A Photogrammetry Software as a Tool for Precision Agriculture: A Case Study

Delgado-Vera, Carlota; Aguirre-Munizaga, Maritza; Jiménez-Icaza, Manuel; Manobanda-Herrera, Nadia; Rodríguez-Méndez, Ana

doi:10.1007/978-3-319-67283-0_21

Cited by 9 publications

(6 citation statements)

References 22 publications

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“…The images were georeferenced using these metadata and the coordinates of eight photogrammetric control targets installed in Area A and five in Area B. The aerotriangulation in this software is performed using a scale-invariant feature transform (SIFT) algorithm, based on the search for similar features in the photographs, with an automatic tie point generation by image matching, and the application of structure from motion (SFM) and multiview stereo (MVS) techniques, resulting in a dense point cloud (Vera et al, 2017). The planialtimetric coordinates of the photo-identifiable control targets were used to adjust the georeferencing of the point cloud and photographs.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of the Radiometric Accuracy of Images Obtained by a Sequoia Multispectral Camera

et al. 2020

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Geometric and radiometric corrections of images obtained by remotely piloted aircraft systems (RPAS) are required for the measurement of the spectral reflectance and calculation of vegetation indices. This study aimed to determine which radiometric calibration procedures allow obtaining suborbital images with more accurate reflectance data and spectral indices based on data collected by a Sequoia multispectral camera coupled to a RPAS on black oat cultivations at the flowering stage located in Eldorado do Sul, RS, Brazil. The orthophoto mosaics were processed without and with radiometric corrections by reflectance calibration ground target and/or solar irradiance sensor of the camera, and the radiometric accuracy of these images was evaluated using spectral reflectance ground data collected by the Crop Circle canopy sensor. The results indicated that the use of a reflectance calibration ground target is recommended to increase the radiometric accuracy of photographs even if the Sequoia solar irradiance sensor is employed. The use of the light gray target in the radiometric calibration resulted in orthophotos with the mean square error of reflectance values lower than 0.01 for all the analyzed bands and spectral indices.

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Section: Methodsmentioning

confidence: 99%

Evaluation of the Radiometric Accuracy of Images Obtained by a Sequoia Multispectral Camera

et al. 2020

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“…With our model, OpenDroneMap (ODM) appeared as the best option in terms of cost-benefit relationship, as shown in Table 5. After conducting a comprehensive review of related works, we identified only one relevant paper [32]. This paper initiated a comparison of tools for agronomy point cloud representation, providing a foundational reference point for our research.…”

Section: Design Of a Synthetic Quality Metric For Software Selectionmentioning

confidence: 99%

“…In comparison to the study in [32], our use case showcased a broader spectrum of tools, presenting image captures from all software tools compatible with our dataset. Additionally, our research introduced a meticulously calibrated quality analysis of point clouds, exceeding the scope of the prior study.…”

Section: Design Of a Synthetic Quality Metric For Software Selectionmentioning

confidence: 99%

Harnessing Digital Twins for Agriculture 5.0: A Comparative Analysis of 3D Point Cloud Tools

Catala-Roman,

Navarro,

Segura-Garcia

et al. 2024

Applied Sciences

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Digital twins are essential in Agriculture 5.0, providing an accurate digital representation of agricultural objects and processes, enabling data-driven decision-making, the simulation of future scenarios, and innovation for a more efficient and sustainable agriculture. The main objective of this article is to review and compare the main tools for the development of digital twins for Agriculture 5.0 applications using 3D point cloud models created from photogrammetry techniques. For this purpose, the most commonly used tools for the development of these 3D models are presented. As a methodological approach, a qualitative comparison of the main characteristics of these tools was carried out. Then, based on some images taken in an orange grove, a quality analysis of the 3D point cloud models obtained by each of the analyzed tools was carried out. We also obtained a synthetic quality index in order to have a way to categorize the different pieces of software. Finally, as a conclusion, we compared the performance of the different software tools and the point clouds obtained by considering objective metrics (from the 3D quality assessment) and qualitative metrics in the synthetic quality index. With this index, we found that OpenDroneMap was the best software in terms of quality-cost ratio. Also, the paper introduces the concept of Agriculture 6.0, exploring the integration of advancements from Agriculture 5.0 to envision the potential evolution of agricultural practices and technologies, considering their impact on social and economic aspects.

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“…This study covers the image acquisition process, generation of the point cloud, and accuracy assessment by evaluating the quality of 3D dense point cloud models and digital surface models by considering geometric as well as visual inspections. Delgado-Vera et al [34] analyzed and compared several photogrammetry tools, i.e., Qgis, MicMac, OpenDrone Map, Ensoamic, VisualSFM, Insight3d, Agisoft, and Pix4d, considering the aerial view images for agricultural land. A case study was performed on the land of the "Agrarian University of Ecuador Experimental Research Center based in Mariscal Sucre, Milagro" using a drone and photogrammetry process to obtain orthophoto.…”

Section: Summary Of the Collected Literaturementioning

confidence: 99%

Evaluation of Photogrammetry Tools following Progress Detection of Rebar towards Sustainable Construction Processes

Qureshi

Alaloul²,

Hussain³

et al. 2022

Sustainability

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In the attainment of digitization and sustainable solutions under Industry 4.0, effective and economical technology like photogrammetry is gaining popularity in every field among professionals and researchers alike. In the market, various photogrammetry tools are available. These tools employ different techniques and it is hard to identify the best among them. This study is an attempt to develop a methodology for the assessment of photogrammetry tools. Overall, 37 photogrammetry tools were found via literature review and open sources, out of which 12 tools were shortlisted. The evaluation process consisted of three steps, i.e., metadata and visual inspection, comparison with the ground truth model, and comparison with the averaged-merged point cloud model. In addition, a validation test was also performed on the final sorted photogrammetry tools. This study followed a sustainable construction progress monitoring theme for rebar and covered the maximum number of photogrammetry tools for comparison by considering the most authentic evaluation and validation techniques, which make it exclusive.

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A Photogrammetry Software as a Tool for Precision Agriculture: A Case Study

Cited by 9 publications

References 22 publications

Evaluation of the Radiometric Accuracy of Images Obtained by a Sequoia Multispectral Camera

Evaluation of the Radiometric Accuracy of Images Obtained by a Sequoia Multispectral Camera

Harnessing Digital Twins for Agriculture 5.0: A Comparative Analysis of 3D Point Cloud Tools

Evaluation of Photogrammetry Tools following Progress Detection of Rebar towards Sustainable Construction Processes

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