Pilot Area of Veneto Region (Italy)

Slides:

Advertisements

Similar presentations

1 SOMIS: Schruns 11/10/2004 A Part of the European Soil portal - A step towards harmonization of Soil Information in Europe Panos.

Advertisements

Harmonization of Soil Information in the Alps Technical and Operational Procedures Harmonization of Soil Information in the Alps Technical and Operational.

EXCHANGE FORMAT Ialina Vinci EXCHANGE FORMAT Ialina Vinci Osservatorio Regionale Suolo - ARPAV Ispra 3-4 February 2005.

1 SOMIS: ISPRA 25/11/2004 A step towards harmonization of Soil Information in Europe Marc Van Liedekerke, Panos Panagos Eusoils.jrc.it:

VENETO REGION PILOT AREA Silvia Obber VENETO REGION PILOT AREA Silvia Obber Osservatorio Regionale Suolo - ARPAV Ispra 3-4 February 2005.

Attribute values are classified, e.g. DR = Depth to rock. S = Shallow ( < 40 cm) M = Moderate ( cm) D = Deep ( cm) V = Very deep ( > 120.

Soil Information System of the Danube River Basin - source of the data for flooding prediction models. Beata Houšková Soil & Waste Unit, Institute for.

1 EnviroInfo 2005 Alpine Area (5 Countries): 11 x 7 = 77 cells Area: 770,000 Km 2 European Soil Erosion Risk Local Italian Alpine Area EU Member Regional.

VENETO REGION PILOT AREA Silvia Obber VENETO REGION PILOT AREA Silvia Obber Osservatorio Regionale Suolo - ARPAV Ispra - February 6-7, 2006.

Ecological soil map of the Alps A cross-border pilot area between Italy and Slovenia Sara Zanolla Stefano Barbieri Giuseppe Michelutti Borut Vrščaj.

Harmonization of Soil Information in the Alps The ECALP Project: Results and Prospects Lombardia Pilot Area Stefano Brenna, Alberto Rocca ERSAF – Agency.

A Multi-Resolution Technique for Comparing Images Using the Hausdorff Distance Daniel P. Huttenlocher and William J. Rucklidge Nov Presented by.

Development of a High-Resolution Global Soil Depth Dataset Jon D. Pelletier Geosciences Dept., University of Arizona Deliverable: gridded high-resolution.

Eco-Pedological Map of the Alpine Territory: a Crossborder Example.

Scan Conversion A. Samal. Scan Conversion Last step in the graphics pipeline Efficiency is a central issue Common primitives – Lines – Polygons – Circles.

PowerPoint D2 L8 Read and plot coordinates in the first quadrant; recognise parallel and perpendicular lines in grids.

1 Section:Plant & Soil Science Unit:Soil Management Lesson Title: Soil Surveys and Land Capability Classification.

Configuring Mash Up Data. External Data In CRM Contact Without Synchronization External Data.

SOILS INVENTORIES We can consider two basic approaches: A. Samples points extracted from a population of points. B. Mapping. For the first an example (at.

2012 Southwest Wildfire Hydrology and Hazards Workshop Evan Friedman and Dr. Paul Santi Colorado School of Mines 3 April 2012.

1 Integration of Turkish Soil Database into European Soil Database Ece AKSOY.

West Hills College Farm of the Future. West Hills College Farm of the Future Where are you NOW?! Precision Agriculture – Lesson 3.

CS 128/ES Lecture 5a1 Raster Formats (II). CS 128/ES Lecture 5a2 Spatial modeling in raster format  Basic entity is the cell  Region represented.

Geographic Information Systems : Data Types, Sources and the ArcView Program.

CS 128/ES Lecture 5a1 Raster Formats (II). CS 128/ES Lecture 5a2 Spatial modeling in raster format  Basic entity is the cell  Region represented.

Graphics Output Primitives Pixel Addressing and Fill Area Dr. M. Al-Mulhem Feb. 1, 2008.

19 th Advanced Summer School in Regional Science Overview and more advanced directions with ArcGIS.

The Lower Coquille Watershed, part of the Coquille Basin is located in Southwest Oregon in Coos county (see figure 1). The Coquille River is the major.

Identifying risk areas for soil degradation by compaction reduction of soil porosity mechanical stressHuman Activity modification of soil properties deterioration.

GIS Analysis. Questions to answer Position – what is here? Condition – where are …? Trends – what has changed? Pattern – what spatial patterns exist?

JRC Ispra - IES 1 Overview of soil data at European scales F. Carré & T. Mayr.

ECOCLIMAP, A GLOBAL DATABASE OF LAND SURFACE PARAMETERS AT 1KM RESOLUTION J.L. CHAMPEAUX, V. MASSON, F. CHAUVIN METEO-FRANCE/CNRM, 42, Av Coriolis,

LANDSLIDE SUCCEPTABILITY MAPPING (Case study of SRILANKA)

THE EFFECT OF THE SURFACE CHARACTERISTICS ON THE DICE RESULTS SEEN BY THE MESONH MODEL M. A. Jiménez, P. Le Moigne and J. Cuxart DICE workshop, October.

Forest soil survey and monitoring in the Czech Republic Prof. Jiri Kulhavy Protection of Soil Resources, September 26 th 2006, Brussel Institute of Forest.

Towards participatory approaches to a Multiscale European Soil Information System Nicola Filippi, Panagos Panos, Borut Vrscaj EUROPEAN COMMISSION JOINT.

Metadata templates and patterns Sergey Sukhonosov, Dr. Sergey Belov National Oceanographic Data Centre, Russia Training course on establishment of the.

JRC-AL: WORKSHOP, DATE DNDC-EUROPE Adrian Leip, Joint Research Centre 1.DNDC-EUROPE: quick description of concept and status 2.Improvement of HSMU-layer.

Lt. Col. Paweł BORYN, PhD POLISH EXPERIENCES IN PREPARING HIGH- RESOLUTION MAPS FOR JTLS.

The pilot area approach as a basis to develop a network Meeting on Harmonization of Soil Information in the Alps JRC Ispra 1-2 July 2004 Ialina Vinci and.

 decimals/cc-7th-fracs-to-decimals/v/converting-fractions-to-decimals-example.

赴国际水稻所访学情况汇报长江大学农学院邢丹英 2010 年 6 月. 学习目的学习时间、地点学习内容学习收获几点体会汇报提纲.

ISPRS Congress 2000 Multidimensional Representation of Geographic Features E. Lynn Usery Research Geographer U.S. Geological Survey.

1 Miskolc, 1 st Digital Soil Mapping WG Danube basin profile Database Beata Houšková Jean Dusart Luca Montanarella Soil & Waste Unit Institute for Environment.

U.S. Department of the Interior U.S. Geological Survey Norman B. Bliss, ASRC Federal InuTeq Contractor to the USGS 6/4/2015 A continental view of soil.

01. Create Raster 02. Classify on scale of Combine Rasters 04. Compute Stats Create Map 01. Create Raster 02. Classify on scale of Combine.

Estimating Groundwater Recharge in Porous Media Aquifers in Texas Bridget Scanlon Kelley Keese Robert Reedy Bureau of Economic Geology Jackson School of.

3.4 – Linear Programming. Ex. 1 Graph the system of inequalities. Name the coordinates of the vertices of the feasible region. Find the max & min values.

Preparing input for the TOPKAPI (TOPographic Kinematic Approximation and Integration) model PRASANNA DAHAL.

The “Ecopedological project of the Alps”: general description Harmonization of Soil Information in the Alps JRC, Ispra1 – 2 July 2004 Francesca Ferraro,

Locating Positions on the Earth’s Surface

Visual Interpretation for Forest Change Detection in Fiji Vilisi Tokalauvere SOPAC Pacific GIS&RS Conference November 2011 Lotus Building, Suva.

1 INM’s contribution to ELDAS project E. Rodríguez and B. Navascués INM.

Land Management and Natural Hazards Unit Incontro tecnico su Indicatori e metodologie a supporto della strategia tematica per il suolo: Studi Pilota in.

南水北调东线第一期工程山东段情况简介. 主要汇报内容二、南水北调山东段工程总体布置三、山东段工程项目划分及工程主要建设内容一、南水北调东线工程概况四、前期工作及工程建设进展情况五、工程总投资.

Re-introduction to GIS

The ecopedological map of the alpine territory the pilot area of the Veneto Region Ispra February 2005 Ialina Vinci and Silvia Obber Agency for.

Hire Toyota Innova in Delhi for Outstation Tour

FEWS Stream Flow (SF) Model ~Progress Report~

Rasterizing Lines 2 Lecture 33 Wed, Nov 14, 2007.

FEWS Stream Flow (SF) Model ~Progress Report~

3.4 – Linear Programming.

EuroDEM and the EuroDEM30 prototype

Jordi Escriu – Facilitator Thematic Cluster #3

ચાલો માટી વિશે જાણીએ All About Soil.

Jordi Escriu – Facilitator Thematic Cluster #3

Image Abstract Data Types, and Operations on Images

Jordi Escriu (ICGC – Catalonia, Spain)

Additional Example 2: Graphing Ordered Pairs Graph and label each point on a coordinate grid. A. L (3, 5) Start at (0, 0)

Presentation of Jordan Case Study First Management Board Meeting

Presentation transcript:

Pilot Area of Veneto Region (Italy) Area: 216 km2

soil map 1:250.000 of Veneto Region

Pilot area INSPIRE GRID

SOIL MAP 1:250.000 rastered by 10 m pixels GRID 1 km 10 m pixel in order to have only 1 SMU value in every pixel

SMU_STU Database of Veneto Region N_STU STU %_STU

Percentage of each STU in every SMU

% of every STU in the pixel % of every STU in the SMU

STUs PIXEL SMU

STU max in the pixel (macro)

1 km PIXEL DESCRIPTION: STU max ZMB1 40% STU2 SDP1 25% STU3 ORN1 20% Bare deposits 15% SMU 1 STU1 SDP1 30% STU2 ZMB1 25% STU3 CTA1 20% Bare deposits 10% PIXEL_id 4525_2618 SMU 2 STU max ZMB1

JOIN Pixel coordinates

Example: Parameter ROO (Depth class of an obstacle to roots within the STU)

STU Database of Veneto Region ROO (depth class)

EXAMPLE: 1 km raster Parameter ROO (Depth class of an obstacle to roots within the STU) No soil