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NCGIS2019 - Revision history
2024-03-29T01:18:53Z
Revision history for this page on the wiki
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https://grasswiki.osgeo.org/w/index.php?title=NCGIS2019&diff=26487&oldid=prev
⚠️Wenzeslaus: /* See also */ fix 2021 link
2021-02-11T16:48:46Z
<p><span dir="auto"><span class="autocomment">See also: </span> fix 2021 link</span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:48, 11 February 2021</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[GRASS GIS at NCGIS2017]]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[GRASS GIS at NCGIS2017]]</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* [[<del style="font-weight: bold; text-decoration: none;">GRASS GIS at </del>NCGIS2021]]</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* [[NCGIS2021]]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[AGU Fall Meeting 2018]]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[AGU Fall Meeting 2018]]</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[Category: Conferences]]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[Category: Conferences]]</div></td></tr>
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⚠️Wenzeslaus
https://grasswiki.osgeo.org/w/index.php?title=NCGIS2019&diff=26484&oldid=prev
⚠️Wenzeslaus: Add NCGIS2021 link
2021-02-11T16:47:03Z
<p>Add NCGIS2021 link</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:47, 11 February 2021</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[GRASS GIS at NCGIS2017]]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[GRASS GIS at NCGIS2017]]</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [[GRASS GIS at NCGIS2021]]</ins></div></td></tr>
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⚠️Wenzeslaus
https://grasswiki.osgeo.org/w/index.php?title=NCGIS2019&diff=25548&oldid=prev
⚠️Kellynm: added photo
2019-03-14T18:58:02Z
<p>added photo</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 18:58, 14 March 2019</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Canopy structural patterns for identifying yield variability in grain sorghum ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Canopy structural patterns for identifying yield variability in grain sorghum ===</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[File:DepthFiltering.png|thumb|right|Comparison of point cloud depth filtering parameters for reconstructing sorghum]]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Description: Deriving crop information from remotely sensed data is a critical component of food security and sustainability efforts such as precision agriculture, soil conservation, and agroecological modeling. Small unmanned aerial systems (UAS) have emerged in recent years as a versatile remote sensing tool used by scientists and agricultural producers for collecting data at very high spatial and temporal resolutions. UAS can provide precisely-timed, fine-grained data for informing management responses to inter-field variability for maximizing crop productivity while minimizing natural resource degradation. Vegetation indices, like Normalized Difference Vegetation Index, calculated from remotely sensed spectral information have been shown to strongly correlate with crop health and are widely used in industry and throughout the literature. Many multispectral sensors for UAS, however, are limited by high cost and low spectral resolution. Furthermore, there has been very little exploration of the use of 3D models of canopy structure to provide information about crop health, population, and stand uniformity. Thus far, techniques for quantifying the geometric properties of morphological surfaces have been limited to terrain landforms. This research goes beyond spectral analysis for remote crop monitoring and investigates how patterns in canopy structure can be used to identify variability in crop health and productivity using remote sensing with low altitude small UAS. A time series of high resolution orthophotos (1cm/pix) and digital surface models (2cm/pix) was created using Structure from Motion (SfM) photogrammetry and analyzed using an open source GRASS GIS temporal framework to investigate the relationship between sorghum canopy morphology and yield variability. A bare earth digital elevation model created from a 2015 aerial LiDAR survey was used to identify and correct any systematic shifts in the crop surface models and calculate crop heights. Canopy structure was categorized using geomorphons and structural metrics to measure canopy roughness and uniformity were calculated to examine correlation with variability in yield. This approach for leveraging 3D canopy structure provided valuable information for characterizing crop status and productivity.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Description: Deriving crop information from remotely sensed data is a critical component of food security and sustainability efforts such as precision agriculture, soil conservation, and agroecological modeling. Small unmanned aerial systems (UAS) have emerged in recent years as a versatile remote sensing tool used by scientists and agricultural producers for collecting data at very high spatial and temporal resolutions. UAS can provide precisely-timed, fine-grained data for informing management responses to inter-field variability for maximizing crop productivity while minimizing natural resource degradation. Vegetation indices, like Normalized Difference Vegetation Index, calculated from remotely sensed spectral information have been shown to strongly correlate with crop health and are widely used in industry and throughout the literature. Many multispectral sensors for UAS, however, are limited by high cost and low spectral resolution. Furthermore, there has been very little exploration of the use of 3D models of canopy structure to provide information about crop health, population, and stand uniformity. Thus far, techniques for quantifying the geometric properties of morphological surfaces have been limited to terrain landforms. This research goes beyond spectral analysis for remote crop monitoring and investigates how patterns in canopy structure can be used to identify variability in crop health and productivity using remote sensing with low altitude small UAS. A time series of high resolution orthophotos (1cm/pix) and digital surface models (2cm/pix) was created using Structure from Motion (SfM) photogrammetry and analyzed using an open source GRASS GIS temporal framework to investigate the relationship between sorghum canopy morphology and yield variability. A bare earth digital elevation model created from a 2015 aerial LiDAR survey was used to identify and correct any systematic shifts in the crop surface models and calculate crop heights. Canopy structure was categorized using geomorphons and structural metrics to measure canopy roughness and uniformity were calculated to examine correlation with variability in yield. This approach for leveraging 3D canopy structure provided valuable information for characterizing crop status and productivity.</div></td></tr>
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⚠️Kellynm
https://grasswiki.osgeo.org/w/index.php?title=NCGIS2019&diff=25546&oldid=prev
⚠️Kellynm: Changed title
2019-03-14T18:46:15Z
<p>Changed title</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 18:46, 14 March 2019</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Materials: [https://ncsu-landscape-dynamics.github.io/futures-talk/ncgis2019.html Slides]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Materials: [https://ncsu-landscape-dynamics.github.io/futures-talk/ncgis2019.html Slides]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>=== <del style="font-weight: bold; text-decoration: none;">Using a time series of 3D crop canopy models derived from sUAS imagery to identify geomorphic </del>patterns <del style="font-weight: bold; text-decoration: none;">related to crop stress </del>===</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>=== <ins style="font-weight: bold; text-decoration: none;">Canopy structural </ins>patterns <ins style="font-weight: bold; text-decoration: none;">for identifying yield variability in grain sorghum </ins>===</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Description: Deriving crop information from remotely sensed data is a critical component of food security and sustainability efforts such as precision agriculture, soil conservation, and agroecological modeling. Small unmanned aerial systems (UAS) have emerged in recent years as a versatile remote sensing tool used by scientists and agricultural producers for collecting data at very high spatial and temporal resolutions. UAS can provide precisely-timed, fine-grained data for informing management responses to inter-field variability for maximizing crop productivity while minimizing natural resource degradation. Vegetation indices, like Normalized Difference Vegetation Index, calculated from remotely sensed spectral information have been shown to strongly correlate with crop health and are widely used in industry and throughout the literature. Many multispectral sensors for UAS, however, are limited by high cost and low spectral resolution. Furthermore, there has been very little exploration of the use of 3D models of canopy structure to provide information about crop health, population, and stand uniformity. Thus far, techniques for quantifying the geometric properties of morphological surfaces have been limited to terrain landforms. This research goes beyond spectral analysis for remote crop monitoring and investigates how patterns in canopy structure can be used to identify variability in crop health and productivity using remote sensing with low altitude small UAS. A time series of high resolution orthophotos (1cm/pix) and digital surface models (2cm/pix) was created using Structure from Motion (SfM) photogrammetry and analyzed using an open source GRASS GIS temporal framework to investigate the relationship between sorghum canopy morphology and yield variability. A bare earth digital elevation model created from a 2015 aerial LiDAR survey was used to identify and correct any systematic shifts in the crop surface models and calculate crop heights. Canopy structure was categorized using geomorphons and structural metrics to measure canopy roughness and uniformity were calculated to examine correlation with variability in yield. This approach for leveraging 3D canopy structure provided valuable information for characterizing crop status and productivity.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Description: Deriving crop information from remotely sensed data is a critical component of food security and sustainability efforts such as precision agriculture, soil conservation, and agroecological modeling. Small unmanned aerial systems (UAS) have emerged in recent years as a versatile remote sensing tool used by scientists and agricultural producers for collecting data at very high spatial and temporal resolutions. UAS can provide precisely-timed, fine-grained data for informing management responses to inter-field variability for maximizing crop productivity while minimizing natural resource degradation. Vegetation indices, like Normalized Difference Vegetation Index, calculated from remotely sensed spectral information have been shown to strongly correlate with crop health and are widely used in industry and throughout the literature. Many multispectral sensors for UAS, however, are limited by high cost and low spectral resolution. Furthermore, there has been very little exploration of the use of 3D models of canopy structure to provide information about crop health, population, and stand uniformity. Thus far, techniques for quantifying the geometric properties of morphological surfaces have been limited to terrain landforms. This research goes beyond spectral analysis for remote crop monitoring and investigates how patterns in canopy structure can be used to identify variability in crop health and productivity using remote sensing with low altitude small UAS. A time series of high resolution orthophotos (1cm/pix) and digital surface models (2cm/pix) was created using Structure from Motion (SfM) photogrammetry and analyzed using an open source GRASS GIS temporal framework to investigate the relationship between sorghum canopy morphology and yield variability. A bare earth digital elevation model created from a 2015 aerial LiDAR survey was used to identify and correct any systematic shifts in the crop surface models and calculate crop heights. Canopy structure was categorized using geomorphons and structural metrics to measure canopy roughness and uniformity were calculated to examine correlation with variability in yield. This approach for leveraging 3D canopy structure provided valuable information for characterizing crop status and productivity.</div></td></tr>
</table>
⚠️Kellynm
https://grasswiki.osgeo.org/w/index.php?title=NCGIS2019&diff=25533&oldid=prev
⚠️Wenzeslaus: See also and categories
2019-03-03T03:02:42Z
<p>See also and categories</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 03:02, 3 March 2019</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Tangible Landscape activities: surface water flow and ponding (with Blender), planting trees (with Blender), first person views (with Blender), trail design (with Blender), routing and blocked streets, HAND, drainage and contributing area, placing a building into the landscape considering variety of tradeoffs (building siting)</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Tangible Landscape activities: surface water flow and ponding (with Blender), planting trees (with Blender), first person views (with Blender), trail design (with Blender), routing and blocked streets, HAND, drainage and contributing area, placing a building into the landscape considering variety of tradeoffs (building siting)</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* NCSU CGA students, postdocs, and faculty were present at the booth.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* NCSU CGA students, postdocs, and faculty were present at the booth.</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">== See also ==</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><!-- including last conference (in the series) and the most recent conference added before this --></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><!-- it would make sense to include also the next conference in the series and (any) next conference recorded --></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [[GRASS GIS at NCGIS2017]]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [[AGU Fall Meeting 2018]]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Category: Conferences]]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Category: 2019]]</ins></div></td></tr>
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⚠️Wenzeslaus
https://grasswiki.osgeo.org/w/index.php?title=NCGIS2019&diff=25532&oldid=prev
⚠️Wenzeslaus: /* NCSU Center for Geospatial Analytics */
2019-03-03T02:58:04Z
<p><span dir="auto"><span class="autocomment">NCSU Center for Geospatial Analytics</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 02:58, 3 March 2019</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== NCSU Center for Geospatial Analytics ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== NCSU Center for Geospatial Analytics ===</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[File:Ncsu cga booth agu 2018.jpg|400px|thumb|right| NCSU CGA booth with a Tangible Landscape demo]]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Organization: Center for Geospatial Analytics at North Carolina State University, Raleigh, North Carolina, United States of America</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [http://geospatial.ncsu.edu/ NCSU Center for Geospatial Analytics] was promoting NCSU, the center, and its educational programs and services.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* A live iterative [http://tangible-landscape.github.io/ Tangible Landscape] demo was part of the booth featuring many algorithms from GRASS GIS.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Tangible Landscape activities: surface water flow and ponding (with Blender), planting trees (with Blender), first person views (with Blender), trail design (with Blender), routing and blocked streets, HAND, drainage and contributing area, placing a building into the landscape considering variety of tradeoffs (building siting)</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* NCSU CGA students, postdocs, and faculty were present at the booth.</ins></div></td></tr>
</table>
⚠️Wenzeslaus
https://grasswiki.osgeo.org/w/index.php?title=NCGIS2019&diff=25531&oldid=prev
⚠️Wenzeslaus: /* Presentations */ add links to slides
2019-03-03T02:49:44Z
<p><span dir="auto"><span class="autocomment">Presentations: </span> add links to slides</span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 02:49, 3 March 2019</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Doug Newcomb (USFWS), Corey White (NCSU Center for Geospatial Analytics)</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Doug Newcomb (USFWS), Corey White (NCSU Center for Geospatial Analytics)</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Materials: [https://wenzeslaus.github.io/grass-gis-talks/ncgis2019_whats_new.html Slides]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== GRASS GIS: Getting Started ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== GRASS GIS: Getting Started ===</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Corey White (NCSU Center for Geospatial Analytics), Doug Newcomb (USFWS)</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Corey White (NCSU Center for Geospatial Analytics), Doug Newcomb (USFWS)</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Materials: [https://wenzeslaus.github.io/grass-gis-talks/ncgis2019_getting_started.html Slides]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Navigating the Geospatial Open Source Software Landscape ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Navigating the Geospatial Open Source Software Landscape ===</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Chris Jones, Anna Petrasova, Devon Gaydos, Kellyn Montgomery, Ross K. Meentemeyer</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Chris Jones, Anna Petrasova, Devon Gaydos, Kellyn Montgomery, Ross K. Meentemeyer</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Materials: [https://ncsu-landscape-dynamics.github.io/pops-talk/ncgis2019.html Slides]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Citizen Science - Processing LiDAR data at Home to compare to the NLCD ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Citizen Science - Processing LiDAR data at Home to compare to the NLCD ===</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Anna Petrasova, Georgina M. Sanchez, Derek Van Berkel, Ross K. Meentemeyer</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Anna Petrasova, Georgina M. Sanchez, Derek Van Berkel, Ross K. Meentemeyer</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Materials: [https://ncsu-landscape-dynamics.github.io/futures-talk/ncgis2019.html Slides]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Using a time series of 3D crop canopy models derived from sUAS imagery to identify geomorphic patterns related to crop stress ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Using a time series of 3D crop canopy models derived from sUAS imagery to identify geomorphic patterns related to crop stress ===</div></td></tr>
</table>
⚠️Wenzeslaus
https://grasswiki.osgeo.org/w/index.php?title=NCGIS2019&diff=25530&oldid=prev
⚠️Wenzeslaus: /* Navigating the Geospatial Open Source Software Landscape */
2019-03-03T02:45:08Z
<p><span dir="auto"><span class="autocomment">Navigating the Geospatial Open Source Software Landscape</span></span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 02:45, 3 March 2019</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Corey White (NCSU Center for Geospatial Analytics), Randal Hale (North River Geographic Systems, Inc)</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Corey White (NCSU Center for Geospatial Analytics), Randal Hale (North River Geographic Systems, Inc)</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Relevance to GRASS GIS: GRASS GIS was used in examples of tickets, commits, and other open source concepts. It was also included in overviews of available software.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Relevance to GRASS GIS: GRASS GIS was used in examples of tickets, commits, and other open source concepts. It was also included in overviews of available software.</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Materials: [https://ncsu-geoforall-lab.github.io/open-science-course/lectures/ncgis2019.html Slides]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Construction of Landscape Level QL2 LiDAR Data Sets for Species Habitat Assessment in Eastern North Carolina ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Construction of Landscape Level QL2 LiDAR Data Sets for Species Habitat Assessment in Eastern North Carolina ===</div></td></tr>
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⚠️Wenzeslaus
https://grasswiki.osgeo.org/w/index.php?title=NCGIS2019&diff=25529&oldid=prev
⚠️Wenzeslaus: /* Navigating the Geospatial Open Source Software Landscape */
2019-03-03T02:42:32Z
<p><span dir="auto"><span class="autocomment">Navigating the Geospatial Open Source Software Landscape</span></span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 02:42, 3 March 2019</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l20">Line 20:</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Corey White (NCSU Center for Geospatial Analytics), Randal Hale (North River Geographic Systems, Inc)</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Corey White (NCSU Center for Geospatial Analytics), Randal Hale (North River Geographic Systems, Inc)</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Relevance to GRASS GIS: GRASS GIS was used in examples of tickets, commits, and other open source concepts. It was also included in overviews of available software.</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Construction of Landscape Level QL2 LiDAR Data Sets for Species Habitat Assessment in Eastern North Carolina ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Construction of Landscape Level QL2 LiDAR Data Sets for Species Habitat Assessment in Eastern North Carolina ===</div></td></tr>
</table>
⚠️Wenzeslaus
https://grasswiki.osgeo.org/w/index.php?title=NCGIS2019&diff=25528&oldid=prev
⚠️Wenzeslaus: /* Presentations */
2019-03-03T02:38:00Z
<p><span dir="auto"><span class="autocomment">Presentations</span></span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 02:38, 3 March 2019</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l3">Line 3:</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Presentations ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Presentations ==</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>=== <del style="font-weight: bold; text-decoration: none;">Creating Urbanization Scenarios </del>with the <del style="font-weight: bold; text-decoration: none;">FUTURES Model </del>===</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>=== <ins style="font-weight: bold; text-decoration: none;">GRASS GIS: What's New? ===</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Description: GRASS GIS is a geospatial analysis and remote sensing software aiming at providing its users </ins>with <ins style="font-weight: bold; text-decoration: none;">an all-in-one tool. GRASS GIS is open source which makes it both free to use but also, for </ins>the <ins style="font-weight: bold; text-decoration: none;">more adventurous, hackable. This talk will give an overview of what the GRASS GIS community provides to the public and will highlight the latest additions to GRASS GIS. These include improvements in import and handling of vector data formats including messy datasets, extended Python capabilities, and easier native data manipulation. Algorithms for interpolation, solar radiation, water flow, and sediment transport now come in parallelized versions, while all raster operations now benefit from new compression algorithms. List of new algorithms includes point clustering, vector topology cleaning, turn support for network analysis, landform and shape detection, image segmentation and clumping, atmospheric corrections for more satellites, and temporal algebra. Experimental features available for download now include concave hull, vector algebra, ground point cloud classification, DEM fusion and blending, object-based classification, Sentinel data handling, and sky-view factor visualization.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Authors: Vaclav Petras, Doug Newcomb (USFWS), Corey White (NCSU Center for Geospatial Analytics)</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">=== GRASS GIS: Getting Started ===</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Description: GRASS GIS is a software for geospatial analysis and remote sensing. It comes with features covering broad spectrum of topics from network analysis to surface hydrology. In many ways, GRASS GIS is similar to other GIS packages, but it also comes with several unique concepts such as computational region, integrated command line, locations and mapsets. These come with advantages praised by advanced users, but at the same time, these concepts often feel unfamiliar to those accustomed to other GIS software. Nevertheless, for over 30 years now, GIS and RS analysts had reasons to learn GRASS GIS often on their own. Reasons include the breadth of functionality, long-term compatibility and the open source nature of GRASS GIS. For GRASS GIS, being open source means more than just escape from recurring license fees. The GRASS GIS development is characterized by high involvement of interested users in the development process hand-in-hand with programmers and scientists. This session aims at providing basis for self-learning GRASS GIS and will be useful whether you have already tried running GRASS GIS or whether you are just checking it out.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Authors: Vaclav Petras, Corey White (NCSU Center for Geospatial Analytics), Doug Newcomb (USFWS)</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">=== Navigating the Geospatial Open Source Software Landscape ===</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Description: Does open source mean for free? Is it free, libre, or open source? Can I use it commercially? What software to choose? Where to start learning about geospatial open source software? Do I have to use Linux? Do I have to share my data online? Do I have to start programing? If you are wondering about any of these questions or you are just curious about open source software in general, this talk is for you. This talk will help you understand the geospatial open source software ecosystem and community and additionally, it will provide an overview of available tools and give hints on how to choose between them.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Authors: Vaclav Petras, Corey White (NCSU Center for Geospatial Analytics), Randal Hale (North River Geographic Systems, Inc)</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">=== Construction of Landscape Level QL2 LiDAR Data Sets for Species Habitat Assessment in Eastern North Carolina ===</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Description: In response to Hurricane Matthew, the State of North Carolina partnered with USGS to undertake a LiDARdata collection updated to 3DEP QL2 standards. This data collection effort has so far generated 360 billionpoints of multiple return LiDAR data in 59 counties in eastern North Carolina. Using native 64-bit GRASSGIS on Ubuntu Linux, forest canopy heights and other structural metrics were generated on a 6.096m (20foot) grid from county LAZ LiDAR datasets and aggregated to 3.5 billion pixel raster layers denotingcanopy heights, point Z value skewness, relative point density at 1-3m and 3-7m, and building footprints.These data layers were compared to 25m buffered point observations of bird species of interest to theUSFWS in eastern North Carolina, 12 digit USGS Hydrologic Unit (HU) polygons, and the 30m resolution2011 National Landcover Dataset (NLCD). Vegetation structure differences between bird species werenoted, as well as geographic differences in structure for Red-cockaded woodpecker (Picoides borealis) ineastern North Carolina. Aggregate vegetation and building statistics were generated for the 12-digitHydrologic Units (HU) for use in aquatic species habitat assessment. Summary statistics for percentagesof Forest, Non-forest, and Building area for each 2011 NLCD class for eastern North Carolina weregenerated to show the level of agreement between NLCD and the LiDAR data classification.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Speaker: Doug Newcomb (USFWS)</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Authors: Doug Newcomb (USFWS), Vaclav Petras (NCSU Center for Geospatial Analytics)</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">=== New Open Source Tool for Plant Pest and Pathogen Spread Modeling </ins>===</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">Description: Urban growth scenario simulation </del>is a <del style="font-weight: bold; text-decoration: none;">powerful tool </del>for <del style="font-weight: bold; text-decoration: none;">exploring impacts </del>of <del style="font-weight: bold; text-decoration: none;">land use change due to urbanization </del>and <del style="font-weight: bold; text-decoration: none;">its effects on </del>landscape. <del style="font-weight: bold; text-decoration: none;">We present FUTURES (FUTure Urban - Regional Environment Simulation) which </del>is a <del style="font-weight: bold; text-decoration: none;">patch-based</del>, <del style="font-weight: bold; text-decoration: none;">stochastic, multi-level land change modeling framework. This </del>model<del style="font-weight: bold; text-decoration: none;">, which was once closed and inaccessible, is now integrated with an open source geospatial platfrom</del>. We <del style="font-weight: bold; text-decoration: none;">will describe our motivation for releasing this project as open source </del>and <del style="font-weight: bold; text-decoration: none;">the advantages of integrating it with </del>GRASS GIS. <del style="font-weight: bold; text-decoration: none;">Then we will show how </del>GIS <del style="font-weight: bold; text-decoration: none;">professionals can start using this tool to empower planners to make informed decisions. FUTURES model has a </del>graphical user interface, <del style="font-weight: bold; text-decoration: none;">pre-processing tools</del>, and <del style="font-weight: bold; text-decoration: none;">is available across </del>all <del style="font-weight: bold; text-decoration: none;">main operating systems</del>. <del style="font-weight: bold; text-decoration: none;">Besides </del>the model <del style="font-weight: bold; text-decoration: none;">itself, we provide free online tutorials </del>and <del style="font-weight: bold; text-decoration: none;">sample datasets so that </del>the <del style="font-weight: bold; text-decoration: none;">potential users can experiment with </del>the model <del style="font-weight: bold; text-decoration: none;">and explore its potential</del>.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Plant diseases and pests directly threaten food production and production of plant-based materials and can also influence agricultural and industrial trade in an area after establishment of necessary quarantine zones. Understanding the potential spread of pests and pathogens </ins>is <ins style="font-weight: bold; text-decoration: none;">thus crucial for protecting the economy and food security. We present </ins>a <ins style="font-weight: bold; text-decoration: none;">new software </ins>for <ins style="font-weight: bold; text-decoration: none;">modeling the spread </ins>of <ins style="font-weight: bold; text-decoration: none;">pests </ins>and <ins style="font-weight: bold; text-decoration: none;">pathogens over a </ins>landscape. <ins style="font-weight: bold; text-decoration: none;">The core of the model </ins>is <ins style="font-weight: bold; text-decoration: none;">implemented as </ins>a <ins style="font-weight: bold; text-decoration: none;">C++ library for performance reasons</ins>, <ins style="font-weight: bold; text-decoration: none;">while the </ins>model <ins style="font-weight: bold; text-decoration: none;">users can choose from a variety of convenient interfaces</ins>. We <ins style="font-weight: bold; text-decoration: none;">provide an R package </ins>and <ins style="font-weight: bold; text-decoration: none;">a </ins>GRASS GIS <ins style="font-weight: bold; text-decoration: none;">module</ins>. <ins style="font-weight: bold; text-decoration: none;">The R package provides integration with the well-know statistical tool R and the GRASS </ins>GIS <ins style="font-weight: bold; text-decoration: none;">provides the module with </ins>graphical user interface, <ins style="font-weight: bold; text-decoration: none;">Python interface</ins>, and <ins style="font-weight: bold; text-decoration: none;">preprocessing and visualization tools. The model as well as </ins>all <ins style="font-weight: bold; text-decoration: none;">its dependencies and integrations are open source</ins>. <ins style="font-weight: bold; text-decoration: none;">This removes any licensing barriers for application of </ins>the model and <ins style="font-weight: bold; text-decoration: none;">gives us an opportunity to openly collaborate on improving the model. It also opens opportunities for </ins>the <ins style="font-weight: bold; text-decoration: none;">model to be scrutinized not only by the traditional peer-review of scientific publications, but also by a review performed by anybody who is interested in using </ins>the model.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras, Anna Petrasova, <del style="font-weight: bold; text-decoration: none;">Georgina M. Sanchez</del>, <del style="font-weight: bold; text-decoration: none;">Derek Van Berkel</del>, Ross K. Meentemeyer</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Authors: Vaclav Petras<ins style="font-weight: bold; text-decoration: none;">, Chris Jones</ins>, Anna Petrasova, <ins style="font-weight: bold; text-decoration: none;">Devon Gaydos</ins>, <ins style="font-weight: bold; text-decoration: none;">Kellyn Montgomery</ins>, Ross K. Meentemeyer</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">=== Citizen Science - Processing LiDAR data at Home to compare to the NLCD ===</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Description: An example of citizen science you can reproduce at home right now. Private citizen processes open data using open source software. Classifications from LiDAR data were processed using GRASS GIS at a computer at home and compared to the NLCD.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Speaker: Doug Newcomb</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Geo For All: Blending OER, Open Data and FOSS in GIS Education ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Geo For All: Blending OER, Open Data and FOSS in GIS Education ===</div></td></tr>
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<td colspan="2" class="diff-lineno">Line 42:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Description: Over the last several years there has been both a maturation of open source geospatial software and a convergence of open educational resources (OER) and open data for teaching and learning geographic information science. This presentation will focus on transitioning an introductory GIS course from using proprietary software and expensive texts to an open source GIS course using OER and open data. Open source software such as QGIS, GRASS, and the R statistical programming language will be covered, as will the “Geo For All” initiative by the Open Source Geospatial Foundation (OSGeo). The presentation will also address the ways in which a transition to OER and open source are having a positive impact on student outcomes in GIS education at a small liberal arts college, as well as how the open GIS course is being used to make a push for wider adoption of open educational resources institution-wide.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Description: Over the last several years there has been both a maturation of open source geospatial software and a convergence of open educational resources (OER) and open data for teaching and learning geographic information science. This presentation will focus on transitioning an introductory GIS course from using proprietary software and expensive texts to an open source GIS course using OER and open data. Open source software such as QGIS, GRASS, and the R statistical programming language will be covered, as will the “Geo For All” initiative by the Open Source Geospatial Foundation (OSGeo). The presentation will also address the ways in which a transition to OER and open source are having a positive impact on student outcomes in GIS education at a small liberal arts college, as well as how the open GIS course is being used to make a push for wider adoption of open educational resources institution-wide.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: David Abernathy, Warren Wilson College</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Speaker: David Abernathy, Warren Wilson College</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Relevance to GRASS GIS: GRASS GIS is taught through QGIS Processing plugin and also directly in more advanced classes. </ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">=== Creating Urbanization Scenarios with the FUTURES Model ===</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Description: Urban growth scenario simulation is a powerful tool for exploring impacts of land use change due to urbanization and its effects on landscape. We present FUTURES (FUTure Urban - Regional Environment Simulation) which is a patch-based, stochastic, multi-level land change modeling framework. This model, which was once closed and inaccessible, is now integrated with an open source geospatial platfrom. We will describe our motivation for releasing this project as open source and the advantages of integrating it with GRASS GIS. Then we will show how GIS professionals can start using this tool to empower planners to make informed decisions. FUTURES model has a graphical user interface, pre-processing tools, and is available across all main operating systems. Besides the model itself, we provide free online tutorials and sample datasets so that the potential users can experiment with the model and explore its potential.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Speaker: Vaclav Petras, NCSU Center for Geospatial Analytics</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Authors: Vaclav Petras, Anna Petrasova, Georgina M. Sanchez, Derek Van Berkel, Ross K. Meentemeyer</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Using a time series of 3D crop canopy models derived from sUAS imagery to identify geomorphic patterns related to crop stress ===</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== Using a time series of 3D crop canopy models derived from sUAS imagery to identify geomorphic patterns related to crop stress ===</div></td></tr>
</table>
⚠️Wenzeslaus