Napredna pretraga

Pregled bibliografske jedinice broj: 1047230

Impact of UAS Image Orientation on Accuracy of Forest Inventory Attributes


Jurjević, Luka; Gašparović, Mateo; Simic Milas, Anita; Balenović, Ivan
Impact of UAS Image Orientation on Accuracy of Forest Inventory Attributes // Remote Sensing, 12 (2020), 3; 404, 19 doi:10.3390/rs12030404 (međunarodna recenzija, članak, znanstveni)


Naslov
Impact of UAS Image Orientation on Accuracy of Forest Inventory Attributes

Autori
Jurjević, Luka ; Gašparović, Mateo ; Simic Milas, Anita ; Balenović, Ivan

Izvornik
Remote Sensing (2072-4292) 12 (2020), 3; 404, 19

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Unmanned Aerial System (UAS) ; photogrammetry ; Structure from Motion (SfM) ; plot-level Lorey’s mean height ; hold-out validation ; leave-one-out-cross validation ; pedunculate oak (Quercus robur L.)

Sažetak
The quality and accuracy of Unmanned Aerial System (UAS) products greatly depend on the methods used to define image orientations before they are used to create 3D point clouds. While most studies were conducted in non- or partially-forested areas, a limited number of studies have evaluated the spatial accuracy of UAS products derived by using different image block orientation methods in forested areas. In this study, three image orientation methods were used and compared: (a) the Indirect Sensor Orientation (InSO) method with five irregularly distributed Ground Control Points (GCPs) ; (b) the Global Navigation Satellite System supported Sensor Orientation (GNSS-SO) method using non- Post-Processed Kinematic (PPK) single- frequency carrier-phase GNSS data (GNSS-SO1) ; and (c) using PPK dual- frequency carrier-phase GNSS data (GNSS-SO2). The effect of the three methods on the accuracy of plot-level estimates of Lorey’s mean height (HL) was tested over the mixed, even-aged pedunculate oak forests of Pokupsko basin located in Central Croatia, and validated using field validation across independent sample plots (HV), and leave-one-out cross-validation (LOOCV). The GNSS-SO2 method produced the HL estimates of the highest accuracy (RMSE%: HV = 5.18%, LOOCV = 4.06%), followed by the GNSS-SO1 method (RMSE%: HV = 5.34%, LOOCV = 4.37%), while the lowest accuracy was achieved by the InSO method (RMSE%: HV = 5.55%, LOOCV = 4.84%). The negligible differences in the performances of the regression models suggested that the selected image orientation methods had no considerable effect on the estimation of HL. The GCPs, as well as the high image overlaps, contributed considerably to the block stability and accuracy of image orientation in the InSO method. Additional slight improvements were achieved by replacing single-frequency GNSS measurements with dual-frequency GNSS measurements and by incorporating PPK into the GNSS-SO2 method.

Izvorni jezik
Engleski

Znanstvena područja
Geodezija, Šumarstvo



POVEZANOST RADA


Projekt / tema
HRZZ-IP-2016-06-7686 - Uporaba podataka daljinskih istraživanja dobivenih različitim 3D optičkim izvorima u izmjeri šuma (Ivan Balenović, )

Ustanove
Geodetski fakultet, Zagreb,
Hrvatski šumarski institut, Jastrebarsko

Profili:

Avatar Url Ivan Balenović (autor)

Avatar Url Mateo Gašparović (autor)

Avatar Url Luka Jurjević (autor)

Citiraj ovu publikaciju

Jurjević, Luka; Gašparović, Mateo; Simic Milas, Anita; Balenović, Ivan
Impact of UAS Image Orientation on Accuracy of Forest Inventory Attributes // Remote Sensing, 12 (2020), 3; 404, 19 doi:10.3390/rs12030404 (međunarodna recenzija, članak, znanstveni)
Jurjević, L., Gašparović, M., Simic Milas, A. & Balenović, I. (2020) Impact of UAS Image Orientation on Accuracy of Forest Inventory Attributes. Remote Sensing, 12 (3), 404, 19 doi:10.3390/rs12030404.
@article{article, year = {2020}, pages = {19}, DOI = {10.3390/rs12030404}, chapter = {404}, keywords = {Unmanned Aerial System (UAS), photogrammetry, Structure from Motion (SfM), plot-level Lorey’s mean height, hold-out validation, leave-one-out-cross validation, pedunculate oak (Quercus robur L.)}, journal = {Remote Sensing}, doi = {10.3390/rs12030404}, volume = {12}, number = {3}, issn = {2072-4292}, title = {Impact of UAS Image Orientation on Accuracy of Forest Inventory Attributes}, keyword = {Unmanned Aerial System (UAS), photogrammetry, Structure from Motion (SfM), plot-level Lorey’s mean height, hold-out validation, leave-one-out-cross validation, pedunculate oak (Quercus robur L.)}, chapternumber = {404} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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