Photogrammetric Image Processing Research Articles

Relationships of Fire Rate of Spread with Spectral and Geometric Features Derived from UAV-Based Photogrammetric Point Clouds

Unmanned aerial vehicles (UAVs) equipped with RGB, multispectral, or thermal cameras have demonstrated their potential to provide high-resolution data before, during, and after wildfires and prescribed burns. Pre-burn point clouds generated through the photogrammetric processing of UAV images contain geometrical and spectral information of vegetation, while active fire imagery allows for deriving fire behavior metrics. This paper focuses on characterizing the relationship between the fire rate of spread (RoS) in prescribed burns and a set of independent geometrical, spectral, and neighborhood variables extracted from UAV-derived point clouds. For this purpose, different flights were performed before and during the prescribed burning in seven grasslands and open forest plots. Variables extracted from the point cloud were interpolated to a grid, which was sized according to the RoS semivariogram. Random Forest regressions were applied, obtaining up to 0.56 of R2 in the different plots studied. Geometric variables from the point clouds, such as planarity and the spectral normalized blue–red difference index (NBRDI), are related to fire RoS. In analyzing the results, the minimum value of the eigenentropy (Eigenentropy_MIN), the mean value of the planarity (Planarity_MEAN), and percentile 75 of the NBRDI (NBRDI_P75) obtained the highest feature importance. Plot-specific analyses unveiled distinct combinations of geometric and spectral features, although certain features, such as Planarity_MEAN and the mean value of the grid obtained from the standard deviation of the distance between points (Dist_std_MEAN), consistently held high importance across all plots. The relationships between pre-burning UAV data and fire RoS can complement meteorological and topographic variables, enhancing wildfire and prescribed burn models.

Drone agrotechnology’s for cotton (Gossypium hirsutum L.) pest and diseases management in Western of Burkina Faso

Drone technologies, also known as "unmanned aerial vehicles" (UAVs) or "unmanned aerial systems" (UAS), have a wide range of applications, including mapping, land-use planning, crop/infrastructure damage assessment, fertilizer spraying and precision crop protection. However, its use is still very limited in the agricultural sector in Africa in general and in Burkina Faso in particular. This study was initiated to explore the potential of UAVs for optimizing cotton yields through monitoring and phytosanitary efficiency. To this end, phytosanitary treatments and monitoring of vegetation status using multispectral drone imagery were carried out on cotton. The experimental sample consisted of four (04) cotton fields in four (04) locations. Phytosanitary treatments and aerial photography were respectively carried out using a DJI AGRAS T16 spray drone and a DJI Phantom 4 Multispectral drone. Phytosanitary treatment with DJI AGRAS T16 drone resulted in savings of 32.41% in treatment duration, 23.58% in water, 1% in pesticides and 10.5% in labor compared with manual spraying, but did not have a positive impact on boll yields due to jassid populations attack. The RGB and NDVI vegetation indices generated by photogrammetric processing of multispectral images acquired by drone enabled us to perceive phytosanitary state of cotton plants during their development cycle. Information provided by these vegetation indices and by this study in general can be used to improve the efficiency of phytosanitary treatments against cotton pests and diseases.

Accuracy assessment of UAS photogrammetry and structure from motion in surveying and mapping

Rapid and accurate surveying has always attracted great interest in all scientific and industrial activities that require high-resolution topographic data. The latest automation and advancement in geomatics engineering are remote sensing solutions using Unmanned Aerial Systems (UAS) and Structure from Motion (SfM) with Multi-View Stereo (MVS) photogrammetry. This research aimed to find the influence of flight height, Ground Control Point (GCP), and software on the geometric accuracy of UAS-SfM-derived Digital Surface Models (DSMs) and orthoimages, as well as to analyze and evaluate the accuracy of UAS-SfM as a rapid and low-cost alternative to conventional survey methods. To achieve the aim of the study, aerial surveys using a fixed-wing UAS and field surveys using RTK GNSS and total station were conducted. A total of 16 photogrammetric projects were processed using different GCP configurations, and detailed statistical analysis was performed on the results. Moreover, the contribution of cross flight on bundle adjustment was investigated empirically by conducting a combined photogrammetric image processing. The analysis revealed that flight height, GCP number and distribution, and the processing software significantly affect products' quality and accuracy. Evaluation of the achieved accuracies was made based on the American Society for Photogrammetry and Remote Sensing (ASPRS) positional accuracy standard for digital geospatial data. The findings of this study revealed that using the optimal flight height and GCP configuration, 3D models, orthomosaics and DSMs can be rapidly reconstructed from 2D images with the quality and accuracy sufficient for most terrain analysis applications, including civil engineering projects.

ROCK MASS DISCONTINUITY DETERMINATION WITH TRANSFER LEARNING

Abstract. Rock mass discontinuity and orientation are among the important rock mass features. They are conventionally determined with scan-line surveys by engineering geologists in field, which can be difficult or impossible depending on site accessibility. Photogrammetry and computer vision techniques can aid to automatically perform these measurements, although variations in size, shape and appearance of rock masses make the task challenging. Here we propose an automated approach for the detection of rock mass discontinuities using deep learning and photogrammetric image processing methods. Two deep convolutional neural network (DCNNs) were implemented for this purpose and applied to basalts in Kizilcahamam Guvem Geosite near Ankara, Türkiye. Red-green-blue (RGB) band images of the site were taken from an off-the-shelf camera with 1.7 mm resolution and a 3D digital surface model and orthophotos were produced by using photogrammetric software. The discontinuities were delineated manually on the orthophoto and converted to masks. The first DCNN model was based on the open-source crack dataset consisting of a total of 11,298 road and pavement images, which were used to train the Resnet-18 model (Model-1). The second model (Model-2) was based on fine-tuning of Model-1 using the study data from Kizilcahamam. After fine-tuning, Model-2 was able to achieve high performance with a Jaccard Score of 88% on the test data. The results show high potential of the methodology for transfer learning with fine-tuning of a small amount of data that can be applied to other sites and rock mass types as well.

Creating the spatial data infrastructure elements by local areas of digital images

The article discusses the main features of creating spatial data infrastructure (SDI) elements based on digital images that lack orientation elements, survey parameters, and imagery projection data. The technology for analyzing such images is based on the photogrammetric processing of single images, using the analytical and geometric features of the transformation of local areas – fragments of images obtained by an ultra-narrow bunch of projecting rays.

Accuracy evaluation of UAS photogrammetry and structure from motion in 3D modeling and volumetric calculations

Photogrammetric surveying using unmanned aerial systems (UAS) and structure from motion (SfM) is a rapidly emerging technique that has been widely used as a valuable research tool in geodesy and related disciplines. We studied surveying and three-dimensional (3D) modeling based on UAS and SfM. In particular, we focus on the accuracy and quality of UAS-SfM in 3D modeling and volumetric calculation of a building with an overhanging feature. For this purpose, two aerial surveys were performed using a fixed-wing and a multirotor aircraft with nadir and oblique camera axes. For validating the results, field surveys were carried out using terrestrial laser scanner (TLS), differential global navigation satellite system, and total station. To study the performance of SfM software on the accuracy and quality of point clouds, UAS images were processed using three software packages: Agisoft PhotoScan, Pix4Dmapper, and 3Dsurvey. As a result of photogrammetric image processing, 3D dense point clouds, mesh models, and digital surface models were generated. For validating the UAS-SfM results, the models were compared with the TLS model and field measurements; absolute accuracy assessments and model versus model comparisons were performed. The most accurate and high-quality 3D models comparable to TLS models were obtained from oblique images. PhotoScan generated relatively more accurate 3D models with the horizontal and vertical accuracy of root mean square error 0.025 and 0.02 m, respectively. The maximum discrepancies in dimensions and volume measurements from the UAS-SfM-derived point cloud were at the level of 0.01 m and 0.66 m3 (0.03%). The results highlighted that using a low-cost UAS and SfM photogrammetry, high-accuracy and high-quality 3D models can be generated. The results confirm that with respect to its rapid data acquisition and centimeter-level accuracy, UAS-SfM can be considered as a suitable alternative approach to conventional measurement techniques, especially in engineering and emergency response.

Accuracy assessment of high-resolution terrain data produced from UAV images georeferenced with on-board PPK positioning

In recent years, unmanned aerial vehicles (UAVs) have increased rapidly and successfully established themselves as a tool for the rapid collection of high-resolution images as baseline data in land cover studies and topographic mapping. In photogrammetry using the SfM-MVS method of processing captured images, indirect georeferencing of the digital data through ground control points (GCPs) is usually applied. But selecting, marking, and coordinating GCPs in hardto-reach terrains is time-consuming and sometimes dangerous or impossible. The main objective of this study is to evaluate the accuracy of high-resolution topographic data (HRTD) products of photogrammetric processing of PPK-directly georeferenced images by SfM-MVS workflow. Direct and indirect methods of georeferencing digital products are compared. The planimetric and vertical root mean square error (RMSE) in the position of the validation points were calculated by the differences between measured coordinates in dense point clouds, orthophoto mosaics, and terrain surfaces (DSM), and precisely measured coordinates of the validation points by GNSSRTK receivers. The analysis is based on a statistical evaluation of experimental data obtained from a TAROT X6-based hexacopter equipped with two different image sensor configurations: 1) Sony RX0 action camera and 2) Sony A6000 mirrorless camera, and 3) DJI Phantom 4 Pro quadcopter with integrated additional L1-GNSS module for direct georeferencing by PPKmethod. HRTD generation was performed with three block control configurations for each UAV: 1) Indirect georeferencing via GCP only, 2) PPK direct georeferencing without GCP, and 3) PPK georeferencing using one GCP. Our research showed that when using L1-GNSS onboard receivers for PPK-georeferencing without any GCPs, the point cloud's planimetric accuracy (RMSExy) was from 0.125 to 0.231 cm, depending on the UAV/camera configuration. However, two flight missions produced significant vertical offsets, most likely due to ionospheric disturbances affecting the resolution of phase cycle ambiguities in the single-frequency receivers used. When adding one control point in the PPK georeferencing method, the planimetric and vertical accuracy of the data is comparable to the indirect GCP referencing method. Furthermore, our results show that camera properties (i.e., focal length, resolution, sensor quality) affect the quality and accuracy of digital products. The HRTDs were also evaluated according to the ASPRS (American Photogrammetry and Remote Sensing Society) Standards for Accuracy of Digital Geospatial Data. Analyzing the accuracy of the HRTDs obtained with the experimental UAV/camera configurations for the test area, the present study shows that the PPK-SfM-MVS workflow can provide quality data with a centimeters accuracy of the photogrammetric products.

Создание пространственной модели рельефа местности по результатам геодезических измерений для анализа воздействия на окружающую среду в условиях малых карьеров

Mining, especially open pit mining, has a significant impact on the terrain. The article discusses the use of geodetic methods to monitor the process of mining and its possible impact on the environ-ment. The created relief model can be used to design the process of quarry restoration after their closure. The mineral wealth of a country is considered an important factor and is linked to the country's economy. Mineral resources are non-renewable, and their extraction and subsequent processing must take into account the rarity of their occurrence, the level of mining technologies to track spatial changes in mining operations. The main idea of this scientific study is to apply geodetic measurement methods to determine the current scale of mining in a quarry using a 3D terrain model. The paper presents an overview of the technologies used in performing geodetic measurements, as well as processing the measured data to assess the state of the spatial distribution of a quarry in order to determine the impact of mining on the landscape. The purpose of this article is to create a spatial terrain model based on the results of geodetic measurements to analyze the impact on the environment in small open pits. Methods of geodetic observations were used to create a spatial model of the terrain. Digital maps were also created by photogrammetric processing of aerial stereo images and subsequent semi-automatic removal of vegetation and other objects.

Мониторинг развития Мордыяхского объекта взрыва газа на Ямале на основе данных дистанционного зондирования Земли

The authors carried out a comprehensive study of the Mordyakh object C15 of a catastrophic gas blowout in 2017 using the Earth remote sensing (RS) data from space, including ArcticDEM digital 3D models. According to the remote sensing data, the researchers proved the rapid growth of the perennial heaving mound (PHM) C15 of about 1 m in height during 14.5 months from March 19, 2012 to June 6, 2013 and that in the next four years its growth rate was about 10 cm per year. They determined that in the period from June 8 to June 19, 2017, an explosion occurred in the arch of the PHM with the formation of a crater. As a result of photogrammetric processing of aerial images from a helicopter, the authors developed a highly detailed 3D model of the crater as of August 26, 2020. They recorded the scattering of frozen soil pieces up to a distance of 90 m, and calculated the approximate volume of the largest of them, which was about 40—50 m3. As a result of the research the authors confirmed the endogenous gas-dynamic mechanism of PHM growth followed by powerful blowout and gas explosions with the formation of giant craters. The results contribute to improving the safety of the operation of oil and gas facilities in the Arctic.

Photogrammetric counts of pacific salmon by means of unmanned aerial vehicles of consumer grade

Methodology for photogrammetric counting of pacific salmon by means of unmanned aerial vehicles (UAVs) of consumer grade is developed. The spawners and spawning redds are counted using photogrammetric processing of aerial images taken by UAVs at monitoring sites. The photogrammetric products (orthomosaics and digital elevation models — DEMs) are analyzed in geographic information systems (GIS). The estimations of relative abundance for the monitoring sites are extrapolated to entire area of potential spawning grounds. There is shown for the first time that DEMs of water channels allow to visualize and count the redds. Detailed description of methodology is presented, including the survey planning and implementation, data processing, fish abundance estimation, data analysis and visualization, and web-publication. Recommendations for choosing UAV, its accessories and software for flight, photogrammetry and GIS are provided. This approach will facilitate objectivity of salmon counts and provide gradual transition from subjective aerovisual methods towards proven and verified digital basis of fish abundance assessment.

Photogrammetric Co-Processing of Thermal Infrared Images and RGB Images.

In some applications of thermography, spatial orientation of the thermal infrared information can be desirable. By the photogrammetric processing of thermal infrared (TIR) images, it is possible to create 2D and 3D results augmented by thermal infrared information. On the augmented 2D and 3D results, it is possible to locate thermal occurrences in the coordinate system and to determine their scale, length, area or volume. However, photogrammetric processing of TIR images is difficult due to negative factors which are caused by the natural character of TIR images. Among the negative factors are the lower resolution of TIR images compared to RGB images and lack of visible features on the TIR images. To eliminate these negative factors, two methods of photogrammetric co-processing of TIR and RGB images were designed. Both methods require a fixed system of TIR and RGB cameras and for each TIR image a corresponding RGB image must be captured. One of the methods was termed sharpening and the result of this method is mainly an augmented orthophoto, and an augmented texture of the 3D model. The second method was termed reprojection and the result of this method is a point cloud augmented by thermal infrared information. The details of the designed methods, as well as the experiments related to the methods, are presented in this article.

Photogrammetric Processing of Tianwen-1 HiRIC Imagery for Precision Topographic Mapping on Mars

The High-Resolution Imaging Camera (HiRIC) onboard China’s Tianwen-1 Mars probe aims to acquire detailed imagery of the Martian surface to comprehensively investigate its topography and geomorphology. The HiRIC is a pushbroom camera comprising three CCDs to simultaneously achieve sub-meter resolution and a large swath. However, processing HiRIC images using the conventional photogrammetric workflow is difficult due to the large shifts and narrow overlapping among the CCD lines. This paper presents a novel approach for photogrammetric processing of HiRIC images for precision topographic mapping that incorporates 1) the fitting of the initial Rational Polynomial Coefficients (RPCs) of images from the HiRIC position and pointing data, 2) a deep-learning-based method for tie-point matching between adjacent CCD images and cross-orbit images, 3) the bundle adjustment of multiple CCD images for tripled-epipolar image generation to ensure inner-orbit consistency, 4) the block adjustment of multiple orbit images to ensure cross-orbit consistency, and 5) dense image matching and space intersection based on the refined RPCs to generate Digital Elevation Models (DEMs). Experimental analyses were conducted using HiRIC images covering the landing region of the Zhurong rover. The results revealed that subpixel accuracy was achieved for image residuals among multiple-CCD or multiple-orbit images. Comparison with the reference data (HiRISE and MOLA DEMs) revealed a mean deviation of less than 7 m in terms of the geometric accuracy and the subtle topographic details of the HiRIC DEM. The presented approach offers a reliable solution for using the new dataset of HiRIC imagery for Mars topographic mapping.

Generation of Large-Scale Orthophoto Mosaics Using MEX HRSC Images for the Candidate Landing Regions of China’s First Mars Mission

Planetary mapping products play a significant role in landing site selection, surface operations, and scientific investigations. This paper describes the techniques and processes used to create geometrically controlled image mosaics for the candidate landing regions of China’s first Mars exploration mission (i.e., Tianwen-1) using Mars Express (MEX) High-Resolution Stereo Camera (HRSC) images. In order to deal with the extremely complex situations due to large data volumes (hundreds of images), various imaging conditions (e.g., 5–80° incidence angles), and long time spans (>10 years), we developed corresponding methods and in-house software for the photogrammetric processing of MEX HRSC images. According to the characteristics of planetary images and multi-line pushbroom imaging, we optimized the algorithms of establishing control network, eliminating blunders, setting weights and processing abnormal images. The generated MEX HRSC image mosaics with a resolution of 12.5 m delivered a high relative accuracy (<1 pixel). Compared with the existing Mars global image mosaics, the generated image mosaics exhibit significantly better spatial resolution. The techniques and methods that we developed to solve the complicated photogrammetric processing problems can also be applied to produce global or large-scale Mars mapping products using existing and new returned orbital images.

Херексуры Юстыда: мультиспектральная съемка, опыт использования БПЛА для комплексного изучения

The article discusses the methodological issues of remote mapping objects of archaeological heritage using unmanned aerial vehicles. A section of the Yustyd river valley on the territory of the Kosh-Agach district of the Altai Republic was chosen as a polygon. The survey area in 2021 covered the territory of the right bank with the maximum concentration of large objects, first of all, khirgisuurs, which are distinguished by a variety of shapes and internal structures. For multispectral shooting of archaeological sites, an unmanned aerial vehicle DJI Inspire 1 (ver. 2.0) was used, a design feature of which was an additional mini-platform located in the rear of the hull. The platform was mounted for the installation of a Parrot Sequoia camera and an additional battery — a source of autonomous power supply for the camera. The process of photogrammetric processing of images was a computer automated digital processing of photographic materials with the subsequent creation of a mosaic orthomosaic. Agisoft Metashape software was chosen for photogrammetric processing of materials. The results obtained were subjected to index (thematic) processing of multispectral images based on a combination of green, red and near infrared channels. In the course of a comparative analysis of the constructed images, the following regularities were found. The MCARI index makes it possible to detect burial mounds and structural elements expressed in geometry (plan). Detection of various “anomalies” characterizing the presence of small elements in the turf layers is possible with additional filter processing. Thus, it has been established that multispectral imaging is a new high-tech tool for performing work: archaeological exploration, searching for new objects and clarifying the configuration of previously studied objects, when mapping stand-alone sites and archaeological complexes in general.

An approach to photogrammetric processing of indirect optical location data

The paper proposes an approach to obtaining images of the objects under investigation based on indirect optical location data. The goal of the study is to increase the graphic similarity of the images and to assign them measuring properties. To achieve this goal, the concept of photogrammetric processing of frame images obtained by conducting indirect optical location in a certain way is formulated. The graphical similarity of the images is proposed to be improved by extracting photometric data related to the object and the background from the registered optical radiation. Based on the selected data, a statistical evaluation of the sample average of the optical radiation intensity from these sources is carried out. The obtained estimates are used to form a monochrome digital image. Adding measurement properties is done by converting the coordinates of the digital image to relative coordinates that have a metric expression. The reason for the decrease in the graphical similarity of the images obtained on the basis of indirect optical location data is determined. In particular, the addition of light waves from different sources, during the allotted exposure time of the photodetector, leads to the merging of the object and the background in the resulting image. The paper presents an approach to the separation of photometric data from different sources that is based on the observation of the phase difference between the emitted and recorded light waves. The authors define the mathematical apparatus for linking the obtained images to the relative coordinate system that is adapted for the case of indirect optical location. The concept of conducting indirect optical location using a special optoelectronic complex is proposed. The study describes the requirements for the equipment of an optoelectronic complex that generates and registers optical radiation with the required parameters. The results of an experiment on the formation of images with measuring properties confirm the feasibility of using the proposed method. Conducting an indirect optical location opens the way to obtaining images of an area that is inaccessible to humans. In particular, the results of the experiment demonstrate that the use of the proposed concept provides images of an object placed behind a light-tight obstacle, which are characterized by the presence of measuring properties and reflect the details of the object under study with high graphical similarit.

Orbital Photogrammetry of Selected Relief Elements with Evidences of Geological Activity in Aitken Crater on the Far Side of the Moon

Achievements in the field of lunar research over the past 10-15 years have brought a lot of important information about the Moon and its interior. In particular, a high-resolution orbital survey performed from low lunar orbit by the Lunar Reconnaissance Orbiter (LRO) station has revealed details of the structure of impact craters, which were not even suspected before. For example, rivers and non-frozen lakes of molten lunar soil in the area of Tycho crater. Another impressive example is the glacier-like tongues of lunar rocks flowing from the central peaks of young impact craters. Or the unexpectedly high frequency of meteorite impacts on the lunar surface. Results of this kind can significantly affect future plans for the exploration of the Moon by automatic weapons and expeditions with a crew. They can also make a noticeable contribution to fundamental research. In this work, using a specific example of the Aitken crater, the possibilities of studying the relief in young impact craters based on photogrammetric processing of orbital images of the lunar surface are shown. The problems of a computational nature in the creation of 3D-models of the lunar relief and their referencing to the selenocentric coordinate system are also considered.

Present Software of photogrammetric processing of digital images

Four open source and three commercial software been used to create point clouds from identical data: images taken at five different locations. The investigation compares elapsed time and the size of the generated point clouds for the different software. Based on the tests, suggestions for users are provided.

Influence of the shape and size of the ground targets on the accuracy of photogrammetric processing

The materials obtained from the unmanned aerial vehicle (UAV) are used to solve many problems, including large-scale mapping and monitoring of linear objects, as well as the ecological situation and monitoring of emergency situations. The promptly obtained photographic materials make it possible to reveal the consequences of man-made human impact associated with degradation of the soil cover, flooding of lands, salinization and pollution of the soil layer, and changes in the vegetation cover. Control points are used for absolute orientation of the generated models in the most projects of photogrammetric processing of aerial photos and images obtained from UAVs. In areas with low contour, before aerial survey, targeting is carried out in the required zones. The research is devoted to the study of the influence of the shape of ground targets on the accuracy of photogrammetric processing. It involved three different types of ground targets located on the land cover along the survey path at a distance not exceeding 1 m from each other. The targets were used as ground control points in the photogrammetric processing of the materials from the UAV. Two three-stripe photographic surveys of the 900 m long track were carried out: with UAV DJI PHANTOM 4 PRO camera FC6310 at a scale of 1:3400 and ground resolution of 1 cm and with the DJI Mavic PRO UAV camera FC220 at a scale of 1:12 700 and ground resolution of 2 cm. In both cases, the direction of flight is north - south, 36 targets were included in the photogrammetric processing. In the first case, 502 images were processed, in the second - 152. The photogrammetric processing for the orthophoto mosaic generation was carried out using the Agisoft Photo Scan Professional software. Four different contrasting sites in the study area were selected for the study: green grass, dry grass, clay, sand. Accuracy was assessed according to two criteria: 1) the degree of visualization of the target on the images; 2) the accuracy of the orthophoto mosaic, generated using various targets.

Assessing the georeferencing accuracy of different amount of image stripes for linear UAV projects

At present, the results of photogrammetric processing of images obtained from UAVs (orthophoto mosaics, digital elevation models, etc.) are widely used for environmental studies. Such materials are especially relevant and in demand for environmental monitoring of hard-to-reach objects. In addition, UAV survey materials are indispensable for impact monitoring, in which observation, assessment and forecast of the state of the natural environment in areas where hazardous and potentially hazardous (NPP) sources of anthropogenic impact are located are carried out. Regardless of the method of georeferencing of images - direct or indirect - the accuracy of the generated product is evaluated by ground control points. The purpose of this study is to assess the accuracy of photogrammetric constructions depending on the number of strips when surveying linear objects from UAVs and on the number of control points used in indirect georeferencing. Five groups of experiments were carried out during the study, three in each group with a different number of strips (from one to three). Five groups are conventionally combined into two sections. In the first section, direct and indirect georeferencing techniques were used with three locally located control points. In the second section, the method of indirect georeferencing was used with a different number of ground control points: six, twelve and thirty-four. Estimates of the accuracy of various tests have shown that an increase in the number of strips does not always lead to an increase in accuracy.

AUTOMATED VOLUME MEASUREMENT OF A WASTE BIN WITH A SMARTPHONE APP BASED ON PHOTOGRAMMETRIC METHODS

Abstract. In order to get accurate information about the volume of a partly filled bin of packaging waste a dedicated smartphone app was developed. The main functions of the app are to collect sets of images, which are sent to an external server (cloud) for automatic photogrammetric image processing. The results, basically the filling volume is transferred back to the user. The photogrammetric workflow includes an orientation and a volume calculation phase. The workflow was extensively tested for its functionality, performance, reliability and possible sources of error. Thereby several tests were conducted to estimate the optimum number of images, the best image configuration and the influence of different filling levels. The results demonstrate, that the filling volume may be automatically and accurately determined, if the configuration of the images is appropriate. Best results were obtained with many images taken nearly vertically.