Adaptation and preparation of a Spatial Regional Reference Framework for MERCOSUR regions.

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Sustainability Impact Assessment: Tools

for Environmental

Social and

Economic Effects of

Multifunctional Land Use

in European Regions

Priority Area 1.1.6.3 "Global Change

and Ecosystems"

CONTRACT No 003874 (GOCE)

Integrated Project

Project Start Date: 01 December 2004

Duration: 48 months

- DELIVERABLE report -

Deliverable number: 8.3.2 b

Deliverable title:

Adaptation and preparation of a Spatial Regional Reference

Framework for MERCOSUR regions.

Organisation name of lead contractor for this deliverable: EMBRAPA

Partners involved: ALTERRA, FAUBA, UDELAR, UFSC.

Researchers involved: Ana Paula Turetta, Gabriel Fonte, Luis Iván Ortiz Valencia, Michael

Van Euapen, Marta Perez-Soba, Heitor Coutinho, Mariano Oyarzaba, Santiago Baeza,

Margareth Simões, Giovanna Fistarol, Sandro Schlindwein.

Due date of deliverable: November 2008.

Actual submission date: April 2009.

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Please indicate the names of the data files linked to this deliverable:

If you have not uploaded any data linked to this deliverable indicate for what reason:

If several project partners have to upload data for one deliverable you may copy the lines and indicate the respective partners and data uploaded!

Project co-funded by the European Commission within the Sixth Framework Programme (2002-2006)

Dissemination level

PU Public

PP Restricted to other programme participants (including the Commission Services

RE Restricted to a group specified by the consortium (including the Commission Services) CO Confidential, only for members of the consortium (including the Commission Services) x

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Objectives: To develop a Spatial Regional Reference Framework (SRRF) for the Sensor

Mercosur Area – La Plata Basin;

To describe the MERCOSUR Cluster Regions.

Activities: State-of-the-art review of existing literature related to concepts of regionalization

in the La Plata basin; definition of the most suitable approach for MERCOSUR.

Results: Proposition of the regionalization of MERCOSUR – La Plata Basin, based on

economic, social and environmental parameters available in global databases and survey of

information about Brazil, Argentina and Uruguay to be included in the project database.

Milestones achieved: MERCOSUR regionalization – La Plata Basin.

Deviations and reasons: The first decision was to work with administrative regions in

countries due to data constraints and the low availability of time to carry out the work.

However, these results had some important limitations that made the team choose to

present a proposal for the regionalization of the La Plata Basin based on the data available in

global databases.

Publications: (1) Manuscript Draft submitted to Elsevier Editorial System(tm) for

Environmental Science & Policy. Title: Spatial Regionalisation in Europe, MERCOSUR and

China for Sustainability Impact Assessment; (2) Abstract submitted and approved to be

present at XIV Brazilian Symposium of Remote Sensing, that will occur on April 2009; (3)

Abstract submitted and approved to be present at ESRI International User Conference (ESRI

UC), that will occur on July 2009

Meetings: Rio de Janeiro Workshop (February 08); Florianopolis Workshop (May 08) and

Montevideo Workshop (June 08), Training at Alterra (November 08).

Remarks concerning further SENSOR activities: This work prepares the expertise

necessary for implementation of the SIAT prototype at a regional level in D 8.3.1a/b and D

8.3.3 MERCOSUR.

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1. Introduction ... 6

2. La Plata Basin... 7

3. Spatial Reference Framework for MERCOSUR ... 8

Phase 1: ... 8

Phase 2 ...10

4. Conclusions ...14

5. References ...15

Annex I ...16

Annex II...23

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Executive Summary

The Mercosur (South Common Market) was implemented in 1991, and includes Brazil,

Argentina and Uruguay, partners in the Sensor TTC project. Despite being close to

completing 20 years of its creation this agreement is still very strongly connected to

economic issues. Social and environmental issues addressed by this group of countries are

rare, resulting in a lack of institutions dealing with common policies for the block, and limited

data available that considers the Mercosur as an integrated region. Therefore, the first

approximation for the creation of cluster regions in the La Plata River Basin, the project case

study region in the Mercosur, considered as spatial units the countries´ administrative areas

that contain a reasonable amount of indicator data. These included the Argentinian

Departments, Uruguayan Censitary Units, and Brazilian micro-regions. This initial approach

for a Mercosur Spatial Regional Reference Framework is being used for the implementation

of the first SIAT prototype, based on the policy case "sugarcane expansion in Mato Grosso

do Sul". The second effort aimed at creating cluster regions from areas with similar

socio-economic and environmental features, more like the procedure adopted by the European

Sensor team. This resulted in an improved SRRF that will be used for the implementation of

the second SIAT prototype, related to the policy case "expansion of afforestation in the La

Plata River Basin". It still needs improvement, but the results are very promising and show

that the Sensor methodology is useful for creating cluster regions in the Mercosur area.

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bio-physical and socio-economic variables describing the regions of the La Plata Basin and to

prepare a spatial regionalization for that area.

The framework of the Sensor approach is based on the DPSIR framework and it is an

adaptation of the ecosystem function approach in that it assesses the direct impact of land

use change on the three pillars of sustainability rather than the indirect effect of

environmental change caused by land use on social and economic sustainability (Sensor

Deliverable Report, 3.1.3). The framework also must reflect how changes in policy can

impact the performance of multiple functions associated to land use.

In MERCOSUR, the SENSOR TTC project is concentrating on the La Plata river Basin where

during recent decades there has been intensive land use change, with rapid expansion and

intensification of cultivation. The case studies are sugar cane expansion in Mato Grosso do

Sul State, Brazil, and forest expansion in Santa Catarina State, Argentina and Uruguay.

The challenge in defining the spatial framework for MERCOSUL is the harmonization of the

regionalization between Brazil, Argentina and Uruguay, because these countries have

different administration regions, with different levels of availability of sustainability indicator

data and policies.

(7)

2. La Plata Basin

In the last five decades development trends have created large divergences in the land cover

of the mid latitudes, with many developed nations experiencing an expansion of native

vegetation over formerly cultivated land, and most developing countries undergoing the

fastest expansion and intensification of cultivation in their history. These contrasting trends,

coupled with global change mitigation/adaptation needs, impose a challenging scenario on

the Rio de la Plata Basin (Figure 1), where the pressures for high short-term land outputs

conflict with their long-term sustainability and the provision of vital ecosystem services. As

the basin assumes a key role for international food security through its growing exports of

agricultural goods, the comprehension of land use change processes and consequences and

its coupling with global environmental change mitigation become an urgent need (Coutinho

et al, 2008). In addition, the long-range linkages of climate, biogeochemical cycling, and

economics give global significance to land cover changes over the basin and demand their

integration into global models. The majority of the territory of the core MERCOSUR region

(Southern Cone Common Market, comprising the South American countries Argentina, Brazil,

Paraguay and Uruguay) belongs to the La Plata river basin. With a total 3.1 million km

2

_{, it is}

the second largest river basin in South America. Thirty-one large dams and 57 large cities,

each with populations in excess of 100,000 persons, including all MERCOSUR capitals, are

located inside the La Plata river Basin (Asunción, Brasilia, Buenos Aires, and Montevideo),

and also the region’s largest metropolitan areas (São Paulo, in Brazil, and Buenos

Aires-Rosario, in Argentina). The total human population of the Basin is estimated to be

approximately 67 million individuals. About 60 percent of the Gross Domestic Product (GDP)

of the MERCOSUR countries plus Bolivia is generated from the La Plata basin area.

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signing of the Treaty of Assumption in Paraguay. The members of this important economic

block in South America are: Argentina, Brasil, Paraguay, Uruguay and Venezuela (which

joined in July 2006). Currently the Mercosur countries have a total population estimated at

311 million inhabitants and a GDP of approximately 2 trillion dollars.

Nevertheless, projects that consider the dimension of the economic block are still rare, which

results in the non-existence of a unified database or a territorial regionalization that

considers natural and socio-economic aspects of the country.

The Sensor TTC project adopted a spatial focus on the total area of MERCOSUR, that

corresponds to the La Plata river Basin as the area of study. The countries which are

participating in this project are: Brazil, Argentina and Uruguay. Greater details about this

question can be obtained in the project Document of Work (DoW).

The La Plata Basin has approximately 3.1 million km

2

_{and represents a very dynamic area}

that expresses very well the current reality in terms of changes in land use in developing

countries. Both in Europe and South America the pressure on natural resources is increasing,

nevertheless, the continents differ in their intervention priorities and the intensities of the

processes, including decision making and policy formulation and implementation. Part of

these differences are due to diverse institutional capability to produce and share data to

enable a regional spatial framework that can be the basis for territorial ordinance planning

and land use policy making.

The SRRF formulation process for the La Plata Basin can be divided into two phases: the first

was based on the administrative regions existing in the area and the second on the global

database available for the area.

Phase 1:

It was decided that the spatial units for MERCOSUR would be the combination of the

Brazilian micro-regions, Argentinean departments and Uruguay’s census units (Figure 2).

This option considered the most detailed information level for each country. In Brazil it was

decided to use the micro-regions since it is possible to obtain quality information for this

administrative level and also because they result from a clustering process. The

micro-regions, which are groups of municipalities, the lowest administrative level in Brazil, have

been used by IBGE (Brazil Institution of Geographic and Statistics) since the 1970´s. The

criterion to create a micro-region is based on the unity of natural, social and economic

characteristics (IBGE, 1970). In the 1990´s the micro-region concept was enhanced and

began to consider some of the peculiarities regarding the organization of space (IBGE,

1997), including the relationship between micro-regions in numerous aspects of production

structure, agriculture, industry, extractive minerals, and fishing. The concept stresses that

micro-regions are not individual, self-sufficient areas but are interdependent.

For the characterization of the administrative units the same variables as used in the

characterization of cluster regions in Europe were used. Table 1 shows these variables and

their availability in the different countries.

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Table 1: Data available for areas characterization in MERCOSUR based on SENSOR EU

criteria.

Figure 2: First SRRF proposal for MERCOSUR.

Variables EU

Brazil

Argentina

Uruguay

Environmental zones

-

Temperature

X

Precipitation

X

Soils

X

Land Cover

X

Forest cover

X

Population Density

X

-

GDP

X

Unemployment rate

X

Livestock

X

Land use

X

-

Agricultural limitations

X

-

Functional Urban Areas

X

-

Amount of beds per local inhabitants

-

(10)

The results of this work were positive since they brought together in a single database

information with the greatest level of detail for the countries involved. Despite this, it was

not satisfactory for the definition of a SRRF for the La Prata basin, which led the group to

look for new alternatives for the definition of the work. This fact can be attributed to three

principal factors:

• Heterogeneity among countries: the countries are very different in many aspects. For

example: Uruguay measures 176,000 km

2

_{while the area of Brazil is 8,500,000 km}

2

_.

This fact defines a series of different organization levels in the countries;

• Based on administrative boundaries: as the administrative boundaries reflect the

differences among the organization level of the countries, it is not a good approach

for the objective of this work;

• Number of regions: in total there are 1,218 administrative units in Brazil, Argentina

and Uruguay.

One question that has to be emphasized is that the methodological concept used in this

phase differs completely from that adopted in Europe, since the characterization of

administrative regions do not allow a new regionalization proposal to be generated based on

the natural and socio-economic similarities within the La Plata Basin.

A further reason for the development of Phase 2 SRRF is that the initial approach did not

enable a test of the transferability of the European SRRF framework, based on the clustering

of regions considering social, economic, and environmental characteristics. Please note that

phase 1 SRRF will be used in the first SIAT prototype, under development, targeted towards

the policy case of sugarcane expansion in the State of Mato Grosso do Sul. Ex-ante impact

evaluation at the State level in Brazil will have best results if carried out using micro-regions

as the basic spatial planning unit.

Phase 2

Phase 2 of the project proposes the creation of similar regions in the La Plata basin based on

the collection of information available in global databases and made available by

international reference institutions (FAO, USGS, etc...). The list of data used, as well as the

sources, can be seen in Table 2.

Table 2: List and references of dataset used in Phase 2.

MERCOSUR

Number of variables

Data source

Soils

1 FAO Geonetwork Portal

Ecological Zones

2 FAO Geonetwork Portal

Elevation

1 FAO Geonetwork Portal

Climate

1 FAO Climpag

Temperature

1 World Clim

Land Use

1 FAO Geonetwork Portal

Roads (Infrastructure)

1 The Pennsylvania State University

Population Density

1 United Nations Environment Programme

The ArcGis 9.3 software (ESRI, Inc., Redlands, CA) was used as the spatial focus for the

micro-regional information plans for Brazil and the ‘departments’ for Argentina and Uruguay.

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After this process, the TwoStep cluster method

1

statistical analysis was run in SPSS version

15 which groups similar areas according to the variables used.

The Two-Step cluster method is an exploratory tool designed to reveal natural groupings (or

clusters) within a dataset which can handle very large data sets. It is implemented in the

statistical software SPSS. It requires only two steps: first, pre-clustering the cases into many

small sub-clusters, and then clustering the sub-clusters resulting from pre-cluster step into

the final number of clusters. The pre-cluster step uses a sequential clustering approach. It

scans the data records one by one and decides if the current record should be merged with

the previously formed clusters or if it starts a new cluster based on the distance criterion.

The procedure is implemented by constructing a modified cluster feature (CF) tree.

The algorithm employed by this procedure has several desirable features:

• Handling of categorical and continuous variables. By assuming variables to be

independent, a joint multinomial-normal distribution can be placed on categorical and

continuous variables.

• Automatic selection of the number of clusters. By comparing the values of a

model-choice criterion across different clustering solutions, the procedure can automatically

determine the optimal number of clusters.

• Scalability. By constructing a cluster features (CF) tree that summarizes the records,

the Two-Step algorithm allows large data files to be analyzed.

Two types of distance measures are considered: the Euclidean distance and the likelihood

distance. The former is available when no categorical variables are specified. The latter is

especially useful when categorical variables are used. The likelihood function is computed

using the normal density for continuous variables and the multinomial probability mass

function is used for categorical variables. All variables are treated as independent.

Importance measures are plotted using a Pearson chi-square statistic as the importance of a

categorical variable and a t-statistic as the importance of a continuous variable. Significance

reports one minus the p value for the test of equality of means for a continuous variable and

the expected frequency with the overall dataset for a categorical variable. For this study 5

categorical variables – soil, environmental zones (2 variables), land use and climate - and 4

continuous variables – roads, population density, elevation and temperature – were

considered.

597 units were considered, corresponding to all the micro-regions of Brazil and the

departments of Argentina and Uruguay which are part of the La Plata Basin. Of these units,

551, or 92.3%, were considered valid for the system analysis.

20 MLPC (Mercosur-La Plata cluster) were identified (Figure 4). The mean size of the MLPC

was 139,471 km

2

_{. The smallest MLPC was the 13}

th

_{with 9,661 km}

2

_{and the biggest was the}

14

th

with 435,562 km

2

(Figure 4). Annex III contains a description of the MLPC in relation to

the variables considered in the analysis.

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0 50.000 100.000 150.000 200.000 250.000 300.000 350.000 400.000 450.000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 MLPC K m 2

Figure 4: Areas in km

2

_{of Mercosur-La Plata cluster (MLPC).}

Table 4: Average and standard deviation of the continuous variables considered in the

analysis of the Mercosur-La Plata cluster (MLPC).

Roads (Km)

Population Density

(hab/km

2

)

Elevation (m)

Temperature

(

o

C)

MLPC

Mean

Std.

Deviation

Mean

Std.

Deviation

Mean

Std.

Deviation

Mean

Std.

Deviation

1 330,456

301,319

30.40

40.01

31.4

18.35

18.5

0.95

2 257,350

232,742

99.24

185.22

40.9

22.27

18.2

1.06

3 650,736

654,651

49.82

112.25

132.3

76.82

18.6

0.63

4 395,704

317,456

8.58

7.70

150.2

61.91

18.1

1.05

5 436,122

315,071

21.36

27.57

77.0

35.06

18.4

0.57

6 247,712

207,115

87.11

253.45

40.6

43.31

18.2

1.07

7 564,514

550,471

17.31

25.04

444.5

291.25

18.3

0.72

8 1,018,328

694,347

20.97

58.90

162.9

144.00

19.1

0.95

9 329,644

368,058

26.66 48.96 1,701.6 1,047.85

18.1

1.62

10 403,472

298,772

185.94 652.27 1,328.0 1,435.62

18.5

1.43

11 504,984

498,552

13.36

13.17

71.6

14.76

20.0

0.31

12 292,801

184,828

44.89

122.73

66.7

36.80

19.2

0.83

13 34,156

35,412 3,886.66 3,223.71

18.8

5.54

18.3

0.75

14 1,390,327 1,432,341

36.14

31.87

624.9

197.18

20.3

0.51

15 582,135

473,811

221.65

534.88

519.0

168.51

19.6

0.66

16 761,596 1,047,872

324.86 1,635.92 1,183.6 1,341.93

19.5

2.24

17 502,672

231,218

72.82

132.97

488.7

121.22

19.1

0.50

18 459,246

418,221

68.43

87.33

679.0

258.38

18.6

0.49

19 310,767

200,611

56.03

44.33

950.4

142.07

18.6

0.55

20 518,729

386,462

119.44

390.42

588.3

246.62

18.3

0.76

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The environmental variables had a strong influence on cluster definition, probably because

they were the most abundant data. The characteristic of environmental data is relevant in

this case, because it is common to find studies at regional scales with very well systematized

natural descriptions, (e.g., FAO Geonetworks). As can be seen in Figure 6, the

environmental variables were the main responsibles for the definition of the Mercosur-La

Plata cluster (MLPC).

0 1 2 3 4 5 6 7 8 9

F

re

q

u

e

n

c

y

Soils Ecol. Zones

Climate Land Use Elevation Temp. Roads Pop.

Density

Variables

Figure 5: Most important variables in

Mercosur-La Plata cluster

(MLPC) definition.

The variables Ecological Zones and Soils had the strongest influence on cluster definition.

However, considering only the socio-economics variables, the population density is the most

important variable in 70% of MLPCa.

4. Conclusions

This was the first approximation of a MERCOSUR – La Plata basin regionalization proposal

where it was possible to identify general domains in the area. However, it is important to

refine and improve the dataset, selecting the most relevant variables and adding

socio-economics data. The methodology was shown to be useful and robust to work with very

large datasets.

Nevertheless, it is worth emphasizing, for the purposes of the SIAT MERCOSUR prototype,

that the division into micro-regions in Mato Grosso do Sul State (Phase 1) will be maintained,

defined as a project study area.

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The Phase 2 SRRF can be further enhanced by the entry of data from Bolivia and Paraguay,

leading to the consolidation of a full La Plata River basin SRRF. The SIAT Mercosur second

prototype will be based on the Phase 2 SRRF, since the case study of forestry expansion is

relevant to at least 3 countries of the basin: Brazil, Argentina, and Uruguay. Simulations of

sustainability impact analysis of potential Mercosur land use policies will greatly benefit from

the proposed SRRF.

5. References

Coutinho, H. L. C.; Noellemeyer, E.; Jobbagy, E.; Jonathan, M. and Paruelo, J. 2008. Impacts

of land use change on ecosystems and society in the Rio de La Plata Basin. In: Applying

Ecological Knowledge to Landuse Decisions. Edited by H. Tiessen & J. W. B. Stewart. A

publication of SCOPE, IAI, and IICA. p. 56-64.

(

www.iai.int/files/communications/publications/institutional/Applying_Ecological_Knowle

dge_to_Landuse_Decisions.pdf)

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2_{Source: IBGE – Population Count.}

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TABLE – RESIDENT POPULATION – 2007

BRAZIL AND GEOGRAPHIC MICRO REGION RESIDENT POPULATION (PERSONS)

Brazil

183.987.291 Goiás

5.647.035 Goiânia - GO

2.032.305 Entorno de Brasília - GO

960.141 Anápolis - GO

517.221 Sudoeste de Goiás - GO

397.387 Meia Ponte - GO

338.147 Porangatu - GO

220.794 Ceres - GO

215.820 Catalão - GO

133.156 Vale do Rio dos Bois - GO

107.317 Vão do Paranã - GO

102.927 Anicuns - GO

100.759 Quirinópolis - GO

95.094 Pires do Rio - GO

90.327 Rio Vermelho - GO

86.362 São Miguel do Araguaia - GO

76.625 Chapada dos Veadeiros - GO

60.267 Iporá - GO

58.845 Aragarças - GO

53.541 TABLE – RESIDENT POPULATION – 2007

BRASIL AND GEOGRAPHIC MICROREGION RESIDENT POPULATION (PERSONS)

Brazil

183.987.291 Minas Gerais

19.273.506 Belo Horizonte - MG

4.831.805 Uberlândia - MG

818.395 Juiz de Fora - MG

724.276 Montes Claros - MG

592.000 Ipatinga - MG

511.551 Divinópolis - MG

456.384 Varginha - MG

426.551 Governador Valadares - MG

412.088 Sete Lagoas - MG

394.264 Itabira - MG

370.378 Uberaba - MG

333.696 Poços de Caldas - MG

326.809 Pouso Alegre - MG

304.788 Januária - MG

269.999 Muriaé - MG

266.786 Teófilo Otoni - MG

258.080 Ubá - MG

257.751 Manhuaçu - MG

257.467 São Sebastião do Paraíso - MG

254.801

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Patos de Minas - MG

245.875 Janaúba - MG

243.080 Conselheiro Lafaiete - MG

235.045 Viçosa - MG

221.406 Passos - MG

218.814 Alfenas - MG

218.752 Barbacena - MG

216.618 Cataguases - MG

211.010 Salinas - MG

208.739 Paracatu - MG

208.367 São Lourenço - MG

204.532 Capelinha - MG

196.894 Patrocínio - MG

194.138 Araxá - MG

191.527 Ponte Nova - MG

187.901 Itajubá - MG

183.888 São João Del Rei - MG

177.648 Almenara - MG

175.991 Frutal - MG

172.124 Ouro Preto - MG

164.204 Pirapora - MG

159.963 Bom Despacho - MG

158.065 Araçuaí - MG

154.850 Formiga - MG

149.047 Aimorés - MG

146.412 Curvelo - MG

145.426 Lavras - MG

143.686 Unaí - MG

142.122 Ituiutaba - MG

136.376 Santa Rita do Sapucaí - MG

134.563 Guanhães - MG

129.450 Oliveira - MG

123.058 Nanuque - MG

118.587 Pará de Minas - MG

117.214 Campo Belo - MG

111.210 Três Marias - MG

93.984 Conceição do Mato Dentro - MG

86.896 Pedra Azul - MG

84.313 Peçanha - MG

83.919 Diamantina - MG

82.840 Piuí - MG

78.699 Andrelândia - MG

72.579 Bocaiúva - MG

66.040 Mantena - MG

61.951 Itaguara - MG

59.767 Grão Mogol - MG

42.046

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TABLE – RESIDENT POPULATION – 2007

Brazil

183.987.291 Mato Grosso

2.854.642 Cuiabá - MT

806.097 Rondonópolis - MT

252.949 Sinop - MT

166.272 Alto Teles Pires - MT

154.675 Colíder - MT

143.517 Tangará da Serra - MT

142.981 Aripuanã - MT

133.006 Alto Pantanal - MT

127.747 Jauru - MT

104.629 Norte Araguaia - MT

103.677 Alta Floresta - MT

101.589 Canarana - MT

92.066 Parecis - MT

77.713 Arinos - MT

75.324 Primavera do Leste - MT

70.653 Alto Guaporé - MT

62.724 Médio Araguaia - MT

62.058 Tesouro - MT

53.472 Paranatinga - MT

33.474 Rosário Oeste - MT

31.619 Alto Paraguai - MT

29.420 Alto Araguaia - MT

28.980 TABLE – RESIDENT POPULATION – 2007

Brazil

183.987.291 Mato Grosso do Sul

2.265.274 Campo Grande - MS

802.066 Dourados - MS

456.396 Iguatemi - MS

212.644 Três Lagoas - MS

137.554 Baixo Pantanal - MS

129.140 Alto Taquari - MS

112.545 Bodoquena - MS

102.158 Aquidauana - MS

100.599 Nova Andradina - MS

84.243 Paranaíba - MS

72.543 Cassilândia - MS

55.386

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Paraná

10.284.503 Curitiba - PR

3.063.140 Londrina - PR

702.867 Maringá - PR

502.201 Foz do Iguaçu - PR

457.510 Cascavel - PR

428.484 Ponta Grossa - PR

419.469 Guarapuava - PR

376.178 Toledo - PR

359.397 Apucarana - PR

270.874 Paranavaí - PR

260.588 Umuarama - PR

256.894 Paranaguá - PR

245.845 Francisco Beltrão - PR

231.021 Campo Mourão - PR

212.794 Cornélio Procópio - PR

177.102 Astorga - PR

176.726 Telêmaco Borba - PR

154.619 Pato Branco - PR

152.464 Ivaiporã - PR

142.508 Cianorte - PR

135.123 Prudentópolis - PR

125.602 Jacarezinho - PR

121.056 Goioerê - PR

118.426 União da Vitória - PR

116.373 Jaguariaíva - PR

100.036 Wenceslau Braz - PR

95.018 Irati - PR

93.866 Capanema - PR

93.055 Palmas - PR

88.852 Rio Negro - PR

84.586 Porecatu - PR

81.236 Pitanga - PR

78.534 Ibaiti - PR

76.566 Assaí - PR

70.554 São Mateus do Sul - PR

60.240 Lapa - PR

45.891 Faxinal - PR

45.381 Floraí - PR

33.069

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TABLE – RESIDENT POPULATION – 2007

Brasil

183.987.291 Santa Catharina

5.866.252 Florianópolis - SC

817.984 Joinville - SC

776.500 Blumenau - SC

626.453 Itajaí - SC

491.086 Chapecó - SC

385.043 Tubarão - SC

356.902 Criciúma - SC

351.113 Joaçaba - SC

310.347 Campos de Lages - SC

288.937 Canoinhas - SC

238.342 Rio do Sul - SC

194.442 São Miguel do Oeste - SC

171.716 Araranguá - SC

168.498 Xanxerê - SC

145.691 Concórdia - SC

139.969 São Bento do Sul - SC

126.176 Curitibanos - SC

117.828 Tijucas - SC

82.667 Ituporanga - SC

53.269 Tabuleiro - SC

23.289

Source: IBGE – Population Count

TABLE – RESIDENT POPULATION – 2007

Brasil

183.987.291 Rio Grande do Sul

10.582.840 Porto Alegre - RS

3.646.763 Caxias do Sul - RS

719.876 Pelotas - RS

493.931 Santa Maria - RS

365.981 Campanha Ocidental - RS

360.633 Osório - RS

321.505 Passo Fundo - RS

321.332 Santa Cruz do Sul - RS

313.323 Lajeado-Estrela - RS

294.046 Gramado-Canela - RS

286.344 Litoral Lagunar - RS

255.717 Erechim - RS

210.826 Santo Ângelo - RS

197.549 Montenegro - RS

190.598 Campanha Central - RS

184.129 Ijuí - RS

180.625 Frederico Westphalen - RS

177.876 Campanha Meridional - RS

168.981 Carazinho - RS

158.669 Vacaria - RS

157.336

(22)

Cachoeira do Sul - RS

153.693 Cruz Alta - RS

150.843 Três Passos - RS

144.599 São Jerônimo - RS

138.184 Camaquã - RS

126.324 Guaporé - RS

124.513 Serras de Sudeste - RS

115.503 Santiago - RS

111.715 Soledade - RS

72.456 Cerro Largo - RS

66.422 Restinga Seca - RS

63.331 Sananduva - RS

60.823 Jaguarão - RS

53.175 Não-Me-Toque - RS

41.465

(23)

Data available from

Brazil, Argentina and Uruguay.

(24)

CLUSTER REGIONS

Brazil

Goiás Main City

POPULATION DENSITY (hab./km²) 3 GDP per capita (US$)4 Anápolis 1.075 8.784 Araçu 154 3.993 Brazabrantes 124 6.404 Campo Limpo de Goiás Not Available 4.296

Caturaí 206 4.642 Damolândia 85 5.166 Heitoraí 230 3.641 Inhumas 614 6.018 Itaberaí 1.471 8.440 Itaguari 127 4.446 Itaguaru 240 5.353 Itauçu 384 5.492 Jaraguá 1.889 5.188 Jesúpolis 121 4.040 Nova Veneza 123 5.599

Ouro Verde de Goiás 210 4.107 Petrolina de Goiás 553 4.463 Santa Rosa de Goiás 171 4.343 São Francisco de Goiás 373 5.130 Anápolis Taquaral de Goiás 210 4.751 Adelândia 115 4.611 Americano do Brasil 134 4.598 Anicuns 962 7.424 Aurilândia 565 4.998 Anicuns Avelinópolis 164 6.560

3_{IBGE Censo demográfico (www.ibge.org.br/SIDRA).}

(25)

CLUSTER REGIONS

Brazil

Goiás Main City

POPULATION DENSITY (hab./km²) 3 GDP per capita (US$)4 Buriti de Goiás 199 4.184 Firminópolis 406 4.517 Mossâmedes 685 5.289 Nazário 300 7.015 Sanclerlândia 497 6.327 Santa Bárbara de Goiás 140 5.309 São Luís de Montes Belos 826 8.268

Turvânia 472 8.873

Aragarças Not Available Not Available Not Available

Anhanguera 55 5.936

Campo Alegre de Goiás 2.463 24.927

Catalão 3.777 35.974 Corumbaíba 1.875 22.173 Cumari 572 5.854 Davinópolis 520 7.039 Goiandira 561 6.227 Ipameri 4.368 13.341 Nova Aurora 303 6.111 Ouvidor 414 26.715 Catalão Três Ranchos 282 5.131 Ceres Not Available Not Available Not Available Chapada dos Veadeiros Not Available Not Available Not Available

Abadiânia 1.044 3.891

Água Fria de Goiás 2.029 13.582 Águas Lindas de Goiás 191 2.099

Alexânia 848 10.466

Cabeceiras 1.114 10.507 Cidade Ocidental 389 3.288 Entorno de Brasília

(26)

Goiás Main City (hab./km²) capita (US$) Corumbá de Goiás 1.063 4.153 Cristalina 6.168 16.355 Formosa 5.807 4.750 Luziânia 3.962 7.662 Mimoso de Goiás 1.387 7.972 Novo Gama 192 2.457 Padre Bernardo 3.138 4.025 Pirenópolis 2.182 4.444 Planaltina 2.539 2.508 Santo Antônio do Descoberto 938 2.196 Valparaíso de Goiás 60 3.156 Vila Boa 1.060 4.963 Vila Propício 2.182 10.080 Abadia de Goiás 136 3.632 Aparecida de Goiânia 289 5.050 Aragoiânia 219 3.540

Bela Vista de Goiás 1.277 11.546 Bonfinópolis 122 3.896 Caldazinha 312 3.814 Goianápolis 162 2.987 Goiânia 741 11.119 Goianira 200 5.619 Guapó 521 3.437 Hidrolândia 944 8.778 Leopoldo de Bulhões 495 5.082 Nerópolis 204 9.534

Santo Antônio de Goiás 133 4.775 Senador Canedo 245 21.327 Goiânia

(27)

CLUSTER REGIONS

Brazil

Goiás Main City

POPULATION DENSITY (hab./km²) 3 GDP per capita (US$)4 Trindade 717 4.528

Iporá Not Available Not Available Not Available

Água Limpa 453 7.617

Aloândia 102 5.316

Bom Jesus de Goiás 1.405 11.793 Buriti Alegre 897 6.827 Cachoeira Dourada 521 31.776 Caldas Novas 1.590 7.701 Cromínia 370 5.147 Goiatuba 2.475 18.112 Inaciolândia 688 8.429 Itumbiara 2.457 15.945 Joviânia 445 7.832 Mairipotaba 461 8.415 Marzagão 228 4.832 Morrinhos 2.846 8.437 Panamá 434 8.543 Piracanjuba 2.405 8.688 Pontalina 1.438 6.298 Porteirão 604 21.274 Professor Jamil 348 4.476 Rio Quente 257 11.136 Meia Ponte Vicentinópolis 737 10.679 Cristianópolis 225 5.285 Gameleira de Goiás Not Available 14.469

Orizona 1.973 8.522

Palmelo 59 4.833

Pires do Rio 1.073 8.425 Pires do Rio

(28)

Goiás Main City (hab./km²) capita (US$) São Miguel do Passa Quatro 538 7.983

Silvânia 2.860 8.918

Urutaí 627 7.369

Vianópolis 954 8.061

Porangatu Not Available Not Available Not Available Cachoeira Alta 1.654 10.030 Caçu 2.251 7.539 Gouvelândia 831 10.841 Itajá 2.550 7.461 Itarumã 3.434 11.294 Lagoa Santa 10.812 Paranaiguara 1.154 5.297 Quirinópolis 3.780 7.501 Quirinópolis São Simão 414 57.715

Rio Vermelho Not Available Not Available Not Available São Miguel do Araguaia Not Available Not Available Not Available

Aparecida do Rio Doce 602 9.282

Aporé 2.901 12.376 Caiapônia 8.653 12.087 Castelândia 297 8.501 Chapadão do Céu 43.393 Doverlândia 3.207 10.050 Jataí 7.174 13.880 Maurilândia 394 7.165 Mineiros 9.067 11.330 Montividiu 1.875 19.474 Palestina de Goiás 1.321 7.820 Sudoeste de Goiás Perolândia 1.030 15.676

(29)

CLUSTER REGIONS

Brazil

Goiás Main City

POPULATION DENSITY (hab./km²) 3 GDP per capita (US$)4 Portelândia 551 11.875 Rio Verde 8.388 17.640 Santa Helena de Goiás 1.128 10.552 Santa Rita do Araguaia 1.362 6.116 Santo Antônio da Barra 452 7.152 Serranópolis 5.527 15.227 Acreúna 1.566 10.959 Campestre de Goiás 274 4.488 Cezarina 416 17.108 Edealina 604 10.716 Indiara 957 7.100 Jandaia 864 22.471 Palmeiras de Goiás 1.540 11.260 Palminópolis 388 7.244 Paraúna 3.781 14.906

São João da Paraúna 3.327 7.467 Turvelândia 934 36.728 Vale do Rio dos Bois

Varjão 519 5.409

(30)

(hab.) Brazil 183.987.291 Goiás 5.647.035 Total Area(km²) Unemployment (%) 5 Land Use (Ton)6 Livestock (Cattle density; unit per km²) 7 GDP Domestic Product (US$)8 Temperature (ºC) 9 Precipitation (mm)10 Soil11 Soil Cover (%)12 Forest Cover13 Conservation Unity14 Anápolis 517.221 8.358 43 Coffe 1,131,000 Sugarcane 551,700 Corn 147,150

137 5.215 30 Not Available Argissolo Vermelho Latossolo Vermelho Planted Pasture 58,6 Temporary Crop 9,6 Natural Pasture 83,8 Seasonal Forest Savana -

5_{ZEE Brasil 2001 - Produto 1 (CD-ROM).}

7_{IBGE Censo Agropecuário (www.ibge.org.br/SIDRA).}

9_{INPE-CPTEC 2008 (http://satelite.cpetc.inpe.br/PCD/).}

11_{EMBRAPA SOLOS (www.cnps.embrapa.br).}

(31)

CLUSTER REGIONS

Resident Population

(hab.)

Social Indicator Economic Indicator Environmental Indicators Brazil 183.987.291 Goiás 5.647.035 Total Area(km²) Unemployment (%) 5 Land Use (Ton)6 Livestock (Cattle density; unit per km²) 7 GDP Domestic Product (US$)8 Temperature (ºC) 9 Precipitation (mm)10 Soil11 Soil Cover (%)12 Forest Cover13 Conservation Unity14 Anicuns 100.759 5.465 45 Sugarcane 726,697 Coffe 251,000 Corn 71,840 162 5.998 34 Not Available Argissolo Vermelho Latossolo Vermelho Planted Pasture 69,5 Temporary crop 7,1 Pastagen Natutral 89,4 Seasonal Forest Savana - Catalão 133.156 15.190 42 Soybean 280,120 Coffe 5,292,000 Corn 215,243

67 14.494 Not Available Not Available

Cambissolos Háplicos Latossolos Vermelhos Argissolos Vermelho Natural Pasture 70,1 Planted Pasture 34,5 Temporary crop 11 Savana - Entorno de Brasília 960.141 38.079 45 Sugarcane 400,248 Coffe

61 6.113 29 Not Available Cambissolos Háplicos Latossolos Natural Pasture 81,4 Savana -

(32)

Brazil 183.987.291 Goiás 5.647.035 Total Area(km²) Unemployment (%) 5 Land Use (Ton)6 (Cattle density; unit per km²) 7 GDP Domestic Product (US$)8 Temperature (ºC) 9 Precipitation (mm)10 Soil11 Soil Cover (%)12 Forest Cover13 Conservation Unity14 Coffe 2,266,000 Corn 522,509 Latossolos Vermelhos Plintossolos 81,4 Planted Pasture 41,5 Lavavoura Temporaria 7,6 Goiânia 2.032.305 6.825 44 Coffe 407,000 Corn 42,441 Soybean 20,725

105 6.638 Not Available Not Available Latossolos Vermelho Cambissolo Háplico Natural Pasture 86,18 Planted Pasture 57,96 Temporary crop 7,08 Savana

(33)

CLUSTER REGIONS

Resident Population

(hab.)

Social Indicator Economic Indicator Environmental Indicators Brazil 183.987.291 Goiás 5.647.035 Total Area(km²) Unemployment (%) 5 Land Use (Ton)6 Livestock (Cattle density; unit per km²) 7 GDP Domestic Product (US$)8 Temperature (ºC) 9 Precipitation (mm)10 Soil11 Soil Cover (%)12 Forest Cover13 Conservation Unity14

Meia Ponte 338.147 21.161 42 Soybean 555,312 Sugarcane 1,324,145 Corn 531,230 102 10.442 30 969 Latossolo Vermelho Argissolo Vermelho Natural Pasture 75,8 Planted Pasture 57,3 Temporary crop 17,4 Savana Seasonal Forest -

(34)

Brazil 183.987.291 Goiás 5.647.035 Total Area(km²) Unemployment (%) 5 Land Use (Ton)6 (Cattle density; unit per km²) 7 GDP Domestic Product (US$)8 Temperature (ºC) 9 Precipitation (mm)10 Soil11 Soil Cover (%)12 Forest Cover13 Conservation Unity14 Pires do Rio 90.327 9.418 39 Soybean 244,150 Coffe 440,000 Corn 107,360 94 8.347 31 Not Available Cambissolos Háplicos Latossolos Vermelhos Natural Pasture 78,4 Planted Pasture 46,5 Temporary crop 11,1 Savana - Quirinópolis 95.094 16.068 44 Soybean 100,780 Rice 6,031 Corn 144,356

70 14.276 Not Available Not Available

Latossolos Vermelhos Argilossolos Vermelhos Natural Pasture 95,4 Pastage Plantada 76,9 Temporary crop 3,4 Seasonal Forest Savana - Sudoeste de Goiás 397.387 53.928 42 Soybean 2,221,641 Sugarcane 3,035,110 Corn 1,811,913

58 13.311 Not Available Not Available _VermelhosLatossolos Argissolos Vermelhos Neossolos Quartzarênicos Natural Pasture 74,7 Planted Pasture 50,2 Temporary crop 16 Savana Seasonal Forest National Park of Emas

(35)

CLUSTER REGIONS

Resident Population

(hab.)

Social Indicator Economic Indicator Environmental Indicators Brazil 183.987.291 Goiás 5.647.035 Total Area(km²) Unemployment (%) 5 Land Use (Ton)6 Livestock (Cattle density; unit per km²) 7 GDP Domestic Product (US$)8 Temperature (ºC) 9 Precipitation (mm)10 Soil11 Soil Cover (%)12 Forest Cover13 Conservation Unity14 crop 16

Vale do Rio dos

Bois 107.317 15.169 43 Soybean 309,950 Sugarcane 2,008,640 Corn 267,412

92 12.988 35 Not Available _VermelhosLatossolos

Natural Pasture 78 Planted Pasture 57 Temporary crop 15,2 Savana Seasonal Forest

(36)

CLUSTER REGION Brasil 183.987.291 Minas Gerais 19.273.506 Main City TOTAL AREA (km²)15 Domestic Product (US$)16 UNEMPLOYMENT (%) 17 Alfenas 73 8.668 41 Alterosa 335 4.838 42 Areado 227 5.632 43

Carmo do Rio Claro 884 7.769 41 Carvalhópolis 81 4.955 46 Conceição da Aparecida 352 6.858 40 Divisa Nova 218 5.015 41 Fama 65 6.199 51 Machado 574 9.509 44 Paraguaçu 380 7.204 52 Poço Fundo 479 5.601 36 Alfenas 218.752 3.881 Serrania 212 5.897 59 Aiuruoca 657 6.217 41 Andrelândia 1.019 5.234 37 Arantina 94 3.502 41 Bocaina de Minas 248 3.329 39 Bom Jardim de Minas 392 4.084 44 Carvalhos 287 3.926 55 Cruzília 530 4.794 45 Liberdade 404 4.770 43 Minduri 223 5.310 38 Passa-Vinte 42 4.345 36 Andrelândia 72.579 4.622

São Vicente de Minas 396 6.265 43

(37)

CLUSTER REGION Resident Population Total Area(km²) Brasil 183.987.291 Minas Gerais 19.273.506 Main City TOTAL AREA (km²)15 GDP Domestic Product (US$)16 UNEMPLOYMENT (%) 17 Seritinga 116 5.332 44 Serranos 215 4.960 42 Araxá 1.172 16.998 36 Campos Altos 573 9.637 39 Ibiá 2.722 18.755 47 Nova Ponte 1.121 48.601 29 Pedrinópolis 373 18.371 47 Perdizes 2.495 20.729 42 Pratinha 669 10.538 37 Sacramento 3.333 31.103 51 Santa Juliana 674 18.277 52 Araxá 191.527 14.199 Tapira 1.067 45.847 45 Alfredo Vasconcelos 72 10.042 41 Antônio Carlos 396 4.927 48 Barbacena 644 7.907 33 Barroso 82 7.342 48 Carandaí 151 8.677 37 Ibertioga 359 4.259 42 Barbacena 216.618 1.744 Ressaquinha 40 11.008 46 Aguanil 230 5.846 42 Campo Belo 531 6.122 45 Cana Verde 206 5.177 41 Candeias 723 5.764 40 Cristais 529 7.923 44 Perdões 267 9.662 42 Campo Belo 111.210 2.595 Santana do Jacaré 108 4.738 48 Santo Antônio do Monte 722 6.575 46

Divinópolis 456.384 864

São Sebastião do Oeste 142 11.030 37

Arcos 204 9.521 42

Formiga 149.047 3.553

(38)

Minas Gerais 19.273.506 Córrego Fundo 107 11.950 50 Formiga 1.332 7.131 43 Itapecerica 783 5.900 41 Pains 185 11.677 42 Pedra do Indaiá 352 7.966 42 Pimenta 365 7.665 38 Campina Verde 3.742 9.819 39 Carneirinho 1.761 11.482 39 Comendador Gomes 1.135 20.122 40 Fronteira 196 106.503 43 Frutal 2.309 9.444 45 Itapagipe 1.508 12.060 47 Iturama 1.250 25.386 40 Limeira do Oeste 1.193 12.293 45 Pirajuba 333 31.372 49 Planura 307 48.589 53

São Francisco de Sales 928 9.913 44

Frutal 172.124 15.813 União de Minas 1.151 11.978 50 Brasópolis 315 4.468 38 Consolação 87 4.413 40 Cristina 315 5.239 37 Delfim Moreira 334 4.175 41 Dom Viçoso 115 4.980 40 Itajubá 293 10.125 42 Maria da Fé 206 4.498 50 Marmelópolis 104 3.859 46 Paraisópolis 367 12.580 43 Piranguçu 171 4.495 37 Piranguinho 131 4.189 41 Itajubá 183.888 2.871 Virgínia 330 4.752 44

(39)

CLUSTER REGION Resident Population Total Area(km²) Brasil 183.987.291 Minas Gerais 19.273.506 Main City TOTAL AREA (km²)15 GDP Domestic Product (US$)16 UNEMPLOYMENT (%) 17 Wenceslau Braz 103 3.805 32 Cachoeira Dourada 256 45.219 42 Capinópolis 611 13.844 44 Gurinhatã 1.950 11.318 34 Ipiaçu 318 10.092 36 Ituiutaba 2.467 10.580 38 Ituiutaba 136.376 8.116 Santa Vitória 2.514 9.250 41 Bias Fortes 49 3.869 49 Lima Duarte 606 4.712 37 Olaria 174 4.583 41

Santa Rita de Ibitipoca 305 4.533 41

Juiz de Fora 724.276 1.211

Santa Rita de Jacutinga 76 5.820 38 Carrancas 712 8.773 46 Ijaci 98 21.295 41 Ingaí 308 9.933 45 Itumirim 248 4.330 46 Itutinga 381 21.514 45 Lavras 581 9.068 29 Luminárias 505 5.274 41 Nepomuceno 599 7.084 40 Lavras 143.686 3.741 Ribeirão Vermelho 40 6.498 43 Bom Sucesso 708 6.396 32 Carmo da Mata 145 6.393 39 Ibituruna 154 6.459 44 Oliveira 450 6.329 46

Santo Antônio do Amparo 497 6.119 46

Oliveira 123.058 2.275

São Francisco de Paula 321 6.561 41 Guarda-Mor 1.206 15.420 42

Paracatu 208.367 4.010

(40)

Minas Gerais 19.273.506

Paracatu 1.784 9.084 34 Presidente Olegário 541 9.334 40

Vazante 171 11.002 43

Alpinópolis 460 7.022 54 Bom Jesus da Penha 212 10.986 51 Capetinga 278 6.561 43 Capitólio 490 6.987 44 Cássia 609 7.437 46 Claraval 162 7.354 45 Delfinópolis 1.102 37.907 54 Fortaleza de Minas 214 30.040 45 Ibiraci 553 24.793 55 Itaú de Minas 139 14.670 39 Passos 1.267 8.321 43 Pratápolis 216 6.014 41 São João Batista do Glória 538 65.702 49

Passos 218.814 6.497

São José da Barra 257 65.492 34

Arapuá 173 9.388 43 Carmo do Paranaíba 774 8.306 43 Guimarânia 371 6.643 40 Lagoa Formosa 297 6.227 32 Matutina 117 7.131 46 Patos de Minas 2.250 8.889 42 Rio Paranaíba 1.336 19.605 44 São Gotardo 47 8.490 30 Patos de Minas 245.875 5.563 Tiros 197 9.390 45

Abadia dos Dourados 866 6.502 45 Coromandel 3.330 9.477 44 Cruzeiro da Fortaleza 187 6.591 46

Patrocínio 194.138 11.839

(41)

CLUSTER REGION Resident Population Total Area(km²) Brasil 183.987.291 Minas Gerais 19.273.506 Main City TOTAL AREA (km²)15 GDP Domestic Product (US$)16 UNEMPLOYMENT (%) 17 Estrela do Sul 814 9.489 37 Grupiara 127 8.177 41 Iraí de Minas 357 9.562 43 Monte Carmelo 1.346 8.070 44 Patrocínio 2.828 10.387 42 Romaria 404 17.874 42 Serra do Salitre 1.316 11.894 39 Córrego Danta 63 8.217 57 Medeiros 294 10.465 42 Piumhi 158 10.498 44

São Roque de Minas 1.020 8.971 45

Tapiraí 281 14.102 43 Piuí 78.699 1.892 Vargem Bonita 76 7.886 28 Albertina 41 19.567 26 Andradas 427 7.701 41 Bandeira do Sul 45 4.125 48 Botelhos 286 5.616 39 Caldas 720 6.991 41 Campestre 580 6.940 40 Ibitiúra de Minas 69 4.009 52 Inconfidentes 150 5.992 46 Jacutinga 257 8.467 51 Monte Sião 253 8.019 43 Ouro Fino 538 9.575 39 Poços de Caldas 424 17.072 44 Poços de Caldas 326.809 4.297

Santa Rita de Caldas 507 6.580 52 Bom Repouso 231 3.339 40 Borda da Mata 293 5.626 47

Pouso Alegre 304.788 4.654

(42)

Camanducaia 457 6.767 49

Cambuí 244 7.764 47

Congonhal 208 6.509 41 Córrego do Bom Jesus 125 3.946 44 Espírito Santo do Dourado 266 6.085 40

Estiva 248 6.336 40 Extrema 215 40.023 32 Gonçalves 192 3.899 46 Ipuiúna 301 6.600 34 Itapeva 180 8.619 47 Munhoz 158 4.822 38 Pouso Alegre 505 11.757 46 Sapucaí-Mirim 262 4.379 36 Senador Amaral 153 4.818 38 Senador José Bento 95 6.666 43 Tocos do Moji 125 5.264 49

Toledo 88 4.373 36

Cachoeira de Minas 305 4.762 37

Careaçu 199 6.192 52

Conceição das Pedras 102 7.153 43 Conceição dos Ouros 188 7.501 39 Cordislândia 198 6.865 39 Heliodora 156 6.532 42

Natércia 192 6.896 42

Pedralva 220 4.966 46

Santa Rita do Sapucaí 364 14.844 55 São Gonçalo do Sapucaí 517 8.479 40 São João da Mata 121 6.729 46 Santa Rita do Sapucaí 134.563 3.384

(43)

CLUSTER REGION Resident Population Total Area(km²) Brasil 183.987.291 Minas Gerais 19.273.506 Main City TOTAL AREA (km²)15 GDP Domestic Product (US$)16 UNEMPLOYMENT (%) 17

São Sebastião da Bela Vista 209 7.770 44 Silvianópolis 296 7.053 44 Turvolândia 226 9.082 51 Conceição da Barra de Minas 289 4.549 39 Coronel Xavier Chaves 141 5.338 39 Dores de Campos 122 6.657 38 Lagoa Dourada 95 4.950 42 Madre de Deus de Minas 440 6.743 45

Nazareno 330 6.136 38

Piedade do Rio Grande 327 16.585 42

Prados 272 4.661 36

Resende Costa 62 4.267 49 Ritápolis 356 4.357 42 Santana do Garambéu 206 3.793 55 São João del Rei 1.484 7.292 36 São Tiago 433 5.086 47 São João del Rei 177.648 4.639

Tiradentes 84 7.580 47 Alagoa 170 5.531 50 Baependi 752 6.107 42 Cambuquira 248 7.716 43 Carmo de Minas 326 7.031 43 Caxambu 107 4.757 40

Conceição do Rio Verde 381 6.427 42

Itamonte 201 7.037 30

Itanhandu 94 12.728 35

Jesuânia 155 5.862 40

São Lourenço 204.532 3.407

(44)

Olímpio Noronha 54 6.729 40 Passa Quatro 96 7.143 44 Pouso Alto 273 7.659 42 São Lourenço 58 6.178 42 São Sebastião do Rio Verde 93 4.522 39 Soledade de Minas 182 4.624 44 Arceburgo 182 10.613 41 Cabo Verde 311 6.992 36 Guaranésia 313 8.774 57 Guaxupé 289 14.153 42 Itamogi 192 5.769 42 Jacuí 403 6.051 41 Juruaia 221 5.811 48 Monte Belo 426 7.098 55 Monte Santo de Minas 561 8.097 29 Muzambinho 398 7.589 43 Nova Resende 393 6.581 41 São Pedro da União 261 6.496 40 São Sebastião do Paraíso 776 8.994 46 São Sebastião do

Paraíso 254.801 4.953

São Tomás de Aquino 227 7.025 48 Água Comprida 453 22.390 47 Campo Florido 1.293 26.580 43 Conceição das Alagoas 1.328 31.770 49 Conquista 644 21.378 45 Delta 90 35.152 48 Uberaba 4.521 14.836 46 Uberaba 333.696 9.376 Veríssimo 1.046 20.818 40 Araguari 2.346 9.699 48 Uberlândia 818.395 18.095 Araporã 243 223.027 48

(45)

CLUSTER REGION Resident Population Total Area(km²) Brasil 183.987.291 Minas Gerais 19.273.506 Main City TOTAL AREA (km²)15 GDP Domestic Product (US$)16 UNEMPLOYMENT (%) 17 Canápolis 829 23.147 42 Cascalho Rico 274 289.838 48 Centralina 313 8.825 43 Indianópolis 742 53.023 43 Monte Alegre de Minas 2.558 11.587 42 Prata 4.902 11.412 45 Tupaciguara 1.653 8.781 41 Uberlândia 4.235 15.704 36 Unaí 142.122 77 Unaí 77 11.862 39 Boa Esperança 745 6.882 54 Campanha 339 6.734 41 Campo do Meio 207 4.226 43 Campos Gerais 699 5.771 40 Carmo da Cachoeira 511 6.216 44 Coqueiral 304 6.911 39 Elói Mendes 531 11.300 41 Guapé 136 4.554 38 Ilicínea 380 5.333 37 Monsenhor Paulo 218 7.470 52 Santana da Vargem 173 7.224 43 São Bento Abade 81 5.745 52 São Thomé das Letras 374 6.038 46 Três Corações 836 13.386 41 Três Pontas 680 7.993 53

Varginha 426.551 6.617

(46)

Alfenas Alterosa Areado Carmo do Rio Claro

Carvalhópolis Conceição da Aparecida Divisa Nova Fama Machado Paraguaçu Poço Fundo Alfenas Serrania 45 298,686 Sugarcane 10,251 Beans 137,672 Corn 76 29,2 Not Available Latossolos vermelhos Argissolos Vermelhos Standing Crop 17,2 Planted Pasture 26,4 Natural Pasture 43,7 Seasonal Forest - Aiuruoca Andrelândia Arantina Bocaina de Minas Bom Jardim de Minas

Carvalhos Cruzília Andrelândia

Liberdade

42 32,196 Corn 68 Not Available Not Available Cambissolos Háplicos Planted Pasture 19,7 Temporary Crop 8,5 Natural Pasture 60,5 Seasonal Forest Cerrado Environmental Protection Area of Serra da Mantiqueira

19_{IBGE Censo Agropecuário (www.ibge.org.br/SIDRA).}

(47)

CLUSTER

REGION Main City

Land Use (Ton)18 Livestock (Cattle density; unit per km²) 19 GDP Domestic Product20 Temperature (ºC) 21 Precipitation

(mm)22 Soil23 Soil Cover(%)24 *

Forest Cover(%)25 Conservation Unity26 Minduri Passa-Vinte São Vicente de Minas

Seritinga Serranos Araxá Campos Altos Ibiá Nova Ponte Pedrinópolis Perdizes Pratinha Sacramento Santa Juliana Araxá Tapira 43 245,831 Soy 481,965 Corn 16,240 Beans 117 28,7 Not Available Latossolos Vermelhos Cambissolos Háplicos Planted Pasture 29,3 Temporary Crop 14,5 Natural Pasture 56,8 Cerrado National Park of Serra da Canastra Alfredo Vasconcelos Antônio Carlos Barbacena Barroso Capela Nova Caranaíba Carandaí Desterro do Melo Ibertioga Ressaquinha Santa Bárbara do Tugúrio Barbacena

Senhora dos Remédios

42 7,885 Beans

38,740 Corn 173 Not Available Not Available

Cambissolos Háplicos Latossolos vemelhos Planted Pasture 25,9 Temporary Crop 13,5 Natural Pasture 53,7 Cerrado Seasonal Forest - Aguanil Campo Belo Cana Verde Candeias Campo Belo Cristais 43 41,490 Corn

1,838 Rice 128 Not Available Not Available

Argissolos Vermelhos Latossolos Vermelhos Standing Crop 9,1 Planted Pasture 42 Natural Pasture 67,7 Seasonal Forest Cerrado -

(48)

Perdões Santana do Jacaré Arcos Camacho Córrego Fundo Formiga Itapecerica Pains Pedra do Indaiá Formiga Pimenta 42 71,415 Corn 130,312 Sugarcane 5,395 Rice

90 Not Available Not Available

Latossolos Vermelhos Argissolo vermelho Planted Pasture 35,6 Temporary Crop 10,4 Natural Pasture 64,2 Cerrado Seasonal Forest - Campina Verde Carneirinho Comendador Gomes Fronteira Frutal Itapagipe Iturama Limeira do Oeste Pirajuba Planura São Francisco de Sales Frutal União de Minas 45 3,582,589 Sugarcane 127,299 Corn 100,981 Soy

Latossolos vermelhos Argissolos Vermelho Planted Pasture 69 Temporary Crop 7,5 Natural Pasture 87,3 Cerrado Seasonal Forest - Brasópolis Consolação Cristina Delfim Moreira Dom Viçoso Itajubá Maria da Fé Marmelópolis Paraisópolis Itajubá Piranguçu 41 2,102 Rice 14,147 Corn

97 Not Available Not Available Latossolos Vermelhos Planted Pasture 22,5 Temporary Crop 9,2 Natural Pasture 53,4 Floresta Ombrófila Environmental Protection Area of Serra da Mantiqueira

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REGION Main City

Forest Cover(%)25 Conservation Unity26 Piranguinho Virgínia Wenceslau Braz Cachoeira Dourada Capinópolis Gurinhatã Ipiaçu Ituiutaba Ituiutaba Santa Vitória 39 10,240 Cotton 98,721 Corn 80,442 Soy

Latossolo vermelho Argissolo vermelho Planted Pasture 67 Temporary Crop 9 Natural Pasture 86 Seasonal Forest Cerrado - Carrancas Ijaci Ingaí Itumirim Itutinga Lavras Luminárias Nepomuceno Lavras Ribeirão Vermelho 42 59,660 Soy

3,157 Rice 153 28,2 Not Available

Cambissolos Háplicos Latossolo Vermelhos Argissolos Vermelho Planted Pasture 20 Temporary Crop 11,5 Natural Pasture 46,35 Cerrado Rain Forest - Bom Sucesso Carmo da Mata Carmópolis de Minas Ibituruna Oliveira Passa Tempo Piracema Santo Antônio do Amparo Oliveira

São Francisco de Paula

41 49,778 Corn 117 Not Available Not Available

Latossolo Vermelho Argissolo vermelhos Planted Pasture 23,4 Temporary Crop 8,3 Natural Pasture 57 Seasonal Forest - Alpinópolis Bom Jesus da Penha

Capetinga Capitólio Cássia Passos Claraval 46 1,210,680 Sugarcane 4,915 Beans 164,458 Corn

104 Not Available Not Available Latossolo Vermelhos

Planted Pasture 37 Temporary Crop 13,4

Natural Pasture 63,4

Cerrado National Park of Serra da Canastra

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Delfinópolis Fortaleza de Minas Ibiraci Itaú de Minas Passos Pratápolis São João Batista do

Glória São José da Barra

Arapuá Carmo do Paranaíba Guimarânia Lagoa Formosa Matutina Patos de Minas Rio Paranaíba Santa Rosa da Serra

São Gotardo Patos de Minas Tiros 41 5,687 Beans 158,019 Corn 32,402 Soy

Latossolos Vermelhos Cambissolos Háplicos Planted Pasture 33,4 Temporary Crop 8,5 Natural Pasture 68,5 Cerrado -

Abadia dos Dourados Coromandel Cruzeiro da Fortaleza Douradoquara Estrela do Sul Grupiara Iraí de Minas Monte Carmelo Patrocínio Romaria Patrocínio Serra do Salitre 43 12,800 Beans 192,361 Corn 76,772 Soy

Latossolos Vermelhos Cambissolos Háplicos Argisolos Vermelhos Planted Pasture 30,6 Temporary Crop 10,2 Natural Pasture 59 Cerrado Seasonal Forest - Albertina Andradas Poços de Caldas Bandeira do Sul 43 4,972 Beans 75,345 Corn

168 Not Available Not Available Cambissolos Háplicos Argissolos Vermelhos Planted Pasture 23,7 Temporary Crop 10 Natural Pasture 47,5 Seasonal Forest Rain Forest -

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REGION Main City

Forest Cover(%)25 Conservation Unity26 Botelhos Caldas Campestre Ibitiúra de Minas Inconfidentes Jacutinga Monte Sião Ouro Fino Poços de Caldas Santa Rita de Caldas

Vermelhos Bom Repouso Borda da Mata Bueno Brandão Camanducaia Cambuí Congonhal Córrego do Bom Jesus

Espírito Santo do Dourado Estiva Extrema Gonçalves Ipuiúna Itapeva Munhoz Pouso Alegre Sapucaí-Mirim Senador Amaral Senador José Bento

Tocos do Moji Pouso Alegre

Toledo

42 2,613 Rice

39,997 Corn 214 Not Available Not Available

Latossolos Vermelhos Argissolos Vermelhos Planted Pasture 23,6 Temporary Crop 18,3 Natural Pasture 50,1 Seasonal Forest Rain Forest - Cachoeira de Minas Careaçu Santa Rita do Sapucaí

Conceição das Pedras

45 3,153 Rice 4,460 Beans

37,026 Corn

97 Not Available 1151 Latossolo vermelhos Cabissolos Háplicos Standing Crop 12,8 Planted Pasture 22,3 Natural Pasture 44,3 Seasonal Forest Rain Forest -

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Conceição dos Ouros Cordislândia

Heliodora Natércia Pedralva Santa Rita do Sapucaí São Gonçalo do Sapucaí

São João da Mata São Sebastião da Bela

Vista Silvianópolis Turvolândia Háplicos Conceição da Barra de Minas Coronel Xavier Chaves

Dores de Campos Lagoa Dourada Madre de Deus de

Minas Nazareno Piedade do Rio Grande

Prados Resende Costa

Ritápolis Santa Cruz de Minas Santana do Garambéu

São João del Rei São Tiago São João Del

Rei

Tiradentes

43 53,756 Corn 140 Not Available Not Available

Cambissolos Háplicos Latossolos Vermelhos Planted Pasture 14,1 Temporary Crop 11,5 Natural Pasture 44,23 Cerrado Seasonal Forest -

São Lourenço Alagoa 41 29,138 Corn 140 Not Available Not Available

Latossolos Vermelhos Cambissols Háplicos Planted Pasture 21,8 Temporary Crop 9 Natural Pasture 54,7 Rain Forest Environmental Protection Area of Serra da Mantiqueira

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REGION Main City

Forest Cover(%)25 Conservation Unity26 Baependi Cambuquira Carmo de Minas Caxambu Conceição do Rio Verde

Itamonte Itanhandu Jesuânia Lambari Olímpio Noronha Passa Quatro Pouso Alto São Lourenço São Sebastião do Rio

Verde Soledade de Minas Háplicos Mantiqueira Arceburgo Cabo Verde Guaranésia Guaxupé Itamogi Jacuí Juruaia Monte Belo Monte Santo de Minas

Muzambinho Nova Resende São Pedro da União

São Sebastião do Paraíso São Sebastião

do Paraíso

São Tomás de Aquino 44

94,798 Corn 731,748

Sugarcane 6,987 Rice

Latossolos Vermelhos Argissolos Vermelhos Standing Crop 19,8 Planted Pasture 28,4 Natural Pasture 44,5 Seasonal Forest -

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Água Comprida Campo Florido Conceição das Alagoas

Conquista Delta Uberaba Uberaba Veríssimo 45 3,621,000 Sugarcane 345,267 Corn 326,004 Soy

Latossolos Vermelhos Argisollos vermelhos Planted Pasture 47,6 Temporary Crop 20,8 Natural Pasture 65,1 Cerrado - Araguari Araporã Canápolis Cascalho Rico Centralina Indianópolis Monte Alegre de Minas

Prata Tupaciguara Uberlândia Uberlândia 44 2,665,100 Sugarcane 243,853 Corn 260,923 Soy

Latossolos vermelhos Argissolos vermelhos Planted Pasture 48,1 Temporary Crop 12,5 Natural Pasture 73,4 Cerrado Seasonal Forest - Boa Esperança Campanha Campo do Meio Campos Gerais Carmo da Cachoeira Coqueiral Elói Mendes Guapé Ilicínea Monsenhor Paulo Santana da Vargem

São Bento Abade São Thomé das Letras

Três Corações Varginha Varginha 44 171,016 Corn 3,150 Beans 2,204 Rice

Latossolos Vermelhos Argissolos vermelhos Standing Crop 20,1 Planted Pasture 20,6 Natural Pasture 35,9 Seasonal Forest Cerrado -