4 introduction to uDig

Getting Started with JGRASS & GIS
Alighiero&Boetti Map Of The World 1989

Silvia Franceschi

Friday, September 10, 2010

“Free Software ... you should
think of ‘free’ as in ‘free
speech,’ not as in “free
beer.””
Richard Stallman


Getting Started with JGRASS and GIS

Objectives

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Installation
!
JGrass can be installed on all operating systems in which
Java Virtual Machine is active:
!
windows
!
linux
!
macOSX

JGrass can be freely downloaded from the website:

www.jgrass.org

There are two types of installation:
!
installation using the complete version of JGrass
!
installation as a uDig plugin 4

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Installation of the Complete Version

The complete version of JGrass is only released for
particular projects or for events such as the current

JGrass_foss4g

To install just click on the executable file and install JGrass
in the desired location.

With this version GRASS tools are also supplied ready for
execution.
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Installation as a uDig Plugin

!
The JGrass uDig plugin can only be installed after the
installation of uDig.
!
Download the recommended version of uDig from
http://udig.refractions.net/download/
!
Install uDig following the on-screen instructions
!
Select from the menu Help -> Find and Install...

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Select to install new features and follow the on-screen
instructions.
Select JGrass from the features to install.

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•The installation of JGrass in uDig adds three new menus to
the menubar:
- Horton Machine
- JGrass
- GRASS

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•The installation of JGrass in uDig adds three new menus to
the menubar:
- Horton Machine
- JGrass
- GRASS
•And two new icons to the toolbar:
− open the scripting editor
− define a work region

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Just as with JGrass, it is possible to install the Axios
extension as a plugin in uDig or in JGrass. This adds tools
for editing and modification of vector data (shp) to the GIS.

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Description of the Work Environment
PROJECT VIEW

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PLAN VIEW

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MAP VIEW

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CATALOGUE, ATTRIBUTES TABLE,...

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Data Viewing
In JGrass-uDig it is possible to view georeferenced data in either
RASTER format or VECTOR format.

For the vector data the uDig features are used.

Further information on this (personalised viewing, network viewing
of the data,...) can be found in the two manuals:

http://udig.refractions.net/confluence/display/EN/Walkthrough+1
http://udig.refractions.net/confluence/display/EN/Walkthrough+2

For the raster data the features of both systems are used depending
on the type of data being viewed.
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Creation of a New Project
The creation of a new project from imported data is
automatic in uDIG. However, it is advisable to be coherent
and ordered in the management of data by creating a new
PROJECT where the desired MAPS can be stored.

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Project Name

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Location where new
project will be saved

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Overview for Data Viewing

•uDig and JGrass work with Drag&Drop logic: all data can be
viewed simply by dragging them into the programme.
•Alternatively, the file can be dragged from Explorer onto:
•catalog: the plan is added to the catalogue but not viewed
•map: the plan is viewed and added on top of all viewed plans
•plan: the plan can be added at any point in the list of active
plans
•project: the plan is added to the open project

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Overview for Vector Data
!
To view a shapefile, from the family of shapfile files, select
the file with .shp extension.
!
Select the file in the computer’s Explorer and drag it to the
Catalog of JGrass.
!
Select the Catalogue tab and, with a right-click, select “Add
to New Map”.
!
Alternatively, it is possible simply to drag the file into the
Map view.

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Movement of the plans up and down
Modifying the view style
Managing the transparency between
plans
Viewing the entire plan

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Tools for feature selection
Queries
Editing vector plans

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Map navigation tools
Zooming and panning

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Overview for Raster Data
Raster data in image format (TIFF, JPG) can be viewed in
JGrass-uDig in the same way as vector data.
This data type, however, cannot be modified from within
the programme. Its sole purpose is that of base
cartographic reference.

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Overview for Raster Data

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JGRASS: Raster Data Analysis

!
In JGrass, data must be organised and grouped according to
a precise logic:
!
DATABASE: a working directory on the hard disk where all
data used and processed by JGrass for the various projects
are stored.
!
LOCATION: physically, this is a directory in the file system
where information relative to the coordinate and projection
system for the data is stored.
!
MAPSET: physically, this too is a directory within the
Location. It represents the JGrass workspace where the actual
data are stored.
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Immagine non
modificabile.

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The data structure within JGrass is completely managed by the
programme. The user only needs to define the DATABASE
directory and the names of the LOCATIONS when these are
created.
The creation of a new Location is done from the menubar:

File -> New -> Other

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Pathname of the
JGrass database

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Name of the new
Location to be
created

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Choice of
Projection System

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Name of new Click ‘add’ to
Mapset create a new
defined here Mapset

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Drag the “.jgrass” file from
the Location to the JGrass
catalog

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Type of data that can be
imported directly into
JGrass

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Reset updates the list of
maps in the Mapset

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To view data from the JGrass Mapset it is advisable to create
a new map. In this way the projection information is
managed in the best way.
Currently, vector data and raster images are projected “on
the fly”. But the support for the re-projection of JGrass raster
data is currently being developed.

Select, with a right-click on the name of the imported map,
“Add to New Map”.

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An important concept in raster analysis is that of Active Region
and Work Region.
The Active Region represents the portion of area where all
calculations will be carried out. That is to say the area where the
GRASS-JGrass tools will work.
In order to view the Active Region it must be dragged into the
Map View from:

Catalog -> Map Graphics -> Active Region Graphic

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If, in the Catalog, more than one Location has been loaded, or
there are more than one Mapaset for a Location, it will be
necessary to indicate to the programme which of the datasets
to work with by selecting the Mapset from the appropriate
dialog box.

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The Active Region is viewed, by default, as a white area on a
green background.
All the analyses carried out with the GRASS-JGrass
commands are only done on the Active Region and at its
resolution.
Therefore, if there are no data in the white area, or if all the
data are covered in green, then these data will not be
processed.

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!
To modify the extension of the Active Region or the various
options associated with it you can use:
!
the style editor button, starting by selecting the plan that
represents the Active Region
!
the icon in the toolbar: this will only modify the extension
of the Active Region but not its resolution

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Click Apply twice!!!

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JGRASS: Work Environment Settings
!
The correct execution of JGrass requires the definition of two
items:
!
Working Mapset: this is the Mapset that contains the data that
is to be analysed
(-> the Active Region that will be used during analysis is the
one relative to the selected Mapset)‫‏‬
!
pathname for the GRASS tools: this is not necessary if you are
only using native JGrass tools. It is indispensable, however, if
you wish to use GRASS tools. Specifically, it refers to the
GRASS installation pathname on your computer. With the
complete version of JGrass the GRASS tools are included in the
JGrass installation directory, and this is the directory to
specify. In all other cases a separate installation of GRASS on
your computer is required.
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JGRASS: Work Environment Settings

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JGRASS: General Tools

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Geomorphological Analysis in
JGRASS: the Horton Machine Package

Silvia Franceschi


Geomorphological Analysis in JGRASS: the Horton Machine Package

Objectives:

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HORTON MACHINE: THE PURPOSE

It has been developed with the purpose of proposing some
quantitative and qualitative tools for the study of catchment
morphology.

• Its main applications have been to alpine catchments of various
dimensions (from a few Km2 to some hundreds of Km2)
• Applications have been made with different types of DEM
(IGM 20m, PAT 10m, LaserAltimetriv 2m)

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HORTON MACHINE: OUR WORK
The starting hypothesis is:

MORPHOMETRY EROSION PROCESSES

Based on this hypothesis, the purpose of the work is to analyse the
erosion processes, the incision processes of the network, and the
possibility of landslides. This is done by considering that the main
geomorphological processes in a catchment are:
• Diffusive erosion on the hillslopes
• Network incision processes
• Landslides
• Sediment transport in the channels

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HORTON MACHINE: THE HISTORY

• Initially, the Horton Machine was a package of stand alone routines
independent of an operating system, written in C using the
FluidTurtle libraries and their input/output defined formats. The
viewing of the calculated matrices was done with other graphical
programs or with Mathematica;
• The second step was to integrate these routines into GIS-GRASS so
as to have a direct graphical interface in TkTcl;
• Now, with the development of JGrass, these routines are being
rewritten in Java and completely integrated into the new GIS system
with a new development model (OpenMI) and new graphical
interface.

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HORTON MACHINE:
The tools are divided in 7 categories:

•DEM manipulation

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HORTON MACHINE:

•DEM manipulation
•Basic topographic attributes

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HORTON MACHINE:

•DEM manipulation
•Network related measures

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HORTON MACHINE:

•DEM manipulation
•Hillslope analyses

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HORTON MACHINE:

•DEM manipulation
•Basin attributes

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HORTON MACHINE:

•DEM manipulation
•Basin attributes
•Statistic

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HORTON MACHINE:

•DEM manipulation
•Basin attributes
•Statistic
•Hydro-geomorphology

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MORPHOLOGY

The topography is represented by a bivariate continuous function
z = f(x,y) with continuous derivative up to the second order almost
everywhere.
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DIGITAL ELEVATION MODELS (D.T.M.)‫‏‬
The representation of data on a regular rectangular constitutes the most
common and most efficient form in which the digital terrain data can be
found.

In this raster form the data is usually
made by reporting the vertical coordinate,
z, for a subsequent series of points, along
an assigned regular spacing profile.

DEM HYPOTHESIS:

•data are significant

•regular squared grid
•8 direction topology 76

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PRELIMINARY OPERATIONS

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import the starting DEM, which is to be
analysed, into JGrass

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define the working region

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pit detection

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pit detection
D8
(maximum slope)‫‏‬

definition of the drainage directions
D8 with correction
(correction on the direction
of
the gradient)‫‏‬

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pit detection
D8

D8 with correction
of
definition of the main network

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pit detection
D8

D8 with correction
of

identification of the existing sub catchments

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pit detection
D8

D8 with correction
of

identification of the existing sub catchments

extraction of the catchment of interest 77

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DERIVED ATTRIBUTES:

• Local Slope (h.slope)‫‏‬
• Local Curvature (h.curvatures or h.nabla)‫‏‬
• Total Contributing Area (h.tca, h.multitca)‫‏‬
• Catchment Divide Distance (h.hacklength)‫‏‬
• Distance to Outlet (h.distance2outlet)‫‏‬

………..

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FIRST STEP: DEPITTING THE DEM

The first necessary operation is to fill the depression points that
are present within a DEM so that the drainage directions can be
defined in each point.

Observations on this topic demonstrate that this calculation
addresses fewer than 1% of the data: usually these depressions are
present because of wrong calculations during the DEM creation
phase and are not, in fact, real depressions in the terrain.

The command used to fill the depressions is:

h.pitfiller

This tool is based on the Tarboton algorithm.

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h.pitfiller

Fills the depressions in the DEM according to the Tarboton algorithm.

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FLOW DIRECTIONS
Flow directions define how water moves along the surface in relation to the
topology of the study region. From the flow directions it is possible to
calculate the drainage directions.
Hypothesis: each DEM cell only drains to one of its 8 neighbours, either
adjacent or diagonal, in the direction of the steepest downward slope.

only 8 possible directions
in which the flow can be directed

this is a limitation of the model
representation with respect to the
real natural flow
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h.flowdirections

This tool calculates the flow direction on the basis of the
steepest downward slope, assigning to each DEM cell one of
its 8 neighbours.
The flow directions numbering convention numbers from 1
to 8 in an anticlockwise direction with 1 being east.
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FLOW DIRECTIONS

In the map each colour
represents one of the 8
drainage directions. The
image also shows the flow
directions numbering
convention. 83

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FLOW DIRECTIONS

Ho cambiato la
direzione di alcune
frecce qui a lato: da
controllare!

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A CORRECTION TO THE PURE D8 METHOD
Using the “pure” D8 method, the drainage directions that are
estimated deviate from the real drainage direction as identified by
the gradients.
The “corrected” algorithm calculates the drainage direction
minimising the deviation of these from the real flow direction. The
deviation is calculated from the pixels at the highest elevations and
carried through going downstream.
The deviation is calculated with a triangular construction and can be
expressed either as angular deviation (method D8-LAD) or as
transversal distance (method D8-LTD)‫.‏‬
The lambda parameter is used to assign a weight to the correction
made to the drainage directions.
This method has been developed by S. Orlandini

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h.draindir
LAD method:
angular deviation check on alpha

LTD method:
transversal deviation check on
delta

The deviation is cumulated from
up-hill pixels. The D8 drainage
direction is redirected to the real
direction when the value of
deviation is larger than an
assigned threshold.
If λ = 0 the deviation counter has
no memory and the up-hill
pixels do not affect the
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THE NEW DRAINAGE DIRECTIONS &
THE NEW TCA
STANDARD
METHOD

What is TCA?
Total Contributing Area,
ma non si vede fino alla
diapositiva 98.

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THE NEW TCA
STANDARD
METHOD

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THE NEW TCA
STANDARD
METHOD

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THE NEW TCA
STANDARD
METHOD

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THE NEW TCA
STANDARD
METHOD

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h.draindir

What does the 10 value
signify - no flow?

Map obtained categorising the Map obtained personalising the
results of the drainage directions tool colours of the original map
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h.draindir
FIXED NETWORK METHOD: in flat areas or where there are manmade
constructions, it can happen that the extracted channel network does not
coincide with the real channel network.

Fixed network

Extracted network

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h.draindir

FLOW FIXED
METHOD

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h.draindir
FLOW FIXED
METHOD

Flow fixed map created by
h.netshapetoflow from a
shapefile of the network

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h.draindir

Fixed network

Extracted network

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h.draindir

Fixed network

Extracted network

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TOTAL CONTRIBUTING AREA
The Total Contributing Area is precisely this: it represents the total area
that contributes to a particular point of the catchment basin.

It is an extremely important quantity in the geomorphological and
hydrological study of a river catchment: it is strictly related to the flows
passing through the different points of the system in uniform
precipitation conditions.

Most of the diffusive methods used to extract stream networks from
digital models are based on this quantity.

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TCA
Where Wj is:
• 1 for pixels that drain into the i-th pixel;
• 0 in any other case for single flow directions.

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TCA
Where Wj is:

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TCA
Where Wj is:

source

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TCA
Where Wj is:

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TCA
Where Wj is:

source

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TCA
Where Wj is:

1 source

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TCA
Where Wj is:

2

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TCA
Where Wj is:

2

source

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TCA
Where Wj is:

2

1 source

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TCA
Where Wj is:

2

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TCA
Where Wj is:

2

source

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TCA
Where Wj is:

3

2

1 source

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TCA
Where Wj is:

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TCA
Where Wj is:

source

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TCA
Where Wj is:

8 7 6 5 4

3
9
2

1 source

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TCA RESULTS COMPARISON
Log(TCA)‫‏‬ Log (LAD-TCA)‫‏‬

La parte in neretto non
l’ho toccata perche’ non
mi e’ chiara - da
revisionare dall’autore.

The figures compare the total contributing areas calculated with the pure D8
method (left) and with the corrected LAD-D8 method (right). In this latter
case the typical maximum steepest parallelisms are not present with a
representation of the flow very near to reality. 105

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h.markoutlets
The correct execution of many applications within JGrass requires a
matrix of the flow directions that have a new additional class value. This
new class (conventionally indicated in JGrass with 10) identifies the basin
outlets, i.e. those pixels that drain to outside the analysed region.
The tool that assigns this new class value marks the outlets:

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GRADIENTS
The gradients are relevant because the main driving force of the flow is
gravity. The gradient identifies the flow directions of the water and also
it contributes to determining the flow velocity.
It must be observed that the gradient tool, unlike the slope tool, does
not use the drainage directions. It calculates only the module of the
gradient. The gradient is in reality a vectorial quantity oriented in the
direction from minimum potential to maximum potential.

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h.gradients

The sub-surface flow is proportional to the slope while the surface
runoff is proportional to the root of the slope. Erosion, and the resulting
sediment transport, depend on the gradients of the topographic surface.
Furthermore, areas with elevated slope values are generally devoid of
soil, being made up of exposed rock.

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GRADIENTS

We can see the deep
network incision and the
flat area near the basin
outlet.
The obviously wrong
calculation in the upper
part of the basin is due
to the joining of DEMs
that were originally
square in shape.

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h.gradient
The gradient calculated with this tool is given as the tangent of the
corresponding angle.
Using the MAPCALCULATOR it is possible to obtain the map of the
gradients expressed in degrees

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h.gradient
The gradient calculated with this tool is given as the tangent of the
corresponding angle.
Using the MAPCALCULATOR it is possible to obtain the map of the
gradients expressed in degrees

atan(gradient)‫‏‬

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SLOPE
This tool estimates the slope in every point by employing the
drainage directions.
Differently from gradient, slope calculates the drop between each
Non e’ chiaro qui da quale
pixel and the adjacent points below. The resulting measure of drop
gruppo viene selezionato
is divided by the pixel length, grande valore. side or its diagonal according
il piu’ along its

to the cases.
The greatest value is the one chosen as slope.

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h.slope

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CURVATURE
Curvature is a measure of the deviation per unit length of the gradient
vector along a curve, f(x,y), marked on the surface under study.
The Longitudinal Curvature represents the deviation of the gradient as
one moves from upstream Le definizioni sono da
to downstream along the envelope of the
rivedere - l’italiano di
gradients. partenza non e’
chiarissimo.
The Plan Curvature is what is obtained when the surface is intersected
with a plane parallel to the (x,y) plane. It is the variation of the vectors
tangent to the contour line passing through the point under study.
The Tangential Curvature is determined by the intersection curve defined
by a plane perpendicular to the gradient direction and tangent to the
contour line at the point.

The tangental and plane curvature are proportional to each other and the
spatial distribution is the same.
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THE CURVATURES
The mathematical definition is quite complex.

Longitudinal curvature Plan curvature
Convesso --> flussi
convergenti?
it represents the deviation of the --> flussi
Concavo it represents the deviation of
gradient along the flowdivergenti? the gradient along the
transversal direction
(it is negative if the gradient (i.e. along the contour lines)‫‏‬
increases)‫‏‬
it measure the convergence (+)
or divergence (-) of the flow

N.B.
Convex sites (positive curvature) represent convergent flow, concave
sites (negative curvature) represent divergent flow.
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NORMAL/TANGENTIAL CURVATURE

Negative - convex curvature: this
case is typical in slope areas where
the flow is subdivided amongst the
neighbouring pixels with lower
elevation by means of the
maximum slope.

Locally divergent topography

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h.curvature

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h.curvatures
Plan Curvature Longitudinal Curvature

Plan curvatures separates the Longitudinal curvatures highlights
concave parts from the convex ones the valleys 117

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TOPOGRAPHIC CLASSIFICATION
It is a means of subdividing the sites of a catchment according to 9
topographic classes defined by the longitudinal and transversal
curvatures.

The 9 classes are grouped into 3
fundamental typologies:

•CONCAVE SITES
•CONVEX SITES
•PLANAR SITES

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h.tc

The program requests the input of the threshold values of the
longitudinal and normal curvatures which define their planarity.

THE VALUE IS STRICTLY RELATED TO THE TOPOLOGY
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h.tc

This tool produces two different maps as output: one with the 9
topographic classes and the other with the 3 typologies.
For the 9 topographic classes the tagging convention is the following:
10 planar – planar sites
20 convex – planar sites
30 concave – planar sites
40 planar – convex sites
50 convex – convex sites
60 concave – convex sites
70 planar – concave sites
80 convex – concave sites
90 concave – concave sites

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h.tc

The map with the 3 typologies contains an grouping of these topographic
classes into the three fundamental typologies:

15 concave sites (classes 30, 70, 90)‫‏‬
25 planar sites (classes 10)‫‏‬
35 convex sites (classes 20, 40, 50, 60, 80)‫‏‬

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h.tc

h.tc 9 classes h.tc 3 typologies

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CHANNEL NETWORK EXTRACTION

3 METHODS ARE IMPLEMENTED
• threshold value on the contributing areas: only the pixels with
contributing areas greater than the specified threshold are defined as
channel heads‫‏‬
• threshold value on the shear stress at the bottom: threshold value
assigned to the ratio between the total contributing area and the
gradient
• threshold value on the shear stress only in convergent sites

HOW IT WORKS: As soon as the first pixel of the channel network is
identified (i.e. the pixel in which the parameter value is greater than the
assigned threshold) all the other pixel downstream of it are part of the
channel network.
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h.extractnetwork

1°method

Threshold on the tca

The threshold depends on:
- dimensions of the pixels
- topographical attributes

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h.extractnetwork
2°method

The threshold is on the
parameter: Non riesco a leggere
l’immagine.

which is proportional to the
shear stress at the bottom.

- pixels dimensions

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h.extractnetwork

3°method

Threshold on the tca of
the concave sites.

- pixel dimensions

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h.extractnetwork

1°method: threshold on the tca

In the resulting raster map the
network pixels have been
assigned the 2 value. Outside
the network there are null
values.
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h.extractnetwork
2°method: threshold on
the product between the
tca and the gradient

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h.extractnetwork

3°method: threshold on
the tca in the concave
pixels

In this case there are various
groups of stream networks,
each one of which corresponds
to a catchment.

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EXTRACTION OF THE WORKING CATCHMENT
• first, define the catchment outlet:
•insert the known coordinates of the point
•use the Query raster tool to select a point directly on the network map
and verify that it is on the network (i.e. has a value of 2).
•the coordinates of this point will be copied to the clipboard
•use the coordinates of the selected outlet in the h.wateroutlet command

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h.wateroutlet
JGrass generates two maps:
• the mask of the extracted catchment
• a chosen map cut on the mask

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h.wateroutlet

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MORPHOLOGICAL ANALYSIS OF A
CATCHMENT
The first step is to execute all the commands seen so far, but only to the
extracted catchment. An alternative method would be to cut the existing
maps along the mask of the extracted catchment using the mapcalculator
command.
‣ h.pitfiller
‣ h.flowdirection
‣ h.draindir
‣ h.wateroutlet
‣ h.gradient
‣ h.curvatures
‣ h.tc
‣ h.extractnetwork
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MORPHOLOGICAL ANALYSIS OF A
CATCHMENT
The best thing to do is to cut the original maps along the mask of the
extracted catchment. The maps to cut are the following:

‣ drainage directions
‣ total contributing area
‣ extracted network
‣ gradient
‣ curvatures
‣ topographic classes
‣ slope

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h.ab

It calculates the drainage
area per unit length (A/b),
where A is the total upstream
area and b is the length of
the contour line which, it is
assumed, drains area A. The
length of the contour
affected is estimated by a
novel method based on
curvatures.

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h.ab
• concave sites convergent sites
• convex sites divergent sites

The stream network pixels are concave sites.

The contour line is locally
approximated to an arc
with radius inversely
proportional to the local
planar curvature
b ~ t'

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h.ab

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THE RESULT OF A/b

The higher values of A/b are
registered on or near the
channel network.
In fact, these are the points
for which the contributing
area is the highest and the
value of b is the lowest.

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THE RESULT OF A/b CHANGING THE
COLOURMAP

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ASPECT
Mathematically, aspect is defined by the following formula:

The aspect is defined as the inclination angle of the gradient. The
conventional reference system puts the angle to zero when the gradient
is orientated towards east and it grows in an anticlockwise direction.
The angle is calculated in radians.

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h.aspect

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h.aspect

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h.aspect

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h.aspect

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THE LAPLACIAN
The laplacian is a close relative of the curvatures and gives a way to
distinguish, in a first iteration, convex sites from concave sites within the
catchment.
Mathematically, the laplacian is defined as:
Nota a pie di pagina
contrasta con quella di
slide 114 - questa mi
sembra giusta, da
controllare.

N.B. Concave sites (positive curvature) imply converging flows, convex
sites (negative curvature) imply diverging flows.

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h.nabla

Digital terrain data do not return reliable curvature values. On
the other hand, the sign of the laplacian is sufficiently correct.
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DEFINITIONS OF CURVATURES

Negative curvature convex element

Positive curvature concave element

Null curvature flat element

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h.nabla

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h.nabla

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h.gc
This tool subdivides the sites of a catchment into 11 topographical classes.
Nine of these classes are those obtained with TC.

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h.gc

It subdivides the sites of a catchment into 11 topographical classes:
nine of these classes are those obtained with TC;

the points belonging to the channel networks constitute a tenth class

(derived from use of the ExtraNetwork command)
the points with high slope values (higher than a critical value)
constitute an eleventh class.

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h.gc
The reclassification of the topological classes is:
15 non-channel valley sites
25 planar sites
35 channel sites
45 hillslope sites
55 unconditionally unstable sites

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THE HACK LENGTH

It is given, assigned a point in the catchment, by the projection of
the distance from the catchment divide along the network (while
it exists), and then, proceeding upstream along the lines of
maximum slope.
For each network confluence, the direction of the tributary with
the greater contributing area is chosen. If the tributaries have the
same area, one of the two directions is chosen randomly.

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h.hacklentgh

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MAGNITUDO: h.magnitudo

The magnitudo of a point is defined as the number of sources
upstream to that point. It can be defined for every point of the
catchment.
If the river network is a trifurcated tree (a node in which three
channels enter and one exits), then there is a bijective
correspondence between the number of sources, or springs, and
the number of channels, defined as follows:
hc = 2ns − 1
hc is the number of channels
ns the number of sources

The mangitudo is also an indicator of the contributing area.
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MAGNITUDO: h.magnitudo

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NETNUMBERING
This tool assigns numbers to the network connections.
It can be used by the hillslope2channelattribute tool to label the
Please review; original
hillslopes that are contributing tonot very
English version
clear. a section of the network with
the same connection number.
Hence, it subdivides the basin into the hillslope areas that
contribute to each connection.

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SUB-CATCHMENT EXTRACTION: h.netnumbering
The sub-catchments depend on the complexity of the network:
a complex network has a large number of sub-catchments
a simple network has a small number of sub-catchments

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SUB-CATCHMENT EXTRACTION: h.netnumbering
The sub-catchments depend on the complexity of the network:
a complex network has a large number of sub-catchments
a simple network has a small number of sub-catchments

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DISTANCE FROM THE NETWORK
This tool evaluates the distance of every pixel in the catchment
from the network. It can work in 2 different ways:

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h.hillslope2channeldistance

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h.hillslope2channeldistance

• calculates the distance in metres • calculates the distance in pixels

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