LiDAR analysis for hazard mapping and forestry management using JGrassTools and gvSIG - presentation given at FOSS4G-EU Paris.

1. ydroloGIS nvironmental
HydroloGIS S.r.l. - Via Siemens, 19 - 39100 Bolzano
ngineering
www.hydrologis.com
gisforchange
www.gis4change.org
gvSIG Association
www.gvsig.org
LiDAR analysis for hazard mapping
and forestry management using
JGrassTools and gvSIG
Silvia Franceschi and Andrea Antonello
FOSS4G-EU 2017 – 2017/07/21

2. Who am I?
●
environmental engineer specialized in hydrology,
hydraulics, geomorphology and forestry
●
PhD in Mountain Environment and Agriculture
●
co-founder of HydroloGIS member of gvSIG
association
●
developer of scientific models contained in the
JGrassTools library in the fields of: hydrology,
hydraulic, forestry
●
OSGeo Charter Member

3. The JGrassTools library
●
an open source geospatial library focused on hydro-
geomorphological analysis and environmental
modeling
●
development started in 2002 at the University of
Trento, Department of Civil and Environmental
Engineering
●
from 2015 integrated as Spatial Toolbox in gvSIG
●
available for installation through the gvSIG Update
Manager as a plugin

4. The JGrassTools library
Models are grouped in sections and
subsections. Main sections are:
●
HortonMachine: geomorphology
analysis
●
Raster and vector processing
●
Mobile tools: support for
Geopaparazzi application for
digital field mapping
●
LESTO: LiDAR Empowered
Science Toolbox Open Source
JGrasstools inside gvSIG:

5. The JGrassTools library
Modules Parameters
Experimental!
Debug mode
Set maximum memory
Modules List
Running options

6. The JGrassTools library: HortonMachine
droloGIS S.r.l. - Via Siemens, 19 - 39100 Bolzano ydrologis.com
drainage direction,total contributing area, network
and watershed extraction, rescaled distances and
hydrologic attributes, slope, curvatures, hydrologic
indexes and geomorphologic attributes

7. The JGrassTools library: Statistics
Interpolation of meteorological data with Kriging (rainfall and
temperature) and Jami (temperature, pressure, humidity and wind)

8. The JGrassTools library: HydroGeomorphology
Evaluation of the maximum discharge for a given precipitation
(works also with statistical information rainfall Intensity-Duration
Curves)
Peakflow

9. The JGrassTools library: HydroGeomorphology
Simplified 1D hydraulic model:
-based on Saint Venant equations
-GIS based: input and output are GIS layers
-calculates the water depth and velocity for each section
-can handle lateral contributes: inflow and outtakes
Data preparation for the Hecras hydraulic software for channels.

10. The JGrassTools library: HydroGeomorphology
Hillslope stability: Shalstab
Stability condition for the
given precipitation
Critical rainfall
simulated area
area interested by the event
DebrisFlow: triggering,
propagation in network and
final propagation on the fan

11. The JGrassTools library: LESTO
Developed in collaboration with the Free University of Bolzano.
The toolbox is mainly dedicated to forestry analysis.

12. The JGrassTools library: LESTO
Adaptive TIN,
generation of DTM
from LiDAR datasets

13. The JGrassTools library: LESTO
Extraction of buildings from LiDAR datasets

14. The JGrassTools library: LESTO
Vegetation: individual tree crown approaches are followed, aimed
to detect position and main characteristics of each single tree.
Modules that work both on
raster and point clouds

15. ●
GIS-based tool for predicting the magnitude of LW
transport during flood events at any given section
within a river basin
●
two main processes related to woody debris:
– LW recruitment
●
from hillslopes
●
from bank erosion
(geology)
– LW transport/propagation
along the network
LW debris model

16. SHALSTAB
model
Unstable slopes connected
to fluvial network
CONNECTIVITY
model
AREAS THAT
PROVIDES LW
Channel
widening
EXTREME
events
INPUTS AND PROCESSES OUTPUTSLEGEND
LW debris model: recruitment

17. TREE HEIGHT
STAND VOLUME
CHM and
semi-empirical model
LiDAR data
single-tree model
EACH TREE:
position, H, DBH
INPUTS AND PROCESSES OUTPUTSLEGEND
LW debris model: recruitment

18. SHALSTAB
model
Unstable slopes connected
to fluvial network
CONNECTIVITY
model
AREAS THAT
PROVIDES LW
TREE HEIGHT
STAND VOLUME
CHM and
semi-empirical model
Channel
widening
EXTREME
events
Volume and dimensions
of available LW
LiDAR data
single-tree model
EACH TREE:
position, H, DBH
INPUTS AND PROCESSES OUTPUTSLEGEND
LW debris model: recruitment

19. SHALSTAB
model
Unstable slopes connected
to fluvial network
CONNECTIVITY
model
AREAS THAT
PROVIDES LW
TREE HEIGHT
STAND VOLUME
CHM and
semi-empirical model
Channel
widening
EXTREME
events
Volume and dimensions
of available LW
LiDAR data
single-tree model
EACH TREE:
position, H, DBH
LW propagation
Field data
monitoring LW transport
1D-HYDRAULIC
model
BRIDGES
DAMS
SECTIONS
geom+KsINPUTS AND PROCESSES OUTPUTSLEGEND
LW debris model: propagation

20. SHALSTAB
model
Unstable slopes connected
to fluvial network
CONNECTIVITY
model
AREAS THAT
PROVIDES LW
TREE HEIGHT
STAND VOLUME
CHM and
semi-empirical model
CRITICAL SECTIONS
AND LW VOLUME
Channel
widening
EXTREME
events
INPUTS AND PROCESSES OUTPUTSLEGEND
Volume and dimensions
of available LW
LW propagation
Field data
monitoring LW transport
LiDAR data
single-tree model
EACH TREE:
position, H, DBH
1D-HYDRAULIC
model
BRIDGES
DAMS
SECTIONS
geom+Ks
LW debris model: propagation

21. ●
step by step procedure
●
split in submodules
LW debris model: workflow

22. ●
the pre-event conditions correspond to bankfull width
(flow event that recurs every 1.5 year)
●
polygon with the extension of the bankfull area (field
survey or remote sensing imagery)
●
the width ratio is
calculated following a
power law of the unit
stream power (pre-event
conditions)
●
parameters of the power
law should be derived
from field observations
(input parameters)
LW debris model: bank erosion

23. ●
correct the bankfull width where a bridge or a check
dam is located with the real width of the structure
●
widening/erosion is avoided for sections where there
are structures and where there is rock (input geology)
LW debris model: bank erosion

24. LW debris model: bank erosion
geology bankfull area
widening area

25. ●
shallow landslides on connected areas deliver logs to
the channels → amount of wood on the unstable and
connected areas
CHM + TSV
LiDAR/CHM
single trees
vegetation paras
(position, H, DBH)
LW debris model: hillslopes input

26. LW debris model: hillslopes input

27. Unstable Connected
Areas
SubBasins
Shalstab
DownSlopeConnectivityCHM + TSV
LiDAR/CHM
single trees
vegetation paras
(position, H, DBH)
connectivity
threshold
●
shallow landslides on connected areas deliver logs to
the channels → amount of wood on the unstable and
connected areas
LW debris model: hillslopes input

28. LW debris model: hillslopes input
connectivity map
drainage area for
each channels
section (subbasins)

29. ●
shallow landslides on connected hillslopes deliver logs
to the channels → amount of wood on the unstable
and connected areas
CHM + TSV
LiDAR/CHM
single trees
vegetation paras
(position, H, DBH)
LW contribute
each section
Unstable Connected
Areas
SubBasins
Shalstab
DownSlopeConnectivity
connectivity
threshold
LW debris model: hillslopes input

30. LW debris model: hillslopes input
vegetation on the
unstable and connected
areas

31. LW debris model: hillslopes input
vegetation on the
unstable and connected
areas

32. LW debris model: total LW recruitment

33. ●
LW is routed downstream using simple Boolean
transport conditions based on:
– ratio between the length of the logs and the width of
the sections (input parameter)
– ratio between the diameter of the logs and the
water depth (input parameter)
●
post-event channel width + water depth are calculated
through the 1D hydraulic model using the peak
discharge
●
identifies the critical sections for the transit of LW in
the given stream network
LW debris model: propagation

34. LW debris model: propagation
critical
non critical

35. http://www.jgrasstools.org
Franceschi Silvia
silvia.franceschi@gmail.com
Antonello Andrea
andrea.antonello@gmail.com
THANKS FOR THE ATTENTION!