Accuracy of Orthomosaic Generated by Different Methods in Example of UAV Platform MUST Q

Liba, Natalja; Berg-Jürgens, J

doi:10.1088/1757-899x/96/1/012041

Cited by 16 publications

(10 citation statements)

References 5 publications

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“…Knowing these parameters is essential for optimal management in seed orchards, including the proper selection of pruning techniques, irrigation needs, phytosanitary management regimes, and the calculation of tree-level characteristics. In addition, UAV use enables the production of various advanced data such as videos [29,30], orthomosaics [31][32][33], and digital terrain and surface models [34,35], which contain the basic inputs for subsequent estimates on the individual-tree level.…”

Section: Introductionmentioning

confidence: 99%

Detecting Individual Tree Attributes and Multispectral Indices Using Unmanned Aerial Vehicles: Applications in a Pine Clonal Orchard

Gallardo-Salazar

Pompa-García

2020

Remote Sensing

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Modern forestry poses new challenges that space technologies can solve thanks to the advent of unmanned aerial vehicles (UAVs). This study proposes a methodology to extract tree-level characteristics using UAVs in a spatially distributed area of pine trees on a regular basis. Analysis included different vegetation indices estimated with a high-resolution orthomosaic. Statistically reliable results were found through a three-phase workflow consisting of image acquisition, canopy analysis, and validation with field measurements. Of the 117 trees in the field, 112 (95%) were detected by the algorithm, while height, area, and crown diameter were underestimated by 1.78 m, 7.58 m2, and 1.21 m, respectively. Individual tree attributes obtained from the UAV, such as total height (H) and the crown diameter (CD), made it possible to generate good allometric equations to infer the basal diameter (BD) and diameter at breast height (DBH), with R2 of 0.76 and 0.79, respectively. Multispectral indices were useful as tree vigor parameters, although the normalized-difference vegetation index (NDVI) was highlighted as the best proxy to monitor the phytosanitary condition of the orchard. Spatial variation in individual tree productivity suggests the differential management of ramets. The consistency of the results allows for its application in the field, including the complementation of spectral information that can be generated; the increase in accuracy and efficiency poses a path to modern inventories. However, the limitation for its application in forests of more complex structures is identified; therefore, further research is recommended.

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Section: Introductionmentioning

confidence: 99%

Detecting Individual Tree Attributes and Multispectral Indices Using Unmanned Aerial Vehicles: Applications in a Pine Clonal Orchard

Gallardo-Salazar

Pompa-García

2020

Remote Sensing

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“…The output of UAV photogrammetry is typically a map or 3D model of a real-world object [7]. Many products can be extracted by aerial imagery, including surface models, orthophotos, 3D building models, contour maps, and volumetric surveys [8]. A drone-based technique for topographic analysis has better accuracy than satellite remote sensing, which has limited resolution and quality depending on various factors, resulting in discontinuities in obtaining correct land information.…”

Section: Introductionmentioning

confidence: 99%

Individual Tree Crown Detection Using UAV Orthomosaic

Tahar

Asmadin

Sulaiman

et al. 2021

Eng. Technol. Appl. Sci. Res.

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Unmanned Aerial Vehicles (UAVs) are increasingly used in forestry as they are economical and flexible. This study aims to present the advantages of the drone photogrammetry method in collecting individual tree crowns, as individual tree crown detection could deliver essential ecological and economic information. The referred accuracy for individual tree crown extraction is 79.2%. Only crowns that were clearly visible were selected and manually delineated on the image because the distribution of the true crown size is significantly different from the segmented crowns. The aim of this study is to investigate UAVs orthomosaics in individual tree crown detection. The objectives of this study are to produce the orthomosaic of tree crown extraction mapping using the Pix4D software and analyze the tree crowns using tree crown delineation and the OBIA algorithm. Data processing involves the processing of aerial images using Pix4Dmapper. Automatic tree crown detection involves a tree crown delineation algorithm and OBIA operations to process the tree crown extraction. The crown delineation algorithm and OBIA algorithm operation will be compared to the actual tree crown measurement in terms of diameter and area. The tree crown delineation method obtained a 0.347m mean diameter difference from the actual tree crown diameter, while the OBIA approach obtained 4.98m. The tree crown delineation method obtained 97.26% of the actual tree crown area, while OBIA obtained 91.74%.

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“…UAV images processing software has taken greats progress toward making it easier to use and to reduce the need for human intervention [8][9][10]. UAVs aerial images can be processed using conventional photogrammetric methods or software from the field of computer vision (CV).…”

Section: Introductionmentioning

confidence: 99%

Study on Using Single UAV’s image for Extraction Measurement of Flat Area

AL-Qadri

Cheng

2020

E3S Web Conf.

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A new technology Unmanned Aerial Vehicles (UAV), is increasingly used by land surveyors for various applications. CV software for processing drone images has made great strides in making it easier to use and reducing the need for human intervention. CV method relies on tie point extraction from a set of overlapping images, which used to generate a model for the area of interest. However, using this technique to process large areas at an acceptable resolution requires huge photos and significant computer resources. Therefore, this study aims to assess the measurement accuracy that can be obtained from a single UAV image, taking into account the accuracy and time consumption. Firstly, the multirotor UAV was used to capture the ground at a certain altitude. Then the data were processed using two software packages. The outcomes of both software were compared against actual data for accuracy assessment. The results show that both processing methods provide excellent accuracy result; the ground resolution is within the range of 0.2~3.7cm\pixel, which comply with international standards. In conclusion, this study demonstrates the feasibility of using high accuracy UAV image to extract the measurement of a flat area with reliable accuracy in a short time.

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Accuracy of Orthomosaic Generated by Different Methods in Example of UAV Platform MUST Q

Cited by 16 publications

References 5 publications

Detecting Individual Tree Attributes and Multispectral Indices Using Unmanned Aerial Vehicles: Applications in a Pine Clonal Orchard

Detecting Individual Tree Attributes and Multispectral Indices Using Unmanned Aerial Vehicles: Applications in a Pine Clonal Orchard

Individual Tree Crown Detection Using UAV Orthomosaic

Study on Using Single UAV’s image for Extraction Measurement of Flat Area

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