using the information system and multi criteria

Proceedings of the Second World Landslide Forum – 3-7 October 2011, Rome

Eliene Coelho(1)

, Luciana Pascarelli(2)

Using the information system and multi-criteria

analysis in the geological risk management in São

Paulo (1) PMSP, São Paulo City Hall, Habisp, Sao Paulo, Brazil.

(2) Consultancy Services and Technical Works Department, Sao Paulo City Hall, Rua Libero

Badaro, 425, Brazil

Abstract Since 1980´s the surveys space could not definitely follow the growth and the density of favelas, and some communities started to trigger the first records of accidents in areas hitherto stable. The mapping made in 2010 is today the largest geological-risk database in the country. Today, all these information are included in the “Habisp”. Habisp is a mapping system of precarious settlements in the city of Sao Paulo, which contains valuable information to face the urban poverty. Poverty which is materialized in Sao Paulo in many ways of informal settlements: slums, irregular settlements, tenement housing, temporary housing and degraded sets. The Habisp stores, organizes, processes and produces high quality geographic information, which serves as support for the technicians of the Housing department in making decisions. The results have been making possible reassessment and adjustment of the low-income intervention projects by the government, prioritizing housing, social-educational infrastructure, and basic-sanitation actions in areas of greatest susceptibility. Keywords: mapping, susceptibility, geographic information, priority

The risk of landslides in large urban centers

Mass movement processes are natural and a part of the cycle/depositional erosion responsible for determining the scenery of the Earth’s surface. Nevertheless, when as the result of a geological process there is an impact on human beings or their property, what comes to light is the concept of a geological accident, implying that besides the physical process some causes of instability also lead to the consequences observed. The first tales of accidents of this sort in the city of São Paulo relate to urban expansion. More fragile areas, such as slopes and river banks began to be occupied without the appropriate planning, and the growing number of people affected by the landslides revealed that there was a considerable part and parcel of the population living in risky settlements.

In the city of São Paulo, the first tales of accidents of this nature are directly linked to the urban expansion recorded since the beginning of the 1930´s. According to Nogueira (2002), the urban spot in the city grew from

355 km2 to 1.370 km2 in approximately five decades. Due to the method adopted by real estate speculation when it came to dividing the land in the city, “urban vacuums” were generated and subsequently occupied by shanty towns and irregular land occupation. Areas of greater environmental fragility, such as slopes and banks of streams also began to be occupied, above all at the end of the 1970´s. At the end of the 1980`s, there exists a record of the first accidents on slopes and in the mid 1990´s, these become ever more frequent and less localized, revealing that a considerable part of the population occupies these areas of risk.

Mapping the risk areas in the city of São Paulo

At the end of the 1990´s, geotechnical companies carried out an analysis of the risk on the slopes of 240 shanty towns, identifying about 60% of the situations at risk for landslides. Although such information has been used for the planning and execution of local interventions, activities to control and prevent such risks per se have been negligible for about a decade (1993 to 2001), whilst at the same time the occupation of the hills grew significantly. Cartographic registries and those of occurrences were also rare, making it impossible to carry out any sort of planning with the necessary efficacy.

In 2010, the City Hall of São Paulo, along with the Institute for Technological Research (IPT) came to the conclusion of the need for “Analysis and risk mapping associated to landslides in the areas of slopes and the banks of rivers and streams in shanty towns in the São Paulo municipality”. More than a geotechnical survey, the mapping geared its focus on the areas of precarious occupation, where the population’s vulnerability was the steepest. In such sites, any type of event, even the minor ones could entail significant damage for the community, vis-a-vis their low perception of risk and the inability to set forth a speedy response and recovery.

The risk estimates were analyzed quantitatively, based on field observations, integrating the analysis parameters contained on a risk card, with the support of aerial images.

The 407 areas investigated were subdivided into risk sectors, due to the fact that the characteristics of the land and above all of the occupations posed

E. Coelho, L. Pascarelli - Using the information system and multi-criteria analysis in the geological risk management in São Paulo

enormous variations within a single shanty town. For each of the sectors, what was evaluated was (1) natural parameters referring to the type of soil topography, natural structures that conditioned land movements, typology of water courses and type and breadth of vegetation and (2) occupational parameters such as the level of interference in the land, the presence of basic infrastructure to supply water, garbage collection and sewage treatment, the condition of public roads and structure of the homes themselves. Additionally to the signs of instability observed, the parameters assessed ended up in the creation of 1.179 risk sectors, with specific levels of criticality according to Table 1.

Table 1: Criteria to rank the degree of risk (simplified from the IPT- 2006)

Degree of

probability

Description

R1

Slopes with little inclination (<17º), natural and on stable soils with low probability of having landslides. Absence of indices of instability. This is the least critical condition.

R2

Slopes with slight inclination with a medium probability of having a landslide. There is evidence already of incipient instability. If the existing conditions are maintained, there is a slight probability that there will be destructive episodes occurring during intense rainfall.

R3

Inclined slopes (>30º) point towards a high potential for developing landslide processes. There is a large amount of evidence regarding instability (cracks on the soils, levels of subsidence of the soil, etc.)

R4

Evidence of instability is expressive (quantity and magnitude). This is the most critical condition. Under such conditions, it is highly probable that there will be destructive events during intense episodes of rainfall.

More than a geotechnical survey, this broader

mapping already carried out in Brazil focused exclusively on settlement areas where the population’s social vulnerability was high. In these sites, any type of event, albeit the smallest ones could cause significant damage to the community, given their low perception of risk and limited ability to respond to the event and recover from it.

In real time, the data collected on the field, which included the perimeters of the areas analyzed, was entered into the Habisp system used the São Paulo City Hall since 2006.

The Habisp system

Habisp is an information system that works through the web, with the ability to store and process alphanumeric and geographic information. The focus is popular housing and the “loci” are the shanty towns, irregular

land settlements, tenements or slums and housing enterprises conceived for the population that lives in those areas.

To understand how it operates, it is necessary to explore some conceptual issues regarding the importance of Information and Communication Technology (ICT) in our present day society. It is also necessary to refer to the issue of making decisions, the construction of indicators and their content, objectives and the dynamism relating to the problem of which it is a part: popular housing.

Habisp arose from an initiative to draw up a strategic plan for social housing, within the realm of the project with Alliance with Cities, and throughout the studies, it turned into a proposal to draft a Municipal Housing Plan (MHP). Without the Habisp and the System of Priorities, both planning instruments, the MHP would not have attained its present day level of sophistication and detail. The proposal encompasses goals and objectives to service housing needs until the year 2024, including the cost for urbanization interventions and land ownership regularizing and the construction of new housing units, settlement per settlement (consult the Municipal Housing Plan: document for debate, www.habisp.inf.br, Figure 1).

Data, information, indicators, knowledge generation, decision making, geographic spaces, popular housing, regularization of land ownership, spatial analysis, maps, registries and population surveys are some of the issues that Habisp relates to. To classify it into a single system modality is not an easy task, these subdivide into categories, in accordance to the activity they support, but Habisp does not fit into a single category, and can be deemed to be a system for managerial information; a transactional processing system or a decision making support tool (BIDGOLI, 1989, apud BARBOSA, 2002).

As part of this classification set forth by Bidgoli (1989, apud BARBOSA, 2002), we can state that Habisp is mostly a management information system, that can be used for planning, control and decision making purposes; condensing or summarizing the information obtained from the transactional data processing systems, with routine and exception reports. The parcel of transactional processing systems in Habisp refers to the housing services part supported by this same system (payment of benefits and issuing land ownership regularization deeds for public areas). Nonetheless, one of its most relevant components, the system to prioritize interventions, brings it closer or even qualifies it as a system that supports the decision making process, although this category so far does not have a broadly accepted definition.

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Figure 1: Picture of the first page on the Habisp System. Source: www.habisp.inf.br. The Housing problem in the large urban centers

Housing, in a very broad sense, is frequently deemed to be key for the problem of poverty; a shanty town or slum is the environment of a poor man according to the operational definition officially adopted at a UN meeting in Nairobi, 2002. It is characterized by an excess of population, precarious or informal housing, inadequate access to drinking water and sanitary conditions and insecurity as part of the ownership of this house.

Throughout the third world, the choice of housing is a complicated calculation of ambiguous considerations. Like the famous phrase of the anarchist architect John Turner. “Housing is a verb”. The urban poor need to resolve a complex equation upon attempting to optimize the cost of housing, guarantee ownership, the quality of the shelter, distance from work and oftentimes their own safety. And for all, the worst situation is a poor and expensive area lacking in public services and without the warranty of ownership (DAVIS, 2006, p. 39).

In São Paulo, occupation in precarious settlements - slums, irregular land plots or tenements – has been a part of the urban scenery for quite some time (Figure 2). The largest city in Latin America has one of the most complex housing problems in the country; and for decades, facing up to this problem has posed a huge challenge for those in government. Concern with the poor, urban poverty and popular housing mixes old and new ideas during each period of history, and successive generations of reformists have struggled for the elimination of slums. The difficulties, in the field of housing management, land market and funding for housing for the low income population become aggravated day after day, thanks to the economic and social problems that exclude the less specialized population from labor markets, evermore demanding and that offer – when they offer – informal employment

with an extremely low compensation; consequently, this means scant opportunities to have access to the formal funding initiatives and their own housing.

Furthermore, the real estate market in São Paulo has attained surreal levels of appreciation. The steep prices are mainly due to the scarcity of supply or land at compatible prices and locations. For those who are poor in São Paulo (families generally with incomes falling below three minimum wages), there are few opportunities, and those that exist at present arise precisely in precarious housing.

Figure 2: Picture of the Jaguaré Slum. Archives of the Municipal Housing Secretariat – Sehab. City Hall of the São Paulo Municipality.

What can be observed as a result of this

informality, is the greater occupation of areas that are subject to environmental restrictions, areas of risk with steep slopes or subject to flooding, contaminated soils, areas close to sanitary landfills or garbage deposits, among others, besides the concentration of a large number of social problems, especially those linked to unsanitary conditions resulting from the absence of basic infrastructure, aggravated vis-à-vis the vulnerability of its inhabitants, caused by factors relating to informal employment, school abandonment or drop outs, early pregnancy, domestic violence and drug trafficking.

If, for the low income population, there are few alternatives and choosing becomes truly difficult, for public management, this problem is further aggravated, making intervention policies ever more complex. To have an anchor for public policies, what is needed, in the first place, is detailed knowledge of which are the problems that will be faced, in the quest to qualify and quantity the true needs. What does it mean to understand each of these low-income occupations in their totality, but also in terms of their specificities, evaluate the resources that are necessary to invest in each of the housing projects or programs, so as to select those which will make it possible to optimize public investment and attain the greater number of people possible among the destitute population.


For the Sehab, the intervention strategies were clear, since work began to draft the MHP: urbanization and regularization of shanty towns and irregular land plots occupied by low-income populations. However there existed the need to particularize that extensive universe of settlements, to know where to truly begin each of the actions: that is to say, which slums to urbanize in the coming years? In the coming month? With resources available at present? Because of this it was necessary to have surveys and more concrete data, besides using analytical instruments with the ability to offer more precise answers on where and how this housing precariousness manifests itself. The geographical aspect of the problem benefitted from the use of spatial analytical instruments of proven efficacy, and it became necessary to build a model that could guide decision making, based on the existing data.

The path chosen was to set forth indicators that could be evaluated individually and offer immediate responses, such as: degree of urbanization of a settlement, the population’s vulnerability, geological conditions etc., and that could be combined into a single index. Through this procedure, the intention was to attain a goal to set up a decision making model that would take into account the large diversity of variables that existed in the context, and mainly the multiple objectives that had to be reached. Four stages were created to define the priority to service a specific settlement through a specific housing program: characterization, classification, eligibility and prioritization, each with its own objective, as can be observed in Table 2. Table 2: Basic objectives of the phases proposed by the Characterization, Classification, Eligibility and Prioritization System. Own draft. (COELHO and PÉREZ MACHADO, 2009)

Characterization Classification Eligibility Priorization

Characterize the

precarious settlements

in the municipality of São Paulo

Classify these areas into

groups that will guide the

type of intervention

that is needed

Select the areas that

will undergo intervention,

already establishing at this phase a cut-off for the actions

Prioritize the activities in those areas

that fulfil the eligibility criteria

The first and foremost stage in the system is that

of characterization, as the results found in future stages will be ramifications of the information collected herein. Subsequently the work of updating the data began, as well as the conceptual definition of the types of settlements that would be serviced by the housing policy, described in Table 3 below.

The principle adopted was simple: according to the objective of the action, the SEHAB defined the focus of prioritization. For urbanization projects, the focus of the action was the most precarious areas in all of the issues analyzed. However, for the regularization of

shanty towns, as in principle the program cannot regularize precarious situations, the focus shifted to acting upon areas with the best indices (COELHO and PÉREZ MACHADO, 2009). Table 3: Precarious settlements in the city of São Paulo: Conceptualization. Own draft. Altered by the CITY HALL OF THE MUNICIPALITY OF SÃO PAULO; ALLIANCE OF CITIES, 2008, p. 50.

Favelas

Informal occupations, self-built on the fringe of urban legislation, predominantly disorderly and with a highly precarious infrastructure. Occupied by low-income families that are social vulnerable.

Irregular

Settlements

Irregular occupations where the division of land presents a layout that allows for the identification of a plot in comparison to a route of access. These are done mainly on land that is predominantly privately owned and acquired through some sort of marketing and may encompass all of the family income brackets.

Tenements

Multi-family collective housing made up of one or more buildings subdivided into several rooms. Sanitary facilities, circulation and precarious infrastructure, and generally overcrowded.

The report “Characterization, Classification,

Eligibility and Prioritization System for Interventions in Precarious Settlements in the Municipality of São Paulo/ Brazil (2007)” highlights two principles set forth for the selection of indicators and indices that jointly make up the prioritization index: (1) protection of the population’s life and the enhancement of livability conditions to acceptable levels; and (2) protection of the most vulnerable population socially. The same report points out that the first formulations carried out by the Sehab divided the priorities stepwise into three levels: high, medium and low, an approach that proved to be lacking, as the universe of settlements demands a much larger scale, which led to the creation of a “prioritization index”, that attributes a score between 0 and 1 to each settlement, being that 0 is the absence of precariousness and 1 maximum precariousness based on a multi-criteria analysis model.

The prioritization index is a summarized index that aggregates other indices through a weighted method. Habisp has a logical matrix where the weights are configured to calculate each of the indices that are part of the system, thus allowing the administrator to interact with and validate the process, and also to adapt it to any change in the situations that may have an impact on the decision making process. In Formula [1]: (COELHO and PÉREZ MACHADO, 2009) we present a mathematical formula to calculate the prioritization index for the urbanization program and for the precarious settlement regularization program.

The indices used arise from several sources or origins. Those of Health and Social Vulnerability were appropriated by the Sehab from other initiatives, which means to say they were not produced exclusively for the prioritization interventions, but serve as a benchmark

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for sectoral policies in health and social assistance, at the municipal sphere. The Paulista Social Vulnerability Index (PSVI) bases itself on data from the 2000 IBGE Census and the Health Index is based on data from the municipal health system for 2006. The urbanization index is calculated based on the data collected on the field and inserted into Habisp, and updated whenever the field team identifies changes in the situation informed; this falls entirely under Sehab´s responsibility.

Treatment of the landslide risk index in the

prioritization system

The risk of washouts and landslides is founded on survey carried out by the Foundation for Support to the University of São Paulo (FUSP), through a partnership with the Institute for Technological Research (IPT), under the title of “Mapping the risks associated to washouts and landslides in slope areas and washout of banks in streams in the shanty towns of the municipality of São Paulo, 2003”, in which the Housing Secretariat participated in indicating those areas that should be subject to analysis by the IPT team, along with the technical people (geologists, engineers and architects) from the sub districts.

The Risk Index for the precarious settlements nevertheless was conceived in the context of the prioritization system, and is calculated for each settlement by using overlay operations (Figures 3 and 4). The Habisp identifies, for each settlement, the percentage of its area (m2) that lies within each risk area and then, through a calculation formula [2], which attributes a weight to each degree of risk, presenting the risk index for wash outs and landslides for the specific settlement.

Considering that the geological risk is a

determinant factor to grant that condition of livability to an area, the use of Habisp as an aid in the new mapping has offered not only the possibility to create a consistent data base on the risks in the city , but has also allowed for the speedy transfer of that knowledge. Nowadays, delimiting the areas surveyed and the main attributes that were part of the evaluation is information that can be accessed by technicians, as well as managers of municipal administration. The location of the risk sectors and the degree of probability that there will be a landslide is also available to universities, research centers, non-government organizations (NGO´s) and other stakeholders of this issue, through Habisp.

IR=(Prb x nrb)/100+(Prm x nrm)/100+(Pra x nra)/100+(Prma x nrma)/100

nrma

[2]

Being that: Prb = % low risk Prm = % medium risk Pra = % high risk Prma = % very high risk

Being that: nrb = weight of low risk nrm = weight of medium risk n

ra = weight of high risk

nrma = weight of very high risk

IP = [(Y – IF) x nf]+(IR x nr)+(IV x nv)+[(Y – IS) x ns] (nf + nr + nv + ns)

[1] Being that: IF = urban infrastructure index IR = index for risks of bank washouts and landslides IV = social vulnerability index IS = health index

Being that: nf = weight of the urban infrastructure index nr = weight of the washout and landslide index nv = weight of the social vulnerability index ns = weight of the health index

Y = Priority Ordainment Factor. (of growing order = 1) (if decreasing order = 0)

Figure 3: Example of the overlay of the layer with the risk mapping (2010) and the shanty town layer. Santa Madalena Park Slum. Source: www.habisp.inf.br.

Figure 4: Example of the interface to update data on the risk sectors (2010). Source: www.habisp.inf.br.


The result of using HABISP can already be seen in the major of government programs in progress. The main one is the Municipal Housing Plan which can be retrofitted quickly and the interventions, could be reordered according to the risk areas in order to include the elimination of the most serious risks by 2016 (including also the provision of financial resources for such actions). Although the elimination of risks only in the year 2016 may seem an unpromising scenario, the recognition of this critical situation is optimistic because it drives the municipality in search of more resources and appropriate technical solutions that allow shortening the schedule. References

BRASIL. Ministério das Cidades / Instituto de Pesquisas Tecnológicas – IPT. Mapeamento de Riscos em Encostas e Margem de Rios. Carvalho, C.S.; Macedo, E.S.; Ogura, A.T. (org). Brasília: Ministério das Cidades; Instituto de Pesquisas Tecnológicas – IPT, 2007.

COELHO, E. C. R. Sistema de Caracteização, Classificação Elegibilidade e Priorização de Intervenções em Assentamentos precários no município de São Paulo/ Brasil. Prefeitura do Município de São Paulo. São Paulo, p. 181. 2007. Disponível em:http://www.habisp.inf.br/theke/documentos/priorizacao/Per_Review_oficial.PDF. Acesso em: 20 Jan. 2011.

COELHO, E. C. R.; PÉREZ MACHADO, R. P. O Sistema de Priorização do Habisp: um estudo de caso. 12 Encontro de geógrafos da América Latina. Montevidéo: [s.n.]. 2009. p. 15. Disponível em: http://egal2009.easyplanners.info/area. Acesso em: 12 Mar. 2011.

DAVIS, M. Planeta Favela. Tradução de Beatriz Medina. São Paulo: Boitempo, 2006. 272 p. ISBN 85-7559-087-I.

NOGUEIRA, F. R. Gerenciamento de Riscos Ambientais Associados à Escorregamento: Contribuição às Políticas Municipais Para Áreas de Ocupação Subnormal. Rio Claro, São Paulo, 2002, 269 p. Tese (Doutorado em Geociências) – UNESP.

IPT/SMSP. Análise e mapeamento de riscos associados a escorregamentos em áreas de encostas e solapamentos de margens de córregos em favelas do município de São Paulo. Laboratório de Riscos Ambientais (LARA/Cetae/IPT) e Assessoria Técnica de Obras e Serviços (ATOS/SMSP/PMSP), 2010

PREFEITURA DO MUNICÍPIO DE SÃO PAULO; CITIES ALLIANCE. Habitação de interesse social em São Paulo: desafios e novos instrumentos de gestão. São Paulo: Janeiro Projetos Urbanos, 2008. 96 p.

PREFEITURA DO MUNICÍPIO DE SÃO PAULO. Plano Municipal de Habitação PMH 2009-2024: documento para debate público. Disponível em: www.habisp.inf.br/doc. Acesso em: 06 Jun. 2011.

UNESP/FUSP/IPT. Mapeamento de risco associado a áreas de encosta e margens de córregos nas favelas do Município de São Paulo (2003/2004)

using the information system and multi criteria

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