RESEARCH PROJECT ROSA ASSESSING PREFERENCES · PDF fileDE ESTUDOS EM ECOSSISTEMAS E PAISAGENS...
Transcript of RESEARCH PROJECT ROSA ASSESSING PREFERENCES · PDF fileDE ESTUDOS EM ECOSSISTEMAS E PAISAGENS...
UNIVERSIDADEDEÉVORAINSTITUTODECIÊNCIASAGRÁRIASEMEDITERRÂNICAS
GRUPODEESTUDOSEMECOSSISTEMASEPAISAGENSMEDITERRÂNICAS
RESEARCHPROJECTROSA
ASSESSINGPREFERENCESFORDIFFERENTLANDSCAPEPATTERNSBYDIFFERENTLANDSCAPEUSERS,INTHEREGIONOFALENTEJO
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
RESEARCH PROJECT ROSA: Assessing preferences for different landscape patterns
by different landscape users, in the region of Alentejo Page 1
I. SEAMLESS INTEGRATED PROJECT AND THE LANDSCAPE AMENITIES MODEL Page 1
II. RESEARCH PROJECT ROSA Page 4
II.1 METHODOLOGY
II.1.1 Study area Page 5
II.1.2 Land cover classes Page 6
II.1.3 Sample area Page 7
II.1.4 Groups of landscape users Page 11
II.1.5 Visual tools
Photos Page 12
Block Diagrams Page 13
II.1.6 Structure of the inquiries Page 14
II.2. POSSIBLE USES OF THE DATA COLLECTED
II.2.1 Proportion of land cover classes (Q methodology) Page 15
II.2.2 Relation with the output indicators from SEAMLESS Page 15
II.3. METHODOLOGY TRIAL: THE INQUIRIES STRUCTURE
II.3.1 First trial Page 16
Test A – squared grid Page 16
Test B – line grid Page 17
Observations Page 18
II.3.2 Second trial Page 18
Test C – Grid and block diagram Page 19
Observations Page 20
References Page 21
2
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
INDEX OF FIGURES
Figure 1 - Organigram of the Landscape Amenities model Page 2
Figure 2 - Study area Page 5
Figure 3 - Maps of clusters results Page 9
Figure 4 - Sample area municipalities Page 10
Figure 5 - Photo manipulation Page 12
Figure 6 - Block diagram Page 13
Figure 7 - Comparing scenarios Page 16
Figure 8 - 1st test grid and photos Page 17
Figure 9 - 2nd test grid and photos Page 18
INDEX OF TABLES
Table 1 - Approaches to achieve the optimum values Page 3
Table 2 - Land cover classes in the study area Page 7
Table 3 - Clusters’ classification Page 8
Table 4 - Sample area municipalities Page 10
Table 5 - Landscape users Page 11
Table 6 - Photos’ numeration Page 14
Table 7 - Main steps of the Q methodology (Barry & Proops, 1999), and it
application in the project ROSA Page 15
INDEX OF ANNEXES
Annex 1 – List of meetings
Annex 2 – CORINE Land Cover 2000 classes (1st stage) and sub-classes of extensification /
intensification
Annex 3 – Landscape Units Maps and crossing Landscape Units / CORINE Land Cover Maps
Annex 4 - PROT 2006 Maps
Annex 5 – Land cover photos, to include in the inquiry
Annex 6 - ROSA - inquiry
3
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
1
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
RESEARCH PROJECT ROSA: Assessing preferences for different landscape patterns by different
landscape users, in the region of Alentejo
This document presents the methodology of the Research Project ROSA, starting presently (Autumn 2008)
in Alentejo, in the southern region of Portugal. This project is developed, in part, in a close relation with the
SEAMLESS integrated project, carried out by a consortium of 30 European partners and led by the
Wageningem University (NL)1. This relation is based on the fact the project ROSA is expected to produce
data that will permit to test the landscape amenities model, developed in the SEAMLESS context. ROSA will
produce data based on the assessment of the suitability of different landscape patterns (compositions of land
cover patches) to a selection of amenity and cultural functions provided by the landscape, through inquiries
to different groups of users. For this reason, the SEAMLESS project and its landscape amenities model are
succinctly presented here.
I. SEAMLESS INTEGRATED PROJECT AND THE LANDSCAPE AMENITIES MODEL.
The SEAMLESS project aims at developing a model integrated framework that allows ex-ante assessment of
the impact of agricultural and environmental policies and technological innovations, on several dimensions of
the agricultural sector and the rural areas. The framework has multi-scale capabilities ranging from field and
farm levels to the EU25 and globe; it is generic, modular, open and uses state-of-the-art software1.
Within SEAMLESS, and increasing during the length of the project, there has been a concern for achieving a
comprehensive evaluation of the social impacts of agricultural change, both in what concerns more common
social dimensions (labor, quality of life), as the dimensions related with the social demand of the landscape
in the present.
The work developed until now by the Portuguese team, under the social indicators framework, is based on
the construction of the Landscape Amenities Model (fig. 1). The model express what kind of amenities
(which non-commodity functions and at what level of intensity) are supported by the landscape, according to
different land cover combinations, evaluating the display of functions in relation of the land cover pattern,
resulting from agricultural activities. It permits to evaluate scenarios for the future, as the change in the land
cover data considering possible variations according to scenarios, will correspond to values of functions, i.e.,
what is going to happen to a function: which is going to decrease, which is going to increase.
The functions considered are those that correspond to a social demand in the today society: a demand for
different activities in the rural landscape, or the demand for the countryside in general, if this concerns
characteristics that people consider important. Examples of such functions are the hunting, the ecoturism or
the search for life quality.
1 www.seamless-ip.org/
2
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
This land cover pattern is expressed in cartography, as the CORINE Land Cover. But it can also be
calculated from the data used in Seamless, even if in a more rough way: the model outputs about the crop
diversity, specialisation, and intensity of agriculture.
If the land cover pattern more valuated by users for a specific function is identified, using specific indicators,
then it is possible to calculate a specific value or set of values, to that type of landscape that would be the
optimum values for each function. If, for alternative scenarios are applied the same indicators, then would be
possible to compare the similarity between the optimum landscape type for a function and the several
scenarios proposed.
The optimum values, based on people’s preferences, can be obtained by extrapolating the results achieved
mainly through four different approaches (Table 1):
Fig. 1 - Organigram of the Landscape Amenities model - in orange is indicated the shorter way to approach proposed, where land cover data is in straight relation with functions. Starting by surveys or expert panels, which gives the information on preferences, it is possible to establish a relation between land cover data and possible functions in the landscape through the index of function suitability (IFS). By this way, it is possible to evaluate scenarios for the future, as the change in the land cover data considering possible variations according to scenarios, will correspond to values of functions, i.e., what is going to happen to a function: which is going to decrease, which is going to increase.
3
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
Approach What is obtained What is
extrapolated
1
Regional study about landscape preferences, based on a set of photos
Based on surveys aiming to assess users preferences from a set of photos representative of different land cover combinations at regional level.
A set of chosen photos
2
Regional study about landscape preferences, based on virtual scenarios
Based on surveys aiming to get users to create favourite virtual scenarios for each function at regional level.
A set of virtual photos
3 Local studies about landscape preferences
Based on surveys that aim to assess users preferences from a set of photos representative of different scenarios at local level.
A set of chosen photos
4 Regional study by expert panel
To be defined with the French team of Clermont-Ferrand.
Description / pattern for chosen landscapes
Optimum values for the
landscape amenities
model outputs indicators
The landscape amenities model has been tested within an approach 3, extrapolating the optimum values
from a local study in a municipality in the Alentejo region (within a National Research project, MURAL, 2005-
2008), which aims at evaluating the preferences of different groups of landscape users, between different
land cover types and, within these, different intensities.
At the moment, the SEAMLESS team in Portugal works to extrapolate the optimum values by an approach 1,
through the starting Regional Research Project ROSA (see point II), and also the approach 4, this one with
the French team in Clermont-Ferrand, for the Auvergne region.
Table 1 – Approaches to achieve the optimum values - People’s preferences can be identified mainly through 4 different approaches, based on surveys or expert panels. Even if the information obtain is different between it, all permit to extrapolate the optimum values needed to apply the landscape amenities model outputs indicators and calculate the index of function suitability.
4
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
II. RESEARCH PROJECT ROSA
The sustainability of the European rural landscapes should be based in aspects as the social demand for
multifunctional landscapes, which can be provided by farmers, if economically profitable, and supported by
national and local authorities for an ecological management (Soliva et al., 2008; Vos and Meekes, 1999).
Thus, it is important to understand which are the social preferences concerning landscape, allowing then the
politicians and management authorities to develop sustainable management plans, based on users demands
and preferences (Dramstad et al., 2006).
Considering such aspects, and taking in account the straight relation between landscape preferences and
the land cover pattern, has been developed several studies to understand the interests and expectations of
local stakeholders in the future landscapes (Lewis, 2008; Tress and Tress, 2003; Petrosillo et al., 2007), to
investigate the public preferences for the effects of proposed changes in land use (Swaffield and
Fairweather,1996) or how such preferences may vary between different groups of users (Fairweather and
Swaffield, 2002).
In Portugal, some reference projects are the IMPAZA Project (Rosário and Carvalho, 2007; Antunes et al,.
2007), where it was studied the impact of the agricultural abandon in the landscape structure in sensitive
areas of the interior of Continental Portugal, the MURAL project (Pinto-Correia et al.2), based on the social
preferences for landscape types at local level, and the ABANDONO project (Pinto-Correia et al., 2006),
where were identified and assessed the rural and agricultural abandonment in continental Portugal.
The methodology proposed in the project ROSA, is based in the straight relation that can be established
between the land cover distribution and the landscape pattern. The landscape is a dynamic and complex
system where natural and cultural factors interact permanently; here, the component related to the land
cover is the most dynamic and the one that more closely depends on management of agricultural uses, at
farm level. Further, the land cover pattern is a highly dynamic component, and therefore has a strong role in
the change of the landscape appearance and character and, as Bell (2001) referrers, often the visual
aspects of a landscape tend to have a bigger influence on people’s judgements than knowledge.
Under this framework, the project ROSA aims:
- To assess, for the region of Alentejo, the land cover types and patterns that better suit the different cultural
and amenity functions, e.g., the functions which value depend solely on social demand;
- To contribute, through design and testing, to the development of methodological tools for the assessment
of the social demand of rural landscapes, for a set of differentiated functions, and of the factors that
determine this demand.
Thus, the land cover pattern, and its changes will be used for the study of the landscape value for various
cultural and amenity functions. Meaning, through the land cover pattern can be possible to assess the
preferences for specific functions and, apply indicators, related to databases, using it in modeling operations.
2 Pinto-Correia, T, Barroso, F., Menezes, H., The changing role of farming in a peripheric South European area: the challenge of the landscape amenities demand. This text is a chapter of an INNOLAND book, not published yet.
5
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
Starting by surveys to users, or expert panels, which gives the information on people’s preferences, it is
possible to establish a relation between land cover data and possible functions in the landscape through the
index of function suitability (see point I). This index (IFS) is calculated identifying the optimum value, or
optimum range of values, of the preferred land cover pattern, for each group of users, e.g., for each of the
cultural and amenity function selected. This permits to compare and evaluate scenarios for the future, as
how the change in the land cover data, considering possible variations according to scenarios, will
correspond to values of functions, i. e., what is expected to happen to a function: which is going to decrease,
which is going to increase.
II.1 METHODOLOGY
II.1.1 Study area
The research project ROSA aims at assessing preferences for different landscape patterns by different
landscape users, in the region of Alentejo. For this reason it is developed in the south region of Portugal,
Alentejo, a NUTS II region, which integrates 5 NUTS III sub-regions and 58 municipalities (fig. 2). Although,
the most traditional and better-known definition of Alentejo counts only with 47 municipalities, the other 11,
now belonging to the sub-region of Alentejo Litoral, belonged previously to the region of Ribatejo. Despite
the definition with the 58 municipalities be the official one, the 47 municipalities define a more coherent
territory, concerning the landscape and the social aspects.
The criteria to define the study area still in discussion, but have been considered until now the NUTS II
definition.
Fig. 2 – Study area – The project ROSA has as study area the region of Alentejo, here represented in it larger definition with 58 municipalities, distributed in 5 NUTS III sub-regions.
PORTUGAL
6
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
II.1.2 Land cover classes
Concerning the land cover pattern, the first step was to identify the land cover classes concerning the
agricultural and forestry areas, in the region of Alentejo, using the CORINE Land Cover (CLC) 2000 data. To
better characterized the land cover pattern of the region were defined levels of extensification / intensification
for each one of the CLC classes identified. However, from such procedure resulted 34 sub-classes (see
annex 2), which, due to the character of this project and the need to integrate such data in inquiries, were
considered as excessive.
In order to reduce it, the CLC classes and it sub-classes were analysed and discussed between the team
work, in meetings (see annex 1) within the research group DYNAMO (Dynamics and Management of Rural
Landscapes), and also with agents of the Ministry of Agriculture, taking in consideration the expert
knowledge and previous projects developed in the region.
In the end was decided to maintain the 15 main classes (based on the level 3 of the CLC 2000), with two of
those divided in levels of extensification / intensification (table 2).
Due to the scale of the CLC data, was decided to define for each class some specific features of this region:
• Class 2.1.1 – Non irrigated arable land – mainly concerning the non irrigated wheat cultures;
• Class 2.1.2 – Irrigated arable land – mostly related to the irrigated cultures of wheat, corn or tomato;
• Class 2.1.3 – Rice fields – despite this culture won’t occupy a high proportion of land cover in Alentejo, it is
very characteristic of certain areas;
• Class 2.2.2 – Fruit trees and plantations – mainly considering orchards, for its frequency in Alentejo;
• Class 2.2.3 – Olive groves – the division in two levels of extensification / intensification of the olive groves
(group 2 in the table 2) were based in expert knowledge. Despite this division do not be take into account in
the CLC data, it was considered important to define it here, due the frequent transition observed in certain
areas of the region, where the traditional, non-irrigated and irregular groves are being replaced by those
more intensive, regular and irrigated;
• Class 2.3 – Pastures – related to the areas of seeded pastures;
• Class 2.4.2 – Complex cultivation pattern – usually areas near villages, and with parcels of different
cultivations as vineyards, orchards or olive groves, among others;
• Class 2.4.4 – Agro-forestry areas – concerns the agro-silvo-pastoral areas of montado (Portuguese). This
class was divided in four levels of extensification / intensification, considering the different crown covers and
shrub covers possible (van Doorn and Pinto-Correia, 2007);
• Class 3.1.1 – Broad leaved forest – corresponds to the Eucalyptus spp. Areas;
• Class 3.1.2 – Coniferous forest – Refers the forestry areas of Pinus pinea, once other species of Pinus
species do not appear significantly in Alentejo;
• Class 3.1.3 – Mixed forest – was considered the mixed forest with Pinus spp. and Quercus spp.;
• Class 3.2.1 – Natural grasslands – non irrigated grassland areas;
• Class 3.2.2 – Moors and heathland – In Alentejo is mainly areas with tall shrub vegetation in non agricultural
areas;
• Class 3.2.3 – Sclerophyllus vegetation – mainly small shrub vegetation in agriculture areas.
7
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
II.1.3 Sample area
Due to the dimension of the study area and the need to establish personal contacts in order to identify the
users and select a sample, a approach has been defined to select 10 municipalities, representative of the
region in what concerns the distribution of the land cover pattern and dynamic. The distribution of the land
cover pattern is the characteristic going to be evaluated in relation to preferences, once the land cover
pattern directly changes according to changes in the agricultural activity and the relating land use systems.
The choice of the municipalities to compose the sample area was based on two different approaches, an
automatic one and an expert one.
The first approach, more automatic and quantitative, was developed through a clusters’ classification, using
the data from the CORINE Land Cover (CLC) 2000 identified within the boundaries of the municipalities
(group 1, table 2), and two indicators of the land cover dynamic: the SWAP, showing the total area of a class
that was lost in a place but gained in another place, and the Net Change, which gives the total change a land
cover class suffered related to the total area of the municipality, for 2000-1990 (Pinto-Correia et al. 2006).
It was made three different tests with the clusters’ classification, considering not only different data
combination but also different number of municipalities and classes of clusters (table 3).
GROUP 1 Corine Land Cover nomenclature
GROUP 2 Extensification / Intensification Level
2.1.1 - Non irrigated-arable land
2.1.2 - Permanently irrigated land
2.1
Ara
ble
land
2.1.3 - Rice fields
2.2.1 – Vineyards
2.2.2 -Fruit trees and plantations Groves with less regular pattern and pastures under cover
2.2
Perm
anen
t cro
ps
2.2.3 - Olive groves Irrigated and mechanized groves with clean ground under cover
2.3 Pastures 2.3 - Pastures (seeded)
2.4.2 - Complex cultivation pattern
crown cover < 10%, shrub cover < 20%
crown cover < 10%, shrub cover > 20%
crown cover 10% - 30%, shrub cover < 20%
2. A
GR
ICU
LTU
RA
L A
REA
S
2.4
Het
erog
eneo
us
agric
ultu
ral a
reas
2.4.4 - Agro-forestry areas (Montado)
crown cover 10% - 30%, shrub cover > 20%
3.1.1 - Broad leaved forest (Eucalyptus spp.)
3.1.2 - Coniferous forest (Pinus pinea)
3.1
Fore
sts
3.1.3 - Mixed forest (Pinus pinea + Quercus spp.)
3.2.1 - Natural grassland
3.2.2 - Moors and heathland (Tall shrub vegetation in non agriculture areas) 3.
FO
RES
T A
ND
SE
MI-N
ATU
RA
L A
REA
S
3.2
Scru
b an
d/or
he
rbac
eous
ve
geta
tion
asso
ciat
ions
3.2.3 - Sclerophyllus vegetation (Small shrub vegetation in agriculture areas)
Table 2 – Land cover classes in the study area – The classes in the group 1 are those coming out from the CLC cartography to the region of Alentejo. The group 2 is related to a sub-division of some group 1 classes, when considered necessary to better define the land cover.
8
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
In the fig. 3 are showed the maps with the municipalities distribution achieved with the clusters classification.
Only the distribution in 6 classes is presented, due to the higher level of detail. Comparing such maps it is
possible to understand that take in consideration the dynamic indicators, SWAP and Net Change, almost
doesn’t affect the results, once only 1 municipality in 58 changed its class of distribution (maps A and B, fig.
3). However, if the 11 municipalities belonging to the NUTS III, Lezíria do Tejo, are not considered, the
results changed strongly, with only 14 of the 47 municipalities remaining in the same classes (map B and C,
fig. 3).
Comparing the results achieved through the clusters classification with the data coming out of previous
projects also developed in this region (as the Pinto-Correia et al., 2006, concerning the abandon tendencies
in Portugal), the clusters seemed little coherent with the regional reality, as known by the various experts
involved in the project. Nevertheless, it is the distribution that considers only 47 municipalities that seems to
be closer to the regional reality.
The second approach, more analytical, was based in the work developed by the CCDRA3 for the PROT
Alentejo4, in 2007, where was defined the Technical and Economical Orientation for the region Alentejo, and
in the project where were defined the landscape units for Portugal, by Abreu et al. (2004), see annexes 3
and 4. PROT was based not only in the present land cover pattern and expert knowledge but also in several
meetings with expert panels where the criteria for the classification and the map output were defined.
Comparing the results of both approaches and taking into account also the knowledge of the work team in
the region, it was decided to work with the results developed for the PROT Alentejo, by its coherence.
Considering all the results, 10 municipalities were selected for the sample group (fig. 4, table 4), where the
survey should be applied (besides a survey to the urban population, to be undertaken in Lisbon). The
selection was made considering the need to have, with these 10 municipalities, a good representation of the
regional reality and also taking into account the availability of agents of the DRAAL (Direcção Regional de
Agricultura do Alentejo / Regional Direction of Agriculture of Alentejo), since they could be a major help in
the establish of first contacts to apply the inquiries.
3 CCDRA - Commission of Co-ordination and Development of Alentejo. 4 PROT Alentejo - Regional Plan of Territorial Management of Alentejo
Number of municipalities considered
Data used in the clusters classification
Number of clusters’ classes tested
58 CLC 2000, Net Change and SWAP 4, 5 and 6
58 CLC 2000 4, 5 and 6
47 CLC 2000 4, 5 and 6
Table 3 – Clusters’ classification – Different combinations used in the three clusters’ tests for the study area, considering different data combinations and the number of municipalities and clusters classes.
9
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
Fig. 3 – Maps of clusters results – Results of the clusters classification, in 6 classes. The map A shows the 58 municipalities distribution, considering the CLC 2000, the SWAP and Net change values. The maps B and C are referred to the distribution of the 58 and 47 municipalities, considering only the CLC 2000 values.
A
B
C
BROAD LEAVED FOREST
ARABLE LAND
COMPLEX CULTIVATION PATTERN
AGRO FORESTRY AREAS
AGRO FORESTRY AREAS AND ARABLE LANDS
FORESTS
10
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
NU
TS II
R
egio
n N
UTS
III
Sub-
Reg
ion
NUTS IV Municipality MAIN FEATURES
Technical and Economical Orientation*
Elvas Irrigated arable land, with a diversified pattern. Mainly maintained by an irrigation system, the Caia system. Proximity of the boarder and presence of a relatively large town, Elvas.
Beef and annual cultures
Ponte de Sor Montado: dense silvo-pastoral system, diversified and rich, where the forest component is very important, with important production of cork oak, of high quality.
Herbivorous in mixed livestock
Alto
Ale
ntej
o
Castelo de Vide
Diversified pattern. Combined large and small-scale farming. Marginal and poor, sloppy areas, covered mostly with shrub. Importance of 2nd home settlements or neo-rurals. NOTE: Possible comparison with previous studies on landscape preferences
Herbivorous in mixed livestock
Reguengos de Monsaraz
Under the influence of the Alqueva dam and it irrigation sub-systems. Strong agricultural character importance of the vineyards, dominating the landscape in many parts of the municipality. Economic dynamisms related with agriculture. Importance of 2nd home settlements or neo-rurals.
Beef and annual cultures
Alen
tejo
Cen
tral
Montemor-o-Novo
Rich agriculture: Montado, good cork production, good pastures, and livestock production. Presence of large and small-scale property. Innovation capacities. Importance of 2nd home settlements or neo-rurals. Central location, in the Lisbon-Madrid axis, close to Évora and relatively close to Lisbon.
Specialization in beef
Vidigueira Intensive olive groves. Diversified agricultural mosaic. Importance of 2nd home settlements or neo-rurals.
Specialization in annual cultures
Ferreira do Alentejo Specialization in
annual cultures
Baix
o Al
ente
jo
Almodôvar Hills and plain, poor pastures and in general poor extensive agricultural systems. Peripheric location.
Beef and annual cultures
Alcácer do Sal Rice fields. Montado. Montado mixed with pine. Beef and annual cultures
ALEN
TEJO
Alen
tejo
Lito
ral
Grândola
Forestry systems: pine trees, mixed Montado with pine trees, dense Montado, dense oak forest, eucalyptus, shrub. High level of urban occupation, including 2nd homes and neo-rurals, comparing with other municipalities in Alentejo. Atractivity due to proximity of the coast and beaches.
Mixed livestock
Table 4 – Sample area municipalities – Each municipality has specific characteristics of the study area, concerning social aspects and dynamics as well as land cover patterns.
Fig. 4 – Sample area municipalities – Selection of the 10 sample municipalities (in yellow) for in the region of Alentejo
* P
into
-Cor
reia
et a
l., 2
006.
11
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
II.1.4 Groups of landscape users
To understand the type of land cover pattern preferred for a specific function, the method proposed relies on
surveys to specific groups of users, being each group related to a function (table 5). According to the
definition given by de Groot (1992) in de Groot (2002), an ecosystem function is “the capacity of natural
processes and components to provide goods and services that satisfy human needs, directly or indirectly”. In
this project are considered those functions resulting from the social demand on landscapes.
Is important to point out that in the users group of farmers is considered the person that manage the farm,
meaning, the person that takes the decisions on the way how to manage the land. In the group of landscape
users connected to the life quality function, the main difference between the second homeowners and the
weekend visitors is that these last are linked with continuity of the visits to the countryside.
It was expected to defined a numbers of inquiries that could allow to be a representative sampling of these
various groups for the region, permitting a confident generalization to the population represented.
Thus, for the groups where the total population is known, as the local inhabitants, the application of a
minimum rate for representativeness will lead to a too large number of inquiries. From another side, the total
population of hunters who practice hunting in the region, or the total population of eco-tourists or weekend
visitors, are impossible to define. As such, the total of 200 for most groups and 400 for the local population
has been defined, since it is a minimum sample size for achieving conclusions as to the behaviour of the
group (Patton, 2002). This number was also discussed with a statistical expert, according to whom the
number of inquiries should be, at least, 380, to allow an extrapolation with 5% error maxim and assure that
99% of the cases will be in the group. With a total of 1200 inquiries the representativeness of the universe
(Alentejo) is guarantee, as well as the representativeness of each class.
Although, it is important to keep in mind that inside each group the inquiries should be distributed in an even
way between the 10 municipalities of the sample area, meaning, it should be applied approximately 20
inquiries per group per municipality.
Function Users Number of inquiries
Hunting Hunters ± 200
Recreation Ecotourists and tourists ± 200
Life quality Second homeowners, weekend visitors ± 200
Identity Inhabitants and neo-rurals (insiders) ± 200
Identity Urbans (outsiders) ± 200
Production Farmers ± 200 (Stratified per farm type)
Table 5 – Landscape users – To identify the social landscape preferences concerning specific functions, were distinguished six groups of users of the rural areas.
12
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
II.1.5 Visual tools
Photos
To assess the social landscape preferences for specific functions, the project ROSA will use inquiries based
on visual support, using photographs. Visual tools have been used in several studies to understand people’s
opinion concerning landscape (Dramstad et al., 2006; Kaplan et al., 1998; Lewis, 2007). Once it creates a
common language between interviewed and interviewees, helping to overcome the technical vs. non
technical speech obstacle (Al-Kodmany, 1999; Luz, 2000), meaning, it can work as a discussion facilitator,
helping them to explain perceptions and concepts in an easier way (Lewis, 2008; Soliva et al., 2008).
Other two important aspects of using photographs in landscape inquiries is the fact of help to focus the
discussion in the specific aspects as a land cover type, and also, be economic and easily reproduced.
The project ROSA is based on surveys supported in photos corresponding to each land cover class or sub-
class identified previously for the region (table 2). To assure the coherence between all the set of photos
used and that each photo is clear in the land cover type represented, all the photos were taken at an
approximately 4 meters high, to permit a good perspective over the land cover.
The photo manipulation obeyed to certain aspects:
• Each photo should have a first plan well defined, only with the land cover type pretended, and a
second plan, more distant, of reference, equal in all the photos;
• Half of the photo should be occupied with soil and the other half with sky (equal in all the photos);
• All the elements present that not correspond the land cover class itself should be minimized;
• All the water surfaces should be erased.
In the fig. 5 is showed an example of the manipulation made to the photos to be used in the inquiries. In the
annex 5 are presented all the final photos used.
+ MANIPULATION:
Fig. 5 – Photo manipulation – Example of the photo manipulation for the class 6 – Olive grove. The two photos got after the manipulation are the representatives of the different levels of extensification / extensification of the olive groves in Alentejo.
Original photo - extensive olive grove manipulated
Final photo - extensive olive grove
Original photo - intensive olive grove Final photo - intensive olive grove
Original photo for the sky and 2nd plan
13
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
All the photos were taken in the same week, with identical weather conditions (minimizing the influence of
different light exposure), in the end of the summer (when the difference between the irrigated and non-
irrigated cultures is well understandable) and with the same camera (keeping the same zoom and focal
length). The experience in previous projects showed that the aesthetic differences between photos, such as
brighter colours or clean sky, may have an important influence in the choices made answering the inquiries.
The exact coordinates of the points where each photo was taken must be registered. This procedure permits
to map it, and, in future, repeat the photo in the exact point, creating a comparable photo base.
Block Diagrams
The block diagrams are visual support tools that permit to illustrate, in a simplified way, a portion of territory
(CETE, 2001).
According to the authors, this tool has as main disadvantage the dependence of who draw it, once it results
of a landscape interpretation, for example, in the selection of the elements to include.
Although, the advantages provided by the block diagram permit to consider it as a useful tool in the
discussion concerning the landscape, once it allows expressing and comparing the different users points of
view, also because it is easily understandable and permits a direct visualisation of a territory portion.
Considering the fact of each block diagram should be made taking in account the final goal, was drawn one
specifically for this project. Due to the block diagram should be used in a large number of inquiries and with
several groups of people (table 7), the design of the block is simple, to be easily understandable. Thus, the
relief represented is generic but still related to the smooth morphology that characterizes the region of
Alentejo.
The portion of territory represented has already the limit of 5 plots, with similar dimensions. This feature
allows simplifying the following statistical analysis.
Fig. 6 – Block diagram – Block diagram used in the inquiries where each person should define which land cover types are the preferred and how to distribute it, allowing to understand the preferred land cover pattern.
14
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
II.1.6 Structure of the inquiries
The survey is based on the demand to compose a photo arrangement to understand how people group the
land uses (see annex 6). Taking in account the land cover types identified previously (table 2), the total of
photos should be divided in two sets, being the one related to the 15 land cover classes (group 1 in table 2),
and other, related to the sub-divisions of those classes with sub-levels of extensification / intensification
(group 2 in table 2).
The inquiry should be divided in three steps:
• First step – Grouping the photos – The first set of photos is showed and the interviewed is asked,
considering the function he/she is representing, to choose the three that represent the preferred land
cover types, and three that represent the land cover types less wanted, explaining the reason of the
choice for each photo;
• Second step – Refining the preferred land cover types – If in the group of photos identified as the most
preferred for a specific function, are some referring to classes with sub-divisions (olive groves and
montado), the interviewed should have the opportunity to replace it, with photos considering such sub-
divisions, explaining why he/she took that decision.
For example, if in the first step was chosen a photo of Montado, in this second stage such photo
should be replaced by one of the four representing the possible sub-divisions Montado.
• Third step – Distributing the land cover types in the block diagram – Using any of the initial 15 photos,
each person should identify the land cover pattern, preferred for the specific function represented,
indicating in each of the 5 parcels of the block the number of the photo wanted (table 8). The number
can be repeated if wished.
GROUP 1 GROUP 2
Land Cover type showed Photo number Land Cover type showed Photo
number
Non irrigated-arable land 1 Permanently irrigated land 2
Rice fields 3 Vineyards 4
Fruit trees and plantations 5 Groves with less regular pattern and pastures under cover 6
Olive groves 6 Irrigated and mechanized groves with clean ground under cover 61
Pastures (seeded) 7 Complex cultivation pattern 8
crown cover < 10%, shrub cover < 20% 91 crown cover < 10%, shrub cover > 20% 92 crown cover 10% - 30%, shrub cover < 20% 9 Agro-forestry areas (Montado) 9
crown cover 10% - 30%, shrub cover > 20% 93 Broad leaved forest (Eucalyptus spp.) 10
Coniferous forest (Pinus pinea) 11 Mixed forest (Pinus pinea + Quercus spp.) 12
Natural grassland 13 Moors and heathland
(Tall shrub vegetation in non agriculture areas) 14
Sclerophyllus vegetation (Small shrub vegetation in agriculture areas) 15
Table 6 – Photos’ numeration – To each photo must correspond a number, allowing to easily identify each one.
15
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
II.2. POSSIBLE USES OF THE DATA COLLECTED
II.2.1 Proportion of land cover classes (Q methodolody)
The Q methodology was developed in the social sciences framework in the 60 years and as been applied in
several different contexts concerning public opinion (Klooster et al., 2008). One of the main features of the Q
method is it attend to obtain patterns of answers across individuals, rather than variables, and allows
describing and understanding the patterns of preferences about specific traits, as the environmental issues
(Barry and Proops, 1999) and the landscape planning and rural research (Swaffield and Fairweather, 1996;
Fairweather and Swaffield, 2002). This two last authors developed several studies associating the Q
methodology with the use of landscape photos, to access people’s preferences land cover changes, showing
the efficiency of this method in landscape issues.
Since the Q-sort method use a data analysis where the matrix is inverted, with the respondents are the
variables and the items are the cases (Klooster et al., 2008), if applied to the inquiries’ answers of the project
ROSA, should permit to identify patterns of answers, according to the different groups of users.
Consequently it should generate a range of values (proportion of class) that will match to the most preferred,
the worst case and the neutral situation, per function. The main steps of the Q methodology and how it can
be used in the project ROSA are described in the table 9.
II.2.2 Relation with the output indicators from SEAMLESS
Understanding the landscape perceptions of specific groups of users can produce important information in
the development of models and possible scenarios to achieve an integrated landscape planning (Folke et al.,
2002).
So, if to each photo is calculated the values of the coefficient for the intensity, as well as the diversity and the
specialisation indicators5 then could be possible to calculate the IFS index to the data collected in this
5 www.seamless-if.org
General steps of the Q methodology In the project ROSA
1 Collection of relevant data concerning the research object CORINE Land Cover 2000 data
2 Selection and formulations of a set of meaningful statements - Q sample – each numbered randomly and printed on separated cards.
Main Land cover classes photos
3 Each inquired person should distribute all the cards through the pre-structured grid (Q-sort).
3 groups of preferences: most preferred, neutral and not wanted
4 Data analysis, with the correlation matrix of all the Q-sorts, submitted to a by-person factor analysis (attitudinal groupings) - 1 representative Q-sort per group.
1 land cover pattern per group of landscape users.
Table 7 – Main steps of the Q methodology (Barry & Proops, 1999), and it application in the project ROSA.
16
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
project, may allow developing different aspects as to evaluate scenarios or the actual land cover pattern in
each municipality or to compare it with the possible scenarios built (fig. 7).
II.3. METHODOLOGY TRIAL: THE INQUIRIES STRUCTURE
II.3.1 – FIRST TRIAL
In an early state of the methodology development, the structure of the inquiry was tested, in order to
understand the reaction of the interviewed to different ways of selecting photos of land cover classes and a
composition of the same.
Two different types of grid and two different ways to present the photos were tested.
The photos of the CLC classes used, were from previous projects and without any kind of manipulation,
Test A – Squared grid
Inquired people: 5 (2 farmers; 1 hunter, 2 tourists).
Time of each inquiry: ± 45 minutes.
Type of grid: Squared grid of 3 x 3 spaces (fig. 8).
Photos presentation: The 19 photos, matching the CLC classes and sub-classes were printed in a sheet,
meaning all the land cover types were seen at once (fig. 8). Each photo had a legend, permitting to clearly
Fig. 7 – Comparing scenarios – Attributing the indicators values to calculate the Index Function Suitability to the ideal and worst land cover patterns (based on the surveys) as well as to the possible scenarios, permits a comparison between it. Such comparison allows inferring about the acceptance of a possible change in the land cover pattern by the landscape users.
Ideal land cover pattern IFS range of values
Worst-case land cover pattern IFS range of values
Scenario 2 (IFS value)
Scenario 3 (IFS value)
Scenario 1 (IFS value)
17
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
understand the land cover showed, and a number, to easily identify it. The grid was filled with detachable
photos equals to those showed in this sheet.
Question proposed: “Can you fill the grid using the photos available, to show the type of place you
considered as good to develop your activity?”
If wished, the photos can be all different or all equal and disposed as preferred.
Main comments made during the inquiries:
• Confuse;
• Pleasant but difficult to imagine the final image in the reality;
• The result seems 3 different places and not 1;
• After understand, is nice to play;
• The photos are too many and a little confuse.
Test B – Line grid
Inquired people: 6 (2 farmers; 2 hunter, 2 locals).
Time of each inquiry: ± 30 minutes.
Type of grid: Line grid of 9 spaces (fig. 9).
Photos presentation: In a first stage were presented photos only of the 15 main CLC classes (group 1 in the
table 2). After the first composition of 9 photos were made, was showed, for each chosen class with possible
sub-classes a second set of photos, that could be used to substituted the first choice (fig. 9).
Question proposed: “Imagining the path you take during your activity, can you fill the grid, with the available
photos, to should the type of place you consider better to do it?”
If wished, the photos can be all different or all equal and disposed as preferred.
Fig. 8 – 1st test grid and photos – In the right is showed the squared grid used. Each one of the 9 spaces should be filled with detachable photos, similar to those presented in the photos sheet (in the left).
18
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
Main comments made during the inquiries:
• Original and pleasant;
• Photos should be clearer;
• Is a good way to talk about territory;
• It misses the cities and the urban areas.
Observations
In a general way both tests showed to be a good method to talk about the land cover pattern but not so good
as a method to build a true land cover mosaic.
The first test seemed to cause confusion by the grid and the try to represent a patch. Also the amount of
photos available were clearly too large. Also the final result, after fill the grid, didn’t seem to be a true
reflection of people’s opinion.
In the second test the line grid seemed to be clearer to understand. The fact of the number of photos has
been reduced was also positive. The difference between each land cover class showed was better defined,
turning the choice of photos faster and with more certain.
II.3.2 – SECOND TRIAL
After several meetings between the teamwork, the DYNAMO research group, the Agriculture Ministry and a
statistical advisor, was decided to test again the structure of the inquiries, retrying the grid (test A of the first
trial) and a new tool, a block diagram.
Fig. 9 – 2nd test grid and photos – In the 2nd test was used a grid of 9 photos in line (top of the figure). The photos presented first referred only to the CLC classes. When some of those classes were sub-divided in sub-classes, was showed a second set of photos, with the sub-division of that class. The red arrow indicates this second set of photos for the case of class of montado, which is sub-divided in four.
19
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
The decision to retry the grid was based on the fact that, in the first trial, the grid had spaces between the
photo placeholders, which seemed to work as a barrier, not letting people to imagine it as a land cover
pattern representation. Thus, in this second trial was tested a grid with all the columns and rows contiguous.
On other hand, retry it using new photos, these ones already from the study area and manipulated to better
represent each land cover type (see point II.1.5), permitted to understand if the photos it selves were a
negative aspect in the lack of success of the first trial.
Each person answered the inquiry, through both methods and was asked to comment each as well as the
general method as a mean to understand the landscape preferences.
In both tests were used the final photos, already from the study area and manipulated. This permitted to
understand if each photo was clear in the land cover type represented.
TEST C – Grid and block diagram
QUESTIONS:
Inquired people: 5 (2 farmers; 1 hunter, 2 inhabitants).
Time of each inquiry: ± 25 minutes.
Photos presentation: To answer the question 1 were showed just the 15 photos corresponding the main CLC
classes (group 1, table 2). Only in the question 2 were presented the photos of sub-levels of olive groves and
montado (group 2, table 2).
Questions proposed:
Question 1 - “Considering your activity chose, from the 15 photos available, those four that show the land
cover type you prefer and those four that show what you dislike more.”
Question 2 (In case of the olive groves and / or montado has been chosen as preferred) – “Being able to
change the photo related to the olive groves and / or montado, to another one more specific, do you prefer to
keep your first choice or change it?”
Question 3 – “Considering the land cover types chosen as preferred:”
Question 3.1 – “Fill the grid with the photos chosen, repeating it as many times as necessary, to better
represent the land cover pattern you prefer.”
Question 3.2 – “Using the block diagram, draw the distribution areas of each land cover type preferred.”
20
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
Observations
The people who answered it considered the inquiry pleasant and easy to understand.
In the question 3, concerning the composition of the land cover pattern, the grid seemed to be easier to
explain than the bock diagram. The fact of, with the block, each person had to draw the distribution of the
different classes, caused some confusion, due to details of scale and landforms. However, was also referred
the block permitted to better represent the proportion of each class.
It was also said that, in the classes of olive groves and montado, the photos showed were not the best, once
in both photos the trees seemed to be little productive.
It is important to referred that the land cover patterns, defined by each person through both methods (grid
and block), were always much different. When asked about this fact and about which method was more
representative of their opinion on the distribution and proportion of the land cover classes, the answer was
clearly that the block was represented better the distribution but the proportion was less reliable.
21
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
References
Abreu C., Correia, T., Oliveira, R., Contributos para a identificação e caracterização da paisagem em
Portugal continental. DGOTDU, Colecção de Estudos 10, Lisboa, 2004.
Al-Kodmany, K., Using visualisation techniques for enhancing public participation in planning and design:
process, implementation and evaluation, Landscape and Urban Planning, Volume 45, 1999, Pages 37-45.
Antunes, A. I., Ramos, I. L., Serafim, M. A. F, Impacte do abandono agrícola na paisagem: perspectivas de
um painel de peritos, Agronomia Lusitana, Volume 51 (4), Pages 331-346, 2007
Barry, J., Proops, J., Seeking sustainability discourses with Q methodology, 1999, Ecological Economics,
Volume 28, Pages 337 – 345.
De Groot, R. S., Wilson, M. A., Boumans, R. M. J., A typology for the classification, description and valuation
of ecosystem functions, goods and services, Ecological Economics, Volume 41, 2002, Pages 393-408.
European Environment Agency, CORINE Land Cover 1990
European Environment Agency, CORINE Land Cover 2000
Fairweather, J. R., Swaffield, S. R.; Visitors’ and Locals’ Experiences of Rotorua, New Zealand: An
Interpretative Study Using photographs of Landscapes and Q Method; International Journal of Tourism
Research, Volume 4, 2002, Pages 283 – 297.
Kaplan, R., Ryan, R. S., Kaplan, S., With people in mind – Design and management of everyday nature;
1998, Island Press, Washington, United States of America.
Klooster, P. M., Visser, M., Jong, M. D. T., Comparing two image research instruments: The Q-sort method
versus the Likert attitude questionaire, 2008, Food Quanlity and Preference, Volume 19, Pages 511-518.
Lewis, J. L.; Perceptions of landscape change in a rural British Columbia community; Landscape and Urban
Planning, Volume 85, 2008, Pages 45-59.
Luz, F., Participatory Landscape Ecology – A basis for acceptance and implementation; Landscape and
Urban Planning, Volume 50, 2000, Pages 157 – 166.
Menezes, H. G., 2007, Integração dos agentes locais na definição e caracterização de unidades de
paisagem. Caso de estudo: concelho de Castelo de Vide. Degree in Landscape Architecture Thesis,
University of Évora.
22
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
Petrosillo. I.; Zurlini, G.; Corlianò, M. E.; Zaccarelli, N.; Dadamo, M.; Tourist perception of recreational
environment and management in a marine protected area; Landscape and Urban Planning, Volume 79,
2007, Pages 29-37.
Pinto-Correia, T., Breman, B., Jorge, V., Dnesboská, M.; Estudo sobre o abandono em Portugal Continental
- Análise das dinâmicas da Ocupação do Solo, do Sector Agrícola e da Comunidade Rural. Tipologia das
Áreas Rurais, University of Évora, Portugal, 2006
Rosário, R. R., Carvalho, N. S.; Breve apresentação do projecto Impaza (PIDDAC 113): “Impacto do
abandono da actividade agrícola na estrutura paisagística de zonas sensíveis do interior de Portugal
continental”, Agronomia Lusitana, Volume 51 (4), Pages 233-238, 2007
Soliva, R., Ronningen, K., Bella, I., Bezak, P., Cooper, T., Flo, B. E., Marty, P., Potter, C.; Envisioning upland
futures: Stakeholder responses to scenarios for Europe’s mountain landscapes; Journal of Rural Studies,
Volume 24, 2008, Pages 56 – 71.
Swaffield, S. R., Fairweather, J. R.; Investigation of attitudes towards the effects of land use change using
image editing and Q sort method; Landscape and Urban Planning, Volume 35, 1996, Pages 213 – 230.
Tress, B.; Tress, G.; Scenario visualisation for participatory landscape planning—a study from Denmark;
Landscape and Urban Planning, Volume 64, Issue 3, 15 July 2003, Pages 161-178.
Patton, M. Q.; Qualitative Research and Evaluation Methods, 3rd edition, 2002, Thousand Oaks, CA:
SAGE.
van Doorn, A., Pinto-Correia, T., Differences in land cover interpretation in landscapes rich in cover
gradients: reflections based on the montado of South Portugal, Agroforestry systems, Volume 70, Issue 2,
2007, Pages 169 – 183.
Vos,W.; Meekes, H.; Trends in European cultural landscape development: perspectives for a sustainable
future; Landscape and Urban Planning, Volume 46, Issues 1-3, 15 December 1999, Pages 3-14.
Folke, C.; Carpenter, S.; Elmqvist, T.; Gunderson, L.; Holling, C. S.; Walker, B.; Bengtsson, J.; Berkes, F.;
Colding, J.; Danell, K.; Falkenmark, M.; Gordon, L.; Kasperson, R.; Kautsky, N.; Kinzig, A.; Levin, S.; Maker,
L., -G.; Moberg, F.; Ohlsson, L.; Olsson, P.; Ostrom, E.; Reid, W. Rockstrom, J.; Savenije, H.; Svedin, U,;
Resilience and sustainable development: building adaptative capacity in a world of transformations, 2002,
Background Paper for WSSD, ICSU Series for Sustainable Development No. 3. Johanenesburg, Resilience
23
Instituto de Ciências Agrárias Mediterrânicas - Grupo de Investigação em Ecossistemas e Paisagens Mediterrânicas
Institute of Mediterranean Agricultural Sciences - Research Group on Mediterranean Ecosystems and Landscapes
Alliance for the Swedish Environmental Advisory Council and the International Council and the International
Council for Science. URL: http://www.resalliance.org/reports/resilienceandsustainabledevelopment.pdf.