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@article{1679276,
author = {Cibula, Róbert and Sackov, I},
article_location = {WARSAW},
article_number = {3},
doi = {http://dx.doi.org/10.2478/forj-2020-0004},
keywords = {geo-visualization; WebGL; level of details; Forest inventory; airborne LiDAR},
language = {eng},
issn = {2454-034X},
journal = {CENTRAL EUROPEAN FORESTRY JOURNAL},
note = {Žádný z autorů nemá afiliaci k MU.},
title = {An integrated framework for Web-based visualisation of forest resources estimated from remote sensing data},
volume = {66},
year = {2020}
}
TY - JOUR
ID - 1679276
AU - Cibula, Róbert - Sackov, I
PY - 2020
TI - An integrated framework for Web-based visualisation of forest resources estimated from remote sensing data
JF - CENTRAL EUROPEAN FORESTRY JOURNAL
VL - 66
IS - 3
SP - 170-176
EP - 170-176
PB - SCIENDO
SN - 2454034X
N1 - Žádný z autorů nemá afiliaci k MU.
KW - geo-visualization
KW - WebGL
KW - level of details
KW - Forest inventory
KW - airborne LiDAR
N2 - Advanced remote sensing technologies has recently become an effective tool for monitoring of forest ecosystems. However, there is a growing need for online dissemination of geospatial data from these activities. We developed and assessed a framework which integrates (1) an algorithm for estimation of forest stand variables based on remote sensing data and (2) a web-map application for 2D and 3D visualisation of geospatial data. The performance of proposed framework was assessed in a Forest Management Unit Viglas (Slovakia, Central Europe) covering a total area of 12,472 ha. The mean error of remote sensing-based estimations of forest resources reached values of 16.4%, 12.1%, -26.8%, and -35.4% for the mean height, mean diameter, volume per hectare, and trees per hectare, respectively. The web-map application is stable and allows real-time visualization of digital terrain model, aerial imagery, thematic maps used in forestry or geology, and 968,217 single trees at forest management unit level.
ER -
CIBULA, Róbert a I SACKOV. An integrated framework for Web-based visualisation of forest resources estimated from remote sensing data. \textit{CENTRAL EUROPEAN FORESTRY JOURNAL}. WARSAW: SCIENDO, 2020, roč.~66, č.~3, s.~170-176. ISSN~2454-034X. Dostupné z: https://dx.doi.org/10.2478/forj-2020-0004.
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