Tangible Modeling with Open Source GIS

Petrášová, Anna; Harmon, Brendan; Petras, Vaclav; Mitášová, Helena

doi:10.1007/978-3-319-25775-4

Cited by 42 publications

(26 citation statements)

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“…In the second case study we apply presented method to merge a lidar-based DEM with a georeferenced, virtual DEM obtained by scanning a physical, scaled model in Tangible Landscape environment [22]. Tangible Landscape couples a malleable physical model with a digital landscape through a cycle of real-time scanning, analysis, and projection.…”

Section: Merging Lidar-and Kinect-based Demsmentioning

confidence: 99%

“…We manually built a physical model from polymerenriched sand of a small section of the area used in the first case study based on the 2015 lidar data at 1 : 420 scale and 4 times vertical exaggeration, to facilitate scanning and interaction. We used projected contours and colorcoded difference of the scanned and real DEM [22,Chapter 4] while building the model to ensure its sufficient accuracy. We then merged the lidar-based and scanned DEMs with fixed overlap width of 15 meters and ran the water flow simulation on the merged DEM over the watershed including the physical model.…”

Section: Merging Lidar-and Kinect-based Demsmentioning

confidence: 99%

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Fusion of high-resolution DEMs for water flow modeling

Petrášová

Mitášová

Petras

et al. 2017

Open geospatial data, softw. stand.

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Background: New technologies for terrain reconstruction have increased the availability of topographic data at a broad range of resolutions and spatial extents. The existing digital elevation models (DEMs) can now be updated at a low cost in selected study areas with newer, often higher resolution data using unmanned aerial systems (UAS) or terrestrial sensors. However, differences in spatial coverage and levels of detail often create discontinuities along the newly mapped area boundaries and subsequently lead to artifacts in results of DEM analyses or models of landscape processes. Methods: To generate a seamless updated DEM, we propose a generalized approach to DEM fusion with a smooth transition while preserving important topographic features. The transition is controlled by distance-based weighted averaging along the DEMs' blending overlap with spatially variable width based on elevation differences. Results: We demonstrate the method on two case studies exploring the effects of DEM fusion on water flow modeling in the context of precision agriculture. In the first case study, we update a lidar-based DEM with a fused set of two digital surface models (DSMs) derived from imagery acquired by UAS. In the second application, developed for a tangible geospatial interface, we fuse a georeferenced, physical sand model continuously scanned by a Kinect sensor with a lidar-based DEM of the surrounding watershed in order to computationally simulate and test methods for controlling storm water flow. Conclusions:The results of our experiments demonstrate the importance of seamless, robust fusion for realistic simulation of water flow patterns using multiple high-resolution DEMs.

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Section: Merging Lidar-and Kinect-based Demsmentioning

confidence: 99%

Section: Merging Lidar-and Kinect-based Demsmentioning

confidence: 99%

Fusion of high-resolution DEMs for water flow modeling

Petrášová

Mitášová

Petras

et al. 2017

Open geospatial data, softw. stand.

Self Cite

View full text Add to dashboard Cite

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“…Geospatial modelling using TUI was further successful in [36] which allowed users a flexible way to sculpt terrain as well as investigate stormwater runoff management options. The interactive control abilities of TUI were further exploited in [37] where physical objects, representative of design models, were employed to more intuitively and easily edit CAD and GIS designs [37] designations.…”

Section: Tangible User Interfacesmentioning

confidence: 99%

Explaining multi-threaded task scheduling using tangible user interfaces in higher educational contexts

Raffaele

Smith

Gemikonakli

2017

2017 IEEE Global Engineering Education Conference (EDUCON)

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“…The effort to couple a physical landscape model with GRASS GIS led to the development of the Tangible Geospatial Modeling System (Tateosian et al, 2010) and Tangible Landscape ( Fig. 1) (Petrasova et al, 2014, Petrasova et al, 2015.…”

Section: Tangible Interfaces For Gismentioning

confidence: 99%

“…The data used in this experiment are available on the Open Science Framework at osf.io/zv3t6 under the Creative Commons Zero license. (Petrasova et al, 2015).…”

Section: Code and Datamentioning

confidence: 99%

Tangible Landscape: Cognitively Grasping the Flow of Water

Harmon

Petrášová

Petras

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Complex spatial forms like topography can be challenging to understand, much less intentionally shape, given the heavy cognitive load of visualizing and manipulating 3D form. Spatiotemporal processes like the flow of water over a landscape are even more challenging to understand and intentionally direct as they are dependent upon their context and require the simulation of forces like gravity and momentum. This cognitive work can be offloaded onto computers through 3D geospatial modeling, analysis, and simulation. Interacting with computers, however, can also be challenging, often requiring training and highly abstract thinking. Tangible computing -an emerging paradigm of human-computer interaction in which data is physically manifested so that users can feel it and directly manipulate it -aims to offload this added cognitive work onto the body. We have designed Tangible Landscape, a tangible interface powered by an open source geographic information system (GRASS GIS), so that users can naturally shape topography and interact with simulated processes with their hands in order to make observations, generate and test hypotheses, and make inferences about scientific phenomena in a rapid, iterative process. Conceptually Tangible Landscape couples a malleable physical model with a digital model of a landscape through a continuous cycle of 3D scanning, geospatial modeling, and projection. We ran a flow modeling experiment to test whether tangible interfaces like this can effectively enhance spatial performance by offloading cognitive processes onto computers and our bodies. We used hydrological simulations and statistics to quantitatively assess spatial performance. We found that Tangible Landscape enhanced 3D spatial performance and helped users understand water flow.

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Tangible Modeling with Open Source GIS

Cited by 42 publications

References 0 publications

Fusion of high-resolution DEMs for water flow modeling

Fusion of high-resolution DEMs for water flow modeling

Explaining multi-threaded task scheduling using tangible user interfaces in higher educational contexts

Tangible Landscape: Cognitively Grasping the Flow of Water

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