Workshop Evidence on European Land Use / DG Regio Belgium Understanding Land Use patterns in Europe...

Workshop Evidence on European Land Use

/ DG Regio Belgium

Understanding Land Use patterns in Europe – EU-LUPA project

Consortium

Sweden

NordRegio

Sweden

NordRegio

Poland

IGSO

Poland

IGSO

TECNALIA

Spain

TECNALIA

Netherlands

ALTERRA

Netherlands

ALTERRA

UAB ETC-LUSI UAB

EU-LUPA Project aim

This project is about combining and aggregating land cover, land use and administrative data into meaningful typologies as potential input for policy making at European, national and regional level.

Working approach

•What are the main characteristics of ongoing changes in land use and land use patterns?

•To what extent and how are changes in land use patterns interacting with ongoing socio-economic developments? Can LUF help to analyse the land use patters?

•How can typologies reflect on both levels of change, i.e. the physical characteristics of land use patterns, and the dynamics behind these changes?

•Are the trends sustainable (performance and efficiency), and to what extent will the ongoing changes compromise future developments? Can LUF help to analyse the efficiency and sustainability of LU patters?

CORINE LAND COVER

Land use/cover (stock))Land use/cover changes (1990-2006)

Basic Regional

Typologies

Comprehensive Regional Typologies

+

Identification of Policy objectivesPolicy

review

Identification of Policy challenges &

Trade-offs

Guidelines & recomendations

Pre-selection of case studies

Validation in case studies

GEODATABASE

Characterization: Socio-econ-amb

indicators

Case studies report

LUEfficiency

LUPerformance

Definition of LUF´s

Dynamics

and trends

drivers

progress of the project

Clustering of land use- Regional Typologies at NUTS3

Assessment of changes: static vs dynamic process

Relation between land use changes and Land Use Functions

Impact of data availability

• Determining typologies is highly dependent on the availability of data

• At this moment three types of data are accessible1. Corine status data for 1990, 2000 and 2006

2. Corine change data for 1990 to 2000 and 2000 to 2006

3. A variety of data characterizing the socio-economic situation in Europe

• At this level of analysis the two first sets of data have been included in the analysis, and provide indications of what would characterize the possible typologies of land cover and land use

Impact of data availability

• Consequently the two important characteristics of land cover are imperative for our analysis:– Data representing land use status, i.e. what is characterising the

land cover situation at three different points of time, and out of that what are the static characteristics of land cover and land use

– Data representing land use change, i.e. what is characterising the land cover and land use between the points of time when registration takes place, and thereby the dynamic characteristics of land cover and land use.

• Due to this, our approach has its focus on the synthesizing of typologies representing as well status (static characteristics) and change (dynamic characteristics)

Characteristics of land cover status

• Approach: Applying a two tier cluster analysis at the NUTS3 statistical level

• Purpose: Ensuring that stable land cover characteristics over the 16 year time period is determined

• Methodology:– For each of the three years a first level cluster analysis has been

conducted, identifying regions characterized by the same land cover situations.

– Based on the outcome of the clustering, 15 clusters have turned out to be advantageous.

– The statistic characteristics of the clusters have been used in a second level cluster analysis, determining regions with similar land cover characteristics over the time perio.

Characteristics of land cover status

• The regional characteristics of the final clusters are shown on the map.

• Due to limitations in data availability for some countries the analysis does not provide full coverage for Europe

• Due to the existence of extreme outlyers in the data material, the number of NUTS3 regions included in each cluster differs very much

Characteristics of land use change

• Approach: Applying cluster analysis at the NUTS3 statistical level, one for each of the time period

• Purpose: Ensuring that change characteristics as well as changes in these characteristics are shown in the analysis

• Methodology:– For each of the two time periods a cluster analysis has been

conducted, identifying regions characterized by the same land cover changes.

– As there are marked differences in the process of land cover changes, an important issue has been not only to identify the changes, but also to show these time based differences

– In order to keep the analyses comparable, the focus has been on percent changes per year


• Sprawl of economic sites and infrastructures– In most of Europe it is an

ongoing phenomenon during the whole period (yellow=low intensity, purple=high intensity)

– There are, however, high intensity activities mostly during 1990-2000 (green colors) or 2000-2006 (blue colors)


• Forest Creation and Management– This is the land cover

change which has been among the most dominant in Europe during the period 1990 to 2006

– In several areas the changes has been ongoing throughout the whole period (yellow and purple)

– The major pattern, however, is an intensification of the process after 2000 (blue)

Characteristics of land use change• Matrix of change 1990-2000

versus 2000-2006– By means of colors both

intensity and time period is shown on the map.

– Colors yellow (low intensity) and Purple (high intensity) show changes which have been ongoing throught the whole period

– Color green show changes which have been mainly ongoing during 1990-2000

– Color blue show changes which have mainly been ongoing after 2000


• Dominating land use changes 1990 to 2006– By means of a cluster

analysis of changes in land cover characteristics the domination of the 9 basic change characteristics have been applied on Europe

Typology structure

Artificial Surfaces

Agricultural Land

Forest Land

Water Bodies

“Extensivity”Intensity

BASIS / MATRIX

Typology structure

Artificial Surfaces

Agricultural Land

Forest Land

Water Bodies

“Extensivity”Intensity

CHANGES

Preliminary Typology

• Preliminary typology– Base color identifying the

matrix:• Red = Artificial surfaces• Brown = Agriculture• Green = Forest areas• Blue = Water body

areas– Color shades identifying

the dominant change characteristics

Typology structure

Artificial Surfaces

Agricultural Land

Forest Land

Water Bodies

“Extensivity”/ MONO FUNTIONS?

Intensity/ MULTIPLE FUNCTIONS?

Why using Land Use Functions in EU-LUPA?

Nr of land use functionsMonofunctionality Multifunctionality

Land

Use

inte

nsity

Extensive

Intensive

Time evolution

Why using Land Use Functions in EU-LUPA?

• Changes based on CLC are too coarse to understand land use dynamics in EU27

• To assess the impacts of land use change in a comprehensive way and not based on the partial views provided by individual indicators: multi-criteria analysis

• The Land Use Functions provide a way of enhancing understanding by:– Multi-functionality – Sustainability: integration of the economic, social and

environmental dimension• Types of regions according to their dominant land

use functions (patterns) and their changes in time (trends)

The six LUFs in EU-LUPA

The LUFs method: aggregation scheme

Basic aggregation scheme, after Paracchini et al. (2008). The symbols represent individual indicators contributing to more than one LUF

Test for the NL: Land Use Functions

LUFS performance per NUTS 2 region in 2000 Changes in LUFS performance between 2000 - 2006 per NUTS 2 region

List of indicatorsIndicator code

Indicator Intrinsic indicator weight

(A)

Pillar balanced weight

(B)

Product

(A) x (B)

Balanced Weight 1

ECO_06.1 Labour productivity 1 0.25 0.25 0.3333ECO_08.1a Value added in agricultural

sector0.5 0.25 0.125 0.1667

ECO_08.1b Value added in energy sector 0.5 0.25 0.125 0.1667ECO_11.1 Growth rate or real GDP per

capita1 0.25 0.25 0.3333

No. ECO indicators 4 0.75 1SOC_01.1 Unemployment rate 1 0.2 0.2 0.2SOC_03.1 Deviation of regional

unemployment rates1 0.2 0.2 0.2

SOC_03.2 Deviation of regional income 1 0.2 0.2 0.2SOC_09.1 Net migration 1 0.2 0.2 0.2SOC_11.1 Alteration in appreciated

landscape heritage1 0.2 0.2 0.2

No. SOC indicators 5 1 1ENV_01.1 Ammonia (NH3) emission from

agriculture1 0.1111 0.1111 0.1429

ENV_01.2 Nitrogen dioxide (NO2) emissions

1 0.1111 0.1111 0.1429

ENV_02.1a Nitrogen surplus 0.5 0.1111 0.0556 0.0714ENV_02.1b Phosphorus surplus 0.5 0.1111 0.0556 0.0714ENV_03.2 Soil sealing 1 0.1111 0.1111 0.1429ENV_04.1 Carbon sequestration 1 0.1111 0.1111 0.1429ENV_06.2 Trends in farmland birds 0.5 0.1111 0.0556 0.0714ENV_06.6 Pesticide use 0.5 0.1111 0.0556 0.0714ENV_09.1 Forest fire risk 1 0.1111 0.1111 0.1429 No. ENV indicators 9 0.78 1

CORINE LAND COVER


Basic Regional

Typologies


+


review


Trade-offs




GEODATABASE


indicators

Case studies report

LUEfficiency

LUPerformance


Dynamics

and trends

drivers

Case studies

Aims:

-To have a better understanding on the drivers and demonstrate the complex interrelated dynamics of land use patterns in the relation to contemporary policy,

-To explain some processes in depth

-To investigate in depth and assess land use multifunctionality

- To validate the proposed typologies

Working groups (35 minutes)1/ Introduction in each WG (5 minutes)key ideas with regard to EU-LUPA approach (methodology-indicators / typologies / drivers-policies)

2/ Round of interventions (20 min) ASK For CONCISE INTERVENTIONSAnswering some questions for debating specific “DRIVING IDEAS” of each WG:1st Round (10 min)•Is this part of the project understood? What are the main appreciations and critiques of this part of the project ? (e.g. drivers linked to patters in order to define policy recommendations framed under ESDP and TA)2nd Round (10 min) –or just open proposals if there is not enough time-•What would be the main advices and recommendations for further steps of the project? (in relation to the critiques, e.g. additional drivers not mentioned, structuring the policy recommendations in relation to LU competencies)

3/ Facilitator outlines main conclusions (5-10 min) before changing to the next WG (changing twice, everybody participating in the 3 WG)

CORINE LAND COVER


Basic Regional

Typologies


+


review


Trade-offs




GEODATABASE


indicators

Case studies report

LUEfficiency

LUPerformance


Dynamics

and trends

drivers

Workshop Evidence on European Land Use / DG Regio Belgium Understanding Land Use patterns in Europe...

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