Territorial projection and points of interest in tourist destinations in the South region (Brazil): An analysis based on the 2019-2021 Tourism Map

Abstract

The objective of this article is to present the municipalities of the South region that stand out in terms of tourist expressiveness, as well as to analyze aspects of the configuration of the collection of Points of Interest (P.I.s). The starting point was the data consolidated in the Tourism Map 2019-2021. It is an exploratory study of qualitative and quantitative approach and document design. The intersection of the indicators: i) establishments and ii) national visits of the mentioned map resulted in 38 municipalities, corresponding to 3.2% of the region, which represent 71.34% of domestic visits, more than 54% of lodging establishments and about 46% of the activities related to tourism. The expressiveness of the set goes beyond the dimension of tourism, it is pluritematic, as demonstrated by analysis of REGIC (Instituto Brasileiro de Geografia e Estatística [IBGE], 2016, 2020). A result of 872 P.I.s was raised. The collection revealed irregular and unequal distribution and configuration. Destinations within the coastal marine system and close to the coast stand out as a whole. The coastal ones in the Natural category, while the noncoastal ones in Culture and Leisure Services and Equipment. It is understood that these results can subsidize the planning and management of the region and destinations.

Keywords
Tourism; Territory; Tourist destination; User-generated content; Southern Brazil

Resumo

O objetivo a que se propõe este artigo é apresentar os municípios da região Sul que se destacam em termos de expressividade turística, bem como analisar aspectos da configuração do acervo de Pontos de Interesse (P.I.s). Tomou-se como ponto de partida, os dados consolidados no Mapa do turismo 2019-2021. Trata-se de um estudo exploratório de abordagem quali-quantitativa e delineamento documental. A interseção dos indicadores: i) estabelecimentos e ii) visitas nacionais do referido mapa resultou em 38 municípios, correspondente a 3,2% da região, que representam 71,34% da visitação doméstica, mais de 54% dos estabelecimentos de hospedagem e cerca de 46% das ACTS. A expressividade do conjunto extrapola a dimensão do turismo, é pluritemática, como demonstrou análise da REGIC (Instituto Brasileiro de Geografia e Estatística [IBGE], 2016, 2020). Foram levantados 872 P.I.s. O acervo revelou distribuição e configuração irregular e desigual. Destinos enquadrados no sistema costeiro-marinho e próximos da costa se destacam no conjunto. Os costeiros na categoria Natural, enquanto os não costeiros na Cultura e Serviços e Equipamentos de Lazer. Entende-se que estes resultados podem subsidiar o planejamento e a gestão da região e dos destinos.

Palavras-chave
Turismo; Território; Destino turístico; Conteúdo gerado pelo usuário; Sul do Brasil

Resumen

El objetivo a que se propone este artículo es presentar los municipios de la región Sur que se destacan en términos de expresividad turística, además analizar aspectos de la configuración del acervo de Puntos de Interés (P.I.s). Se ha tomado como punto de partida los datos consolidados en el Mapa del turismo 2019-2021. Es estudio exploratorio de abordaje cuali-cuantitativo y delineamiento documental. La intersección de los indicadores: i) establecimientos y ii) visitas nacionales del referido mapa resultó en 38 municipios, o sea, 3,2% de la región, que representan 71,34% de la visitación doméstica, más de 54% de los establecimientos de hospedaje y aproximadamente 46% de las ACTS. Tal expresividad extrapola la dimensión del turismo, es pluritemática, como demostró el análisis de la REGIC (Instituto Brasileiro de Geografia e Estatística [IBGE], 2016, 2020). Fueron levantados 872 P.I.s. El acervo evidenció distribución y configuración irregular y desigual. Destinos encuadrados en el sistema costero marino y próximos de la costa se destacan. Los costeros en la categoría Natural, mientras los no costeros en la Cultura y Servicios y Equipos de ocio. Esos resultados pueden subsidiar el planeamiento y la gestión de la región y de los destinos.

Palabras clave
Turismo; Territorio; Destino turístico; Contenido generado por el usuario; Sur de Brasil

1 INTRODUCTION

This article presents an investigation carried out within the scope of a research group focusing on the relationships between tourism, territory, and development. The South region of Brazil was selected as the study area because it is the authors' priority intervention area and academically familiar. Also, its geographical location was considered strategic within Mercosur given the proximity and border relationship with other member states: Argentina, Paraguay, and Uruguay. The intersection of the variables "Accommodation Establishments" and "Estimated Number of Domestic Visitors" from the 2019-2021 Tourism Map database (MINTUR) and the Lozato-Giotard (1990) theorization of the tourist space were the starting points for this investigation.

The 2019-2021 Tourism Map (MINTUR) is an instrument of the Programa de Regionalização do Turismo [Tourism Regionalization Program] that allows a reading of the spatial distribution of tourism in Brazil. The arrangement is the foundation for priorities, resource distribution, and public policy development. Five variables are mapped: Number of Accommodation Establishments; Number of Jobs in Accommodation Establishments; Estimated Number of Domestic Visitors; Estimated Number of International Visitors; and Collection of Federal Taxes from the Accommodation Establishments. Among the five Brazilian macro-regions, the South is in an intermediate position in four of the five variables mentioned. In International Visits, it ranks second, only behind the Southeast.

The Map database allows observing the performance of tourism at different levels: municipal, tourist regions, state, and macro-regional. This study addressed the macro-regional and municipal levels. The political and administrative division of the South comprises three (3) states and 1,191 municipalities, distributed as follows: Paraná (399), Santa Catarina (295), and Rio Grande do Sul (497). The 2019-2021 Tourism Map (MINTUR) has 739 municipalities, categorized as follows: A = 10; B = 54; C = 94; D = 436; E = 145. The five categories (A, B, C, D, E) result from cluster analysis¹.

The database of the Tourism Map shows an important territorial picture of Brazilian tourism and its historical evolution since the category of municipalities in the Map mirrors materiality and support². The established hierarchies represent different processes and levels of tourism intensity that have occurred over time. Despite this understanding, the investigation interpreted this same basis through the lens of Lozato-Giotard's (1990) theory, a perspective that has demarcated an alternative panorama of leadership and socio-economic and tourist influence that a small group of municipalities (3.2 % of the total) has in the macro-region.

Through additional territorial analysis focused on this group of municipalities, we sought to reveal the composition and configuration of the Points of Interest (POIs). According to Padrón-Ávila and Hernández-Martín (2017), POIs correspond to specific places in a tourist destination that attract visitors interested in enjoying the resources that integrate it and make possible the tourism practices. They can be attractions and resources, provided those places are accessible to visitors. One of the ways of identifying and getting to know POIs is through social media, platforms, and web portals, from information posted by users known as user-generated content (UGC) (Corrêa & Hansen, 2014; Souza & Machado, 2017; Silva et al., 2017; Mayer et al., 2017; Boaria & Frantz dos Santos, 2018).

Along these lines, the spatial knowledge of tourist destinations, usually part of the planning and management processes, involves the identification of relevant information from the online world, that is, user-generated content. This is used as a reference for travel planning, mobility programming, routines of fruition and consumption, and therefore directly impacts the destination's image and the effective dynamics.

The research design for investigating the POIs' composition and configuration is flexible and can be performed by combining a set of strategies of low technical complexity and managed with simple, accessible, and mainly open-access technology. Therefore, it has potential for use and replication by public and private actors, at different levels and units of analysis, to reinforce the link between territorial knowledge and destination management and planning (Lozato-Giotard, 1990; Pearce, 2003; Longley et al., 2013; Ferreira, 2016; Fonseca, 2016).

The research problem was formulated as follows: how does tourist spatialization arising from the indicators of the 2019-2021 Tourism Map, repositories, and databases, combined with the survey and description of the Points of Interest (POIs), can be operationalized to express the importance and magnitude of tourism in municipalities in the South region of Brazil, and assist in destination management?

Therefore, based on 2019-2021 Tourism Map indicators, this study aims to identify which municipalities in the South have greater territorial representation in tourism, and survey and examine aspects regarding the configuration of the set of Interest Points (POIs) in these destinations. By doing so, we aim to provide elements to contribute to the understanding of the spatial context of the South region and to provide insights for destination management (Barrado Timón, 2004; Valls, 2006; Mazaro, 2010, Longjit & Pearce, 2013; Flores & Mendes, 2014; Pearce, 2016; Coutinho & Nóbrega, 2019).

The following section describes the method used to achieve the study objectives, followed by the presentation and discussion of results, which point to the great importance of tourism in the municipalities that make up a set derived from the intersection of the selected variables in the region surveyed. The last section presents the final remarks and the cited references.

2 METHODOLOGY AND THEORETICAL FRAMEWORK

This paper presents the results of an exploratory study combining qualitative and quantitative methods and a documentary approach. For Severino (2016), exploratory research proposes to gather data and information about an object of study to delimit a field of work and bring the researcher closer to the manifesting characteristics of that very object. Veal (2011) points out that these approaches are widely accepted today in leisure and tourism studies, as they are considered complementary.

Similarly, Goldenberg (2004) argues that the combination of quantitative and qualitative research allows researchers to cross-check their conclusions to have greater confidence that their data are not the product of a specific procedure or particular situation (p. 62). Therefore, we share the author's assumption that quantifiable aspects and the experience of the objective reality are interdependent.

Regarding the design, the investigation was based on the concept of Godoy (1995), which defines documentary research as the investigation of materials of different nature that have not yet been treated analytically or that can be re-examined, looking for new or complementary interpretations (p. 21). The primary sources used were: databases available on Mapa do Turismo [Tourism Map], a platform maintained by the Ministry of Tourism, and reports, studies, and publications by the Instituto de Pesquisa Econômica Aplicada [Institute for Applied Economic Research – IPEA], particularly on characteristic tourism activities (ACTs); the SIDRA tool [Sistema IBGE de Recuperação Automática, “IBGE System for Automatic Retrieval”]; and the survey Regiões de Influência das Cidades [“Areas of Influence of Cities”, REGIC], both of which are maintained by the Instituto Brasileiro de Geografia e Estatística [“Brazilian Institute of Geography and Statistics”, IBGE]. However, complementary publications were also consulted. The strategies for extracting and treating these documentary sources are detailed below.

As mentioned, the South macro-region was chosen as the surveyed area, and it represented the first scope of analysis. The second was established from the theorization of the tourist space by Lozato-Giotard (1990), who argues about the existence of multiple tourist spaces. Therefore, it becomes necessary to search for territorial classifications and typologies. To this end, the author proposes and combines two geographical criteria: the spatial presence of tourism (intensity of tourist flows, division, and coexistence with other forms of occupation) and the spatial forms (tourist facilities, as well as impacts on the environment). These two Lozato-Giotard's criteria, applied to the Tourism Map database, lead to the initial and more direct observation of two variables: (i) estimated number of domestic visits and (ii) number of accommodation establishments.

In the Tourism Map database, each variable alone provides different rankings of the municipalities. As for the two variables (domestic visits and accommodation establishments), a cut of the first 50 ranked positions showed an intersection (which is understood herein as the set of municipalities ranked among the first 50, in both variables) of 38 municipalities. These municipalities were defined as the study group for the next steps. Then, an exploratory search was carried out: (i) at SIDRA-IBGE on demographic data (estimated population for the year 2019) and economic data (Gross Domestic Product by municipality, accounted for the year 2017); (ii) on Characteristic Tourism Activities – ACTs on the IPEA database. This allowed the emergence of a broader picture of socio-economic data and tourism performance regarding these 38 municipalities.

In the intermediate stage, it was possible to examine this group of municipalities in light of the Area of Influence of Cities survey, known as REGIC. To this end, two more current versions published in 2016 and 2018 (IBGE, 2016, 2020) were used. We were able to test the territorial importance shown previously for both. Moreover, we intended to observe the scope of the 38 highlighted municipalities and how they are hierarchized in the REGIC mapping, as well as the set of other municipalities that articulate with those identified, encompassing several population areas with an explicit irradiating role within the scope of the South Brazilian region.

After establishing the socio-economic and tourist performance panorama, the final stage of the investigation consisted of identifying the Points of Interest (POIs) in the 38 municipalities. Conceptually, following the proposal of Padrón-Ávila and Hernández-Martín (2017), POIs correspond to specific places that have various resources which attract visitors. Together, resources and attractions, which are sometimes intertwined, can be considered usual components of destination management concepts and models, as they are founding elements and promoters of tourist spaces and destinations (Urry, 2001; Valls, 2006; Framke, 2014; Pearce, 2003, 2014, 2016).

POIs have a given location, can be demarcated, are accessible, their use is not restricted to residents, and tend to interest visitors who identify them in research on different sources of information (Padrón-Ávila & Hernández-Martín, 2017). More recently, apps designed for smartphones and other devices, websites, social networks have become increasingly popular in travel planning. They are used to search for information and share content and interact with other users (e.g., comments, photos, videos, ratings). This is known as user-generated content (UGC) (Corrêa & Hansen, 2014; Souza & Machado, 2017; Silva et al., 2017; Mayer et al., 2017; Boaria & Frantz dos Santos, 2018).

Indeed, POIs represent the effective spatial interaction between people and places, with "creative" potential at the reach of a few clicks on a mobile device or computer connected to the web. A quick and straightforward link from any location to the virtual universe is sufficient for its exposure and digital circulation as a UGC element. It entails the activation of an unlimited process of supplying images, ratings, and reviews, which now plays a role as a virtual deposit of information or a showcase for those planning trips. The identification of the POIs is critical for understanding the spatial logic of tourism, in the interpretation as a phenomenon with territorial implications and critical for destination management processes.

At that stage, a data matrix of the POIs in the 38 municipalities was created using Microsoft Excel® 2016 and collected with a Web Scrapers tool on Google (Figure 1). We opted for the Google search engine because it is the most popular digital information resource. In addition, the piece of information of interest is, as previously mentioned, a form of user-generated content (UGC) (Souza & Machado, 2017). In this sense, this choice converses with theoretical assumptions of the research and central references such as Urry (2001), Framke (2014), Lipovetski and Serroy (2015), and Rudzewicz (2018), referenced in studies by Stock (2005) and Èquipe MIT (2011).

In this proposal for the territorial analysis of tourism, three points are highlighted:

1. geographical references: they have multiple meanings, operate as locational and symbolic support for tourist practices, simultaneously individual and social, susceptible to fashion change, patterns, behaviors, and regulations;

2. subjects: they have intentions, create projects, and choose practices and places that evoke prospects for an aesthetic and multi-located living, tensioned and animated by the ordinary, the extraordinary, and the recursive. One agrees with the criticism of the word "attractions" as if it determined the action of individuals in the face of objects and facilities. Hence the importance of surveying UGC sources.

3. mobility: better understood as a practice, not a flow, as much as destinations stem from practices, notably aimed at recreation/games, discoveries, rest/self-care, shopping, and socializing.

The content extraction was carried out between May 13 and May 22, 2020, and followed the procedure proposed by Oliveira and Porto (2016) when they examined the TripAdvisor platform. The 38 URLs corresponding to "Plan your Trip" or "Points of Interest" links of the municipalities on the Google portal were handled using the Import.io tool, which identifies, extracts, and transforms data, often bulky and in HTML format, into structured data. The following elements were selected for extraction: point of interest and classification; rating; number of reviews. The latter is understood as a possible indication of frequency, popularity, and virtual density and solely corresponds to additional research information (Tables 2 and 3).

Table 2
Points of Interest distributed into Coastal-Marine and Non-coastal systems (IBGE, 2019), municipalities, categories, and number of reviews

		Nature POIs	No. of reviews	Culture POIs	No. of reviews	Leisure Services and Facilities	No. of reviews	Others POIs	No. of reviews	POIs (Total)	No. of reviews (Total)
Coastal		275	380,211	123	312,485	87	380,204	9	23,852	494	1,096,752
	Balneário Camboriú	25	50,569	10	38,552	5	34,926	3	2,574	43	126,621
	Bombinhas	35	66,307	3	2,284	2	1,549			40	70,140
	Capão da Canoa	3	1,458			4	14,304			7	15,762
	Florianópolis	34	95,633	9	84,029	15	63,254	1	14,259	59	257,175
	Garopaba	17	11,776	3	512	2	979			22	13,267
	Guaratuba	15	30,723	3	866	1	18			19	31,607
	Itajaí	8	15,242	12	10,922	5	8,899			25	35,063
	Itapema	9	9,522	1	1,882	3	2,682			13	14,086
	Joinville	4	4,898	10	8,219	7	14,301	1	536	22	27,954
	Matinhos	24	11,031							24	11,031
	Paranaguá	33	8,550	12	4,669	5	191	1	3,732	51	17,142
	Pelotas	1	75	9	7,493	2	6,556	1	4	13	14,128
	Penha	12	19,101	2	5,433	2	116,355	1	2,477	17	143,366
	Porto Alegre	5	9,714	30	129,491	30	109,801	1	270	66	249,276
	Rio Grande	5	2,917	6	5,429	2	3,477			13	11,823
	São Francisco do Sul	30	11,298	9	7,865					39	19,163
	Torres	11	24,196	2	2,498	2	2,912			15	29,606
	Tramandaí	4	7,201	2	2,341					6	9,542
Non-coastal		42	111,815	180	410,088	143	658,626	13	39,722	378	1,220,251
	Bento Gonçalves			29	26,783	9	13,202	1	30	39	40,015
	Blumenau	8	782	23	14,445	10	14,122	1	108	42	29,457
	Canela	4	18,657	15	55,129	16	64,240			35	138,026
	Cascavel			3	4,017	3	4,015	1	3,822	7	11,854
	Caxias do Sul	2	1,636	12	6,313	6	9,945	1	1,870	21	19,764
	Chapecó			5	1,551	3	6,403			8	7,954
	Curitiba	2	1,318	26	191,667	36	271,270	1	18,357	65	482,612
	Foz do Iguaçu	3	64,332	11	45,104	8	63,342	3	7,840	25	180,618
	Gramado	4	5,630	20	38,710	21	152,331	3	5,959	48	202,630
	Guarapuava	3	3,726	2	927	1	2,388			6	7,041
	Lages	1	336	6	968	2	2,478	1	1,736	10	5,518
	Londrina	4	5,808	6	6,187	5	7,595			15	19,590
	Maringá			6	13,733	7	27,151			13	40,884
	Passo Fundo			2	79	2	4,883			4	4,962
	Ponta Grossa	7	8,941	4	1,611	2	1,189			13	11,741
	Santa Maria	2	524	3	581	1	327	1	-	7	1,432
	Santana do Livramento	1	125	1	54	3	1,278			5	1,457
	Toledo			1	81	4	7,778			5	7,859
	Umuarama			2	1,320	2	2,758			4	4,078
	Vacaria	1	-	3	828	2	1,931			6	2,759
Grand total		317	492,026	303	722,573	230	1,038,830	22	63,574	872	2,317,003

• Source: Organization: Prepared by the authors.

Table 3
Points of Interest – by coastal/non-coastal location (IBGE, 2019), category, subtype, and number of reviews

Coastal			Non-coastal
POIs - Category and Subtype		No. of POIs	No. of reviews	POIs - Category and Subtype		No. of POIs	No. of reviews
Nature		275	380,211	Culture		180	410,088
	Beach	181	280,579		Museums/memorial	65	130,416
	Mountain/hill/mound	25	52,486		Cathedral, church, temples, and the like	32	62,868
	Protected area and the like	21	13,014		Winery/distillery	22	5,502
	Island	16	3,083		Monument/landmark	22	44,895
	River/waterfall/and the like	7	3,596		Architectural ensemble/landscape	12	19,441
	Trail	6	8,349		Cultural Center/gallery	8	45,541
	Dunes	4	6,348		Overpass/bridge	4	1,422
	Peak/Ridge	3	2,429		Fair/market	4	63,146
	Lake/pond/lagoon	3	898		Mill/Plant	2	1,224
	Sierra	2	2,511		Monastery	1	277
	Bay/cove/inlet (saco)	2	3		Cultural itinerary	1	71
	Cave	2	2,787		Urban historic center	1	1,087
	River mouth	1	393		Port	1	3,453
	Cavern	1	15		Sanctuary	1	13
	Botanical Garden	1	3,720		Studio (street box camera)	1	382
Culture		123	312,485		Lighthouse/tower	1	12,418
	Museums/memorial	39	26,604		Cableway	1	17,281
	Cathedral, church, temples, and the like	17	16,153		Cave (religious visitation)	1	651
	Monument/Landmark	11	20,081	Leisure Services/Facilities		143	658,626
	Cultural Center Gallery	9	46,049		Urban park	53	356,404
	Overpass/bridge	8	18,786		Square/plaza	27	57,507
	Trapiche/pier	6	22,599		Theme park	20	187,473
	House/big house/townhouse/solar	4	909		Recreational park - ecological - services	14	7,168
	Breakwater/Jetty	4	10,942		Water park	10	7,148
	Fair/market	4	123,918		Viewpoint	8	14,621
	Urban historic center	3	419		Amusement park	5	15,115
	Sanctuary	3	3,234		Waterfront/boardwalk/stairs/and the like	4	12,255
	Lighthouse/Tower	3	2,276		Game/Entertainment Center	1	734
	Fortress	3	12,913		Kart track	1	201
	Architectural ensemble/landscape	2	1,995	Nature		42	111,815
	Marina	2	5,248		Protected areas and the like	19	95,657
	Cave (religious visitation)	2	320		River/waterfalls/ and the like	8	7,921
	Cultural itinerary	1	-		Mount/hill/mound	8	921
	Winery/distillery	1	30		Botanical Garden	3	6,886
	Cemetery	1	9		Doline	1	-
Leisure Services/Facilities		87	380,204		Island	1	8
	Square/plaza	27	39,716		Lake/pond/lagoon	1	168
	Urban park	21	124,931		Furna	1	254
	Viewpoint	13	35,059	Others		13	39,722
	Water park	7	18,589		Zoo	4	29,357
	Waterfront/boardwalk/staircases/ and the like	7	7,410		Educational/scientific institution	3	7,634
	Amusement park	5	3,795		Factory Shop	3	761
	Theme park	2	116,724		Tourist Service Center	2	234
	Recreational/ecological park/services	2	33,144		Park/pavilion/exhibition center	1	1,736
	Sports/recreational Facilities	2	803
	Fee fishing	1	33
Others		9	23,852
	Educational/scientific institution	4	18,265
	Tourist service center	2	540
	Park/pavilion/exhibition center	1	55
	Zoo	1	2,515
	Thematic boat	1	2,477
Grand total		494	1,096,752		Grand total	378	1,220,251

• Source: Research data. Organization: Prepared by the authors.

Figure 1
Data extraction process

The first matrix of POIs required an individual analysis of the municipalities and presented items to eliminate the records corresponding to adjacencies (POIs of neighboring municipalities) and, above all, duplications, common in virtual destination conurbation, verified, for example, in Itajaí – Balneário Camboriú – Itapema, Blumenau – Gaspar, Gramado – Canela, Guaratuba – Matinhos, Paranaguá – Pontal do Paraná. After eliminating these items, the next step required a new documentary investigation regarding each of the matrix elements available on specific websites, Google (Portal web and Maps).

Subsequently, the items were classified from a combination of coding techniques (Yin, 2016) and an inventory of the tourist offer (Lima, 2011; Fratucci & Moraes, 2020; Almeida Moraes et al., 2020). This procedure allowed distinguishing the matrix items according to category (e.g., nature, culture, leisure services, and facilities, others) and subtype (e.g., beach, museum, monument, square, park, others). Each municipality/item was also classified as to whether it is integrated into a coastal-marine system (IBGE, 2019), depending on the geographical position of a considerable portion of the 38 municipalities and the importance of the coastline for the conformation of the South region. The final matrix yielded two products: (1) a spatialization created in MyMaps³ software and (2) a picture of the POIs collection in the South region.

The configuration analysis sought to reflect on the geographic specificities and nature of the POIs, drawing on Pearce (2003) and, notably, on Lozato-Giotard (1990). The aspects related to the management of these destinations addressed characteristics of the configuration identified as prominent in the planning and management processes of the locations. More significant support was obtained in the literature on tourist destinations in the following references: Barrado Timón (2004), Valls (2006), Mazaro (2010), Longjit and Pearce (2013), Flores and Mendes (2014), Pearce (2016), Coutinho and Nóbrega (2019).

The theoretical-methodological assumptions explained here allowed us to accomplish this study's objectives, and the results are outlined below.

3 DISCUSSION AND RESULTS

3.1 Intersection and south region destinations

The data in Table 1 show the intersection of 38 municipalities resulting from the crossing of two variables from the 2019-2021 Tourism Map database, domestic visits and accommodation establishments, and data about population, GDP, and tourism enterprises (ACTs). This group accounts for 3.2% of the 1,191 municipalities in the South region. However, it represents 71.34% of the visitation in that region, more than 54% of the accommodation establishments, and about 46% of the ACTs, which shows the vitality of the tourism sector and the effectiveness of the filters used in the composition of the intersection for the purposes of this analysis, since they provide conciseness to the observed set and distinctiveness in relation to the others, despite the capillarity of its geographical distribution, as observed in Figure 2.

Table 1
South region municipalities resulting from the intersection

Municipalities (UF)	Domestic visits [1]	%	Accom. establish. [1]	%	Population (2019) [2]	%	GDP 2017 (thousand reais) [2]	%	ACTs [3]	%	Total esta- blish. in the economy [3]	%	ACTs x total establish. in the economy (%)
Intersection	24,298,851	71.34	2,080	54.18	10,429,346	34.79	443,505,613.00	39.54	51,997	45.98	728,884	41.61	7
Bal. Camboriú (SC)	1,640,662	4.82	117	3.05	142,295	0.47	148,510.00	0.46	1,466	1.30	13,957	0.80	11
Bento Gonçalves (RS)	164,856	0.48	17	0.44	120,454	0.40	5,531,266.00	0.49	633	0.56	9,854	0.56	6
Blumenau (SC)	491,498	1.44	34	0.89	357,199	1.19	6,008,744.00	1.43	1,513	1.34	26,740	1.53	6
Bombinhas (SC)	395,872	1.16	132	3.44	19,769	0.07	598,278.00	0.05	545	0.48	2,220	0.13	25
Canela (RS)	147,149	0.43	48	1.25	44,998	0.15	1,001,465.00	0.09	422	0.37	2,975	0.17	14
Capão da Canoa (RS)	393,051	1.15	36	0.94	53,049	0.18	1,441,573.00	0.13	454	0.40	4,908	0.28	9
Cascavel (PR)	494,928	1.45	40	1.04	328,454	1.10	11,374,861.00	1.01	1,255	1.11	22,353	1.28	6
Caxias do Sul (RS)	479,511	1.41	27	0.70	510,906	1.70	21,717,020.00	1.94	2,092	1.85	34,942	1.99	6
Chapecó (SC)	234,259	0.69	29	0.76	220,367	0.74	8,890,178.00	0.79	763	0.67	15,369	0.88	5
Curitiba (PR)	3,868,494	11.36	185	4.82	1,933,105	6.45	84,702,357.00	7.55	10,182	9.00	155,296	8.87	7
Florianópolis (SC)	3,338,541	9.80	275	7.16	500,973	1.67	19,512,519.00	1.74	4,467	3.95	38,703	2.21	12
Foz do Iguaçu (PR)	1,107,641	3.25	151	3.93	258,532	0.86	13,463,838.00	1.20	1,491	1.32	13,288	0.76	11
Garopaba (SC)	150,856	0.44	38	0.99	23,078	0.08	534,079.00	0.05	289	0.26	1,554	0.09	19
Gramado (RS)	959,445	2.82	163	4.25	36,232	0.12	1,720,061.00	0.15	799	0.71	4,554	0.26	18
Guarapuava (PR)	250,161	0.73	27	0.70	181,504	0.61	5,606,255.00	0.50	602	0.53	9,034	0.52	7
Guaratuba (PR)	300,792	0.88	25	0.65	37,067	0.12	762,614.00	0.07	343	0.30	2,036	0.12	17
Itajaí (SC)	197,409	0.58	28	0.73	219,536	0.73	21,913,882.00	1.95	932	0.82	16,810	0.96	6
Itapema (SC)	574,437	1.69	17	0.44	65,312	0.22	1,698,077.00	0.15	411	0.36	5,919	0.34	7
Joinville (SC)	618,768	1.82	46	1.20	590,466	1.97	27,378,205.00	2.44	1,821	1.61	31,127	1.78	6
Lages (SC)	122,683	0.36	25	0.65	157,544	0.53	5,074,152.00	0.45	554	0.49	8,712	0.50	6
Londrina (PR)	695,250	2.04	37	0.96	569,733	1.90	19,235,188.00	1.71	2,439	2.16	38,238	2.18	6
Maringá (PR)	563,477	1.65	35	0.91	423,666	1.41	16,906,177.00	1.51	2,167	1.92	35,105	2.00	6
Matinhos (PR)	335,122	0.98	26	0.68	34,720	0.12	746,001.00	0.07	280	0.25	2,156	0.12	13
Paranaguá (PR)	198,623	0.58	50	1.30	154,936	0.52	9,856,374.00	0.88	776	0.69	6,474	0.37	12
Passo Fundo (RS)	349,768	1.03	23	0.60	203,275	0.68	8,584,861.00	0.77	954	0.84	15,302	0.87	6
Pelotas (RS)	283,409	0.83	34	0.89	342,405	1.14	8,573,355.00	0.76	955	0.84	16,059	0.92	6
Penha (SC)	144,918	0.43	41	1.07	32,531	0.11	673,705.00	0.06	299	0.26	1,675	0.10	18
Ponta Grossa (PR)	114,198	0.34	34	0.89	351,736	1.17	14,533,645.00	1.30	1,112	0.98	18,703	1.07	6
Porto Alegre (RS)	3,020,513	8.87	133	3.46	1,483,771	4.95	73,862,306.00	6.58	7,903	6.99	119,540	6.82	7
Rio Grande (RS)	696,471	2.04	33	0.86	211,005	0.70	9,215,701.00	0.82	777	0.69	8,249	0.47	9
Santa Maria (RS)	428,404	1.26	21	0.55	282,123	0.94	7,152,149.00	0.64	283	0.25	4,772	0.27	6
Sant'Ana do Livramento (RS)	175,810	0.52	24	0.63	77,027	0.26	2,575,389.00	0.23	936	0.83	14,206	0.81	7
São F. do Sul (SC)	205,939	0.60	20	0.52	52,721	0.18	3,993,553.00	0.36	267	0.24	2,169	0.12	12
Toledo (PR)	201,066	0.59	18	0.47	140,635	0.47	5,929,258.00	0.53	528	0.47	9,125	0.52	6
Torres (RS)	354,626	1.04	43	1.12	38,732	0.13	1,162,766.00	0.10	363	0.32	3,080	0.18	12
Tramandaí (RS)	324,818	0.95	17	0.44	51,715	0.17	1,011,455.00	0.09	269	0.24	2,689	0.15	10
Umuarama (PR)	134,223	0.39	15	0.39	111,557	0.37	3,284,406.00	0.29	414	0.37	7,463	0.43	6
Vacaria (RS)	141,203	0.41	16	0.42	66,218	0.22	2,131,390.00	0.19	241	0.21	3,528	0.20	7
Others in the South	9,763,282	28.66	1.759	45.82	19,546,638	65.21	678,212,219.00	60.46	61,082	54.02	1,022,846	58.39	6
Total South	34,062,133	100	3.839	100	29,975,984	100	1,121,717,832.00	100	113,079	100	1,751,730	100	6

• Note.
• ^[1]
  adapted from “Mapa do turismo brasileiro 2019-2021”, by Ministério do Turismo, Brasília, DF, 2019a;
• ^[2]
  adapted from “Sistema de Recuperação Automática – SIDRA”, by Instituto Brasileiro de Geografia e Estatística, n.d. (https://sidra.ibge.gov.br/territorio);
• ^[3]
  adapted from “Extrator de Dados”, by Instituto de Pesquisa Econômica Aplicada, n.d. (https://www.ipea.gov.br/extrator/).
• Source: Organization: Prepared by the authors.

Figure 2
South region and the set of the 38 municipalities

In addition to these aspects, the demographic weight in the municipalities filtered by the proposed intersection is also evident. Together these municipalities account for 10,429,346 inhabitants, representing 34.79% of the total in the South region (Table 1). Similarly, the high economic importance is also observed since the group represents 39.54% of the region's GDP.

This crossover revealed the nodal points of an urban influence network in the South region (Figure 2). By crossing this result with data from the REGIC survey by IBGE (2016, 2020), we were able to confirm the territorial importance of this set and foresee its influence on an even larger set. Most of the cities in this set are linked to the others by commuting movements and conurbation processes, creating Population Arrangements. This, in turn, makes the group of municipalities identified through the procedure adopted in the study even more important.

The largest Population Arrangements, which reveal the leadership of the network of cities in the South, are linked to the three capitals, Curitiba (P.R.), Florianópolis (S.C.), and Porto Alegre (R.S.). It is important to highlight that Florianópolis is among the least populated Brazilian metropolises (with less than 1 million inhabitants). Curitiba and Porto Alegre, on the other hand, are the most populous arrangements in the region.

There are also two other types of population arrangements evident in the list of 38 municipalities identified. One of them is the Border Arrangement. In this case, Foz do Iguaçu (P.R.), together with Ciudad Del Este in Paraguay, and Santana do Livramento (R.S.), together with Rivera in Uruguay play a pivotal role, both regionally and nationally. The second arrangement with a particular feature refers to some of the coastal municipalities, characterized as Coastal Tourist and Summer Population Arrangements, such as Itajaí-Balneário Camboriú (S.C.), Itapema (S.C.), Matinhos-Pontal do Paraná (P.R.), Torres (R.S.), among others. Also, with unique features, there are port municipalities, such as Paranaguá (P.R.) and Rio Grande (R.S.), which were considered in isolation, but whose economic relevance generates many flows (IBGE, 2016, 2020).

By realizing that these 38 municipalities make up population arrangements with centrality involving various types of displacements – either for work or for health, leisure, and sport purposes – as can be seen from the analysis of REGIC, it is confirmed not only the importance but also the enlargement of its territorial influence.

It should be emphasized that of the 38 municipalities that support the socio-economic and tourist centrality in the South, 18 are inserted in the coastal-marine system according to the IBGE (2019) classification. We believe that this fact highlights a territorial feature observed in this investigation, i.e., the tremendous importance of the coast for the three states of the region in terms of population, economy, and tourism.

3.2 Points of interest (POIs)

The Points of Interest (POIs) are of strategic importance in understanding the status of tourist destinations in the municipalities considered, notably because they provide information generated by the users. These, in turn, interactively, use and feed content for smartphone and other devices apps, in addition to websites, social media, and other information sources. As a rule, these resources and tools include images, comments, conditions of access, price of products and services, and reviews, among other elements. Indeed, they constitute what is commonly called user-generated content (UGC), clearly affecting the planning and management processes since the POIs are sites that attract a significant number of people.

The survey of the POIs in the 38 destinations initially yielded 1,232 POIs. After individual analysis of the items to eliminate the records corresponding to adjacent POIs in neighboring municipalities and duplicate occurrences, the final matrix was consolidated with 872 records, organized into four (4) categories and 59 subtypes (Lima, 2011; Fratucci & Moraes, 2020; Almeida Moraes et al., 2020), as shown in Tables 2 and 3. In general, the situation can be described, according to the relationship between category and subtypes, based on the following:

1. The Nature category accounts for 36.65% (n = 317) of the selected items. Regarding the subtypes, 17 records were found. The greater emphasis, however, is on beaches (57.10%), protected areas and the like (12.62%), mountains, hills, and mounds (10.41%), islands (5.36%), rivers, waterfalls, and the like (4.73%).

2. The Culture category includes 34.75% (n = 303) of the items. It is divided into 24 subtypes, among which the following stand out: museums and memorials (34.32%), cathedral, church, temples, and the like (16.17%), monuments and historic landmarks (10.89%), winery/distillery (7.59%), cultural center/gallery (5.61%), architectural ensemble/landscape (4.62%).

3. Leisure Services and Facilities category gathers 26.38% (n = 230) of the occurrences, distributed in 12 subtypes, of which eight items are given greater prominence: urban park (32.17%), square/plaza (23,48%), theme park (9.57%), viewpoint (9.13%), water park (7.39%), parks (leisure, ecological, or services) (6.96%), waterfront/boardwalk/staircases/ and the like, (4.78%), amusement park (4.35%).

4. The remaining items, 2.52% (n = 22), were grouped under Others. They correspond to educational and scientific institutions, zoos, tourist service centers, factory stores, parks/pavilions/exhibition centers, and a thematic boat.

Table 2 shows the distribution of the POIs in the municipalities that make up the intersection, according to the category. We opted, here, for a subdivision of the data presentation into two groups of municipalities. This separation meets the condition of belonging or not to the Coastal-Marine system, according to Plataforma IBGE Cidades (2019), as a way to enhance this crucial territorial feature of the set of 38 municipalities, detailed in the previous section.

The results speak directly to Lozato-Giotard's (1990) spatial theorization. The distribution by category and the specificity of the POIs are consistent with fundamental aspects of "tourist sitology" (p. 40) as well as other analyses of the author regarding the relevance of geographical criteria, alone or combined, in the spatial distribution of tourism, perspective recognized, albeit with different approaches, in the theories of Boullón (1997), Urry (2001), Pearce (2003), and Hayllar et al. (2011).

Manifestly, it is possible to notice that the South region has a collection of POIs resulting from a clear and balanced combination of (i) natural and (ii) human and technical factors. Lozato-Giotard (1990) assigns the former a decisive role, while he assigns an essential role to the latter group. However, the interpretation of this balance depends on specific subtleties associated with the overlap between the factors mentioned and the basis for their classification in categories and subtypes.

To a better understanding, it should be noted that the Nature category groups the POIs whose sites are eminently natural, with low anthropization. At first glance, it represents 36.65% of the occurrences. However, according to Lozato-Giotard (1990), the influence of natural factors goes beyond elementary physical demarcations. It is enough to look into how aspects concerning the landscape (particularly the surroundings), vegetation, climate, and especially the water component (therapeutic, recreational, contemplative uses) play and participate in the arrangement and viability of the POIs classified in other categories, an example of what happens with urban parks, squares, lookouts, or waterfronts.

In a wider dimension, the relevance of the winter climate for tourism in the countryside, such as Lages, Ponta Grossa, Guarapuava, Vacaria; or in the mountains, such as Bento Gonçalves, Gramado, Canela, and Caxias do Sul. Moreover, otherwise, the beaches – 20.76% of the surveyed POIs – usually have a well-established tourism history, clearly visible in coastal developments.

The items in the categories Culture, Leisure Services and Facilities, and Others correspond directly to human activity, according to Lozato-Giotard (1990) hechos de la civilización (p. 51). Here the urban environments and their landscapes stand out, the seaside towns, institutions of art and culture, religious events, sports, leisure and recreation venues, business, entertainment, and leisure facilities. 66.65% of the collection of POIs are related to the hechos de civilización systematized by the geographer.

The Nature category clearly highlights the appeal of coastal environments to tourists, evinced in the high projection of beach POIs, which, together with protected areas and landforms, account for 80.13% of the total POIs. In turn, Culture mirrors the interest of tourists in knowledge, memory, and faith, and devotion – the three main pillars of this category. Museums and memorials, religious temples, and monuments/landmarks account for 61.38% of the POIs. In the leisure dimension, three other components stand out with 65.22%. In this case, the primary triad – parks, squares, and plazas, theme parks – suggests a strong overlapping of POIs with leisure facilities and places of everyday life in cities, public spaces par excellence, clearly open and imbricated in the urban fabric, as well as the search for fantasy, imagination, and entertainment outlets (theme parks).

Following these notes, we now adopt a different perspective on this collection. To this end, we must observe the diversity of categories and subtypes of POIs regarding the geographical location of the surveyed destinations. This articulation allows verifying the hegemonic character of the coastal zone and its surroundings as the preferential location for tourist practices in the South. As shown in the previous section, the centrality of tourism in the 38 South region municipalities is different among the 20 non-coastal and the 18 in the coastal-marine system (IBGE, 2019).

According to a study by IBGE (2019), although the diversity of the coastal territory, the contact with the sea/ocean provides common elements (vegetation, fauna, geomorphology) that define a specific environmental unit. For Lozato-Giotard (1990), heliotropism and the beach, the social life on the seafront, and the formula "sun-sea-sex" are among the most significant achievements of society in terms of tourist attendance.

Investigations by Urry (2001) and Pearce (2003) also demonstrate and justify the reasons why coastlines are notable loci of tourist practices. This study confirms the findings of these authors. In the South region of Brazil, like many other territories worldwide, the coastal zone is a traditional and long-established setting for the imaginary of pleasure, rest, and relaxation, a common choice for developing tourism practices and social aesthetics.

The 18 coastal destinations comprise 56.65% (n = 494) of the surveyed POIs, broken down into 48 subtypes. The distribution by category is as follows: nature 55.67%, culture 24.90%, leisure services, and facilities 17.61%, other 1.82% (Table 1). In turn, the 20 non-coastal municipalities are home to 43.35% (n = 378) of the surveyed POIs, comprising 41 subtypes. The distribution by category is as follows: culture 47.62%, leisure services, and facilities 37.83%, nature 11.11%, and other 3.44% (Figures 3 and 4).

It is pertinent to distinguish another perspective that can be interpreted from the coast and neighboring regions. Among the non-coastal ones, Blumenau, Canela, Caxias do Sul, Gramado, and Curitiba are located less than 200 km (by road) from their state coastline. It is now a group of 23 destinations located mainly on the coast or in nearby regions. From this perspective, the coastal zone and neighboring regions demarcate the main territory of the region since this new group now has 80.85% of the POIs surveyed.

Finally, the results further indicate that the distribution of the POIs between destinations is uneven. What is most

striking, however, is the multiplicity of configurations and combinations of categories and subtypes. It appears that in terms of the nature and arrangement of POIs, the Southern destinations are significantly heterogeneous, as suggested by Figures 3, 4, 5, 6, and 7.

Figure 3
Points of Interest in coastal municipalities

Figure 4
Points of Interest in non-coastal municipalities

Figure 5
Points of Interest – Nature category

Figure 6
Points of Interest – Culture category

Figure 7
Points of Interest – Leisure Services and Facilities category

As shown in Figures 3 to 7, the heterogeneity poses a greater challenge for municipality governance of tourist destinations because of what they must implement to achieve quality standards for monitoring and management of places of effective visitation. The strategic discussion on destinations includes various themes and management models. Attention is usually directed to performance, competitiveness, and sustainability (Barrado Timón 2004; Valls, 2006; Mazaro, 2010; Framke, 2014; Pearce 2014, 2016), and these aspects certainly can be added to the many other elements that emerge at the macro-regional, state, and municipal levels of a diffuse picture of tourism places of use and development.

4 FINAL REMARKS

This study has achieved its objective by identifying the municipalities in the South region of Brazil with high territorial relevance for tourism in the 2019-2021 Tourism Map database and the description of the POIs in their geographical scope. It contributes to a closer look and a better spatial understanding of the tourism industry's objective situation. In this context, recognizing the centrality and breadth of influence of municipalities – aspects that emerged from the interpretation of the REGIC arrangements – rank among the most relevant.

The process of understanding these aspects was permeated by the consistency observed between empirical emerging from the data included in the analysis, and the theory by Lozato-Giotard (1990), which contends that the spatialization of tourism is closely linked to geographical features. Along these lines, the author's proposal on the combination of natural, human, and technical factors reflected in the configuration of the set of POIs highlighted in the destinations surveyed herein.

Therefore, studies with this design can provide a framework for tourism development policies because they deal with assessing the importance and influence of destinations, from which two lines of reflection stand out.

The first concerns the understanding of which actors (public, private, community/third sector) concern and depend on the functioning of the POIs. In this sense, it is important to examine institutional and organizational prerogatives. For Coutinho and Nóbrega (2019), the foremost contemporary challenge of destination governance is divided into institutional and organizational issues. Although it was not the objective of this article to examine the regionalization program, it is understood that the diagnostic interpretation is a crucial element for assessing the effectiveness and viability of public policies.

In the institutional field, the State's attributions, which in terms of territory, according to the Brazilian legal system, involve the three federative levels, various institutions of management, monitoring, inspection and control, and a dense network of legal devices. The organizational field concerns the stakeholders in the governance network, at different levels of interdependence, cooperation, and connection, forming an arena that involves problems, conflicts, interests, and powers (Salvati, 2004; Coutinho & Nóbrega, 2019).

Therefore, understanding the territorial influence of the municipalities is paramount to expand the potential for effectiveness of a tourism development policy, which can take territory as a starting point. A diffuse set of POIs tends to accentuate the political, technical, and social pressure on and among the entities that keep the appropriate prerogatives. In short, the condition of a "tourist destination" depends on the actors' ability to manage the use and visitation of places, complying with safety and quality standards, and adequate communication to the public.

The second line concerns the adjustment of the management of the POIs visitation process (Pearce, 2016). Management that considers the diversity found avoids generic measures that overlook the particularities in the arrangements. An efficient strategy can be achieved through the integration and cooperation between destinations, with the design of cooperative visitation programs or resorting to some sort of certification, according to the configuration and institutional specificities of the POI in question.

Although the classification in a category and subtype may suggest a similar basis for the elements (181 beaches, 104 museums/memorials, 74 urban parks, and the 513 others found in their respective classifications), the management of the POIs will effectively find multiple configurations. There are beaches with an intensely urbanized coastline of 7 km, such as Balneário Camboriú, and there are small stretches, not urbanized, isolated spots, like those in Bombinhas. Factors such as the area, internal zoning, integration with the surroundings, use by residents, visitation (amount, seasonality) help to blur this equation even further.

The proposal to understand this entanglement, based on the selected indicators and the outlined methodological design, represents the study's main contribution to the field. Moreover, the results found here constitute relevant support for strategic decisions by tourism actors.

The assumption that visitors search for different sources of information before the trip or while en-route (Padrón-Ávila & Hernández-Martín, 2017) is a crucial element for understanding the POIs and the spatial reach of tourism and its spatial dynamics, along with how they review and rate these sites on social media and digital platforms, thus feeding back user-generated content (UGC) (Corrêa & Hansen, 2014; Souza & Machado, 2017; Silva et al., 2017; Mayer et al., 2017; Boaria & Frantz dos Santos, 2018), is an important element for understanding the POIs and the spatial reach of tourism and its spatial dynamics.

Even so, it seems imperative to recognize the limitations imposed by the scope of analysis. The examination of the configuration of the POIs may prove insufficient to account for the complexity of the tourist phenomenon, particularly in this period of history, marked by the outbreak of the pandemic of COVID-19 in the year 2020, whose developments in the field of tourism have yet to be fully unveiled. Also, the POIs repertoire and type were extracted from a single source (Google Portal), and although it can be argued that this search engine is widely used, other channels or sources must be sought, not least because the user behavior and the travel support technologies are dynamic elements themselves.

There is also an opportunity for further investigations, both to replicate the path undertaken here in other scales, contexts, and even using different indicators – in whole or in part – from those that were operationalized in this research effort, as well as initiatives that address the gaps that were not possible to explore in this endeavor, among which a thorough examination of the Tourism Regionalization Program stands out. In terms of the continuity of the research, it is expected to advance in the analysis of data related to tourist municipalities in the South region of Brazil, expanding the range of information. We understand that the methodological procedure is fruitful enough to contribute to the maturation of the situation (diagnostic level) and project scenarios and policy proposals.

• 1
  The classification shows the contribution of municipalities to the tourism economy, ranging from “A” for those with the highest performance to “E” for those with the lowest performance. To categorize the municipalities, the Ministry of Tourism performs a quantitative crossover of the five variables in its database (Ministério do Turismo, 2019b).
• 2
  The categorization in the Tourism Map serves, among other aspects, to guide the Regionalization Program, whose operationalization is difficult in terms of implementation, namely the need to respect administrative limits for the design of the regions. However, the understanding in this investigation is that the database has consistency to support studies that aim to understand territorial relevance. The pertinent and necessary analysis of the referred program constitutes an object which should be addressed in further research, since it goes beyond the scope outlined in this paper.
• 3
  https://www.google.com/maps/d/u/0/edit?mid=1q1S4RjncieI8gLPQz9_f-j2oac5GDV_x&usp=sharing
• How to Cite: Chemin, M.; Filippim, M. L.; Abrahão, C. M. S. (2021). Territorial projection and points of interest in tourist destinations in the South region (Brazil): An analysis based on the 2019-2021 Tourism Map. Revista Brasileira de Pesquisa em Turismo, São Paulo, 15 (3), e-2156, May./Ago. http://dx.doi.org/10.7784/rbtur.v15i3.2156

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Edited by

Editor: Glauber Eduardo de Oliveira Santo

Publication Dates

• Publication in this collection
  06 Aug 2021
• Date of issue
  Sep-Dec 2021

History

• Received
  30 July 2020
• Accepted
  16 Oct 2020