2016 foss4 g track: grass gis point cloud exploratory data analysis an open source toolkit for...

GRASS GIS Point Cloud Exploratory Data AnalysisAn Open Source toolkit for point cloud data processing

September, 2016

Robert S. [email protected]

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mailto:[email protected]

grass.osgeo.org

A reliable and flexible open source analytical geospatial processing engine

2

grassmac.wikidot.com

https://grass.osgeo.org

http://grassmac.wikidot.com/

Introduction

• Exploratory Analysis?

• What/Why GRASS?

• GRASS with point cloud?

• Examples

• Future?

• Take aways

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Exploratory Analysis

• Point Cloud

• Vast amounts of data

• Millions / Billions of Points

• Challenges

• Visualize

• Validate

• Analyze

• Rapid

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Processing Workflow Overview

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Map Display

2D / 3D

View

Integrate

Bash / Python

Script

#!

r.out.gdal

v.out.ogr

Export

r.* - Raster

v.* - Vector

i.* - Imagery

g.* - General

db.* - Database

t.* - Time

Analyze

r.in.lidar

v,in.lidar

Import

GRASS GIS - Point Cloud Data Import

$ r.in.lidar -e -o --overwrite input=<required> \ output=<required> method=min zrange=5000,6000 \ resolution=2.0 return_filter=last class_filter=2

-e = extend computational region based on dataset

-o = override dataset project - use grass database

-- overwrite = overwrite dataset - often needed in exploratory mode

method = choose statistic (min, mean, max…etc) for raster import binning

zrange = only import points between 5000 and 6000

return_filter = filters by first, middle, last return

class_filter = filters by classification (2 = ground)

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Format: ASPRS - LAS*

Computational Region

• Raster processing significant & powerful

• Vector processsing not as important

• except when deriving vectors from raster

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Interstate 25, Albuquerque, NM

Mobile LiDAR Visualization

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I-25, Albuquerque, NM211.8 million pointssize 7.2 GB3 miles

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grass terminal window

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r.in.lidar graphical user interface (gui)

Interstate 25 Intensity Image

Moblie LiDAR (0.3 ft GSD)

0 100

feet

Assessment

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0 100

feet



0 100

feet

Assessment

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Calabacillas Arroyo, Albuquerque, NM

Change Detection

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LiDAR 20101.4 m NPS182 MB

Photogrammetry 20145M Points 37M Points6-inch GSD

1.27 GBprocessing time: 52

seconds

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highlights: r.in.lidar x 2

•r.in.lidar• dsm

• dsm

•r.mapcalc

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r.mapcalc

r.mapcalc --overwrite expression="SGM_minus_LiDAR = SGM_2014_CAB - LiDAR_2010_CAB"

2014 2010 difference- =

Extract change areas (raster & vector)differences between ±1 & ±10 feet

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Santa Fe, NM

Data Validation

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strip 101 flight line109.4 million points

size 3.78 GB7 minutes and 31 seconds

strip 100 flight line102.1 million pointssize 3.54 GB

Visualize / Analyze - ~37 mi. by 0.45 mi. point clouds

Santa Fe County, NM

Spatial Distribution and Regularity

• density grid =

• 2 X design ANPS =

• 2 * 0.71 = 1.42 m

• 90 percent of the cells in the grid =

• 1 point

• Using individual (single) swaths,

• only the first return points

• located within the center part

• Excluding acceptable data voids

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•r.in.lidar•intensity

•dsm

•count

•r.stats•ps.map

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Strip 101 Point Per Cell Map4.66 ft GSD

0 0.5

miles

Strip 101 Intensity Image4.66 ft GSD

0 0.5

miles

Strip 101 Color Relief MapElevation in feet

0 0.5

miles

-i intensity method=min

r.in.lidar

count

return=first

• number of points in cell

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count

• Strip 100 = 0.10% = zero

• Strip 101 = 0.08% = zero

r.stats -acpl in=$map4 sort=asc sep=comma output=- > output/$map21

cat output/$map21 | grep ^0, >> output/zero_count.csv

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output - visualization

ps.map --overwrite input=output/$map22 output=output/$map23ps2pdfwr -dPDFSETTINGS=/prepress -r1200 output/$map23

Strip 100 Strip 101

Strip_100_intensity_466ft Strip_101_intensity_466ft

Rio Grande, NM

1960s - River Centerline

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LiDAR 2014Santa Fe County

strip 101 flight line swaths109.4 million points


LiDAR 2014Santa Fe Countystrip 100 flight line swaths102.1 million pointssize 3.54 GB4 minutes and 2 seconds

Bureau of Reclamation 1962 Photos83.2 million pointssize 2.16 GB12 hours, 52 minutes and 55 seconds11 square miles11 river miles

Rio Grande Bosque Farms, NM


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• r.in.lidar• intensity (ortho)

• dsm

• i.segment• obia

• r.slope.aspect• r.roughness.vector

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1962 Digital Surface Model (DSM)

Color Shaded Relief (elevation in meters)

0 1

kilometers

1962 Photography − U.S. Bureau of Reclamation

Point Cloud Orthophoto (0.6 m GSD)

0 1

kilometers

r.in.lidar

-i intensity dsm

1960s vintage QL2 surface

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0.51962 Object Based Image Analysis (OBIA)

threshold=0.5 (i.segment) random colors

0 1

kilometers



0 1

kilometers



0 1

kilometers



0 1

kilometers



0 1

kilometers



0 1

kilometers

i.segment

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1962 Aspect Map

Point cloud derived aspect (in degrees)

0 1

kilometers

1962 Slope Map

Point cloud derived slope (in degrees)

0 1

kilometers

r.slope.aspect

slope aspect

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1962 Topographic Dispersion Map

Surface roughness Fisher’s K parameter (r.roughness.vector)

0 1

kilometers

1962 Topographic Strength Map

Surface roughness vector strength (r.roughness.vector)

0 1

kilometers

strength fisher’s k

g.extensionr.roughness.vector

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1962 Topographic Dispersion Map

Surface roughness Fisher’s K parameter (r.roughness.vector)

0 1

kilometers

1962 Topographic Strength Map

Surface roughness vector strength (r.roughness.vector)

0 1

kilometers

strength fisher’s k

g.extensionr.roughness.vector

Grohmann, C.H., Smith, M.J. & Riccomini, C., 2011. Multiscale Analysis of Topographic Surface Roughness in

the Midland Valley, Scotland. Geoscience and Remote Sensing, IEEE Transactions on, 49:1200-1213. http://

dx.doi.org/10.1109/TGRS.2010.2053546

http://dx.doi.org/10.1109/TGRS.2010.2053546

Boca Negra Arroyo, Albuquerque, NM

Drainage Basin Study

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Mid-Region Council of Governments 2010 LiDAR187.6 million points (1.4 m NPS)


Boca Negra Arroyo, Albuquerque, NM


• r.in.lidar• dsm

• r.watershed• accumulation

• direction

• basin

• flow path

• v.generalize

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DSM

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Elevation: MRCOG2010 (feet) 0 5

miles

Flow Accumulation

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Flow Accumulation0 5

miles

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Basin Boundary

v.generalize input=$map8 output=$map10 method=chaiken threshold=6 --overwrite

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Basin Boundary - 16.3 sq. miles

Lubbock, TX

DSM Development - Targeted Building Collection

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2016 Photogrammetric Semi-global Matching Point clouds1 file: 141 million points (3-inch GSD)

size 4.82 GB3763 total files - 502 square miles

4 hours and 18 minutes

Lubbock, TX


• r.in.lidar• dsm

• r.to.vect• polygon outline

v.hull• generalize

v.buffer• interior clip

• r.out.gdal• output GeoTiff

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2016 Lubbock Digital Surface ModelSemi−global matching photogrammetric point clouds (3763)

0 10

miles

Point Cloud DSM

• Decimated Point

Cloud

• 141 M -> 4 M (2%)

• 4.6 GB -> 140 MB

• r.in.lidar

• 3.0 ft GSD

• 4 hours processing

• 6 core machine

• 10 simultaneous

GRASS databases

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2016 Lubbock DSMColor Relief Map (elevation in feet)

0 0.5

miles

2015 Lubbock DSMColor Relief Map (elevation in feet)

0 0.5

miles

r.in.lidar

2015 leaf-off 2016 leaf-on

2016 Lubbock Normalized Difference Vegetation Index (NDVI)

DSM / NDVI Candidate Building Detection

Buildings

Candidate Building 0 0.25 44

New Candidate Buildings

2016 NDVI

• GRASS Development Team, 2015. Geographic Resources

Analysis Support System (GRASS) Software, Version 7.0. Open

Source Geospatial Foundation. http://grass.osgeo.org

• Michael Barton, PhD. - GRASS Macintosh Binaries http://

grassmac.wikidot.com/

Acknowledgements

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http://grass.osgeo.org

http://grassmac.wikidot.com/

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