring it back to the office to upload or process your imagery. It’s as simple as that!

We’ll be releasing Companion Computer publicly in a few days, sign up for our newsletter to hear when it’s available. As always, feel free to contact us with questions or feedback.

PPK GPS Tests Completed

With the Emlid Reach RTK GPS Receivers now available, we’ve been conducting tests to determine their accuracy and working on the integration into the E384 and E386. The goal was to determine relative, or scale, accuracy as well as absolute accuracy verified with a survey grade Trimble R6 Model 4.

We post-processed the data in three different ways to explore the effect each would have on the resulting data. For PPK GPS processing, there is a receiver onboard the aircraft and another stationary receiver on the ground. The ground receiver (base station) is used to calculate corrections to refine the position of the airborne receiver. The base station also calculates a precise GPS coordinate for itself, with the option of writing in another, more accurate coordinate if desired. We constructed orthomosaics on the Drone Data Management System™ using geotags calculated from the Reach base station and the Trimble base station, using either the Reach base coordinate or the Trimble base coordinate. The combinations for each test are listed below.

Base Station CorrectionsBase Station Coordinate
ReachReach + CORS
ReachTrimble R6-4 + ODOT VRS
Trimble R6-4Trimble R6-4 + ODOT VRS


It was clear straight away that there was an offset between the Reach and Trimble coordinates, so we focused on scale accuracy for this test. The offset is clearly visible in the image below, where emp is the Reach base station coordinate and 6 is the same coordinate shot by the Trimble R6. To measure the scale accuracy of the Reach-only orthomosaic, we measured distances between several pairs of GCPs in different directions. The error was 3cm in each case.

GCP PairReach Orthomosaic (m)Trimble R6-4 (m)



Processing the geotags using the Emlid Reach base station but using a coordinate shot by the Trimble R6-4 resulted in very good accuracy relative to the Trimble shot GCPs, with an RMSE of 3.36cm.

GCPError (cm)



Finally, processing using the trimble base station for both corrections and the base coordinate yielded similar results to those obtained with the Reach corrections, RMSE 3.54cm.

GCPError (cm)

These results should be considered very preliminary, as there were a number of factors that could have adversely affected the accuracy. The Reach coordinate may improve once we are able to calculate it with a closer VRS. The mission was collected with a relatively high GSD of 3.5cm/pixel, so it is difficult to pick the GCPs accurately.

Still, there are some conclusions we can draw from this data. Even without a good base station coordinate, the Reach system can produce very good scale accurate results. When paired with a higher quality coordinate, the Reach can produce very good absolute GCP coordinates. If a fixed position can be marked once by a survey grade GPS, then it can be used as a reference point for all missions in the same area, forever. It may also still be possible to obtain similar results with the Reach alone using the VRS network or Precise Point Positioning.

We’ll run more tests to verify the accuracy, but initial results are very good. We’re now making the first deliveries of the Reach system to select clients before a wider release in the very near future.

Automated Optical Crack Detection in Pavement

At Event 38, we build drones for data collection, sensors and post-processing software. That puts us in the unique position of being able to support the full workflow from flight to results but also gives us all the tools we need to explore novel applications for drone data. Today, we’ll investigate the capability of drones to automatically capture, quantify and report on the presence of cracks in pavement. We’ve written an algorithm that automatically filters cracks from imagery and then calculates their length, width and density.



Our algorithm uses ortho-rectified and stitched color imagery only. A series of morphological transformations is made to highlight then quantify the position and shape of each crack while ignoring irrelevant changes in color and texture. Although it would seem helpful, point cloud (elevation) data from LiDAR or photogrammetry would require excessive data collection to resolve height differences at the scale of most common cracks.



Using automated image processing only, we are able to separate real cracks in pavement from wet spots, stains, painted lines and tire marks.

The algorithm can be adjusted to discern cracks of different sizes. Detecting smaller cracks increases the rate of false positive detection, but most can be filtered so that small cracks are only detected when they occur together in groups.

We’ve also created a set of analytics tools that organize data about the cracks into human-readable statistics. These values can be used to compare the density of cracks between areas or over time.

Estimated Average Width1.01cm
Total Area14.46m²
Density (linear distance/unit area)0.7267m-1



This algorithm works best on light colored, clean pavement. Asphalt and tar hide the contrast of cracks and return few results for cracks less than 4cm wide. Surfaces with deteriorating coatings can also cause too many false positive returns because the peeled layers create edges and shadows that appear as cracks to the algorithm.



Despite the limitations, there are useful applications for crack detection and monitoring. Because the cracks can be quantified and mapped by density, the data can be used to determine when repairs are due and to monitor deterioration over time. Because the cost of collection and processing is small, it can be applied to many common commercial and industrial applications such as parking lot and private road maintenance.

Data for this study was collected at 35m altitude with a 12MP sensor. Assuming a small, square or rectangular project area and using an Event 38 multirotor mapping drone, data could be collected at a rate of about 1.2 acres per minute of flight. Including battery changes, an operator could cover up to about 45 acres per hour. If the project area is a long, thin strip of pavement such as bridges, roads, highways or runways, a fixed wing E384 or E386 could be used to cover significant distances quickly. An E384 could cover up to 21km linear distance over the course of an 80 minute flight making three passes at different angles.

We are encouraged by the promising early results from this algorithm but more user feedback is needed. If you can collect high resolution data or are interested in a joint research project, please contact us to discuss your application.

Color, NIR and NDVI imagery According to Iowa State

The Integrated Crop Management News, and Iowa State University Extension and Outreach program recently published an informative article on how to choose the right imagery, in regards to best management practices for Color, NIR, and NDVI imagery. Read the full article, here or continue on below:
May 17, 2016 via Iowa State University Extension and Outreach: Integrated Crop Management 

Figure 1. Shown from left to right are examples of Color, near infrared (NIR), and Normalized Difference Vegetative Index (NDVI) images. The images were captured with a Rotary Platform small Unmanned Aerial System (sUAS). 

Key Points:

  • RGB (color) imagery is similar to viewing a digital photograph taken from a plane.
  • Near infrared (NIR) imagery provides a greater assessment of plant health than traditional photos by visualizing color bands outside of what the human eye can see.
  • Normalized Difference Vegetative Index (NDVI) is a commonly provided index that assesses crop vigor based on a mathematical interpretation of color and near infrared data.
  • Imagery is very useful to identify areas of crop variability, but field scouting is often still required to verify the cause of variability.

As spring leads into summer, don’t forget to consider aerial imaging as part of a continuous improvement plan for crop production. Remote sensing and the use of aerial imagery has been used for decades in agriculture, but we’ve seen the number of imagery providers grow extensively since 2010. The use of imagery can vary from farm to farm but several common uses include: variable rate fertility recommendations, assessing water management performance, quantifying soil compaction and machinery induced yield limiters, locating late season weed outbreaks, and generally evaluating the consistency of crop vigor across a field.

Most producers will source imagery from an input service provider or a technology service provider. Service providers work with a range of different platforms to capture crop imagery. After an image is captured and processed, these service providers often give more than one final image back to a grower. It is important to know the differences between the types of images and how each can be used to benefit a grower. Three of the most common images provided are color (RGB), Near Infrared (NIR) and the Normalized Difference Vegetative Index (NDVI).

Comparing Imagery Types:

Color RGB (Red, Green, Blue): also known as color imagery are images that most closely represent how the human eye would see a field from a plane.

  • Provide shape and definition to problem areas that would be difficult to define at ground level.
  • Available from most aerial imagery platforms.
  • Typical uses: Color imagery provides an opportunity to identify areas potentially in need of greater water management and the effects of management systems; i.e., turnarounds in the headlands and planter skips. Additionally, it can be used to do an initial quantification of lost production acres.

The figure below shows a typical RGB image of a corn field that was captured on June 25, 2014 by a contract flight. The image had a pixel size of 0.8 ft.  In this field we can identify the following production features: planter skips, drowned out spots, and areas damaged by turning equipment.

Color imagery does have limitations.  Generally, the crop needs to be significantly stressed in order to see a visual difference that can be identified in a color image. Additionally, color imagery provides little opportunity to distinguish small differences in areas of high yield. Color imagery also has less value prior to a full canopy due to excessive soil saturation in the image.


Near Infrared Imagery (NIR): also known as color infrared imagery, uses a false color composite to display information that would normally be invisible to the human eye. The NIR map shows areas of highly vigorous crops in bright red and weak crops or bare soil in gray.

  • Plant health is displayed with a greater range of detail than the color image. Plants will often show response to damage or disease in NIR images before the same response is visible with a color image.
  • NIR is commercially available from most imagery vendors and is typically part of the base imagery package.
  • Typical uses: Quantify machinery induced crop limiting factors and weed detection. Provides higher levels of detailed assessment for defining management zones, making fertilizer recommendations, quantifying ponding or water management effectiveness, and generally assessing crop vigor across a field.

The figure below shows a typical NIR image of the same corn field that was captured on June 25, 2014 by a contract flight. The image had a pixel size of 0.8 ft. In this field we can identify the following production features: drowned out spots, turnarounds in the headlands, machinery induced crop limiting factors, and areas where water damage occurred, but did not kill the plant population are visible.

NIR maps have a key advantage over color RGB in that they show crop performance and vigor in much greater detail. The goal in agriculture is to have a uniform emergence and vigor throughout a field. NIR maps can provide key information related to whether this goal has been met across a field. In the example image below some artifacts are controllable while others are not. The wet spots in the field are likely not controllable without significant investments in drainage. These areas are already likely well understood by the producer.  The higher resolution issues from machine traffic and individual row emergence can be resolved and are actionable through an increased focus on planter management.


Normalized Difference Vegetative Index (NDVI): is a calculated index used to monitor crop health and photosynthetic activity. The higher the index value the greater the crop vigor.  A color gradient is applied to make the image easier to interpret. A commonly used gradient is red to green; red being the low values and green being the high. Typically four colors are used with each representing approximately 25% of the field. This is similar to how a yield map represents data.

  • One of the simplest indices, commonly provided by imagery providers as part of a standard imagery package.
  • Two different types of NDVI image: Calibrated and Uncalibrated/Maximum Variation Scaling.
    • Calibrated NDVI images can be used to show changes in vegetation due to management systems or other factors over time.
    • Uncalibrated or Maximum Variation NDVI images can be used to show crop vigor at a particular point in time. It’s the most common type currently provided by imagery providers.
  • Typical Uses: NDVI imagery has been widely used to assess crop vigor across a field, areas of ponding and changes in field conditions over time.

The figure below shows a typical uncalibrated NDVI image that was calculated using the contracted flight imagery captured of the corn field on June 25, 2014. The image was calculated with a 0.8 ft pixel size. In this field we can identify the following production features: planter skips, drowned out spots, areas damaged by turning equipment, variation in the amount of water damage for some areas, and boundaries for where damage occurred.

Similar to NIR the NDVI map shows variability in crop vigor in greater detail than a standard color image. Color scaling for the NDVI map does need to be considered when making recommendations based on the imagery. Uncalibrated NDVI which is the most common form will always results in areas of red and green within the field, even if the entire field is relatively strong or relatively poor. As a result, NDVI is a good information source for quickly evaluating different production zones or artifacts within a field but scouting is still required to assess the magnitude and cause of the variability.


Links to this article are strongly encouraged, and this article may be republished without further permission if published as written and if credit is given to the author, Integrated Crop Management News, and Iowa State University Extension and Outreach. If this article is to be used in any other manner, permission from the author is required. This article was originally published on May 17, 2016. The information contained within may not be the most current and accurate depending on when it is accessed.

Process Maps, NDVI and 3d Models for Free

With the Drone Data Management System™ officially out of beta testing, I thought it would be helpful to go through and show new users how they can still use it to process orthomosaics, NDVI maps and 3d models with imagery from any drone for free. This isn’t intended to be a comprehensive guide to mapping techniques, but I’ll go through the basics for the sake of those with no experience. If you already have some data you’re ready to try, skip to the post-processing section below.

Data Collection

First of all, to make any map, you need to collect the right kind of imagery. For a drone, that means collecting images that point almost straight down and overlap at least 60% with its nearest neighbors front and back as well as side to side. In other words, if your camera has a field of view of 100 meters on the ground along the path of travel, it should move only 40 meters between shots. In general, 60% is an adequate overlap balancing coverage and avoiding excessive data collection, which slows down processing.

Planning for overlap and sidelap for Pixhawk vehicles is straightforward if you use the Mission Planner Survey (Grid) function. You can read more about that here: ArduCopter Wiki

DJI doesn’t provide planning tools for surveying missions, but some third parties do offer these features for the Phantom 3, 4 and Inspire 1. The UgCS app, for example, lets you plan a mission on a PC and then load it onto your drone. UgCS is free for private use and supports automated survey mission planning with camera and drone presets for DJI vehicles.

If your drone doesn’t have a gimbal, do your best to fix the camera pointing straight down. This might mean aiming a little forward to compensate for a multirotor’s pitch in flight. Most drones in ordinary weather conditions should be able to maintain adequate overlap. DDMS compensates for small angles off vertical that may be in some images.

Once you’ve collected all the raw images, give them a quick look. Make sure they aren’t blurry, don’t have part of your drone in frame, and that they appear to have significant overlap. It’s not necessary to geotag your imagery before processing, but there are advantages to doing so if you can. It speeds up processing, scales your map, reduces warping artifacts and makes it possible to take measurements from your orthomosaic. If your drone is running on Pixhawk and you’ve triggered your camera using the distance trigger function, DDMS can automatically geotag your images if you upload the telemetry log (.tlog) with your images. DJI drones automatically add geotags to each image.


Uploading to DDMS is simple. First, sign up here using just an email address. Then log in and click Create Mission. Enter a description for your mission and select the images and supporting files (.tlog) from your flight. Then just click Upload. At this point, your job is done, leave your browser open on this page until it prints a message that all images have been uploaded successfully!

To add NDVI or a 3d model to your mission, open the Missions Page in a new browser tab, select your mission and click the Analyze Images button. Be sure to leave the upload page open until it finishes. On the Analysis page, you’ll have the option to add NDVI and 3d Model generation. More apps are available with a paid membership.


Sample “Analyze Images” Page, Select Apps Here

Our NDVI process is optimized for NGB (NIR, Green, Blue) converted cameras such as our own custom filters/cameras and similar options like those from MaxMax. Some converted cameras, particularly the small, cheap ones, have serious problems with rolling shutter distortions. These distortions make stitching much more difficult as they aren’t consistent like the distortions from a lens, so try to check out some sample imagery before choosing a camera.

DDMS will take all your images and automatically process them into a 10cm/pixel geotiff (higher resolution available with paid memberships). If geotags are included, the mosaic will be georeferenced. It also automatically tiles your map for viewing online using Map Viewer. You can download the raw geotiff and NDVI mosaic for offline viewing by clicking Access Downloads on the mission page. Often times these files are too large for ordinary picture viewing software to open. QGIS or GlobalMapper are good options for offline viewing of geotiffs, but it’s almost always slower to work with these large files offline.

The Analyze Images page also shows you the status of each step of processing as it progresses. When each step reaches ‘Ready’ status, you can access the result by clicking directly on it. In Map Viewer, toggle between the ortho-mosaic and NDVI results by selecting the layer from the upper-right corner and adjusting the opacity slider.


Composite of two Map Viewer Windows, Raw NGB Orthomosaic on Left, NDVI on Right

DDMS also recreates a 3d model of each mission. Select the 3d Model app and download the files to explore using Sketchfab, Meshlab or another modeling package.

by Event38
on Sketchfab

Although the beta period is over, we are still actively seeking feedback from the community. We see a lot of users doing things we didn’t expect them to do with drone maps and we want to keep encouraging that kind of experimentation!

You can read more about the Drone Data Management System™ here. We have more apps available for the Pro and Advanced tiers, like DVI, 3d PDF, DSM, KMZ, Volume Calculation and Point Cloud Exports.

Proving ROI through Drone Stockpile Measurement in Mines and Quarries

Event 38 recently completed a case study on the use of drones for mining and quarry applications. In cooperation with a customer operating dozens of quarries, we compared and analyzed the accuracy and resource cost of using the E384 and Drone Data Management System™ with manual measurement to determine stockpile volumes. We found that switching to drone data collection reduced the required man-hours by approximately 60% while producing results within 2% of manual measurement.

To learn more, download the full text of the Quarry Stockpile Measurement by Drone Case Study.


Click here for more information on the Drone Data Management System™. The data for this case study was collected by the E384 but our other drones use the same data collection technique and sensors. Click here to learn more about Fixed Wing vs. Multirotor drones.

Traveling with The E384 – By Guest Author Frank Sedlar

Article By Guest Author:

Frank Sedlar

The sparse vegetation of Western Mali offers little protection from the sweltering sun. But today in the bush, even if there was cover everyone would still be subjecting themselves to the sun. It’s not everyday a UAV is flying overhead.

A group of kids excitedly giggle and point their necks skyward to catch a glimpse of Event 38’s e384 as it effortlessly glides overhead. I take a quick glance at my ground station before transitioning from pilot to crowd-control in order to clear a spot for the e384 to come in after it’s mission – a mission with a flight time of 60 minutes covering an area of nearly 4 km2 at a resolution of 5 cm/pixel. It’s an impressive performance but this flight time comes at a cost. To be capable of flying for 100 minutes you need a very large wingspan. 1.9 meters to be exact. Before I could perform this mapping in this remote area of Mali, I had to find a way to transport the e384 from the U.S. to West Africa.

The stockcase sold by Event 38  is excellent. Sturdy, customized exactly for the e384, and it comfortably fits all the necessary equipment. It’s a very good option to safely transport the e384. That is unless you need to fly. The total dimensions of the case (55’’ x 13’’ x 13’’) amount to 81’’. A bulky case by any stretch of the imagination that will not only guarantee you oversized baggage fees (typically above 60’’) on all domestic and international airlines but will even exceed the maximum baggage dimensions on some carriers. Delta for instance has maximum baggage dimensions of 80’’.

A second consideration when flying with the e384 arises from the batteries. It is extremely dangerous, and prohibited on all airlines, to have LiPo batteries (especially the powerful 10,000 mAh LiPos used on the e384) in your checked luggage. Rapid changes in temperature or pressure can have disastrous effects on LiPo batteries Note – before flying with LiPo’s always discharge them to a storage voltage and put them in a LiPo sack.

To travel to Mali I needed a case with the smallest possible dimensions and a means to carry on the LiPo batteries.

Enter the undisputed heavyweight champions of hard case carry, Pelican. After some exhaustive research I settled on a two part Pelican solution to transport the e384.

  1. A Pelican 1740 Long to hold the e384 and some sharp tools (knife, screwdrivers, etc) that the TSA won’t allow to be carried on. Dimension 44’’x16’’x14’’  = 74’’. Cost $320
  2. A Pelican 1510 with the 1519 Lid Organizer to hold the batteries, cameras, transmitter and a host of tools. Dimensions 22’’x14’’x9’’ = 45’’. Cost $160 + $25
  • Both cases use Pelican’s pluck and play foam to customize the exact fit.

1740 Long 

The 1740 Long perfectly fit the e384 with the tail section disassembled. Furthermore the case doesn’t appear as oversized baggage. In a number of flights with this case a quick smile to the airline representative working the check in counter has gotten this case ticketed as normal luggage (that’s a $300 dollar smile). When navigating an airport the wheels and handles on this case make transportation a one man job. Finally it doubles as a great desk for your ground station.

1510  + 1519 

The 1510 is designed to be the maximum FAA carry on size so it will fit in any overhead compartment. The lid organizer holds all of the tools needed for the e384, including the long range telemetry transmitter. The telescoping handle and the addition of wheels making traveling through airports a breeze.

The cost of this setup amounts to $510 USD, which if you’re lucky will pay for itself in the savings from over sized baggage fees from just one round trip flight. Furthermore Pelican cases give you a peace of mind when your e384 is at the mercy of rough baggage handlers in Bamako or long drives in the back of pickup trucks through “roads” in the African Bush.

The e384 is in a class of it’s own when it comes to flight time and ease of use. And with the right cases the e384 and its impressive 1.9m wingspan can efficiently be transported as easy as drones half its size.

Photos by Frank Sedlar and Andrea Amici

Frank Sedlar owns Vela Aerial.  He is currently a Fulbright Fellow to Indonesia where he works with the Government of Jakarta and Peta Jakarta  to coordinate an urban drone research program. He moonlights as a journalist for Carryology  exploring better ways to carry.

Drones for Business Use – Fixed Wing or Multi-rotor?

Drones for Business Use – Fixed Wing or Multi-rotor?

Founded in 2011, Event 38 builds and sells easy to use drones, sensors and a Drone Data Management System-TM . Customers all over the world use our drones for Construction, Environmental Conservation, Mining, Surveying and Precision Agriculture.


June, 2015 –  If someone mentions the word drone today most of us think of a four or six propeller frame with a camera mounted below thanks to their tremendous growth achieved in the consumer world. You can buy a drone that fits in your hand or one as large as a manned helicopter.

But for the business user there is another alternative, the fixed wing UAV.

So if you are a farmer, surveyor, construction company, or researcher which do you choose?

For the past four years we have been focusing on small and medium sized business and overwhelmingly, the fixed wing UAV is the drone of choice.

Drones are used today for a rapidly growing list of business purposes including: agriculture, surveying, construction, security, environmental conservation, inspection, aerial & cinematic photography, and a long tail of research applications.

As the cost of digitizing the physical world has decreased from $thousands to $pennies per acre, drone technology is solving age-old problems and creating unprecedented new opportunities. Sensor technology has also made tremendous progress – we are able to measure more things more accurately than ever before. Today we can track every single plant in a crop field at the leaf level. And for the first time, drones are able to work in areas that have been inaccessible or too dangerous to consider using manned aircraft.

Finally, we believe that we have only scratched the surface of drone, sensor, and software/analysis capabilities. As regulatory environments solidify and the technology continues to advance, the sky is the limit.

Drone Purchase Considerations

There are no real standards in our industry from which to easily make comparisons when deciding which drone to buy. In general, industrial users pick drone solutions based on several criteria:

  • Application specific requirements – what problem am I solving and what and how much data needs to be collected?
  • Endurance – how long and how far can it fly?
  • Payload capacity – how much weight can it carry?
  • Cost – what is the initial price and total cost of ownership?
  • Ease of use – how easy is mission planning, autonomous flight, and  data collection & management?
  • Software capabilities – what do I do with the data once it’s collected?
  • Customer service and technical support – how good is post-sale support if I have a problem?

So which type of drone do you choose?

Above all else, you need to consider the problem you are trying to solve. What data do you need, are there geographical and/or regulatory constraints, what analysis capabilities exist, and how much drone operations experience do you need to have? And remember that drones and sensors collect data, period. The key is in creating actionable information from the data collected.

In many cases either a multirotor or a fixed wing drone can solve the need at hand. As you might expect, there is much overlap in capabilities. However to generalize a little:

  • If an application only needs limited geographical coverage (ie real estate photography) or has narrowly defined physical constraints (ie bridge inspections) and needs relatively straight forward data collection sensors (ie short video and RGB still photography) then a multirotor drone makes sense.
  • On the other hand, if the user application requires wider geographic coverage (ie 500 acre farm) or needs highly specialized sensors, (ie multispectral camera, thermal imaging, Lidar, etc) or needs to operate at higher altitudes, then a fixed wing drone is probably a better alternative.

Benefits of multi-rotor drones

Many consumer oriented drones have been successfully employed in commercial applications and others built specifically for industrial use are extending those capabilities.

There are obvious things that they can do better, for example, get into confined spaces, ie under bridges, they can hover over a specific area to capture more information, and they need little space to take off and land. Here are a few pros and cons:


  • Cost – Usually less expensive
  • Applications – really good at aerial photography and hi resolution video
  • Ease of use – good
  • Access confined spaces more easily


  • Endurance – less flight time
  • Payload capacity – usually less weight
  • Customer service – little support if you are buying a consumer drone
  • Occasional bugs, ie “fly away”

Multi-rotor Summary – Most multirotor drones can fly up to 15-30 minutes carrying a still or video camera weighing less than 500 grams. They are relatively easy to use and moderately priced, usually in the $1,500-$4000 range. Leading manufacturers include DJI, 3D Robotics, and Parrot but there are literally hundreds of manufacturers from which to choose.

Benefits of fixed wing drones

When it comes to mapping anything but very small parcels, fixed wing aircraft win hands down due to the overwhelming endurance advantage. For the serious business user, this is usually the deciding factor. Additionally, fixed wing drones can fly faster when needed and can fly much higher – important for work sites above 5000’ elevation.


  • Endurance – fly as much as 10x longer and cover more geography in a single flight
  • Payload capacity – can carry more weight
  • Applications – larger selection of sensors


  • Cost – usually more expensive
  • Ease of Use – not as easy as a multirotor
  • Size – requires more space for storage and transport

Fixed Wing Summary – The fixed wing drone is a true workhorse for the business user. Most of these drones can easily fly a 250-1,000+ acre plot in a single flight and can carry a wider range of sensors than their multi-rotor counterparts. In general, they are priced in the $3k-30k+ range depending on the application. Leading manufacturers include Event 38, Agribotix, and Sensefly/eBee but of course there are literally hundreds of others.

You choose

Event 38 has been providing drones to business users and researches since 2012 and more than 80% of our customers choose the E384 fixed wing drone.

The E384 costs 5-20 times less than our competitors, has an industry leading flight time of two hours, and can carry a 1 kilogram payload. The E384 can fly a 1,000 acre farm in a single flight and capture data at the 2 centimeter level.

Customers have flown our drones for thousands of hours all over the world. Whether it’s a farmer in Brazil, a surveyor in Africa, or a conservationist in Belize, the fixed wing drone is the UAV of choice.

However as multirotor drone capabilities continue to increase, realtors, photographers, and others find the multirotor UAV to be their drone of choice.

We look forward to the day when both types of drones are used in combination, ie capture large data plots with the fixed wing drone and zero in on specific areas of interest with the multirotor. The good news is that as users we have so many useful choices available to us today.

our comments and feedback are much appreciated! What do you think? Contact us anytime.

 About Us

Event 38 designs and manufactures drones, specialized optical sensors, and a cloud based Drone Data Management System-TM for small and medium sized businesses. Today we have customers in 49 countries using our products for agriculture, surveying, construction, environmental preservation, and other applications. Please visit our website, or contact us for additional information.

Crop Scouting with Drones – A Case Study in Precision Agriculture

Founded in 2011, Event 38 builds and sells easy to use dronessensors and a Drone Data Management System-TM . Customers all over the world use our drones for Construction, Environmental Conservation, Mining, Surveying and Precision Agriculture.

Precision agriculture, and crop scouting in particular, is about to take a big step forward with the use of drone technology. Countless crop management improvements will be developed once the FAA publishes regulations for commercial use of drones in 2015.

Precision Agriculture
Through recent advancements in drone technology, the cost of collecting vast amounts of information on large areas of land has decreased to pennies per acre. New, sophisticated sensors let us gather data at the plant (leaf) level at a moment’s notice, which supports speedy decision-making and an opportunity for farmers to attain higher crop yields. By adding additional data sources, we expect to find hidden relationships and make further improvements in farm management. This combination of drones, sophisticated sensor hardware, and big data predictive and prescriptive analytics will revolutionize farm management in the near future.

Crop Scouts
Crop scouts perform a key service to farmers to ensure crop success. Typically, they are engaged to identify crop issues, (i.e., pests, soil condition, disease, plant health, weeds, etc.) and to make recommendations for treatments/interventions. Currently, they periodically sample small areas and generalize their findings to the whole field. In the near future, crop scouts will use drones to analyze the complete planting area, quickly identify issues, and provide recommendations for highly localized treatments.

Case Study Results
Today we can gain basic insights about the crop. In the future we will be able to identify and quantify specific issues, allowing the farm manager to take measured action only when financially appropriate.

  1. Spotlight areas of interest for ground investigation
  2. Determine crop height and growth
  3. Calculate crop health with NDVI
  1. Spot certain insects, diseases, weeds and pests
  2. Determine economic intervention threshold levels
  3. Count livestock and determine grazing land health
  4. Time series and predictive analytics

In late-July, 2014, we flew our E384 fixed-wing drone over a 75-acre cornfield in central Ohio.

The E384 has an industry leading flight time of two hours, and can carry a 1 kilogram payload.                             
The E384 can fly a 1,000 acre farm in a single flight and capture data at the 2 centimeter level.


The flight lasted about 15 minutes, was flown at 400 feet completely autonomously, and captured 140 images at a 3cm/pixel resolution.

Below are some of the findings we observed.

1. Spotlight Areas of Interest
By viewing the whole planting area, crop scouts are able to identify particular areas of interest to follow up with an examination on the ground.

Figure 1A Flyover at 400ft
Anomalous patches of bare soil visible from the air.Fig1A
Figure 1B 3cm Resolution
A more detailed view of a square shaped depression on the right side of Fig 1A, with stronger growth on one edge.1b
Figure 1C
A section of a field that shows unusual growth between rows.1c
Figure 1D
A more detailed view of the growth out of rows that most likely indicates the presence of weeds.1d

2. Determine Crop Height
Today we can sample the planting area to determine plant height. Taking periodic readings of the same area will give crop scouts an indication of plant growth over time.

Figure 2A
A cross section selection of the corn field.2A
Figure 2B
The elevation through the cross section shows the corn to be approximately 8 feet tall. 2B
In another area of the field, we identified problems with compaction or tractor damage. We can see dips in the plant height from the air if we look at a cross section of plants across a tractor track. This shows about a 1 foot difference in height. This result can be used later to help determine economic thresholds for late stage spraying.

3. Calculate Crop Health with NDVI

NDVI (Normalized Difference Vegetation Index) is a simple analytical tool that indicates chlorophyll activity in plants but is also strongly correlated to plant biomass, leaf area index, and plant stress symptoms.

Figure 3A The NDVI calculation shows no plant growth at all in many of these rows, after a late application of herbicide.
3AFigure 3C The patch below appears to be either a very infertile soil or just too wet to grow anything.
Figure 3B
The area at the top of this view appears to be growing very well compared with the rest of the field. The hill appears to be sloping down into the grass waterway, with the strong growth happening on the uphill side and weaker or average growth on the downhill side of the waterway. The same thing happens again a little further downhill at the edge of the field just 25-35 yards away and the same effect is not present in other areas that receive similar sunlight at low angles.3B

Event 38 is working with crop scouts and researchers to develop next generation tools for precision agriculture. We are actively seeking collaboration with farmers, researchers, developers, and commercial partners. Your comments and feedback are appreciated. Tell us about improvements you would like to see in the near future.”

About Event 38

Founded in 2011 and with customers all over the world, Event 38 Unmanned Systems is a leading provider of easy to use unmanned aircraft (drones)sensors and a Drone Data Management System-TM  for Construction, Environmental Conservation, Mining, Precision Agriculture and Surveying.

Our drones offer longer flight times, larger payloads, higher resolution sensors and cost 5-20 times less than our competitors.

If you ever have any questions or feedback, please feel free to contact us anytime. We’re always happy to answer any questions!