Photogrammetry Software Research Articles

Large wood (LW) 3D accumulation mapping and assessment using structure from Motion photogrammetry in the laboratory

A Structure from Motion (SfM) photogrammetry-based methodology for precise mapping of large wood (LW) accumulations in fluvial systems is presented. The technique may be useful for routine inventory and rapid volume estimation of complex LW structures that tend to divert or obstruct flow in rivers. Our methodology is validated by means of laboratory experiments, ranging from elementary to complex arrangements of LW components and organic fine material (OFM). Seven experimental setups were used as the basis for (i) manual approximations of 2.5D and 3D geometric reference volumes, (ii) 2.5D volume models based on mesh geometry, (iii) a closed (‘watertight’) 3D mesh from an unorganized point cloud and (iv) estimates of porosity. A commercially available SfM photogrammetry software package, Pix4Dmapper, was used for point cloud and simplified mesh generation. In order to obtain more precise volumes, 3D surface models are required. Accordingly, we generated 3D watertight mesh models of the unorganized point cloud using the screened Poisson Surface Reconstruction (PSR) technique. The Pix4D volume tool (2.5D) resulted in an overestimation (2.9 to 52.7%) of the geometric volume (3D), due to the convex hull approximation of the geometry normal to the surface plane. PSR (3D) resulted in more precise volumes, showing deviations from the geometric volume (3D) in a range of −15.9 to +10.6%, as the algorithm could capture concavities and involuted surfaces on the accumulation. Assuming that the difference between 3D and 2.5D volume models represents many of the voids visible within or on the surface of the deposit, this volume can be used as an estimate of porosity. Our assessment suggests that image-based SfM methodology is well-suited for further investigations in LW research, due to its time and cost efficiency in comparison with other conventional surveying techniques. The methodology can be used to generate high quality point cloud and mesh models of log jam formations; these may be used by river managers and researchers to quantify accumulation volume and thus gain a better understanding of LW composition and the influence of wood geometry on hydraulic flow conditions.

DENOISING OF 3D POINT CLOUDS

Abstract. A method to remove random errors from 3D point clouds is proposed. It is based on the estimation of a local geometric descriptor of each point. For mobile mapping LiDAR and airborne LiDAR, a combined standard mesurement uncertainty of the LiDAR system may supplement a geometric approach. Our method can be applied to any point cloud, acquired by a fixed, a mobile or an airborne LiDAR system. We present the principle of the method and some results from various LiDAR system mounted on UAVs. A comparison of a low-cost LiDAR system and a high-grade LiDAR system is performed on the same area, showing the benefits of applying our denoising algorithm to UAV LiDAR data. We also present the impact of denoising as a pre-processing tool for ground classification applications. Finaly, we also show some application of our denoising algorithm to dense point clouds produced by a photogrammetry software.

MEASUREMENT ACCURACY ON 3D POINT CLOUD GENERATED USING MULTISPECTRAL IMAGERY BY DIFFERENT CALIBRATION METHODS

Abstract. The state-of-the-art lightweight multispectral cameras are widely used for low altitude remote sensing, also can be exploited as a tool for close-range photogrammetry application. The acquired imagery can be used for generating the 3D model using Structure-from-Motion/ Multi-view Stereo (SfM/MVS) processing software. In photogrammetry, camera calibration is an essential step for accurate measurement. The parameter of the camera system can be estimated using photogrammetric self-calibration bundle-adjustment, or by automatic and straightforward calibration procedure developed by computer vision (CV) community. When using SfM/MVS photogrammetry software, the pre-calibration value is not required, as the algorithm calculates the parameter as a part of point cloud construction process. Nevertheless, processing with the uncalibrated image is only suitable when no metric accuracy required in the modelling project. This paper aims to evaluate the measurement accuracy on generated 3D point cloud based on different estimated parameter method. The evaluation of measurement accuracy started by estimates the camera’s interior parameter using two different approaches; photogrammetric self-calibration bundle-adjustment and computer vision calibration. The estimated parameter from both methods then imported into commercial SfM/MVS software to construct the 3D point cloud. The point cloud also generated using uncalibrated images and used for measurement accuracy assessment. All parameters applied to the same datasets involved three different check-fields. Two accuracy assessments were performed by comparing the check-points and check-distance extracted with the total station measurement. As a result, the point cloud generated using photogrammetric approach provides the most accurate result on both assessments. While the automatic on-the-job self-calibration shows inconsistent results.

Three-dimensional image-based approach for imperfect structures surface modeling

Great attention has been given, in the scientific literature, to the effect of initial imperfections on the structural behavior of experimental samples under compression loads. Geometrical reconstruction of the as-built surface is therefore required to allow accurate numerical modeling. High-precision systems for inverse engineering are expensive, and most of the times geometrical imperfections are rather complex to be described without high computational efforts. In this paper, an image-based approach to model the surface of imperfect structures using open-source software and a common digital camera is presented. The proposed approach aims to generate high-quality surfaces from real imperfect structures, by employing the surface-from-motion and multi-view stereo techniques. A controlled frame capture is introduced to decrease both the computational effort and number of repeated correspondences. The surface fit is then computed by meshing the dense cloud of points and adjusting several surface regions describing the samples’ profiles. The procedure is illustrated by using two damaged tubular member samples reconstructed by the proposed approach. Then, resulted geometries are verified by comparing measures from a three-dimensional high-precision laser scanner and a common mechanical procedure. Finally, a comparison of three-dimensional mappings of a ship panel with proposed approach and commercial photogrammetry software is performed. Verification results refer to the possibility of prototyping geometry surfaces from real imperfect samples by using inexpensive hardware and public domain software tools with acceptable level of accuracy.

The Potential of Low-Cost UAVs and Open-Source Photogrammetry Software for High-Resolution Monitoring of Alpine Glaciers: A Case Study from the Kanderfirn (Swiss Alps)

Unmanned Aerial Vehicles (UAV) are a rapidly evolving tool in geosciences and are increasingly deployed for studying the dynamic processes of the earth’s surface. To assess the potential of autonomous low-cost UAVs for the mapping and monitoring of alpine glaciers, we conducted multiple aerial surveys on the Kanderfirn in the Swiss Alps in 2017 and 2018 using open hardware and software of the Paparazzi UAV project. The open-source photogrammetry software OpenDroneMap was tested for the generation of high-resolution orthophotos and digital surface models (DSMs) from aerial imagery and cross-checked with the well-established proprietary software Pix4D. Accurately measured ground control points served for the determination of the geometric accuracy of the orthophotos and DSMs. A horizontal (xy) accuracy of 0.7–1.2 m and a vertical (z) accuracy of 0.7–2.1 m was achieved for OpenDroneMap, compared to a xy-accuracy of 0.3–0.5 m and a z-accuracy of 0.4–0.5 m obtained for Pix4D. Based on the analysis and comparison of different orthophotos and DSMs, surface elevation, roughness and brightness changes from 3 June to 29 September 2018 were quantified. While the brightness of the glacier surface decreased linearly over the ablation season, the surface roughness increased. The mean DSM-based elevation change across the glacier tongue was 8 m, overestimating the measured melting and surface lowering at the installed ablation stakes by about 1.5 m. The presented results highlight that self-built fixed-wing UAVs in tandem with open-source photogrammetry software are an affordable alternative to commercial remote-sensing platforms and proprietary software. The applied low-cost approach also provides great potential for other regions and geoscientific disciplines.

Tool mark analyses for the identification of palaeolithic art and modern graffiti. The case of Grottes d’Agneux in Rully (Saône-et-Loire, France)

The identification of technical traits derived from the analyses of photogrammetric 3D models can be used for archaeological objectives. In this paper, we are proposing a methodology for discrimination of parietal engravings based on 3D models build with photogrammetry software. Our case study are the caves of Agneux, two small caverns with an astonishing number of graffiti on their walls. Most of these graffiti were made since 19th century, but with some examples of depictions that are compatible with the technical features of Palaeolithic art.The analyses of the marks in some lines in Agneux I have demonstrated the use of different tools. Virtual illumination has been applied to identify and read words and dates which can be discarded as prehistoric. These results will be compared with replicative experiments. This methodology could be useful for the discrimination of prehistoric graphic expressions in panels with a biography of long-term human interventions.

Acquisition of Volumetric Models of Skull Base Anatomy Using Endoscopic Endonasal Approaches: 3D Scanning of Deep Corridors Via Photogrammetry

In this study we aim to evaluate the feasibility of creating volumetric models of highly intricate skull-base anatomy-previously not amenable to volumetric reconstruction-using endoscopic endonasal approaches. Ten human cadaveric heads were dissected through the nasal corridor to expose anterior, middle, and posterior cranial fossi structures and the pterygopalatine and infratemporal fossi. A rigid endoscope with a 30° lens was used to capture the images. Subsequently, a photogrammetry software was used to align, smooth, and texturize the images into a complete 3-dimensional model. An average of 174 photographs were used to construct each model (n= 10). In the end, we achieved high-definition stereoscopic volumetric models of the nasal corridor; paranasal fossae; and anterior, middle and posterior fossae structures that preserved structural integrity. Strategic points of interests were labeled and animated for educational use. Endoscopic volumetric models represent a new way to depict the anatomy of the skull base; their use with 3-dimensional technologies could potentially improve the visuospatial understanding of narrow surgical corridors for education and surgical-planning purposes.

A New Fast and Low-Cost Photogrammetry Method for the Engineering Characterization of Rock Slopes

Digital photogrammetry (DP) represents one of the most used survey techniques in engineering geology. The availability of new high-resolution digital cameras and photogrammetry software has led to a step-change increase in the quality of engineering and structural geological data that can be collected. In particular, the introduction of the structure from motion methodology has led to a significant increase in the routine uses of photogrammetry in geological and engineering geological practice, making this method of survey easier and more attractive. Using structure from motion methods, the creation of photogrammetric 3D models is now easier and faster, however the use of ground control points to scale/geo-reference the models are still required. This often leads to the necessity of using total stations or Global Positioning System (GPS) for the acquisition of ground control points. Although the integrated use of digital photogrammetry and total station/GPS is now common practice, it is clear that this may not always be practical or economically convenient due to the increase in cost of the survey. To address these issues, this research proposes a new method of utilizing photogrammetry for the creation of georeferenced and scaled 3D models not requiring the use of total stations and GPS. The method is based on the use of an object of known geometry located on the outcrop during the survey. Targets located on such objects are used as ground control points and their coordinates are calculated using a simple geological compass and trigonometric formula or CAD 3D software. We present three different levels of survey using (i) a calibrated digital camera, (ii) a non-calibrated digital camera and (iii) two commercial smartphones. The data obtained using the proposed approach and the three levels of survey methods have been validated against a laser scanning (LS) point cloud. Through this validation we highlight the advantages and limitations of the proposed method, suggesting potential applications in engineering geology.

Making terrains: Surveying, drones and media ecology

Site surveys are foundational to the design of landscapes. Rapid technological innovations have caused the range of phenomena that can be surveyed and the forms that landscape surveys can assume to radically expand. This article presents findings from two long-term site surveying experiments using drones, real-time kinematic surveying equipment, photogrammetry, GIS and 3D modelling software. Rather than focusing on drones as objects, attention is placed on the aesthetic and techno-experiential interpretation of sites through a media ecology approach, examining the co-constructive, qualitative relationships among technology, humans and landscapes. Research results describe the unique capacities drone technologies can provide, emphasizing the modelling of site-specific, spatiotemporal landscape change over time, and expanded techno-aesthetic capacities for fieldwork and sensing of place. These results are compared with other modes of site modelling to discuss differences. Conclusions posit that a media ecology approach can provide effective tools to critically assess modes of landscape interpretation at a time when technical means to encounter landscapes continue to diversify.

Reef Rover: A Low-Cost Small Autonomous Unmanned Surface Vehicle (USV) for Mapping and Monitoring Coral Reefs

In the effort to design a more repeatable and consistent platform to collect data for Structure from Motion (SfM) monitoring of coral reefs and other benthic habitats, we explore the use of recent advances in open source Global Positioning System (GPS)-guided drone technology to design and test a low-cost and transportable small unmanned surface vehicle (sUSV). The vehicle operates using Ardupilot open source software and can be used by local scientists and marine managers to map and monitor marine environments in shallow areas (<20 m) with commensurate visibility. The imaging system uses two Sony a6300 mirrorless cameras to collect stereo photos that can be later processed using photogrammetry software to create underwater high-resolution orthophoto mosaics and digital surface models. The propulsion system consists of two small brushless motors powered by lithium batteries that follow pre-programmed survey transects and are operated by a GPS-guided autopilot control board. Results from our project suggest the sUSV provides a repeatable, viable, and low-cost (<$3000 USD) solution for acquiring images of benthic environments on a frequent basis from directly below the water surface. These images can be used to create SfM models that provide very detailed images and measurements that can be used to monitor changes in biodiversity, reef erosion/accretion, and assessing health conditions.

Comparison of GNSS-, TLS- and Different Altitude UAV-Generated Datasets on the Basis of Spatial Differences

In this study, different in-situ and close-range sensing surveying techniques were compared based on the spatial differences of the resultant datasets. In this context, the DJI Phantom 3 Advanced and Trimble UX5 Unmanned Aerial Vehicle (UAV) platforms, Zoller + Fröhlich 5010C phase comparison for continuous wave-based Terrestrial Laser Scanning (TLS) system and Network Real Time Kinematic (NRTK) Global Navigation Satellite System (GNSS) receiver were used to obtain the horizontal and vertical information about the study area. All data were collected in a gently (mean slope angle 4%) inclined, flat vegetation-free, bare-earth valley bottom near Istanbul, Turkey (the size is approximately 0.7 ha). UAV data acquisitions were performed at 25-, 50-, 120-m (with DJI Phantom 3 Advanced) and 350-m (with Trimble UX5) flight altitudes (above ground level, AGL). The imagery was processed with the state-of-the-art SfM (Structure-from-Motion) photogrammetry software. The ortho-mosaics and digital elevation models were generated from UAV-based photogrammetric and TLS-based data. GNSS- and TLS-based data were used as reference to calculate the accuracy of the UAV-based geodata. The UAV-results were assessed in 1D (points), 2D (areas) and 3D (volumes) based on the horizontal (X- and Y-directions) and vertical (Z-direction) differences. Various error measures, including the RMSE (Root Mean Square Error), ME (Mean Error) or MAE (Mean Average Error), and simple descriptive statistics were used to calculate the residuals. The comparison of the results is simplified by applying a normalization procedure commonly used in multi-criteria-decision-making analysis or visualizing offset. According to the results, low-altitude (25 and 50 m AGL) flights feature higher accuracy in the horizontal dimension (e.g., mean errors of 0.085 and 0.064 m, respectively) but lower accuracy in the Z-dimension (e.g., false positive volumes of 2402 and 1160 m3, respectively) compared to the higher-altitude flights (i.e., 120 and 350 m AGL). The accuracy difference with regard to the observed terrain heights are particularly striking, depending on the compared error measure, up to a factor of 40 (i.e., false positive values for 120 vs. 50 m AGL). This error is attributed to the “doming-effect”—a broad-scale systematic deformation of the reconstructed terrain surface, which is commonly known in SfM photogrammetry and results from inaccuracies in modeling the radial distortion of the camera lens. Within the scope of the study, the “doming-effect” was modeled as a functional surface by using the spatial differences and the results were indicated that the “doming-effect” increases inversely proportional to the flight altitude.

An Optimization of Small Unmanned Aerial System (sUAS) Image Based Scanning Techniques for Mapping Accident Sites

<div class="section abstract"><div class="htmlview paragraph">Small unmanned aerial systems have gained prominence in their use as tools for mapping the 3-dimensional characteristics of accident sites. Typically, the process of mapping an accident site involves taking a series of overlapping, high resolution photographs of the site, and using photogrammetric software to create a point cloud or mesh of the site. This process, known as image-based scanning, is explored and analyzed in this paper. A mock accident site was created that included a stopped vehicle, a bicycle, and a ladder. These objects represent items commonly found at accident sites. The accident site was then documented with several different unmanned aerial vehicles at differing altitudes, with differing flight patterns, and with different flight control software. The photographs taken with the unmanned aerial vehicles were then processed with photogrammetry software using different methods to scale and align the point clouds. The point cloud data produced with different vehicle / flight pattern / altitude combinations was then quantitatively compared to terrestrial LiDAR scan data. The results are presented here, as well as recommendations based on equipment and desired output.</div></div>

Manual geo-rectification to improve the spatial accuracy of ortho-mosaics based on images from consumer-grade unmanned aerial vehicles (UAVs)

The global spatial accuracy of ortho-mosaics based on images from consumer-grade unmanned aerial vehicles (UAVs) is relatively low. The use of ground control points (GCPs) improves the accuracy but it requires RTK-GNSS (global navigation satellite system) measurements in the field. The objective of this study was to evaluate manual geo-rectification after ortho-mosaicking as a cost-effective alternative to GCPs or UAVs equipped with RTK-GNSS. Google Earth images and A-B lines used for tractor auto-steering were used for manual geo-rectification with a free geographic information system (GIS) and remote-sensing (RS) software (QGIS). Two different photogrammetry software (Agisoft Photoscan and Pix4DMapper) were used for ortho-mosaicking. Images were captured in three fields at two altitudes (40 and 80 m) with a multi-rotor camera drone equipped with a GNSS without ground reference (Phantom 4). The results showed that flight altitude and photogrammetry software had no impact on the spatial accuracy and that manual geo-rectification significantly improved the spatial accuracy. Root mean squares (RMSEs) for ortho-mosaics without geo-rectification was in the range of 4 to 28 m and the range was 0.6 to 2.5 m and 0.5 to 1.1 m for geo-rectification based on Google Earth images and A-B-lines, respectively. RTK-GNSS tagged UAV images and the use of GCPs gave average RMSEs of less than 0.1 m. It was concluded that manual geo-rectification offers a feasible alternative to GCPs and UAVs with RTK-GNSS when spatial accuracy of about 1 m is acceptable.

Evaluation of Photogrammetry and Inclusion of Control Points: Significance for Infrastructure Monitoring

Structure from Motion (SfM)/Photogrammetry is a powerful mapping tool in extracting three-dimensional (3D) models from photographs. This method has been applied to a range of applications, including monitoring of infrastructure systems. This technique could potentially become a substitute, or at least a complement, for costlier approaches such as laser scanning for infrastructure monitoring. This study expands on previous investigations, which utilize photogrammetry point cloud data to measure failure mode behavior of a retaining wall model, emphasizing further robust spatial testing. In this study, a comparison of two commonly used photogrammetry software packages was implemented to assess the computing performance of the method and the significance of control points in this approach. The impact of control point selection, as part of the photogrammetric modeling processes, was also evaluated. Comparisons between the two software tools reveal similar performances in capturing quantitative changes of a retaining wall structure. Results also demonstrate that increasing the number of control points above a certain number does not, necessarily, increase 3D modeling accuracies, but, in some cases, their spatial distribution can be more critical. Furthermore, errors in model reproducibility, when compared with total station measurements, were found to be spatially correlated with the arrangement of control points.

Acquisition of 3D models with submillimeter-sized features from SEM images by use of photogrammetry: A dimensional comparison to microtomography

The use of three-dimensional models for analysis has been increasing in various fields. This study aimed to analyze the process of acquiring 3D meshes by photogrammetry using scanning electron microscopy (SEM) images. 3D models were reconstructed from different numbers of SEM images using a free photogrammetry software. The 3D models obtained were aligned and compared quantitatively to a model obtained by microtomography (microCT). The results suggest that it is possible to reconstruct 3D photogrammetric models with micrometric precision using SEM. However, the error depends on the number of images used for 3D reconstruction (and on the rotation angle). The best result obtained by photogrammetry at 9° step showed a percentage error of 0.3%. The worst result (27°) had a 1.4% error compared to those obtained by microCT. SEM photogrammetry is capable of providing surface details almost as accurate as microCT and therefore, it can be an interesting alternative for the analysis of external surfaces.

3D MODELING FOR ROCK ART DOCUMENTATION USING LIGHTWEIGHT MULTISPECTRAL CAMERA

Abstract. This paper discusses the use of the lightweight multispectral camera to acquire three-dimensional data for rock art documentation application. The camera consists of five discrete bands, used for taking the motifs of the rock art paintings on a big structure of a cave based on the close-range photogrammetry technique. The captured images then processed using commercial structure-from-motion photogrammetry software, which automatically extracts the tie point. The extracted tie points were then used as input to generate a dense point cloud based on the multi-view stereo (MVS) and produced the multispectral 3D model, and orthophotos in a different wavelength. For comparison, the paintings and the wall surface also observed by using terrestrial laser scanner which capable of recording thousands of points in a short period of time with high accuracy. The cloud-to-cloud comparison between multispectral and TLS 3D point cloud show a sub-cm discrepancy, considering the used of the natural features as control target during 3D construction. Nevertheless, the processing also provides photorealistic orthophoto, indicates the advantages of the multispectral camera in generating dense 3D point cloud as TLS, photorealistic 3D model as RGB optic camera, and also with the multiwavelength output.

A COMPARISON BETWEEN TLS AND UAV TECHNOLOGIES FOR HISTORICAL INVESTIGATION

Abstract. The architectural and sculptural value of the investigated Cultural Heritage has suggested a variety of possible approaches ranging from the traditional modus operandi to the implementation of innovative technology. The conducted research implemented digital and automatic photogrammetry software using Structure from Motion or SFM. These techniques which involve the convergence of different disciplines, such as Computer Vision and photogrammetry seek to generate 3D models, that is the mathematical representation of the investigated 3D objects. The integration of UAS, photogrammetry and TLS develops 3D models able to provide more detailed information. The main purpose of the present research is to test the potentialities offered by the new survey and 3D processing systems in order to carry out historical analyses and investigations in closed environments and for small scale architecture. Starting from the acquired data, the 3D models of the altars allow a 3D comparison between the works object of study and Pozzo’s treatise, also allowing speculation about their possible relations, providing extraordinary outcomes from the point of view of survey integrated methodologies and from the point of view of historical and geometric interpretation.

Low-Cost CSI Using Forensic GPR, 3D Reconstruction, and GIS

At a time in which several law enforcement agencies all around the world are facing severe expenditure reviews, the increasing use of low-cost solutions during crime scene investigations (CSI) can be a sustainable solution without being detracting from a scientific and rigorous forensic approach. Recently, some private companies are trying to satisfy the growing needs of the police to have cheaper and faster techniques to survey crime scenes and to obtain results with scientifically high-level outputs, more or less comparable with similar outputs from more expensive instruments. This paper reported results from a crime scene in which a low-cost GPR instrument, a free 3D photogrammetry software, and an open-source geographical information system (GIS) were deployed. The collection, processing, and analyses of these data will provide a very promising starting point for future low-cost and professional applications.

UAVs for volcano monitoring: A new approach applied on an active lava flow on Mt. Etna (Italy), during the 27 February–02 March 2017 eruption

Mt. Etna (Italy) with 55 effusive events in the last six years is one of the most active volcanoes in the world, with a million people living on its flank and thousands of tourists who visit it every summer.For this reason, the lava flow monitoring for risk mitigation and Civil Protection purposes is one of the fundamental tasks of the Cartographic Laboratory of the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo. This activity was traditionally performed using data collected from the field (with terrestrial GPS surveys) and from helicopter taking visible and thermal images. During the 27 February–02 March 2017 eruption the FlyEye Team, applied Unmanned Aerial Vehicles to monitor the active lava flow. Two high-resolution UAV surveys were performed on the lava flow field on the south flank of Mt. Etna, between 3050 and 2600 m a.s.l., obtaining almost 1170 images. Structure-from-Motion techniques were applied to create orthophotos and Digital Elevation Models (DEM) of the lava flow field and surroundings. The obtained DEM has a resolution of 14.2, and 20.7 cm/px for the main lava flow and the west branch, respectively. On the wall, the 96% of the lava flow field was mapped using aerial images by UAV covering an area of 0.3 × 106 m2. Lava flow volume was calculated with the topographic approach: difference between post- and pre-eruption surface, DEM 2017 and DEM 2014, respectively. The impossibility of spreading the GCPs homogenously distorted the resulting DEM; for this reason, it was necessary to align the lava flow point clouds, obtained from the photogrammetry software, to the basal 2014 DEM. Subtracting the two DEMs a lava flow thickness grid resulted leading to a total volume of 1.4 × 106 m3 and an error estimation of about 20%. Finally, dividing the total volume for the effusion duration (63 h) a mean output rate of 6.2 m3/s resulted. The calculated volcanological parameters have the same order of magnitude of the previous activity of Mt. Etna, between 2011 and 2016. This research demonstrates that UAV photogrammetry was successfully exploited during an eruptive crisis, allowing a first fast processing, to obtain an orthophoto of the lava flow field, useful for “decision makers” and a further slower processing for the realization of a high-resolution DEM. The latter makes it possible to update the topography, another important argument for Civil Protection purpose. This paper describes a methodology that could be applied during other natural events in extreme environmental conditions.

Detection of palm oil bud rot employing artificial vision

This paper describes the development of a system capable of capturing, processing, and analysing images of palm oil plantations in order to detect and identify bud rot disease. The process begins with the capturing of images using the DJI Phantom 4 UAV, which is first configured for a flight plan of the desired area and altitude. The resulting images are processed by photogrammetry software to create orthomosaics. The developed algorithm uses the grayscale of the generated orthomosaic and identifies the palms affected by bud rot. This is accomplished using the sliding-window method, by which smaller samples of the image are used and evaluated independently. Each sample is then extracted with a ULBP feature vector that numerically represents the texture of the image and is classified by means of a previously trained logistic regression model, allowing the recognition of positive cases of the disease. Possible positive cases are further distinguished using the non-maximum suppression algorithm. The system was tested with different images than the images used for training and for establishing the set point. As a result, the system showed a 92% precision and a 96% of sensitivity for bud rot disease detection. These results are satisfactory in terms of detecting bud rot disease using a low-cost system.