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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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