Napredna pretraga

Pregled bibliografske jedinice broj: 973930

A novel automated method for the improvement of photogrammetric DTM accuracy in forests


Gašparović, Mateo; Simic Milas, Anita; Seletković, Ante; Balenović, Ivan
A novel automated method for the improvement of photogrammetric DTM accuracy in forests // Šumarski list : znanstveno-stručno i staleško glasilo Hrvatskoga šumarskog društva, 142 (2018), 11-12; 567-577 doi:10.31298/sl.142.11-12.1 (međunarodna recenzija, članak, znanstveni)


Naslov
A novel automated method for the improvement of photogrammetric DTM accuracy in forests

Autori
Gašparović, Mateo ; Simic Milas, Anita ; Seletković, Ante ; Balenović, Ivan

Izvornik
Šumarski list : znanstveno-stručno i staleško glasilo Hrvatskoga šumarskog društva (0373-1332) 142 (2018), 11-12; 567-577

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

Ključne riječi
digital terrain model (DTM) ; vertical accuracy ; LiDAR ; lowland forest

Sažetak
Accuracy of a Digital Terrain Model (DTM) in a complex forest environment is critical and yet challenging for accurate forest inventory and management, disaster risk analysis, and timber utilization. Reducing elevation errors in photogrammetric DTM (DTMPHM), which present the national standard in many countries worldwide, is critical, especially for forested areas. In this paper, a novel automated method to detect the errors and to improve the accuracy of DTMPHM for the lowland forest has been presented and evaluated. This study was conducted in the lowland pedunculate oak forest (Pokupsko Basin, Croatia). The DTMPHM was created from three- dimensional (3D) vector data collected by aerial stereo-photogrammetry in combination with data collected from existing maps and field surveys. These data still present the national standard for DTM generation in many countries, including Croatia. By combining slope and tangential curvature values of raster DTMPHM, the proposed method developed in open source Grass GIS software automatically detected 91 outliers or 3.2% of the total number of source points within the study area. Comparison with a highly accurate LiDAR DTM confirmed the method efficiency. This was especially evident in two out of three observed subset areas where the root mean square error (RMSE) values decreased for 8% in one and 50% in another area after errors elimination. The method could be of great importance to other similar studies for forested areas in countries where the LiDAR data are not available.

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,
Šumarski fakultet, Zagreb

Citiraj ovu publikaciju

Gašparović, Mateo; Simic Milas, Anita; Seletković, Ante; Balenović, Ivan
A novel automated method for the improvement of photogrammetric DTM accuracy in forests // Šumarski list : znanstveno-stručno i staleško glasilo Hrvatskoga šumarskog društva, 142 (2018), 11-12; 567-577 doi:10.31298/sl.142.11-12.1 (međunarodna recenzija, članak, znanstveni)
Gašparović, M., Simic Milas, A., Seletković, A. & Balenović, I. (2018) A novel automated method for the improvement of photogrammetric DTM accuracy in forests. Šumarski list : znanstveno-stručno i staleško glasilo Hrvatskoga šumarskog društva, 142 (11-12), 567-577 doi:10.31298/sl.142.11-12.1.
@article{article, year = {2018}, pages = {567-577}, DOI = {10.31298/sl.142.11-12.1}, keywords = {digital terrain model (DTM), vertical accuracy, LiDAR, lowland forest}, journal = {\v{S}umarski list : znanstveno-stru\v{c}no i stale\v{s}ko glasilo Hrvatskoga \v{s}umarskog dru\v{s}tva}, doi = {10.31298/sl.142.11-12.1}, volume = {142}, number = {11-12}, issn = {0373-1332}, title = {A novel automated method for the improvement of photogrammetric DTM accuracy in forests}, keyword = {digital terrain model (DTM), vertical accuracy, LiDAR, lowland forest} }

Časopis indeksira:


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


Citati