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  • Drone based LiDAR survey of Oil & Gas assets in the jungle of Gabon (80 000ha)

    In difficult to reach places in Africa, LiDAR surveys are often prohibitively expensive and can take a long time to perform. Delays due to poor weather, long ferries and bureaucratic processes make it a challenge to undertake accurate and critical information regarding terrain conditions. Drone and LiDAR technology has evolved significantly in the past few years allowing high resolution data to be made available over some of the largest and remotest areas. 3DroneMapping was contracted by a prominent Oil and Gas producer in Gabon to perform a comprehensive survey of its assets and expansion projects. The requirements were to produce ground level DTM and high resolution orthomosaics over 80 000ha. The entire site is covered with dense rainforest jungle. This data would help engineers better plan for pipeline routes and road extensions between new extraction platforms. Using a specialized fixed wing VTOL (vertical take off and landing) drone, the project could be surveyed with an adapted LiDAR scanner. The 3.4m wingspan drone used for the project is specially modified for long range and heavy lift capabilities that can carry a 3kg scanner unit for up to 3 hours while travelling at approximately 80KPH. The LiDAR scanner was an essential part of the operation due to its ability to penetrate vegetation and measure ground levels. A total of 5 215km was flown over 11 days to cover the 80 000ha site. This was done in very challenging conditions due to high levels of humidity, dust and other pollutants. Communications were particularly challenging as the dense jungle reduced radio broadcast power significantly. A total of 5TB of raw data was captured and processed into useful DTM and orthomosaic products in under 3 weeks.

  • Drone based LiDAR surveys for the feasibility of renewable energy production

    Drone have been used for many years post-construction of renewable energy projects such as solar and wind farms for inspection purposes. The use of a drone based camera setup with either a thermal, multispectral or visible light spectrum sensor is an affordable, safe and fairly quick operation. But drones are becoming increasingly competitive in the pre-construction phases too. The feasibility studies are critical for renewable projects as they provide a technical summary of a proposed sites' capacity, suitability and profitability. Data from feasibility surveys helps designers and engineers optimise their plant and layout of a potential energy provider. It also is a source of hard evidence for financiers to further justify the expenditure of a large construction project. In their very nature, feasibility studies do not have very large budgets. They often need to be undertaken rapidly with low costs and with as little impact to the local population as possible. This is to attempt to restrict persons from "speculating" about a potential project and possibly increasing land costs, rental rates or generally trying to profit unduly with prior knowledge. Our services have been used successfully over the past years to provide such services to potential renewable energy projects all over Africa. LiDAR scans done from our fixed wing UAVs can cover up to 10 000ha per day to produce high resolution DTM and DSM data products that are used by our clients for CFD (computational fluid dynamic) modeling. This is all done in a cost effective manner while keeping our footprint and time on the ground to a minimum. CFD modeling is used to asses the feasibility of the site for energy recover products such as wind turbines. It allows the user to locate areas over a site given collected wind and other weather data and combine this with accurate terrain roughness or DSM products obtained from drone LiDAR surveys. Operators can also fine tune positions of plant within the simulation to get the best possible energy production. Historically, these DSM products were obtained from Google Earth, SRTM or other sources. While these are free products, they are incredibly rough and inaccurate. These may work for very initial planning phases of a project, but certainly are not suitable for fine level adjustment, planning and calculations for energy production potential of a site. High resolution LiDAR derived DSM combined with CFD modelling gives outstanding results and helps quantify and justify the position of plant for maximum production as well as reliability in terms of yield. Not only are LiDAR derived DSM products produced, but high resolution orthomosaics are also captured, allowing engineers and designers to carefully plan routes to ferry materials for construction phases, for grid transmission line design and connections as well as spatially locating all other services. Using a drone based LiDAR system is easily the most affordable and accurate way of undertaking a sites feasibility for renewable energy production. Contact 3DroneMapping for more information: info@3dronemap.com

  • Remote mine LiDAR surveys via the internet (drone-in-a-box)

    3DroneMapping has been working hard to provide its clients, particularly in the mining sector, a solution for rapid, high frequency LiDAR surveys at remote sites. It was noticed particularly during COVID-19, that travel to and from difficult to reach sites for skilled personnel like surveyors and pilots became a challenge. As periodical surveys like stockpile report timelines are fixed, there became a great danger of delaying the data capture and end reporting due to travel restrictions or issues of cargo clearance complications. For this reason, 3DroneMapping decided to work on a remote survey solution for repeated fixed locations. For the past 2 years, 3DroneMapping's R&D division has been working with its partners in East Africa to demonstrate the financial feasibility of medical cargo deliveries via a drone platform. The study was based on a "hub and spoke" design where a central base coordinated the routings, monitored flights and liaised with ground staff at remote sites like clinics and hospitals, up to 115km away. As radio communication with the base station and the drone were impossible due to terrain and distance, a internet based link was designed to control and command operations. This proved highly effective and it was realized that the control link was now in fact limitless as the aircraft could be controlled from anywhere in the world. From the lessons learnt in East Africa, the team quickly modified the communications link to work for survey specific drones and LiDAR payloads. A package was designed with a CCTV camera and a weather station that would allow operators to remotely undertake surveys from anywhere in the world. All that was required locally was a brief training for mine staff on drone setup, battery charging and data upload. In practical numbers, surveys could be undertaken as rapidly as possible. The only limitation would be data transfer and processing time. Previously, such surveys required cargo transfer, site mobilization, data capture, demobilization and equipment repatriation. Not only is there a dramatic reduction in turnaround times, but the costs are more than halved when undertaken remotely via the internet. Such high intensity surveys can be useful for volumetric surveys, site condition monitoring, level reports and general construction. #mining #droneinabox #aerialsurvey #LiDAR #dronesurvey #volumes #remotedrone

  • Drone survey of a Mali lithium mine

    3DroneMapping was appointed as consultants to undertake an aerial survey of a potential lithium mine site in southern Mali. The project comprised a total surface area of approximately 18 000 hectares. The client requested orthomosaics and DTM products be produced. Control points were placed around the site. These were surveyed to within 20mm accuracy with survey grade GPS. As RTK was not an option due to long baselines, post processing of raw GNSS measurements was done. Flight operations took 3 days with an average of 3 flights per day due to restricted access to electricity. a total of 850km was flown in very challenging conditions. Daily temperatures often exceeded 40°C and winds were in excess of 14m/s. Post processing of trajectories gave excellent results from the INS system. All values were within tolerance. Target images were referenced in XYZ and OPK ready for photogrammetric routines. Photogrammetry was relatively straight forward and standard outputs exported. Minor manual classification of DTM was required as most artifacts could be separated via automated algorithms. Processing was completed in 72 hours DTM, orthomosaic and contours were generated as final outputs. This was a fairly simple survey done in challenging environmental conditions. The main reason for the missions success was careful planning and maintaining efficiency in the field. For our oldest aerial survey drone, this was its last mission as it will be retired. The aircraft has done incredibly well over the past few years, flying many thousands of kilometers. It has collected mud from over 12 different countries on its skid plate and is functioning perfectly. However, it is now time to bid it adieu as we usher in a new era of photogrammetric sensors, more flight time and ease of operation.

  • Drone based LiDAR accuracy tests

    For the past 15 months, 3DroneMapping has been working on its drone based LiDAR system. There have been enormous changes in the INS and LiDAR sensor market and these sensors are now much cheaper, more accurate and smaller than ever before. But most critically, software has kept up to date with changes in the small LiDAR market and has offered some very useful tools to get the absolute best results from such small sensors. As solid state LiDAR units are becoming more common, it is now very possible to place them in more challenging environments. While they still need to be clean and not exposed to extreme vibrations, EMF and water, they are far more robust. Also, heavy lift aircraft are becoming more popular these days as the standard payload for a LiDAR and imager are between 1.2 - 1.6kg. So why is LiDAR so important as a payload for aerial survey? Mainly because of the ability for LiDAR to "see" though vegetation. There are other factors too such as: Increased swath coverage Reduced data capture time Reduced processing time Ease of ground classification Reliability of ground classification Here are a few samples that compare LiDAR based pointclouds to those generate from standard photogrammetry (images only or PhoDAR) As can be seen, LiDAR gives very good coverage over densely vegetated areas. Cultivated fields (in this case maize) has been a huge headache for photogrammetrists when using images only for determining DTM. As this type of photogrammetry can only measure what it "sees", often ground is not visible and thus not taken into account. Far more ground points are surveyed from LiDAR and help determine where natural ground levels actually are. In some cases, reflection from reflective surfaces such as water can cause photogrammetry software to create depressions or spikes in pointclouds based from images. More often is the case, these are not classified as noise as there are neighbor points that are generated to create a pseudo surface. LiDAR sensors only require about 35-25% sidelap. The angles of data capture do not require large overlaps (unless a calibration is being done). This means that far less distance needs to be travelled for data capture of the same area. The example below is for 50ha at 120m AGL. LiDAR coverage is only 6.99km but using a 48MP camera with 35mm lens would take 17.39km to achieve the same coverage(at 65% sidelap) Processing time is really dependent on the hardware and software being used and what workflows are in place. Our office findings is that the processing time that is automated(tie point generation, alignments, raw data extraction, etc) are very similar for areas 1000ha and up. But there is a massive reduction in manual editing and classification when using LiDAR data. Here, very little manual intervention needs to take place and processing times are as little as 3% of that required to clean PhoDAR data. LiDAR data can further be refined by strip adjustment software. This software takes into consideration certain drifts in the INS measurements, sensor inaccuracies and reflectance issues. All of this is calculated and the block adjusted accordingly. The results from such adjustment can be dramatic and certainly help in following classification and noise identification routines.

  • Aerial Survey of Kinshasa, DRC

    3DroneMapping undertook an aerial survey of a site along the Ndjili River, Kinshasa in the Democratic Republic of the Congo. The project comprised a total surface area of approximately 10 000 hectares. The client requested orthomosaics and DTM products be produced. Various ground control points / markers were required for the aerial survey of an area. These needed to be established and coordinated as well as additional quality checkpoints. Each control point was to be surveyed to within 20mm accuracy or better. Additional points were collected to aid the accuracy of the point cloud registration. These included road markings, spot levels and other points that could be interrogated during the photogrammetric processes. These points will form part of the secondary control points to check on the accuracy derived from the primary control points. Effective data capture for this project necessitated the use of a fixed wing drone. Since these typically require a large flat runway to take off and land, a futile attempt was made to locate such a place near the area of interest. Finding a secure, empty and obstruction free area in densely populated Kinshasa was a very tall order and none could be located. It was decided to rather change to a slightly less efficient airframe that can take off and land vertically but can transition into fixed wing flight for greater efficiency. Such an aircraft is called a VTOL (Vertical Take-off and Landing) Since the Civil Aviation Authority required certain technologies to work in controlled airspace, additional safety features were added to the airframe such as Automatic Dependent Surveillance–Broadcast (ADS-B) which allows for all aircraft to locate each other, strobe lighting and automated avoidance systems. The aircraft used was of our own 3DroneMapping design and built by our inhouse Research & Development team. In addition to the required safety equipment, the airframe was equipped with long range communications (C2 or command and control) systems, high-capacity dual power delivery mechanisms, and multiple redundancy control surfaces. The aerial survey componentry consisted of a calibrated metric camera with 60MP sensor and a INS system. The INS is composed of a dual frequency L1/L2 multi-constellation receiver and Inertial Measuring Unit (IMU). These units are capable of measuring angles and positions up to 400 times a second to within 1cm in terms of position and 0.004 ° in terms of pitch, roll and yaw. Every camera shutter exposure was precisely logged inboard the INS to extrapolate coordinates and orientation. A dual frequency base station was also operated during flight operations to be used in the next phase of trajectory processing. Aerial survey requires precise flight planning to determine where the aircraft and by extension, the camera will be orientated for data capture. This was planned to meet the clients target accuracies of 5cm. Since the mission is automated, several factors need to be considered such as changes in terrain levels. The aircraft was planned to be operated at certain level above the ground. As the distance between the camera and the terrain change, so does the overlap between images. Retaining the correct overlap between images is crucial for accurate aerial survey. The project was planned for 35% side lap and 70% forward lap. The trajectories of the aircraft during survey sorties were determined by means of precise point positioning (PPP) and PPK (precise point kinematic) using the dual frequency base station running at the time of data capture. In addition to the position of the aircraft being determined along the flight trajectory, its orientation angles were determined at every point along the trajectory through the use of an inertial measurement unit (IMU). The tightly-coupled GNSS-IMU trajectory was calculated with NovAtel Inertial Explorer. Using the orientations and GPS-based positions of the aircraft, an accurate image geolocation coordinate list could be generated.

  • 28 000ha aerial survey by drone(in 4 days)

    Post COVID-19 hard-lockdown season has started up with 3DroneMapping's Uganda office undertaking a 28 000ha aerial survey of a sugar cane estate. The estate required the services of 3DroneMapping to produce highly accurate Digital Terrain Modelling (DTM) and orthophotos. These products were in turn to be used by agricultural engineers for the planning and development of irrigation systems as well as for internal use by the estate to maintain and understand the drainage patterns of fields. Aerial survey over such a large area is no easy feat. Careful flight planning had to be done in order to maintain efficiency for the flight as well as to retain accuracy for post processing of data. Aerial surveys are very hard to produce and unpredictable over homogenous surfaces (terrain that appears similar from above) as the aerial triangulation(AT) process done after the data capture require common points between images to align strips. 3DroneMapping has been testing and implementing a INS/GNSS system into our payload and workflow that negates the need for Aerial Triangulation completely. This means that strips can now be flown with side overlap as low as 30% (as opposed to the industry standard of 70-75% for UAV captured data). Not only does this double the area that can be covered in a flight, but it dramatically decreases processing time of the model while allowing the rectification and pointcloud generation of very challenging terrain. Despite all the delays and challenges that COVID-19 has created, having such a highly efficient data capture method and aircraft meant that the entire 28 000ha contiguous site was captured in 4 days only. Processing of the data to produce raw (unedited or classified pointclouds and orthomosaics) took a further 4 days to achieve. End to end delivery took only 3 weeks (inclusive of ground control establishment, travel and data transfer)

  • LiDAR compared to Drone PhoDAR

    At 3Dronemapping, we often get asked how our data and end products compare to traditional LiDAR captured from manned aircraft. Each of the methods and instruments used to generate datasets have their own pros and cons. Certain project sites may be better suited to LiDAR while others would benefit from PhoDAR. This article hopes to indicate the differences between the methods of data capture and suggest where each is best utilized. LiDAR (Light Detection and Ranging), is a remote sensing method that uses light in the form of a pulsed laser to measure ranges (variable distances) to terrain. This coupled with IMU and GNSS measurements allows us to reference the laser data and is adjusted to ground control points. Further data capture with a high resolution still camera allows for orthophoto generation. All of the above are transported in a manned aircraft, many of which are specifically designed for aerial survey and have the necessary rating from their respective aviation regulators. Such systems cost hundreds of thousands of dollars and are very susceptible to damage from dropping, dust, etc. PhoDAR on the other hand is a slightly misleading acronym. PhoDAR is a portmanteau word that joins the words “photography” and “LiDAR.” The technology creates 3D point clouds by processing imagery. PhoDAR is another name for structure from motion (SfM) photogrammetry and is essentially how aerial surveys where done in years gone by using 9-inch film and very large metric cameras. No direct measurements are made to the ground, but this method uses GNSS and IMU observations like LiDAR that also directly geo-reference the data. This is the most common way of undertaking an aerial survey via drone While both systems can be installed on either a manned or unmanned aircraft, airborne laser scanners are typically too heavy and power intensive as a payload for drone. The modern LiDAR sensors that are light enough for use on a drone are still too under-powered and suffer from limited range and poor return frequency meaning the aircraft must fly a lot lower and slower to make economic sense. These systems are also prohibitively expensive. Ground control surveys are essential for both LiDAR and PhoDAR. Points for the referencing for the survey to the terrain and need to be evenly distributed over the site. Both systems use DG or direct geo-referencing with GNSS and IMU observations to perfectly accurate levels to initial create the survey block adjustment. It is important to note that LiDAR is "better" than PhoDAR or visa versus. Each has their own strengths and weaknesses and each method are better suited to certain projects. Let us discuss the various pros and cons then see what system applies best to a few scenarios. LiDAR Pros Can cover large areas as the aircraft can efficiently cover more area than a drone Multiple return pulses can "see" through vegetation Data is collected in real time Vertical accuracy of about 7cm LiDAR Cons Fairly expensive to survey, especially for smaller areas (<8 000ha) Classification of terrain features is still done autonomously / manually Pointclouds need to be coloured by imagery Pointclouds are less dense compared to PhoDAR (1-3 points per m²) Aircraft requires fuelling and can be a challenge in rural areas Aircraft requires a tarmac runway nearby to reduce ferry PhoDAR Pros Very cost effective for areas up to 25 000ha Quick deployment Good for rural or difficult to reach projects Can take-off / land anywhere Generates an orthomosaic as a by-product Very dense pointclouds (5-15 points per m²) Vertical accuracy of about 7cm PhoDAR Cons Cannot cover large areas efficiently Subject to strong winds Cannot "see" into contiguous vegetation Does not work well over homogeneous terrain like beaches Classification of terrain features is still done autonomously / manually Accuracy and end products are virtually the same for both methods. While not the subject of this article, orthomosaics from drones tend to be clearer and have greater colour depth since they are captured closer to the ground and have less dust or "air" to see though. Both data sets need to run though specialized pointcloud editing software to remove any outliers from high or low noise points in respect of laser data reflecting of dust / rain particles of from poor geometry fixes extracted from photogrammetry software. Both datasets then need to be run through various algorithms to further extract vegetation, buildings, bridges, water, etc. LiDAR data capture is best utilized for large areas (no less than 8000ha) where time is a concern. It is good for collection of large datasets (mine exploration, flood risk analysis, national surveys) or a string of sites that can be capture in a single flight. It excels in densely forested areas where laser returns can penetrate gaps in the foliage. In areas where there is controlled airspace such as near airports, manned aircraft can much easily be directed by air traffic control. PhoDAR does well for areas up to 25 000ha. More time will however be spent on the ground however to cover the same area. Remote sites such as islands, farms, mines are good places for PhoDAR if portion of the ground is visible between vegetation. Since drone surveys do not carry as many site establishment costs compared to manned aviation, project with smaller budgets can afford accurate surveys. As drones are portable, surveys can be done in very remote locations and very time efficiently. Since ground control surveys would need to be done in either case, only a single deployment is needed to do both ground control and the PhoDAR data capture. It is important to not only chose the correct data capture method for your project but also to use a reputable company with experience and the correct equipment. Airborne laser systems that make up LiDAR and the aircraft are not cheap to own or operate. The companies that undertake these types of surveys are generally reliable and well established. However, there are many companies that offer inferior PhoDAR surveys by using improper aircraft, sensors and software. It is best to seek out a firm that has many years of experience in the field and has all the correct hardware with processing knowledge. info@3dronemap.com | www.3dronemapping.com

  • Rapid aerial survey of a proposed graphite mine

    3DroneMapping was recently called to map a very remote proposed graphite mine in East Africa. The client gave a very short window for the survey to be undertaken as they required that information to begin the planning of drilling locations, camp establishment and access road design. Using a custom built fixed wing platform with medium format sensor, dual frequency PPK logger and long range radios, the 3800ha site was surveyed in one day. Initial ground control was established over the site in the morning and flight operations began shortly after midday. Aerial triangulation and classification of data took a further 2 days to complete. Despite the remoteness of the site, the undulation of the terrain (varied from 1230m - 2100m ASL)and the vegetation coverage, we managed to hand over the data well within the timeline. info@3dronemap.com | www.3dronemapping.com

  • Why you need to clean your drone data

    Data derived from drone photogrammetry is great. It is feature rich and often contains more information than you would ever need. Pointclouds are at times so dense that they can exceed 50 points per square meter. But is all this high definition data really worth much to the end client and is it comparable to traditional outputs from terrestrial survey or LiDAR? Some photogrammetry software allows for moderate filtering of tie-points that makes up the final pointcloud. While this removes undulation and inaccuracies in the model, it still doesn't extract vegetation, buildings, structures, etc. The pointcloud generated is based of multiple intersections of all objects visible in the image. Thus there is no distinction between these objects. This type of model is called a Digital Surface Model (DSM) and can not be used for contour generation Some photogrammetry software allows for moderate filtering of tie-points that makes up the final pointcloud. While this removes undulation and inaccuracies in the model, it still doesn't extract vegetation, buildings, structures, etc. The pointcloud generated is based of multiple intersections of all objects visible in the image. Thus there is no distinction between these objects. This type of model is called a Digital Surface Model (DSM) and can not be used for contour generation Many amateur mappers believe that to create ground level contours is to simply remove the concentric rings that form around tress, buildings etc. This is not recommended as the integrity of the model is still unedited and the terrain may vary due to classification around buildings or larger clumps of vegetation. This practice may work for small single trees or buildings, but what for large plantations? Contours do not simply disappear (unless they terminate into a body of water) and have to have a beginning and end. The classification of pointcloud data is very time consuming. There are semi-automated tools available that can do limited DTM editing. Most of these tools do not allow for terrain editing and interpolation. Large fields of crops such as maize can not simply be classified as "vegetation" and removed from the DTM as it would create holes in the terrain model. Here the ground needs to be interpolated over to retain the profile. Since pointcloud data is so dense, the client would need very powerful machines and expensive software to interrogate a dataset. This creates a processing bottleneck and should be thinned to make the model more meaningful and user-friendly. Spatial thinning of pointclouds does exactly this where we can define model keypoints that are crucial in representing the terrain while removing the superfluous ones. This dramatically cuts down file sizes while maintaining model integrity. Flatter areas will have less points but steeper or changes in slope angle will have a denser group. Typical data sets of 10 000 000's of point can be re-sampled to just 50 000 for a typical 1000ha area. info@3dronemap.com | www.3dronemapping.com

  • Data processing services to the public

    Much of our time at 3DroneMapping is spent in office, processing data. We have worked with terabytes of information over the years, seen the development and evolution of software, hardware and the general end requirements of our clients. Because we have been in the industry for such a long time, we have gained valuable experience and have a solid understand of photogrammetry and GIS routines. Much of our time at 3DroneMapping is spent in office, processing data. We have worked with terabytes of information over the years, seen the development and evolution of software, hardware and the general end requirements of our clients. Because we have been in the industry for such a long time, we have gained valuable experience and have a solid understand of photogrammetry and GIS routines. Finding the right software to undertake photogrammetry routines is very difficult. It takes months to evaluate the limitations and highlights of the software. This often comes at a cost as the software needs to be purchased, researched and finally "data driven". The financial cost as well as time spent on this is very taxing. What we have found is that there is no single offering or suite available that can provide the best option for all cases. Especially when dealing with high accuracy data, the "all-in-one" bundles don't come close to matching the accuracy and end result that a few good ones do. Aerial triangulation is best handled by dedicated software. The same goes for orthomosaic generation, pointcloud editing, data conversion and projection. We also know that there is no single setting or procedure for all datasets. Each project has been captured differently in terms of sensor type, topography, terrain, altitude and flight planning. Operators need to be aware of these variances and using experience, apply the model that bests suits the data. Pointcloud editing is possibly the most important aspect of our work. Here we use interactive tools to determine ground levels, vegetation, buildings, roads. This is known as classification and is crucial when creating a DTM (Digital Terrain Model). DTM is limited to the terrain points only, thus when contours are generated, they are representative of the natural ground levels and exclude features like vegetation, buildings, etc. This is a very time consuming process and requires operators to interactively interrogate the data in 3D to check and edit classifications. Pointcloud editing is possibly the most important aspect of our work. Here we use interactive tools to determine ground levels, vegetation, buildings, roads. This is known as classification and is crucial when creating a DTM (Digital Terrain Model). DTM is limited to the terrain points only, thus when contours are generated, they are representative of the natural ground levels and exclude features like vegetation, buildings, etc. This is a very time consuming process and requires operators to interactively interrogate the data in 3D to check and edit classifications. 3DroneMapping is now offering our experience, hardware and software capabilities to the public. Clients are now find it easier in some circumstances to collect the data themselves but ask us to process the data for them into orthomosaics, classified pointclouds, etc. Often the client has time restrictions, or inadequate hardware / software to process data correctly. Data collected by our clients often arrives via harddrive or is uploaded to our FTP site(not recommend for datasets over 100gb) and processed on one of our workstations. Final products are delivered in whatever method is convenient. A typical 1000ha rural location with 50% vegetation cover can be processed as 4cm/pixel and 0.5m vertical contours in 1.5 days. For more information, please contact info@3dronemap.com #orthophoto #contours #data #processing #server #photogrammetry

  • Landslide and flood analysis in Uganda using drone data

    In late 2018, the Bududa region in Eastern Uganda experienced torrential rain for a number of days. The area falls just outside of Mount Elgon National Park on the Kenyan border and is characterized by its extinct volcanic crater, dense tropical rain forest and very intensive agricultural activities on steep slopes. Given the high saturation of the soil and large mass of water, landslides where experienced in the area, causing major damage to property. Already saturated mud flowed into rivers along with other debris blocking normal discharge. This lead to localized flooding. Unfortunately, many villagers are settled close to the river banks and numerous buildings where either washed away or badly damaged. A number of lives were sadly lost. In order to assess the damage and to place preventive measures in place, the Office of the Prime Minister of Uganda along with the World Bank approached 3DroneMapping in providing detailed orthophotos of 2 major regions identified to be the worst affected by the flooding / land slides. The request was also for ground level filtered DTM at a very high resolution. Since 3DroneMapping is one of the very few authorized legal drone operators in Uganda and we have the requisite equipment / experience for high accuracy and efficient aerial surveys, we were the best choice for the project. The Bududa valley is very steep, with valleys ranging from 1300m - 2800m AMSL. This tight space within the valley is densely vegetated with tall trees, houses, agricultural activities, etc. Since the areas of interest varied 1000m in altitude, flight-planning for photogrammtric purposes was required to be parallel to the ground. Land areas where identified and used in planning. Control points where also placed over the areas for survey with a survey grade GPS. These where used to ensure that ac curacies required by the client where adhered to. Our 2m wingspan, dual engine airframe was used for the flight operations. This has the advantage of being able to carry a high resolution full frame camera as well as PPK equipment for well over 2 hours. However it requires a large area for landing which was in short supply in valley. A smaller PPK equipped wing was used for the harder to reach areas that uses a parachute for landing, enabling it to be deployed in the higher locations where communications with the larger aircraft where limited. Processing of data required a high level of skill and experience. Images where photogrammetrically rendered to produce high resolution orthophotos and pointclouds. These pointclouds where then classified to extract ground levels. Due to the steepness of the terrain and dense vegetation, most automatic algorithms used to classify data could not be used and manual editing was required. This time consuming process took many man (and woman!) hours to complete. The end pointcloud, stripped of all vegetation, buildings, rivers and other non-ground points was triangulated and gridded into a Digital Terrain Model (DTM) for the client to use to slope analysis, etc. Mapping teams in Uganda are already working on the data to calculate densities of settlements, digitizing areas of concern and possible short term, high risk locations. We are confident that this data will be put to good use to both mitigate future disasters and also enable good spatial planning. #Dronesurvey #aerialsurvey #naturaldisaster #Uganda #Bududa #dronemapping

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