Mid-term Review Meeting - WP1

Mid-term Review2/Jul/15

Project SLOPE1

WP 1 Definition of requirements and system analysis


Project SLOPE2

T1.1 Users and System requirements

Brussels, July 2th, 2015


Overview

Status: Completed (100%) Length: 3 months (from M1 to M3) Involved Partners

Leader: ITENE Participants: GRAPHITECH, CNR, KESLA, COAST, MHG, BOKU,

FLY, GRE, TRE Aim: Gather information about user requirements to guide

future developments Output: Deliverable D1.01 (Submitted)


Procedure4

1. Identifying user groups

2. Developing functionalities

3. Creating relation Matrix

4. Developing questionnaires

5. Contact with End Users

6. Anlysis and conclusions


1. Identifying user groups5

1. Forest owners

2. Harvesting contractors

3. Transport companies

4. Mill companies

5. Biomass processing companies

6. Foresters / specialists


2. Developing functionalities6


3. Creating relation Matrix7


4. Developing questionnaires8


5. Contact with End Users9

Forestry related partners identified possible contacts

Phone / personal meeting were done to fill in questionnaires

Detailed info needed -> detailed questionnaires -> long time needed to answer them

Average time per contact in interviews: 30min - 1h


6. Anlysis and conclusions10

Total: 23 questionnaires

Locations: Austria, Italy (Trento), Finland, Ireland


6. Anlysis and conclusions11

PlanningFor selecting a harvesting area, the system should:

Consider cost and demand as a factor to select a harvesting areaDetermine the volume of timber available in the harvesting zoneAllow to know the age of treesMeasure trees heightDetermine slope and roughness of the terrainDetermine accessibility of the zone (road placement)

For marking a tree, the system should:Measure dimensions of treesDetermine quality of woodRegister specie and age of treesBe able of read all this information just before marking a treeIdentify trees unmistakably


Deliverable Index D1.0112

All info and results gathered in D1.01


Deliverable Annex13


Mid-term Review 2/Jul/15

Contact info

Juan de Dios Daz ([email protected])Emilio Gonzalez([email protected])

Thank you for your attention

mailto:[email protected]:[email protected]


Project SLOPE

T1.2 Hardware and equipment definition



Overview

Status: Completed (100%) Length: 3 Months (From M1 to M3) Involved Partners

Leader: Graphitech Participants: CNR, COAST, MHG, BOKU, FLY, GRE, ITENE

Aim: define the hardware and machinery specification on a system requirements basis

Output: D.1.04 Technical Requirements Report


GoalsThe Objective of the task was:

Define the Hardware and Software equipment including; Instruments and tools to collect forest information before

harvesting; Instrument and tools to collect timber information during the

harvesting; Instrument and tools for resources tracking;


Workflow


Forest SurveyRemote Sensing Information from: satellite, aerial, UAVs and Terrestrial laser Scanning: Multiresoultion forest survey

Satellite: Large scale (region), several repetion along time. Cost depending on spatial resolution

Airborne: Medium Scale (depending of altitude) not suitable for multiple repetion. High cost

UAVs: Small scale (plot) possible multiple repetion, high resolution. Medium Cost

TLS: Very small scale (portion of plot), Information not achieved from the above. Time consuming Medium cost.


Satellite Images

Technical SpecificationsNumber of Satellites: 5Orbit Altitude: 630 km in Sun-synchronous orbitGlobal Revisit Time: 1 DayInclination: 97.8 degrees (solar-synchron)Ground sampling distance (nadir): 6,5 mPixel size (orthorectified): 5 mSwath Width: 77 km

Sensor Bands440 510 nm (Blue)520 590 nm (Green)630 685 nm (Red)690 730 nm (Red Edge)760 850 nm (Near IR)


UAVVehicle 96cm wingspan Less 0.55kg dry-weight (0.68kg with RGB payload, 0.71kg with NIR payload) 45-50 minute flight time 40-90 km/h cruise speed Up to 45km/h or 12m/s wind resistance Up to 3Km radio link Up to 12sqkm coverage Linear landing Image resolution/pixels of 3-30cm Autopilot Payload Resolution 16MP 35 mm equivalent focal length 24mm Flight altitude (4cm/px GSD) 130 m


Workflow

1

2

3

4

5

5

6

6


Trees markingTagsUltra High Frequency RFID tags work at 868-902MHz. Standard for logistics and storageapplications.

Low cost (passive tags) and long reading range(4-5 meters).

Reader

Fully integrated handheld UHF RFID USB/Bluetooth reader


Cableway and Carriage

Check the weight of the timber Read the tags Check the presence of operators

below the line Open automatically the

electronic chockers Communicate with processor

head and with the server and the black box, transmitting the current situation, such asposition, working speed, fuelconsumption


Processor Head Processor model ARBRO 1000 S

The factors determining the hydraulic demand (the resistance to advance) are the density/size of branches and the friction of the knives against the bark.

The lower productivity compared to roll processors is not influent, since the extraction of trees by cablecrane is relatively slow.

Relatively simple structure and electronics.


Head Processor1. Machine control

system2. External control

system Compact rio + Externalindustrial pc

3. Actuators direcltycontrolled from machine control system.

4. External sensors.

1

2

3 4


Head Processor

1) The new actuator bar for scanners scanning the cross section of log 2) Chain sawing module for sensing cutting forces and optimization of the cross-cut3) Feed power sensor4) Camera/3D vision sensor5) Colour camera(s) scanning side of the log 6) Ultrasound stress wavevelocity scanner 7) RFID reading system12

3

4

5

6

7


Tracking system

Option 1 included manual RFID reader and tracking device in trucks,

Option 2 included fixed RFID reader with tracking device integrated in the truck.


ConclusionsThe Achievements of the task are: Hardware and Software requirements have been defined; The identified resources will be the input for the future

developments during each specific tasks; The requirements and hardware sorted out from this deliverable

are the backbone of SLOPE system, however some future refinements can be needed.

The left of the responsible partner KESLA has caused a delay on deliverable submission, however all the adopted remedial actions have ensured that this had no effect on the other task activities.


Contact info

Federico Prandi: [email protected]


mailto:[email protected]


Project SLOPE

T1.3 Human Machine Interface (HMI) definition

Brussels, July 2nd, 2015


Task Overview

Status: Completed (100%) Length: 3 Months (From M2 to M4) 5 Involved Partners

Leader: GraphiTech Participants: MHG, GRE, TRE, ITENE

Aim: define the user interface for the whole SLOPE system, including: User interface needs Web user interface requirements In-vehicle and on-field devices interfaces

Output: D.1.02 Human Machine Interface


Process State of the art

User interfaces in forest production

Analysis of available user interfaces within consortium

Interface Requirements analysis Actors Use Cases

Interfaces definition Web client Mobile client In-vehicle client ERP


User Interface Analysis

Human-Machine Interfaces can be seen as the parts, software or hardware handling the interaction between humans and machines[] Computer can have several different purposes ending in an open-ended dialog between users and computer.



Analysis of each available interface and classification against different types of HMI:

Direct manipulation interface Graphical user interface (GUI) Web User interfaces (WUI) Command Line Interfaces Touch User Interfaces Hardware User Interfaces Batch Interfaces Gesture interfaces

Intelligent User Interfaces Non-Command User interfaces Object Oriented User interfaces Tangible User Interfaces Task-Focused Interfaces Text based interfaces Zero Input Interfaces



Available interfaces Grap

hica

l use

r in

terf

ace

Web

-bas

ed

inte

rfac

e

Touc

h us

er

inte

rfac

e (M

obile

)

Hard

war

e In

terf

ace

Batc

h In

terf

ace

Touc

h U

ser

Inte

rfac

e (V

ehic

le)

Inte

llige

nt U

ser

inte

rfac

e

Dire

ct

Man

ipul

atio

n In

terf

ace

Task

focu

sed

inte

rfac

e

Ges

ture

Inte

rfac

e

Forestry Resource Planning System (MHG) V V V

Forest Analysis and Monitoring (TREE) V V V V V

Intelligent Harvesting Heads V V V

Cable Crane System (GRE) V V V

Geographical Information System for Environmental Planning (GRAPHITECH)

V V V V


User Interface Requirements

From: User requirements reports (D.1.1) SLOPE reference scenario

Results: Requirements list Use cases by actor and interface


User Interface Requirements List

Selecting and planning harvesting area Provide trees information (height, age) Provide area information (available timber volume, ) Determine slope and roughness of the terrain Determine accessibility of the zone (road placement, road width, road slope, landing areas)

Tree marking Register specie and age of trees Be able of read all this information just before marking a tree

Cable Corridors Allow the estimation of total amount of timber to be harvested. Allow the selection of the intermediate support.

Cost Estimations Show harvesting costs based on users planning choices

Traceability Provide location of logs


User Interface Requirements List

Harvesting monitoring/tree identification Show weather conditions and forecast. Estimate market demands. Obtain values of productivity and statistics of development of harvesting activities (related to the plan). Detect unmistakably each tree, accordingly to how it was marked. Show tree data before harvesting operation.

Contingency plans Show possible failures or breakages

Online Purchases Register species of trees Develop a platform including mentioned characteristics and specifying provenance of logs

Inventory Show logs in different states (standing, ready to be harvested or harvested) Show accessibility of the zone (road placement) Show quality of wood


Use cases


Human Machine Interfaces Design

Based on principle of least astonishment human beings can only pay attention to one thing at one time exploit users' pre-existing knowledge as a way to minimize the learning

curve functionally similar or analogous programs with which your users are

likely to be familiar

Takes in account a conservative sector like Forestry

Takes in account already existing consortium platforms


HMI Design - Desktop

Web based application (HTML5/WebGL Based) Easy integration into other systems Task based interface

Analytics Operation Forest


HMI Design - Desktop

Main Functionalities: Analytics: set of tools to retrieve geometrical and geophysical (like slope and soil

components) information about the property and about the places of interest fordetermined operation or dataset

Terrain Providers, Imagery Providers, Measurement, Slope Analysis, Cadastral & Public Data,Points of Interest, Roads

Operation: tools to manage different operation related to harvesting and to plan themin determined temporal interval

Cableway Planning, Working Area Setup, Felling, Buildings & Terminals, Logistic, HarvestTracking, Weather Forecast

Forest: Tools to inspect the forestry inventory datasets and all the operation related toforest resource planning.

Area Selection, Trees Visualization, Virtual Marking, Stem Visualization Tool


HMI Design Desktop - Analytics

View of the Ground lidar scan or images

Inspect datasheet and forestry operation chart s of ana area


HMI Design Desktop - Operation

Road construction and set property boundary

Insert in the scenario all the structure to plan the operation


HMI Design - Mobile

Main Functionalities: Tree and Forest Inventory: singe tree and area inspection. Logs and wood: to obtain the position on the map of all

the logs that have to be harvested. Machines: to visualize on the map the area of work and

the evolution of the harvesting and felling procedures Virtual Forest: show a simplified version of the forest

developed for the desktop platform Layers: Select additional layers to be applied to the map. Transportation: to show road and truck fleet movement

Subset of desktop functionalities Exploits mobile device capabilities (e.g. GPS, Camera) Tagging support for Forest Operators


HMI Design In-Vehicle

Enrich already existing In-Vehicle systems Based on:

TRE RTFI: Harvest Production Monitoring & Control In-Vehicle Harvesting Head control system

PDA or Large screen tablet (10+ inches) 3 parts: Map, Function menu, Widget menu

Main Functionalities: Map & Function menu: similar to mobile Widget menu:

Quality Index: currently processed log quality Operation: to access scheduled operations Manage work time: set break intervals, optimize scheduling based on conditions Report issue: like failure/breakage, emergency call, etc. Work time clock: time left before break Climate and weather information: like weather forecast


HMI Design In-Vehicle

Widget menuReal-time quality index

Function menu

Map


HMI Design ERP Module

Separated interconnected views 1 unique portal

Management of log inventory Online purchasing/auctions For wood buyers/sellers and

sawmills One web interface with different

views and modules


Conclusions

Guidelines for the definition of the SLOPE project interfaces Web Mobile In-vehicle Integrated ERP system

Based on: State of the art Use cases Explicit requirements

Subject to changes during the integration phase User requirements Integration testing feedbacks


Contact info

Daniele Magliocchetti: [email protected] Panizzoni: [email protected]



Project SLOPE

T1.04 Mountainous Forest inventory data model definition

WP 1 - Definition of requirements and system analysis



Overview


Leader: CNR Participants: GRAPHITECH, COAST, MHG, BOKU, FLY, GRE, TRE

Aim: To define the required information for the FIS data population. Define data and metadata model of the FIS

Output: D.1.03 [M6]


Data formats and standards

Spatial Data

Standards for Openness and Technical Interoperability INSPIRE

Spectral data

Data collected by the harvesting machines

Sensor standards

Forestry related standards

Automatic Identification and data capture

Standards in Entity Identification

Geographic Standards


Data formats and standardsSpatial Dataseveral typologies of spatial data anddifferent source of geographic information

Spectral Dataspectroscopy for the analysis of wood chemical-physical properties, hyperspectral imaging of wood, hyperspectral imaging of forest.


Data formats and standardsData collected by the harvesting machinesRelevant variables, representing the characteristics of the harvesting system in the SLOPE scenario, will be measured with transducers/sensors. Some of the measured variables aim at monitoring machines parameters, enabling security, energy-saving, real-time control and automation functionalities. Some machines parameters will be also correlated to quality indices of the harvested material (e.g. cutting quality index).Another series of data are those collected by the sensors to determine parameters related to the wooden material characteristics (i.e. data from NIR and hyperspectral sensors, data from stress wave tests) or to measure geometrical features of the logs.


Integrated models

Multisource data

Multiscale data

Multitemporal data

The realization of forest inventories is strongly related to the harmonization of different data provided by different sources (different remote sensing or ground-based measurements) with different scales (different spatial and temporal resolutions) and different units. This process can be performed by means of dedicated elaborations and databases with geographical referencing functionalities (GIS).


Overview of existing databases and services

EU forest datasets

Datasets available in the SLOPE pilot areas

ITAL

Y

Tren

to P

rovi

nce

AUST

RIA

Sal

zbur

g


Required information to populate the FIS

to develop an interactive system for cableway positioning simulation (CwPT)

to assist tree marking forestry measurements estimations (TMT)

to define technology layers (harvest parameters) (TLT)

to support novel inventory data content (IDC)


Annex A:

TABLES OF DATASETS FOR FIS POPULATION

TABLE A1: FOREST

FOREST

INFORMATION

(definition) [unit]

INPUT DATA

TYPE

[SCALE/spatial resolution]

{temporal resolution}

STANDARD

RELEVANCE

SOURCE/

SENSOR

High relevant

Relevant

Mod. relevant

Not relevant

TMT

TLT

CwPT

IDC

TERRAIN

Elevation

(height above ellipsoid -GPS- or height above geoid -Mean Sea Level -MSL)

[m]

Information directly derived from input data

Vector contour lines

DEM

raster elevation data

[Spatial Resolution: from 90 m to 10 cm]

shape files,

Geotif ,

DTED

Topographical data sources

SRTM elevation data

LiDAR data

Slope

(per cent change of elevation over a specific area)

[%]

Information derived from elevation

Vector contour lines

DEM


[typical resolutions of 1 arc-second (approx. 30 meters) and 1/3 arc-second (approx. 10 meters), and in limited areas at 1/9 arc-second (approx. 3 meters)]

geotif image


SRTM elevation data

LiDAR data

ALS

Aspect

(horizontal direction to which a mountain slope faces

Aspect is the direction of the maximum rate of change in the z-value from each cell in a raster surface)

Information derived from slope

DEM


geotif image


SRTM elevation data

LiDAR data

Topographic roughness (ruggedness)

(e.g. standard deviation of slope, standard deviation of elevation, slope convexity, variability of plan convexity)

Information derived from slope

DEM


WCS


LiDAR data

ALS

Canopy height model (CHM)

(representation of the difference between the top canopy surface and the underlying ground topography)

Derived from DTM and DSM

(by filtering LiDAR point clouds to separate ground and canopy hits)

WCS

LiDAR data

ALS

FOREST STAND

Forest structural type

(Land-use and land-cover classification of forest and non-forest areas)

Raster maps

vector maps

Multispectral images

Land Cover datasets

FI

LiDAR data

Location

GIS coordinates

ETRS89

GRS 80

SRID

UTM

WGS84

StanForD

GPS

Ownership of the plot/s

(public or private ownership)

Cadastral raster maps/vector data

Alpha-numerical data

Land Parcel Identification System

StanForD

Land registry

Identification of the plot

[ID]


StanForD

FMP

Stand boundaries

Cadastral raster/vector data


Land registry

FMP

Size of stand

[hectare]



Land registry

Size of harvesting unit

[hectare]

Vector data

FMP

Stand density

(a quantitative measure of stocking expressed either absolutely in terms of number of trees, basal area, or volume -with or without bark- per unit area, or relative to some standard condition)

[number of trees/ha]


FMP

Harvest plan

Basal area

(cumulative area of the trees sections at breast height)

[m2/hectares]


FMP

Harvest plan

Standing volume

(the timber volume of all the standing trees in a forest stand. It can include the sole commercial timber volume -up to a minimum diameter-, all the tree volume -including non commercial stem volume, branches and tops- or present this data in a more comprehensive form -commercial volume, residual volume, total volume-)

[m3]


FMP

Harvest plan

Forest harvest intensity/removal rate

[%] percentange of the original standing volume

[n. marked trees/ha]

[m3]

Data derived from marked trees and original standing volume


FMP (as recommendation)

Harvest plan

Silvicultural practice

(silvicultural perscriptions at the stand )


FMP

TREE

Individual position of trees

Data derived from Laser scan data and UAV

GIS coordinates

Point cloud files

Shape files

Kml files

1 LiDAR data

2 ALS

3 TLS data

Tree DBH

(Average DBH value

Individual DBH value)

[cm over bark]

cm over bark

StanForD

4 Caliper measurement

5 TLS data

Tree Height

(Average height value - Individual height value of the vertical distance from ground level to the highest green point on the tree)

[m]

Information derived from the CHM

WFS

1. Relascope/ tape method measurements

2. Fertility class of the stand and DBH

3. TLS data

Tree Volume

(cubic measure of the amount of wood including stem, branches, stump and roots)

[m3]

Information derived from trees height, basal area, shape

TLS data

Tree Species

Percent species composition

Individual tree species

[species name]

Information derived from in field survey or determined from NDVI and RENDVI, or RGB images

Species Code

Norway Spruce = NS

Strata

StanForD

FI


RGB areal photos

Age of trees

(Percent age composition)

FI

FMP

Statistical, historical data

Field sampling (coring)

Crown width

(average of four perpendicular crown radii)

[m]

Index number for each tree with XYZ Coordinate for each tree

WFS

1. LiDAR

2. ALS

Crown thickness

(Live crown depth)

[m]

RGB data photographic

1. Multispectra LiDAR data

2. ALS

Stem volume

(above ground volume production, without branches and stump)

[m3]


StanForD

1. LiDAR data

2. ALS

3. TLS data

Stem straightness

[cm/m]

Stem diameter at 10cm intervals up the tree. Each diameter has a XYZ for the center point of the tree

StanForD

4. TLS

Stem taper

Diamater measurement at 10cm intervals to 7cm min top diameter

StanForD

1. ALS

2. TLS

3. CTL-harvester measurements

Stem length

[m]

TLS


Tree leaning

[%]

XYZ center point for each diameter interval

StanForD

2. ALS

3. TLS

Branchiness

[number of branches / lm]

Branch diameter in CM embedded in stem file

1. TLS


Position of the lowest branch in the trunk

Embedded in stem file with XYZ position up the tree

1. TLS

Damaged trees

(Insect attacks

Fungi attacks

Failed trees)

Information derived from the NDIV

From in field inspection

1. ALS

2. Hyperspectral images

Marked trees

Virtual flag

FMP

RFID tags

Physical flag

RESTRICTIONS

Accessibility

(if any machine can reach the harvesting site)

Information derived from road network, slope and topographic roughness

Raster maps

Geospatial vector data


SRTM elevation data

Lidar data

ALS

FMP

Bearing capacity

(maximum average contact pressure between the harvesting machines and the soil which should not produce shear failure in the soil)

[kN/m2]

Site classification map

Snow cover

(minimum height of snow that hampers harvesting activities for a certain period and area)

[days]

Information derived from hydrological data

Hydrological datasets

Presence of protected animal species

Type of restrictions

Field survey

FMP

Presence of protected trees

GIS coordinates of protected trees


FMP

Protected reserves

Map and borders


FMP

FOREST

INFORMATION

(definition) [unit]

INPUT DATA

TYPE

[SCALE/spatial resolution]

{temporal resolution}

STANDARD

RELEVANCE

SOURCE/

SENSOR

High relevant

Relevant

Mod. relevant

Not relevant

TMT

TLT

CwPT

IDC

FOREST STAND

Forest structural type

(Land-use and land-cover classification of forest and non-forest areas)

Raster maps

vector maps


Land Cover datasets

FI

LiDAR data

Location

GIS coordinates

ETRS89

GRS 80

SRID

UTM

WGS84

StanForD

GPS

Ownership of the plot/s

(public or private ownership)

Cadastral raster maps/vector data



StanForD

Land registry

Identification of the plot

[ID]


StanForD

FMP

Stand boundaries



Land registry

FMP

Size of stand

[hectare]



Land registry

Size of harvesting unit

[hectare]

Vector data

FMP

Stand density

(a quantitative measure of stocking expressed either absolutely in terms of number of trees, basal area, or volume -with or without bark- per unit area, or relative to some standard condition)

[number of trees/ha]


FMP

Harvest plan

Basal area

(cumulative area of the trees sections at breast height)

[m2/hectares]


FMP

Harvest plan

Standing volume

(the timber volume of all the standing trees in a forest stand. It can include the sole commercial timber volume -up to a minimum diameter-, all the tree volume -including non commercial stem volume, branches and tops- or present this data in a more comprehensive form -commercial volume, residual volume, total volume-)

[m3]


FMP

Harvest plan

Forest harvest intensity/removal rate

[%] percentange of the original standing volume

[n. marked trees/ha]

[m3]

Data derived from marked trees and original standing volume


1. FMP (as recommendation)

2. Harvest plan

Silvicultural practice

(silvicultural perscriptions at the stand )


3. FMP

TREE



GIS coordinates

Point cloud files

Shape files

Kml files

1. LiDAR data

2. ALS

3. TLS data

Tree DBH

(Average DBH value


[cm over bark]

cm over bark

StanForD

4. Caliper measurement

5. TLS data

Tree Height


[m]


WFS



3. TLS data

Tree Volume


[m3]


1. TLS data

Tree Species



[species name]


Species Code

Norway Spruce = NS

Strata

StanForD

2. FI

3. Multispectral images

4. RGB areal photos

Age of trees


1. FI

2. FMP

3. Statistical, historical data

4. Field sampling (coring)

Crown width


[m]


WFS

1. LiDAR

2. ALS

Crown thickness

(Live crown depth)

[m]



2. ALS

Stem volume


[m3]


StanForD

1. LiDAR data

2. ALS

3. TLS data

Stem straightness

[cm/m]


StanForD

4. TLS

Stem taper


StanForD

1. ALS

2. TLS


Stem length

[m]

5. TLS


Tree leaning

[%]


StanForD

2. ALS

3. TLS

Branchiness



1. TLS




1. TLS

Damaged trees

(Insect attacks

Fungi attacks

Failed trees)



1. ALS


Marked trees

Virtual flag

FMP

RFID tags

Physical flag

RESTRICTIONS

Accessibility



Raster maps



SRTM elevation data

Lidar data

ALS

FMP

Bearing capacity


[kN/m2]


Snow cover


[days]





Field survey

FMP




FMP

Protected reserves

Map and borders


FMP

TREE



GIS coordinates

Point cloud files

Shape files

Kml files

1. LiDAR data

2. ALS

3. TLS data

Tree DBH

(Average DBH value


[cm over bark]

cm over bark

StanForD

4. Caliper measurement

5. TLS data

Tree Height


[m]


WFS



3. TLS data

Tree Volume


[m3]


1. TLS data

Tree Species



[species name]


Species Code

Norway Spruce = NS

Strata

StanForD

2. FI

3. Multispectral images

4. RGB areal photos

Age of trees


1. FI

2. FMP

3. Statistical, historical data

4. Field sampling (coring)

Crown width


[m]


WFS

1. LiDAR

2. ALS

Crown thickness

(Live crown depth)

[m]



2. ALS

Stem volume


[m3]


StanForD

1. LiDAR data

2. ALS

3. TLS data

Stem straightness

[cm/m]


StanForD

4. TLS

Stem taper


StanForD

1. ALS

2. TLS


Stem length

[m]

5. TLS


Tree leaning

[%]


StanForD

2. ALS

3. TLS

Branchiness



1. TLS




1. TLS

Damaged trees

(Insect attacks

Fungi attacks

Failed trees)



1. ALS


Marked trees

Virtual flag

FMP

RFID tags

Physical flag

RESTRICTIONS

Accessibility



Raster maps



SRTM elevation data

Lidar data

ALS

FMP

Bearing capacity


[kN/m2]


Snow cover


[days]





Field survey

FMP




FMP

Protected reserves

Map and borders


FMP


Annex A:

TABLES OF DATASETS FOR FIS POPULATION

TABLE A 2: INFRASTRUCTURES AND BUILDINGS TABLE A 3: HYDROGRAPHY

TABLE A.5: RISK FACTORS

TABLE A.5: COMMUNICATION

INFRASTRUCTURE NETWORK

INFORMATION

INPUT DATA

(TYPE)[SCALE]

STANDARD

RELEVANCE

SOURCE

High relevant

relevant

Mod. relevant

Not relevant

TMT

TLT

CwPT

IDC

ROAD NETWORK

Primary public roads

Road graph

Road polygon

geospatial vector data

Functional Road Class (FRC)

Shapefile

kml files

Public road network databases

WIGeoStreet

Roads congestion

GPS mounted on the Truck

Web service

Secondary public roads

Road graph

Road polygon


Shapefile

kml files

Public road network databases

WIGeoStreet

Roads congestion

GPS mounted on the Truck

Web service

Forest roads

Road graph

Road polygon


Shapefile

kml files

FMP

WIGeoStreet

Public or private ownership

( catastrial classification)

Shapefile

kml files

Type of use

( e.g. exclusive use for forest activities/not exclusive use for forest activities)

alpha-numerical attribute on GIS layer

National Road codes

FMP

Forest road classes

(e.g. truck road, tractor road, etc.)

alpha-numerical attribute

National codes

Maps

FMP

Landing sites

Size of the landing site

(information derived by iterative computation by the forester or automatic detection/segmentation of areas)

LiDAR and ALS

Location of the landing site

(information derived by iterative computation by the forester or automatic detection/segmentation of areas)

Hystorical data

LiDAR and ALS

Stocking areas

Size [m2]

Hystorical data

LiDAR and ALS

Location [LAT, LONG]

BUILDINGS

buildings

Location

Maps

ALS

Overall dimensions

OVERHEAD POWER

TRANSMISSION LINES

Coodinates of Cables end points

GIS coordinates

Shapefile

kml files

Maps

ALS

GAS PIPELINES

Position of the pipe

Shapefile

kml files

Maps

WATER PIPELINES

Position of the pipe

Shapefile

kml files

HYDROGRAPHIC DATA

(surface water)

INFORMATION

INPUT DATA

(TYPE)[SCALE]

STANDARD

RELEVANCE

SOURCE

High relevant

Relevant

Mod. relevant

Not relevant

TMT

TLT

CwPT

IDC

drainage network with features such as rivers, streams, canals, lakes, ponds, coastline, dams, and streamgages.

Hydrography Dataset (e.g.)

drainage basins as enclosed areas (in size categories)

Watershed Boundary Dataset (e.g. )

COMMUNICATION

INFORMATION

INPUT DATA

(TYPE)[SCALE]

STANDARD

RELEVANCE

SOURCE

High relevant

relevant

Mod. relevant

Not relevant

TMT

TLT

CwPT

IDC

GPS satellite coverage

RTK Coverage

GPS Coordinates

ETRS89

GRS 80

SRID

UTM

WGS84

AT&T Map

local area telephone network

GPRS Telecoms Service provider coverage

GPS Coordinates

UMTS/3G Coverage Map

UMTS/3G Coverage Map


Annex B: TABLES OF DATA ON FOREST

PRODUCTION QUALITY AND AVAILABILITY


Annex C:

TABLES OF DATA DERIVED FROM THE FIS


ConclusionsReport D1.03 is a reference for the implementation of:

D2.01 Remote Sensing data and analysisD2.02 UAV data and analysis D2.03 TLS data and analysis

D2.04 the Harvest simulation toolD2.05 the Road and logistic simulation module

Data and metadata model defined in the D1.03 will be the base for the implementation of the mountainous forest information system database (T 5.01)

The report D1.03 defines also data acquired by means of non-destructive or semi-destructive testing techniques, for the multi-sensor characterization of the harvested material. A prerequisite for this is the definition of the technical characteristics of the hardware/sensors instrumenting the harvesting machines (Task 1.2 D1.04).


Contact info


Mariapaola Riggio: [email protected]

mailto:[email protected]


Project SLOPE

WP1 T1.5 - System Architecture

Brussels, 2nd July, 2015


Overview


Leader: MHG Participants: GRAPHITECH, FLY, TRE, ITENE

Aim: Design the technology specification of system architecture Output: D.1.05 System architecture specifications


Objectives

Design the technology specification of the system architecture

Specify applications and technologies to be used Specify design principles Design model and interfaces for application

integrations in different integration levels Design deployment platform


Deliverable in brief

Specify existing applications and technologies Describes each partners applications and

technologies What current applications/systems can do What technologies they use How we can integrate them to the SLOPE

platform

-> Architecture should support many different kind of technologies



Specify architecture design model to be used Specifies design principles are used in the SLOPE

platform architecture Service oriented architecture With SOA we can loosely integrate very

different systems together Goal is to make integrations with minimum

modifications to exsisting codebases Architecture diagrams



Specify integration technologies Specifies integration technologies and components

to be used on this platform Liferay -> Presentation level integration

(different ways to integrate) Web Services (SOAP/REST) for service level

integration GeoServer -> spatial data from SLOPE FIS

database



Specify deployment platform for the SLOPE Describes the deployment platform

Use neutral, scalable cloud service for deployment (not inside any partners secure infrastructure)

This helps to open access for every partner that needs

Jelastic PaaS-platform for deployment


System Architecture Overview


Component Diagram


Summary

Deliverable can be found from SLOPE Dropbox folder Feedback and communication delays affected to the delivery time. This didnt affect

to execution of another tasks. All objectives were reached that are in the DOW. Deliverable specifies technologies, architecture model, partner applications,

integration patterns and slope deployment platform. System architecture specification can be updated during project Specified system architecture brings good guidelines/framework for SLOPE FIS

development


Mid-term Review 2/Jul/2015

Contact info

Veli-Matti Plosila [email protected]

Seppo Huurinainen [email protected]


mailto:[email protected]:[email protected]

Project SLOPEProject SLOPEOverviewProcedure1. Identifying user groups2. Developing functionalities3. Creating relation Matrix4. Developing questionnaires5. Contact with End Users6. Anlysis and conclusions6. Anlysis and conclusionsDeliverable Index D1.01Deliverable AnnexContact infoProject SLOPEOverviewGoalsWorkflowForest SurveySatellite ImagesUAVWorkflowTrees markingCableway and CarriageProcessor Head Head ProcessorHead ProcessorTracking systemConclusionsContact infoProject SLOPETask OverviewProcessUser Interface AnalysisUser Interface AnalysisUser Interface AnalysisUser Interface RequirementsUser Interface Requirements ListUser Interface Requirements ListUse cases Human Machine Interfaces DesignHMI Design - DesktopHMI Design - DesktopHMI Design Desktop - AnalyticsHMI Design Desktop - OperationHMI Design - MobileHMI Design In-VehicleHMI Design In-VehicleHMI Design ERP ModuleConclusionsContact infoProject SLOPEOverviewData formats and standardsData formats and standardsData formats and standardsIntegrated modelsOverview of existing databases and servicesRequired information to populate the FISAnnex A:TABLES OF DATASETS FOR FIS POPULATION Annex A:TABLES OF DATASETS FOR FIS POPULATION Annex B: TABLES OF DATA ON FOREST PRODUCTION QUALITY AND AVAILABILITY Annex C:TABLES OF DATA DERIVED FROM THE FIS ConclusionsContact infoProject SLOPEOverviewObjectivesDeliverable in briefDeliverable in briefDeliverable in briefDeliverable in briefSystem Architecture OverviewComponent DiagramSummaryContact info

Date post:	13-Apr-2017
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Mid-term Review Meeting - WP1

Education