%PDF-1.4 % 1 0 obj << /Type /Pages /Count 2 /Kids [ 2 0 R 129 0 R ] >> endobj 2 0 obj << /Type /Page /Parent 1 0 R /Resources << /ProcSet [ /PDF /Text /ImageB /ImageC /ImageI ] /Font << /QuickPDFFf5e0c6da 76 0 R /QuickPDFF112065cc 128 0 R >> >> /Contents [ 5 0 R ] /MediaBox [ 0 0 595.2756 841.8898 ] /CropBox [ 0 0 595.2756 841.8898 ] >> endobj 3 0 obj << /Type /Catalog /Pages 1 0 R /Metadata 131 0 R >> endobj 4 0 obj << /Producer (Debenu Quick PDF Library 11.15 \(www.debenu.com\)) /Creator (Debenu Quick PDF Library 11.15 \(www.debenu.com\)) /CreationDate (D:20220919115636+02'00') /ModDate (D:20220919115642+02'00') >> endobj 5 0 obj << /Length 3955 /LC /iSQP >> stream 0 Tr /QuickPDFF112065cc 14 Tf 0 0 0 rg 100 Tz 0 Tw 0 Tc 0 Ts BT 1 0 0 1 66.4558 770.8329 Tm (Assessment of the Possibility of Using the SAND Library for Processing Point)Tj 1 0 0 1 59.4488 752.1709 Tm (Clouds in the Big Data Environment on the Example of UAV-LiDAR Data for a)Tj 1 0 0 1 278.5908 733.5089 Tm (Forest)Tj ET /QuickPDFF112065cc 11 Tf 0 0 0 rg BT 1 0 0 1 48.1688 703.0447 Tm (Dorota Marczykowska, Jaroslaw Czajka, Wojciech Ostrowski and Magdalena Pilarska-Mazurek \(Poland\))Tj ET /QuickPDFF112065cc 11 Tf 0 0 0 rg BT 1 0 0 1 56.6929 661.0148 Tm 14.663 TL (Key words: )' ET /QuickPDFFf5e0c6da 11 Tf 0 0 0 rg BT 1 0 0 1 141.7323 661.0148 Tm 14.454 TL (Engineering survey; Geoinformation/GI; Laser scanning; Remote sensing; Data)' (processing tools; Point clouds; Forestry; UAV-LiDAR)' ET /QuickPDFF112065cc 11 Tf 0 0 0 rg BT 1 0 0 1 56.6929 618.4951 Tm 14.663 TL (SUMMARY)' ET /QuickPDFFf5e0c6da 10 Tf 0 0 0 rg BT 1 0 0 1 56.6929 163.8497 Tm 13.14 TL (__________________________________________________________________________________________)' ()' (Assessment of the Possibility of Using the SAND Library for Processing Point Clouds in the Big Data Environment on)' (the Example of UAV-LiDAR Data for a Forest \(11679\))' (Dorota Marczykowska, Jaroslaw Czajka, Wojciech Ostrowski and Magdalena Pilarska-Mazurek \(Poland\))' ()' (FIG Congress 2022)' (Volunteering for the future - Geospatial excellence for a better living)' (Warsaw, Poland, 1115 September 2022)' ET /QuickPDFFf5e0c6da 11 Tf 0 0 0 rg BT 1 0 0 1 56.6929 590.1487 Tm 14.454 TL (UAV-LiDAR surveys deliver very dense point clouds, with over 300 pts/m2. This density is close to that of)' (terrestrial laser scanning \(TLS\) and allows to use UAV data in almost the same way as TLS in some)' (applications. One of the application areas is forest management, where high density of point cloud enables)' (automation of many forest inventory and planning processes, but TLS surveys are nearly impossible to do)' (due to dense vegetation and very low efficiency of measurements. Together with the Dragonfly Vision)' (company, we are carrying out a project in which a solution using UAV-LiDAR data for exactly that purpose)' (is created. Such a dense point cloud for large areas means billions of points to process. It requires a lot of)' (computing power. A tool combining GPU and the benefits of distributed environment has very high potential)' (to improve analysis of this kind of data. SAND library is a part of CENAGIS project, developed by the)' (Faculty of Geodesy and Cartography at the Warsaw University of Technology. This python library allows to)' (analyze and process point clouds using GPU and is designed to work with pySpark. Appropriate experiments)' (were carried out to determine the possibility of using SAND library and the calculation time needed for large)' (data sets. The influence of the set size on the total computation time was investigated. The possibilities of)' (creating canopy height model \(CHM\) and determining forest structural attributes were also checked. In this)' (study multiple ways to create height model using SAND were tested, such as: maximal raster value, planes)' (fitting, and pit-free-like approach with processing data in layers. Capability of determining single tree)' (features based on point cloud, like height or 2D area of canopys extent was also investigated. The library)' (implements few clustering methods and statistics for clusters, which can be used to analyze individual trees.)' (All these functions show not only that manipulating a point cloud of forest by SAND and pySpark is)' (possible, but also that these instruments together enable creation of comprehensive tools for foresters. These)' (tools are able to process data obtained for large areas in a reasonable time. Thanks to the variety of methods,)' (algorithms and the availability of a wide parameterization, SAND library also provides an excellent )' ET endstream endobj 6 0 obj << /Length 485 /Filter /FlateDecode >> stream xMSK%1)'y,m'ͦ `*-J#A%BF_x5gaN$X$79jlzR6;Vb1)ꆮe5U'Y I%($Ҝs*x5n(VXAH MhA{kq]'|=ڛ+X8ʞ$xmRJ)5_1,Ӂ*N1$r#R] D6@! o8jO(W{[(n?:{9މm(|꩟l \E} H +yCD dl<eܡN& .Fj[-F{u+JF3(u=g<뱅ZE0gpY3 :һȰCyC-adr*:[ҖAQp4 ;aaT}18 ¼-8LPsΣBj=q*ߖ{>r endstream endobj 7 0 obj << /Length 316 /Filter /FlateDecode >> stream xMRKnCAۿSpk`y^Uu[jIɒT%C/:b}Rx\%=
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