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<!doctype html> <html lang="en">
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<head>
<meta charset="utf-8">
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<title>Kosice 2019 Summer School Lecture</title>
<meta name="description" content="Slides for Vienna 2018 presentation">
<meta name="author" content="Helena Mitasova">
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</head>
<body>
<div class="reveal">
<!-- Any section element inside of this container is displayed as a slide -->
<div class="slides">
<section>
<!--<h4 style="color: #707070">AAS 2018</h4>-->
<h2 style="margin-top: 0.0em;color: #000">
Exploring changing landscapes with dynamic visualizations and tangible interaction in GRASS GIS and with Tangible landscape </h2>
<p>
<h4 style="color: #707070">Helena Mitasova</h4>
<!--<img height="50px" style="margin-top: 2em" src="img/cgaBlack.png">
<h5 style="color: #000">North Carolina State University</h5>-->
<p>
<img src="img/hofierka.jpg" height="120">
<img src="img/petrasova.jpg" height="120">
<img src="img/vpetras.jpg" height="120">
<img src="img/baharmon.jpg" height="120">
<img src="img/payam.jpg" height="120">
<img src="img/Justyna_Jeziorska.jpg" height="120">
</p>
<p><small>J.Hofierka, A.Petrasova, V. Petras, B.Harmon, P.Tabrizian, J.Jeziorska</small>
<p><img src="img/cgaBlack.png" height="40"> <img src="img/4x1white.jpg" height="25">
</section>
<section>
<h3>Dynamic Digital Earth </h3>
<ul>
<li class="fragment">Digital Earth vision is now a reality:
Earth is mapped at many spatial and temporal scales from global by satellites to local microscale by drones
<li class="fragment">Only fraction of collected data is used to full potential
<li class="fragment">Geospatial analytics and modeling is deployed to use these data
to improve disaster response, water and food security, everyday life and well being
<li class="fragment">Geospatial surface modeling - foundation for many methods and tools
</ul>
</section>
<section>
<h2>The beginnings</h2>
</section>
<!--
<section>
<h3>Pioneering concept of dynamic spatial surfaces</h3>
<p>Waldo Tobler:
<p>geospatial phenomena as fields - scalar, vector and tensor
<p>
<img height="330" src="img/surfaces/Tobler_govfiscal.jpg">
<img height="330" src="img/surfaces/Tobler_pressuretomodesurface.jpg">
<p><small>Images from Professor Tobler's slides</small></p>
</section>
-->
<section>
<h3>Theoretical foundations: terrain analysis</h3>
<p>Terrain as continuous field <i>z=f(x,y)</i>,
<br>represented by isolines, manually deriving secondary fields
<p>
<img src="img/surfaces/Krcho_krivosti.jpg" height="380">
<p> <small>Profle Curvature isolines (Krcho 1973), </small>
</section>
<!-- <section>
<section>
<h3>Computational foundations: digital terrain models</h3>
<p>EuroCarto III Graz, 1984: Krcho,J., H.Mitasova, E.Micietova, Theoretical concept and data structures of complex digital terrain model and its interdisciplinary applications
<p>
<img src="img/surfaces/TINgrassnviz2.jpg" height="170">
<br> <img src="img/EurocartoGraz3.jpg" height="200">
<img src="img/EurocartoGraz2.jpg" height="200">
<br><small>Thank you for supporting our participation 34 years ago</small>
</section>
<h3>Pioneering dynamic geospatial surfaces</h3>
<p> <img height="300" src="img/surfaces/Tobler_MapMachine.jpg">
<img height="300" src="img/surfaces/Tobler_thankyou.jpg">
</section> -->
<section>
<h3>Digital terrain modeling with splines</h3>
<p>Spatial interpolation by Regularized Spline with Tension (RST) method:
from scattered points to regular grids, with simultaneous
derivation of topographic parameters
<p>
<img src="img/surfaces/curvature1993.jpg" height="400">
<br> <small>Profle Curvature draped over mesh surface, (Mitasova, Mitas, Hofierka 1993)</small>
</section>
<section>
<h3>Implementation in open source GRASS GIS</h3>
<p>Method became available to broad community,
many developers improved the code
<p>Surface with changing tension animation: tension helps to control overshoots
<p><img class="stretch" src="img/surfaces/tension.gif">
<p><small>25 years: GRASS4.1 s.surf.tps, v.surf.tps, v.surf.rst; GRASS7.4; contributions of 8+ developers</small>
</section>
<section>
<h3>Implementation in open source GRASS GIS</h3>
<p>Quadtree-based segmentation made it applicable to large point data sets
<p>Simultaneous topographic analysis: slope, aspect, curvatures
<p><img height="320" src="img/surfaces/quadtrees.png">
<img height="330" src="img/surfaces/topoanalysiscerl9803crop.gif">
</section>
<section>
<h2>Modeling and analysis of surfaces from multitemporal observations</h2>
</section>
<section>
<h3>From digitized contours to lidar point clouds</h3>
Lidar technology transformed topography mapping in 21st century
<p><img height="400" src="img/surfaces/digitized_cont2d_jr1999zoom.png">
<img height="400" src="img/surfaces/pointcloud2d_jr2009zoom.png">
<p>Do we still need interpolation?</p>
</section>
<section>
<h3>North Carolina lidar surveys</h3>
Coastal surveys started in 1996, second statewide survey just finished.
<br>Survey in 1999 included Jockey's Ridge dunes: dense, noisy scattered point cloud
<p><img height="440" src="img/surfaces/lidstorast1m.jpg">
</section>
<section>
<h3>North Carolina lidar surveys</h3>
Coastal surveys started in 1996, second statewide survey just finished.
<br>Survey in 1999 included Jockey's Ridge dunes: dense, noisy scattered point cloud
<p><img height="440" src="img/surfaces/lidstorast.jpg">
</section>
<section>
<h3>Regularized spline with tension for lidar</h3>
RST smoothing properties and quadtree segmentation
made it suitable for generating high resolution elevation models from millions of points
<p><img height="450" src="img/surfaces/liddfdm1e.jpg">
</section>
<section>
<h3>Regularized spline with tension for lidar</h3>
By tuning the tension coupled with smoothing, we remove noise and derive topographic parameters at a desired level of detail:
<br>profile curvature and slope draped over surface with changing tension
<p><img class="stretch" src="img/surfaces/lidar_tension_curv.gif">
</section>
<!--
<section>
<h3>DEM feature extraction</h3>
<p> Dune crests were extracted from profile curvatures of DEMs spanning 44 years
<br>to quantify dune migration rates and direction
<p>
<img height="350" src="img/surfaces/rfpfig4pcurv.jpg">
<img height="350" src="img/surfaces/rfpfig4crestevol.jpg">
ADD GRAPHS linear loss of elevation since 1953, accelerating migration 3-6 m/yr,
</section>
-->
<section>
<h3>DEM time series in GRASS temporal framework</h3>
<ul>
<li>DEM time series for Jockey's Ridge dunes derived from data acquired by
<ul>
<li>photogrammetry (1974-98),
<li>lidar (1999-2018),
<li>structure from motion from UAS imagery (2016-2018)
</ul>
</ul>
<img height="100" src="img/surfaces/timeline.png">
<img height="150" src="img/surfaces/timeline3D.png">
<br>
<img height="130" src="img/surfaces/temp_plot_leeward_pt.png">
<img height="130" src="img/surfaces/temp_plot_windward_pt.png">
<br><small>Gebbert, S., Pebesma, E., 2014. A temporal GIS for field based environmental modeling. Environmental Modelling and Software 53, 1-12.</small>
</section>
<section>
<h3>DEM time series visualization</h3>
<p>Jockey's Ridge 1974 - 2017: southward migration, landform transformation
from crescentic dune to sand starved, fast moving parabolic dune
<!-- <img height="350" src="img/surfaces/jrseries.png"> -->
<img class="stretch" src="img/surfaces/jr_74_17_anim3dlgfix.gif">
</section>
<section data-animate="1,13" data-path="img/surfaces/JR_anim/JR_anim">
<h3>DEM time series visualization</h3>
</section>
<section>
<h3>Post-hurricane Mathews ripples</h3>
<p>Orthphoto from UAS survey, october 2016
<img height="500" src="img/surfaces/uas_ortho_2016small.jpg">
<br><img width="300" src="img/surfaces/scalbar.png">
</section>
<section>
<h3>Annual dynamics from Planet imagery</h3>
<p> Satellite imagery at 3m resolution, September 2017 - July 2018, captures impact of
storm in March 2018 with large ripples similar to those observed post Mathews
<p>
<iframe data-autoplay width="580" height="360" src="img/surfaces/sep17_july18.mp4" frameborder="0" allowfullscreen></iframe>
<p><small>Planet: world’s largest constellation of Earth-imaging (micro) satellites providing daily observations
for entire Earth at 3m resolution</small>
</section>
<section>
<h3>Contours time series</h3>
Contours capture the landform change but they are hard to read
<br> <img height="260" src="img/surfaces/jr_74_2017_16mcontour.png"> 16m
<br> <img height="230" src="img/surfaces/jr_74_2017_20mcontour.jpg"> 20m
<!-- <img height="130" src="img/surfaces/jr16/legend.png"> -->
</section>
<section >
<h3>Space-Time cube visualization</h3>
<p>DEM time series is converted into space-time voxel model in TGRASS and evolution of a contour
is represented as isosurface: 16m and 20m </p>
<img height="400" src="img/surfaces/jr16/animation.gif">
<!--<img src="img/jr18/animation.gif"> -->
<img height="400" src="img/surfaces/jr20/animation.gif">
</section>
<section>
<h3>Jockey's Ridge evolution analysis</h3>
<p>DEM time series: evolution quantified using TGRASS and surface analysis tools
<ul>
<li>linear trend in loss of peak elevation at 0.3m per year
<li>accelerating horizontal migration from 3m/yr to 6m/yr
<li>total sand volume is stable, but the <strong>core</strong> (sand that has not moved) is shrinking
<li>vegetation increased, but dune still kills trees on the leeward side
<li>management challenges: dynamic feature confined to static park boundaries
</ul>
<p>
<!--<img height="150" src="img/surfaces/core_2017_cut6.jpg">-->
<img height="200" src="img/surfaces/jr_74_17_cut3.jpg">
<img height="200" src="img/surfaces/peakregression_1950_2017.png">
</section>
<section>
<h3>Jockey's Ridge story</h3>
<p>The 43 m high dune was a transient landform
<p><img height="200" src="img/surfaces/JR_photosevol_17_50_08.jpg">
<br>
<img height="220" src="img/surfaces/Kittytrees1900.jpg">
<img height="220" src="img/surfaces/JR_2017_burriedtrees.jpg">
<p><small>Dune in early 1900 and in 2008, 2016</small>
</section>
<section>
<h2>From observations to modeling of processes</h2>
<p>
<br>
<img height="140" src="img/surfaces/yakima_panorama_1s.jpg">
</section>
<section>
<h3>Water flow, soil erosion, storm surge</h3>
<p>Land surface controls water and sediment flow across landscapes
<p>Critical processes and impacts: surface runoff, flooding, storm surge, soil erosion
<p><img height="220" src="img/surfaces/secrefstorm2006Alberto.jpg">
<img height="220" src="img/surfaces/secref8-8-03ditch.jpg">
<img height="220" src="img/surfaces/IreneRodanthe.jpg">
</section>
<section>
<h3>Water flow</h3>
<p>Using surface gradients to compute flow accumulation:
Evolution of water depth over complex terrain
under steady rainfall and uniform surface conditions
<p>
<!--<img height="180" src="img/surfaces/elevationnc1_f.gif"> it is more confusing than helpful-->
<img height="370" src="img/surfaces/water.gif">
<p>Geometry-based solution
</section>
<section>
<h3>Sediment transport</h3>
<p>Combining flow accumulation and slope:
<br>Evolution of sediment transport capacity
<p>
<img height="370" src="img/surfaces/lsfac.gif">
<p>Geometry-based solution
</section>
<section>
<h3>Erosion and deposition</h3>
<p>Net erosion and deposition computed as change in sediment transport capacity:
<br>simple to compute in GIS, combined with parameters for landcover and soils
<p> <img height="350" src="img/surfaces/p5ed_f.gif">
<small>Unit Stream Power Based Erosion-Deposition,
Mitasova, H., J. Hofierka, M. Zlocha, L.R. Iverson, 1996</small>
</section>
<section>
<h3>Path sampling of continuous fields</h3>
<p> Next step: robust solution of shallow water flow equations and process-based sediment transport
<p>
<img width="45%" src="img/surfaces/fanimwalk.gif">
<img width="45%" src="img/surfaces/fanimhhcolp.gif">
<p>Solver based on duality of particles and fields works for noisy surfaces, captures ponding in depressions.
<p><small>Mitas and Mitasova, 1998; Mitasova, Thaxton, Hofierka, McLaughlin, Moore, Mitas, 2005</small>
</section>
<!--
<section>
<h3>Example application</h3>
<p>CC middle school? Germany field?
<p> <img width="25%" src="img/surfaces/water01dsmall.gif">
<img width="25%" src="img/surfaces/wrrwater01.jpg">
<img width="25%" src="img/surfaces/wrrwaterdc.jpg">
<img width="25%" src="img/surfaces/wrrwaterdc.jpg">
</section>
-->
<section>
<h3>Modeling surface runoff and erosion/deposition</h3>
<p>Impact of construction on erosion and deposition, limitations of stream buffer protection
<p> <img width="90%" src="img/surfaces/middleschool_scen.jpg">
</section>
<section>
<h3>High resolution water flow</h3>
<p> Street level modeling of surface runoff: lidar-based DEM
and path sampling
<p>
<img height="450" src="img/surfaces/carywater_ortho_lg.jpg">
<img height="450" src="img/surfaces/water_stormdrains_zoom.jpg">
</section>
<section>
<h3>Ultra-high resolution water flow modeling</h3>
<p> UAS-based surveys: cm-resolution DEMs
<br>Path sampling simulations capture impact of microtopography: tillage
<p>
<img height="450" src="img/surfaces/uas_03_depth.gif">
</section>
<section>
<h3>Beyond bare ground</h3>
<ul>
<li>updating urban topography
<li>lidar and geomorphons for individual trees extraction for viewscape analysis
<li>lidar point clouds voxel-based analysis - vegetation structure and patch index
</section>
<section>
<h3>Changes in urban topography</h3>
<p>
UAS-based surveys: efficient updates of urban topography
<p>
<p><small>2015 lidar updated with 2018 UAS data: forested area replaced by a new school</small>
<p>
<img height="360" src="img/surfaces/uas_lidar_update.gif">
</section>
<section>
<h3>Updating lidar DSM using UAS based SfM</h3>
<p>2015 lidar updated with 2018 UAS data for area on Centennial Campus where two new buildings were built,
trees cut and stormwater control is being updated
<p>
<img height="350" src="img/surfaces/centennial_uasupdate.gif">
<p>2015 lidar, UAS-based DSM is inserted, tilt identified and corrected
</section>
<section>
<h3>Urban topography: UAS updates</h3>
<p>3D model of area with new buildings and removed trees
<p>
<img height="450" src="img/surfaces/CC_uas2018_full3D.jpg">
</section>
<!--
<section>
<h3>Beyond bare earth surface: vegetation</h3>
Geomorphons (Jasiewicz, Stepinski 2013) for vegetation surfaces from lidar, UAS
<br><small>individual tree detection and trunk modeling (Tabrizian et al. 2018)</small>
<br>
<img height="250" src="img/surfaces/geomorphon.png">
<img height="250" src="img/surfaces/trunk_replace.jpg">
<br> <small>row crop growth analysis</small>
<br>
<img height="170" src="img/surfaces/geomorph_cropsurface_zoom.jpg">
</section>
-->
<section>
<h3>Individual tree detection from lidar</h3>
<p><small>Payam Tabrizian PhD research project</small>
<ul>
<li>Geomorphons (Jasiewicz, Stepinski 2013) applied to vegetation surface:
summits represent individual trees.
<li>Detected deciduous trees are replaced by modeled trunks to improve accuracy of viewscape analysis
</ul>
<p>
<img height="260" src="img/surfaces/geomorphon.png">
<img height="260" src="img/surfaces/trunk_replace.jpg">
</section>
<section>
<h3>Improved viewshed extent</h3>
<p><small>Payam Tabrizian PhD research project</small>
<p>Viewshed based on bare ground DEM, lidar DSM, and modeled trunks
<p>
<!--<img height="160" src="img/surfaces/viewscape_DSM.jpg">-->
<img height="180" src="img/surfaces/viewscape_DEM.jpg">
<img height="180" src="img/surfaces/thick_view.jpg">
<img height="180" src="img/surfaces/thin_view.jpg">
<img height="180" src="img/surfaces/view_photos.png">
</section>
<section>
<h3>Beyond bare earth surface: urban topography</h3>
Solar irradiation during summer solstice at NCSU Centennial Campus
<p>
<img height="430" src="img/surfaces/summer_solstice_centennial.gif">
</section>
<section>
<h3>Beyond bare earth surface: vegetation voxel models</h3>
Generalized Fragmentation Index:
slice of raw point cloud and slice of fragmentation index 3D raster
<p>
<img height="250" src="img/surfaces/profiles_points_and_ff.png">
<img height="200" src="img/surfaces/profile3d.png">
</section>
<section>
<h3>Beyond bare earth surface: vegetation voxel models</h3>
Slicing through fragmentation index 3D raster
<p>
<img height="400" src="img/surfaces/voxels_vegetation_anim.gif">
<small>Petras, V., D. J. Newcomb, and H. Mitasova. 2017. Generalized 3D fragmentation index derived from lidar point clouds. In: Open Geospatial Data, Software and Standards 2(9). DOI 10.1186/s40965-017-0021-8 </small>
</section>
<section>
<h2>Tangible interface for surface analysis and process modeling</h2>
</section>
<section>
<h3>Tangible Landscape</h3>
<p> Bringing people together around GIS: Tangible user interface for GRASS GIS
<p>Designed to make working with geospatial data and simulations engaging, and fun</p>
<p>
<img height="180" src="img/surfaces/tangible_landscape_compcrop.jpg">
<p>
Petrasova, A. et al. (2018). Tangible Modeling with Open Source GIS. Second edition. Springer International Publishing.
<a href="https://doi.org/10.1007/978-3-319-89303-7">https://doi.org/10.1007/978-3-319-89303-7</a>
</section>
<section>
<h3>How does it work?</h3>
<iframe data-autoplay width="50%" height="330" src="https://www.youtube.com/embed/Cd3cCQTGer4?rel=0&showinfo=0&loop=1&playlist=Cd3cCQTGer4" frameborder="0" allowfullscreen></iframe>
<img height=380 src="img/surfaces/rendered_diagram_2.png">
<p>Tangible Landscape couples a digital and a physical model through a continuous cycle of 3D scanning, geospatial modeling, and projection</p>
</section>
<section>
<h3>Interactions</h3>
<p><img height="450" src="img/surfaces/tl_interactions_all.jpg">
</section>
<section>
<h3>Coupling with 3D rendering</h3>
<p><img height="450" src="img/surfaces/process4.png">
</section>
<section>
<h3>Design scenario analysis</h3>
<p><img height="480" src="img/surfaces/process7.png">
</section>
<section>
<h3>Tangible Landscape for designers and researchers</h3>
<p>
<img height="300px" src="img/surfaces/tl_planting_3.jpg">
<img height="300px" src="img/surfaces/TL_scientists.jpg">
</section>
<section>
<h3>Tangible Landscape for education</h3>
<p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/jX6FurEeW28?rel=0" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
<img height="260" src="img/surfaces/collaboration2.JPG">
</section>
<section>
<h3>Tangible Landscape for communities</h3>
Platform for decision-making and science communication
where people of different backgrounds can interact.
<p>
<img height="220px" src="img/surfaces/bhigames_composite.jpg">
<br>Tangible Landscape website:
<a href="tangible-landscape.github.io">tangible-landscape.github.io</a>
<br>TL wiki: github.com/tangible-landscape/grass-tangible-landscape/wiki
</section>
<section>
<h3>Open Science</h3>
<p>Developing open source software and contributing to OSGeo projects:
<p>GRASS GIS <a href="https://grass.osgeo.org/">https://grass.osgeo.org/</a>
<p>Tangible Landscape <a href="https://tangible-landscape.github.io">tangible-landscape.github.io</a>
<p>Open access educational material:
<p>NCSU GeoForAll Lab Courses and Workshops
<a href="https://geospatial.ncsu.edu/geoforall/courses.html">https://geospatial.ncsu.edu/geoforall/courses.html</a>
<p><img height="280" src="img/surfaces/geovizlab_people2018.jpg">
<br><a href="https://geospatial.ncsu.edu/geoforall/publications.html">NCSU GeoForAll publications</a>
</section>
<section>
<h3>Thank You!</h3>
<p>Thank you all for your contributions to the field - data, methods, algorithms and tools,
that helped to bring the discipline to its current thriving state </p>
<p>
<iframe data-autoplay width="700" height="350" src="https://www.youtube.com/embed/Uje8ORyhBaQ?rel=0&showinfo=0&loop=1&playlist=Uje8ORyhBaQ" frameborder="0" allowfullscreen></iframe>
</section>
<section>
<h3>Appendix</h3>
Links to related talks:
TL webinar, GRASS7, Lidar, ICC talk etc.
<p>
discuss future: data for erosion to captiure the dynamics like for JR to improve the models, high accuracy is needed
higher intensity rainfalls lead to increased erosion renewing interest in erosion and sediment contriol
</section>
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