Kick-Off Meeting - WP2

Project SLOPE
1
WP 2 – Forest information collection and
analysis

SLOPE WP 2 – Task 2.1
Kick-off Meeting
8-9/jan/2014
Andrea Masini, PhD
Remote sensing and multispectral analysis
Remote Sensing Department
Flyby S.r.l.

Task 2.1: general description
Kick-off Meeting
8-9/jan/2014
• design of an automatic chain that provides a first level forest
inventory exploiting satellite imagery
• calculation of NDVI (Normalised Difference Vegetation
Indices) to monitor tree growth and biomass production also
in mountainous environment
• first level forest inventory used also to drive more accurate
UAV/in-situ measurements
• satellite-based data fusion with other data to achieve more
accurate results

Task 2.1: participants
Kick-off Meeting
8-9/jan/2014
•Flyby S.r.l. (Leader)
• CNR
• Coastway
• TreeMetrics

Task 2.1: expected output
Kick-off Meeting
8-9/jan/2014
• Deliverable D2.01 (month 8 – August 2014) :
Report on remote sensing data collected, on the
methodologies and the algorithm to extract needed
information and on the generated output

Use of satellite data for forestry
Kick-off Meeting
8-9/jan/2014
Satellite imagery can be extremely
useful in the forestry sector in
particular for :
• forest health near real-time
monitoring
• accurate and wide forest
inventory

Kick-off Meeting
8-9/jan/2014
Use of satellite data for forestry
Studies
Different type of analysis

Kick-off Meeting
8-9/jan/2014
LOW SPATIAL
RESOLUTION
EO data used so far for forestry

Kick-off Meeting
8-9/jan/2014
EO data used in the past for
• Cover Change Detection
• Mapping biophysical structure
• Mapping ecosystem services (carbon, water)
• Modelling trends under change scenarios
• Generating management plans

Kick-off Meeting
8-9/jan/2014
The vegetation indexes

Kick-off Meeting
8-9/jan/2014
Forest classification

RapidEye satellite imagery
Kick-off Meeting
8-9/jan/2014

Kick-off Meeting
8-9/jan/2014
RapidEye satellite – Forestry Studies

Kick-off Meeting
8-9/jan/2014
RapidEye satellite - Forestry

Other high resolution satellite data
Kick-off Meeting
8-9/jan/2014
We will investigate the following data:

Kick-off Meeting
8-9/jan/2014
Task 2.1 main objectives
• design of an automatic chain that provides a first level
forest inventory exploiting satellite imagery
• calculation of NDVI (Normalised Difference Vegetation
Indices) to monitor tree growth and biomass production also
in mountainous environment
• first level forest inventory used also to drive more accurate
UAV/in-situ measurements
• satellite-based data fusion with other data to achieve more
accurate results

TreeMetrics
“PROVIDE MOREWOOD FROM LESSTREES”

INVENTORY PLANNING AND MANAGEMENT

WP 2.3: On-Field Digital Surveys:The
Problems
• Productive Area
• Stratification
• Stocking
• Stem Taper Variation
• Stem Quality Variation

Terrestrial Laser Scanning Forest Measurement System
(AutoStem Forest)
Automated 3D Forest
Measurement System

Technology & Services
3. Greater Forest Product Knowledge
Product Volumes
30%
9%
7%
7%
7%
8%
23%
9%
6.1
5.8
5.5
5.2
4.9
4.6
4.3
3.7

WP 2.3: On Field Digital Survey Systems
1. Forest Mapper System (SatForm 3D, Remote
Sensing, Aerial LIDAR & Imagery)
2. Terrestrial Laser Scanning Forest Measurement
System (AutoStem Forest)
3. Real Time Forest Intelligence

1st Phase = Plot Selection
2nd Phase = Stratification

Select the right plot locations =
Better predict log product breakout
Product >50%
Sawlog
Pallet
Pulp

NewWeb Based System: Forest Mapper

New Stand Analytics – Log distribution

Technology & Services
6. ForestValuation

2. Online ForestValuation & Harvest Planning System (The ForestWarehouse)

Full Integration – ‘Closed Loop Control’
Multisource data
Tree modeling
Parameters relationsHarvest control
Forest pre-stratification
Initial area
Spatial generalization
Geostatistics
Area correction
Spatial analysis for
field plots locations
TLS recording
Field survey
Forest Mapping FIELD INVENTORY
Automated Processing
FINAL
STRATIFICATION
WEB SERVICES
DATA ANALYTICS

Some ExampleTrials: International
Validation & Facts
 SkogForsk Sweden 2009/2013
 Coillte Results
 2008 UCC Stats Department
 2010/2011 Industrial Trial Results
 Scotland 2008/2013
 Forest Research, Forest Enterprise Scotland
 James Jones
 Other Results
 Greenwood Resources Oregon
 SkoglandScap Norway
 Forestry South Australia
 US Journal of Forestry
 Island Timberlands Canada

Example: Skogforsk Sweden
Strömsjöliden
Remningstorp
Site Trees Stands
Remningstorp 257 10
Strömsjöliden 586 7

Manual control measurements of all logs
-Diameter and length
-Approximately one diameter per meter
-Average from two diameter
measurements per sampling point
At Remningstorp 34 trees were
measured by the operator using a caliper
Control trees
Example: Swedish Government Validation

Harvester production data
- Stem length and diameter measurements were used as reference
- Sample trees were harvested and harvester data collected
- Diameter measurements registered every 10 cm of stem
- Diameter from approx. 0.8 m height to last cut in tree
Strömsjöliden
Remningstorp

- GIS software onboard harvester for linking tree measurements from
harvester with TLS
- Manually registering made by the operator at the sample plots
Linking harvester measurements with TLS data

meterH
100
200
300
400
500
Height
0 1000 2000 3000
0
100
200
300
400
500
Height
0 1000 2000 3000
Control trees at Remningstorp, stand 343
Spruce 343-1-06Pine 343-3-12
Diameter
Harvester
Control
TLS

Site Species
Number of
trees
Mean trees
size1 (m3) Bias Std Dev RMSE
Remningstorp Pine 94 1.12 0.00 0.13 0.13
1.3% 11.6% 11.7%
Spruce 185 1.01 -0.01 0.11 0.11
-0.9% 9.2% 9.2%
Birch 16 0.44 -0.01 0.10 0.10
-8.0% 15.6% 17.5%
Strömsjöliden Pine 275 0.47 0.02 0.04 0.05
3.0% 8.8% 9.3%
Spruce 339 0.27 0.01 0.04 0.04
2.6% 9.4% 9.7%
Birch 29 0.21 0.01 0.03 0.03
2.6% 12.9% 13.2%
Volume estimates on individual trees
1. Volume: on bark, excluding top
Sweden Final Results: January 2013

Position of in-vehicle device to driver
preference

Shape File & Machine Location: Geo-fence Sound
Alarm, Feature Sound Alarm (Rivers, ESBWires etc.)

Final On-Field Survey:Tree GPS position
and actual product breakout

Kick-off Meeting
8-9/jan/2014
Task 2.4 - 3D Modelling for
harvesting planning

Kick-off Meeting
8-9/jan/2014
• Objectives;
• Scheduling;
• Participants and roles;
• Overview
Outlook

Kick-off Meeting
8-9/jan/2014
Objectives
Task 2.4 Goal: To generate and make accessible a detailed
interactive 3D model of the forest environment.
The WP’s purpose is to develop methodologies and tools to
fully describe terrain and stand characteristics, in order to
evaluate the accessibility for and efficiency of harvesting
technologies in mountain forests.

Kick-off Meeting
8-9/jan/2014
Scheduling
Start Month: 7
End Month: 15
Deliverable: Harvest simulation tool based on 3D forest model
Total MM: 20
Task leader: GRAPHITECH;
Participants: CNR, KESLA, COAST, BOKU, GRE, FLY, TRE

Kick-off Meeting
8-9/jan/2014
Participants role
GRAPHITECH(10): Task Leader. It has in charge the development of tool for representing
the virtual 3D environment of the mountain forest as well as the of the virtual system
on mobile and machine-mounted displays. Finally it will be involved into the
developmet of the solution for interactive cableway positioning.
CNR(1): Definition of the “technology layers” (i.e. harvest parameters) and
methodologies to coordinate tree marking with the subsequent harvesting operations.
KESLA(1): Acting as final user in order to simulate the behaivor of own machine into the
virtual system
COAST(2): Provide the input model for the virtual system combining the information of
task 2.1, 2.2 and 2.3

Kick-off Meeting
8-9/jan/2014
Participants role
BOKU(2): it will be involved into definition of the “technology layers” (i.e. harvest
parameters) then on the developmet of the solution for interactive cableway
positioning.
GRE(1): Acting as final user in order to simulate the behaivor of own machine into the
virtual system
FLY(1): Provide the input model for the virtual system combining the information of task
2.1, 2.2 and 2.3
TRE(2): Development of the Forest WarehouseTM for mountain forestry and support
the deployment of the virtual system on the machine-mounted display

Kick-off Meeting
8-9/jan/2014
Platform Core
Using the remote data (Satellite, UAVs orthophotos and digital surface model) combined
with on field information (TLS), each single tree feature will be segmented including its
deducted geometric properties.
Task 2.1
Task 2.2
Task 2.3
3D forest model
Virtual 3D
environment

Kick-off Meeting
8-9/jan/2014
3D Modelling for harvesting planning
What we mean with 3D forest modelling?

Kick-off Meeting
8-9/jan/2014
Functions
• Forestry measurements estimations;
The platform will allow the combination of accurate tree profile information
with up to date remote sensing data.
• Interactive system for cableway positioning simulation.
• Definition of the “technology layers” (i.e. harvest parameters);
Technological layers show technical limitations of machines and
equipment on different forest areas.
• Deployment of the virtual system on mobile and machine-mounted displays.

Kick-off Meeting
8-9/jan/2014
Functions
• Forest WarehouseTM (Treemetrics) for mountain forestry integration;
The Forest Warehouse is a web-based forest planning system that performs
bucking (log making) simulation through software developed by TRE.

Kick-off Meeting
8-9/jan/2014
3DVisualizationTechnologies
Interfaces Scenario
• Desktop
• Mobile
• In-vehicle embedded
Systems
Approaches
• Desktop Visualization Platform
with Mobile Porting
• Web-Client Visualization
Platform
Desktop Platform
• Open-Source Library for 3d
visualization (OpenInventor, Vtk,
Openscenegraph)
• 3d Engine ( UdK, Irrichlicht
Engine, Unity 3d)
Technologies
Web Client
• WebGL : implementation of
OpenGL ES 2.0 for web,
programmable in JavaScript
• Java Applet based on Opensource
Globe Nasa World wind

Kick-off Meeting
8-9/jan/2014
Thank you for your attention
DR. FEDERICO PRANDI
Federico.prandi@graphitech.it
Fondazione Graphitech
Via Alla Cascata 56C
38123 Trento (ITALY)
Phone: +39 0461.283394
Fax: +39 0461.283398

Project SLOPE
61
T 2.5 – Road and Logistic planning
Trento, January 8th, 2014

Index
62
1. Task objectives
2. Approaches for sites location and flow allocation decisions
3. Approaches to estimate traffic in existing roads
4. Proposed work plan
5. Contact info

1.Task objectives
63
 Task objectives:
 Identify and analyze logistics elements within the forest and their characteristics
for site locations and flow allocation decisions
 Integration of the data with the global forest model
 Build and validate and Optimization model to allocate landings with the mills and
plants
 Build a model to estimate traffic on individual sections for road maintenance and
construction purposes
 To be developed from M8 to M13
 Includes development of “D2.05 Road and logistic simulation module”
 Due to Month 13.
 Partners involved: all
 ITENE (leader), GRAPHITECH, CNR, BOKU, FLY

2. Approaches for sites location and flow
allocation decisions
64
 The goal is to determine an optimal (minimum cost) forest logistic
network to respond future demands
 The approach should determine:
 Location of facilities (specially for new requirements)
 Size an capacity of facilities (storage areas and processing sites)
 Volume to harvest in every landing and stand area
 Volume of timber to transport from landings to facilities (it gives a
first estimation of road traffic for road planning)
 Volume of product to transport from facilities to demand sites
 The model should consider inputs like location of landing áreas,
intermediate sites (storage, buffers), processing sites, demand sites,
demand volumes, routes, type of routes and distances between theses
sites.

65
 Location of a single facility by center-of-
gravity method
 Output: XY coordinates for the facility
 Optimization based only on distances
 Binary model (source-sink)
 Useful for a first estimation of a facility location
to be supplied from specific lands

66
 Location of selected number of facilities
by the exact center-of-gravity method
 Output: XY coordinates of a selected number
of facilities
 Optimization based only on distances
 Useful for a first estimation of 2 or more
facility locations to be supplied from specific
lands

67
 P-median multiple facility location
 Output: selected facilities from a list of
candidate sites receiving flows from other sites
 Optimization based on transport costs and fix
costs, but lack of capacity constrains and other
inventory costs
 Useful for a first estimation of 2 or more facility
locations to be supplied from specific lands

68
 Mixed integer linear programming
problem
 Output: selected facilities and optimal flows
between nodes
 Optimization based on transport costs and fix
costs, capacity constrains and inventory costs
 Three stages model
 More appropriate approach for a network with
more than 2 node types
lands in
forest
storage
and
facilities
(saw, mills,
biomass)
Demand
sites

69
 Dynamic linear programming
 Consider changing demand
 Output:
 Selected facilities
 Size an capacity of facilities (storage and processing sites)
 Volume of harvest in every landing and stand área
 Volume to transport:
 Timber from landings to facilities
 Product from facilities to demand sites
 Decision to expand production capacity in a specific
period in the planning horizon
 Minimize total costs for timber supply and
transport, investment and operational costs,
product transport cost to demand sites, fixed
cost for capacity expansion
-
200
400
600
800
1.000
1.200
1 2 3 4 5 6 7
Period Demand Volume
lands in
forest
storage
and
facilities
(saw,
mills,
biomass)
Demand
sites
(normally
cities)

70
 Previous Work
Facilities Location Models: An Application for the Forest Production
and Logistics
JUAN TRONCOSO T. 1, RODRIGO GARRIDO H. 2, XIMENA IBACACHE J. 3
July 2002
1 Departamento de Ciencias Forestales, Pontificia Universidad Católica de Chile, Casilla 305,
Correo 22, Santiago, Chile. E-mail: jtroncot@puc.cl
2 Departamento de Ingeniería de Transporte, Pontificia Universidad Católica de Chile.
3 Escuela de Ingeniería Forestal, Universidad Mayor.

71
 Stand
Cable
ways
forest
lanes

72
minor
road
main
road
land
land
land
stand
stand
stand

73
Solution flow
Possible flow
lands in forest storage and
facilities (saw,
mills, biomass)
Demand sites
(normally cities)

74
 INPUTS
 Demands of product per each period and type of quality from demand site
 DATA COLLECTION FOR THE MODEL
 Positions of stands, lands, storage areas, processing sites (saw, paper mills and
biomass heating and power plants), demand sites
 Volume available to harvest in every stand per quality of timber and destination (saw,
mill or energy)
 Position for stand respect existing roads
 Slope or grade of difficulty to access
 Capacity of ground to support specific machinery
 Size and availability of skyline deployment sites
 Capacity and location of storage areas and buffers, and processing sites
 Characteristics of processing sites and conversion facilities
 Distances between different nodes

75
 COST FACTORS
 supply and transport operational costs
 final product transport cost to demand sites
 fixed cost for capacity expansion during the planning horizon
 investment associated to construction of a new site
 OUTPUT
 Selected facilities
 Size an capacity of facilities (storage and processing sites)
 Volume of harvest in every landing and stand área
 Volume to transport
 Timber from landings to facilities
 Product from facilities to demand sites
 Decision to expand production capacity in a specific period in the planning horizon

76
 Once the different sites and locations have been selected, and flows between
sites have been determined for each future period,
 A Logistics Resource Planning Model will be used to determine the volume to
harvest in every period in every land, processing and transport means, and a
more precise estimation of traffic in every individual sections of road in terms of
number of trip per vehicles type (size, weight) in each period
 This traffic estimation will allow to define plans for road maintenance and
construction in the forest area, taking into account the capability of roads to
accept trucks and cranes of different weights and sizes

77
 Similarities to DRP method
Land 1
SITE: Saw Plant
X
City 1
Product demandHarvest orders
Land 2 City 2

78
SITE: Saw Plant X
Minumum Batch (harvest) (m3/period) 500
Lead time (number of periods) 1
Safety stock (m3) 200
Period 1 2 3 4 5 6 7
Demand Volume (m3) 400 500 600 1.000 500 600 1.000
Available Stock (m3) 700 300 300 200 200 200 100 100
Harvest recepcion (m3) - 500 500 1.000 500 500 1.000
Harvest order launch (m3) 500 500 1.000 500 500 1.000
Land 1
To harvest (m3) 500 500 1.000
Available m3 in land 1 2.000 1.500 1.000 -
Size of vehicle (m3) 10
Number of vehicle trips size 10m3 50 50 100
land 2
To harvest (m3) - - - 500 500 1.000 -
Available m3 in land 1 3.000 2.500 2.000 1.000 1.000
Size of vehicle (m3) 10
Number of vehicle trips size 10m3 50 50 100 -

3. Proposed work plan
79
 Understand the forestry supply chain and logistic processes. Choose a real scenario (ITENE, BOKU)
 Review literature and formulate an Optimization model for logistics site location and flow allocation
decisions (BOKU)
 Define a model to estimate traffic in existing roads (CNR)
 Identify elements for the models:
 Relevant logistics locations within the forest (GRAPHITECH, CNR, FLY, ITENE)
 Gather info and contact with the different agents of the forest product processing (ITENE)
 Define and analyze relevant characteristics of the logistics elements (ITENE)
 Integration with the global forest model (ITENE)
 Implement the Optimization model to allocate landings with the mills and plants and traffic calculation
on individual sections (BOKU)
 Validation of model with a real scenario (BOKU)
 Implement the model for road planning based on the amount of timber to be transported and
identification of traffic on existing forest infrastructure (CNR)

4. Contact info
80
 Emilio Gonzalez
 egonzalez@itene.com
 Patricia Bellver
 pbellver@itene.com

Kick-Off Meeting - WP2

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Kick-Off Meeting - WP2