Finkl, C.W. and Makowski, C., 2021. Alongshore classification and morphometric analysis of developed coastal belts: An example from Uruguay, South America. Journal of Coastal Research, 37(5), 906–922. Coconut Creek (Florida), ISSN 0749-0208.

Approximately half of the 666-km long Uruguayan coastal belt length is characterized by continuums of developed urban centers that are associated with ports and harbors, residential, recreational, military, shore protection, and/or commercial facilities that occur in association with agricultural pursuits. Modification of the Biophysical Cross-shore Classification System (BCCS) to include such features of anthropogenic change along with naturally occurring coastalscapes permits classification of developed and undeveloped coastal belts based on interpretation of satellite imagery. Characterization of alongshore domains was based on conjoining archetypes into catenary sequences that typify coastal belts both alongshore and cross-shore. Based on interpretation of satellite imagery acquired from Google Earth Pro, Uruguayan coastal belts were divided into six separate departments (Rocha, Maldonado, Canelones, Montevideo, San Jose, Colonia) and characterized by the alongshore widths of archetypes that extended from offshore to several kilometers inland. Compilation of coastal belt catenas showed that promontories and headlands, which comprise resistant igneous and metamorphic rocks, function as anchor points along the shore and are widely interspersed by sedimentary (littoral) domains that contain mainland and barrier beaches that are backed by beach-dune couplets, wetlands, lagoonal flats, and developed upland archetypes. Typical alongshore super domains, which were concised from cross-shore archetypical consequences, include the following predominant types of sequences: Barrier-Beach-Dune, Beach-Dune-Lagoon, Beach-Dune-Wetland, Beach-Dune-Upland, Beach-Cliff-Upland, Beach-Wetland-Flat-Lagoon, and Rock-Cliff-Upland. Certain archetypes, such as rock and developed, were prevalent throughout the coastal belt codifications with their representative symbolizations appearing in the variable code sequences of domains and super domains. Morphometric analysis tables were also compiled with alongshore lengths of domains and super domains, as well as percentages of individual department and Uruguayan coastal belts. This examination of the Uruguayan coast showed for the first time that the BCCS can characterize anthropogenically developed units with naturally occurring biophysical features. Interpreted cross-shore transects, alongshore domains, and all-encompassing super domains allow for a comprehensive classification and morphometric analysis of offshore, inshore, and onshore components along Uruguay's natural and developed coastal belts.

Because there are many spatially complex environments and eco-geomorphological features in coastal belts, specialized classifications are required to differentiate naturally occurring biophysical zonations that are interspersed with anthropogenically developed areas (Finkl, 2004; Finkl and Makowski, 2019a,b; Finkl, Makowski, and Vollmer, 2014; Kelletat, Scheffers, and May, 2013; Klemas, 2014; Makowski, 2014; Makowski and Finkl, 2016; Makowski, Finkl, and Vollmer, 2015, 2016, 2017; Rasid and Pramanik, 1990; Schowengerdt, 1983; Wang et al., 2015). The coast of Uruguay is no exception, with approximately half of its coastal zone occupied by variable densities of urban development that range from large metropolitan areas, such as the capital of Montevideo, to dispersed small coastal towns and villages that cater to maritime pursuits and recreation. The Uruguayan coastal zone thus provides an opportunity for bimodal urban-rural classification of coastal belts using the Biophysical Coastal Classification System (BCCS) (Finkl and Makowski, 2020a,b,c). Occurring on a trailing continental margin in South America, the cross- and alongshore BCCS classifications can be compared with those of the Oregon coast on a leading continental margin in North America (cf. Finkl and Makowski, 2021b). This paper provides an illustrative example of how the BCCS can be applied to a developed coastal belt situated in a geotectonic setting that contains ancient cratonic (shield) remnants amid younger sedimentary terranes.

Geographic Location, Biophysical Settings, and Developed (Urbanized) Regions

Uruguay is a relatively small country (175,020 km2), the second-smallest nation in South America after Suriname, that lies on the SE coast of the continent, south of Brazil and north of Argentina (Figure 1). The country broadly lies between 33°45′ and 34°10′ South Latitude, marking northern and southern coastal boundaries that demarcate about 660 km of coastline. Its northern coast faces the South Atlantic Ocean, whereas its southern coast faces the Río de la Plata Estuary. Although some researchers regard it as a gulf or a marginal sea of the Atlantic and others consider it to be a river, this hydrologic zone is commonly recognized as the estuary of the Rio Paraná Guazú and Rio Uruguay (as well as the Paraguay River, which drains into the Paraná River). The delta of the Río de la Plata comprises the confluence of several rivers that discharge at the head of the estuary. The breadth of the ria-type estuary (e.g.,Isla and Espinosa, 2021) increases seaward from the deltaic zone reaching a width of about 225 km, measured from Maldonado in Uruguay to San Clemente del Tuyú in Argentina. If the Río de la Plata is regarded as an estuary river, it is among the widest in the world with an area of about 35,000 km2. According to Baigun, Colautti, and Maiztegui (2018), the La Plata River system is a funnel coastal plain tidal river with a semiclosed shelf at the mouth. The La Plata River is the world's widest freshwater system and an estuary that drains into the second-largest basin in South America and the fifth largest basin in the world. Oceanic tides are relatively weak with an average tidal range about 15 cm at Montevideo and ranging up to 50 cm at other locations along the coast (Isla and Espinosa, 2021), but they flow almost 200 km up the Paraná and the Uruguay rivers from their mouths on the estuary (Mianzan et al., 2001). Uruguay has a humid subtropical climate (Cfa, according to the Köppen climate classification) (e.g., Kottek et al., 2006; Peel; Finlayson, and McMahon, 2007). Average highs and lows in summer (January) in Montevideo are 28°C and 17°C, respectively, although the high humidity makes the temperatures feel colder, and rainfall averages 950 mm annually. According to the Coastal Belt Linked Classification (CBLC) that links Large Marine Ecosystems (LME) (e.g., Sherman and Hempel, 2008) with terrestrial Ecoregions (ER) (e.g., Bailey, 1998; Dinerstein et al., 2017; Finkl and Makowski, 2020d, 2021a), LME14 (Patagonian Shelf Large Marine Ecosystem) borders coastal Uruguay, whereas terrestrial environments are identified as ER574 (Uruguayan Savanna Ecoregion).

Figure 1

Location map of the Uruguayan coastal belt showing the regional position of the study area on the southeast coast of South America (shown in the inset map with a red oval) south of Brazil and north of Argentina, facing the South Atlantic Ocean and Río de la Plata estuary. The Large Marine Ecosystem (Patagonian Shelf; LME14) and terrestrial ecoregion (Uruguayan Savanna; ER574) are listed according to the Coastal Belt Linked Classification (CBLC) (Finkl and Makowski, 2020d) and the six department regions classified in this study have been delineated along the coast. Figures 2 through 7 are based on the country's six department geographical positions along the coast from east to west.

Figure 1

Location map of the Uruguayan coastal belt showing the regional position of the study area on the southeast coast of South America (shown in the inset map with a red oval) south of Brazil and north of Argentina, facing the South Atlantic Ocean and Río de la Plata estuary. The Large Marine Ecosystem (Patagonian Shelf; LME14) and terrestrial ecoregion (Uruguayan Savanna; ER574) are listed according to the Coastal Belt Linked Classification (CBLC) (Finkl and Makowski, 2020d) and the six department regions classified in this study have been delineated along the coast. Figures 2 through 7 are based on the country's six department geographical positions along the coast from east to west.

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Figure 2

The 176.2-km long coastal belt throughout the Rocha Department extends from the southern border of Brazil southward and includes the Rocha Super Domain with an archetype codification of Beach-Dune-Wetland-Lagoon (Be-Du-W-L). Red lines separate the individual domain segments that were classified throughout the department. This coastal belt is divided into 13 Biophysical Cross-shore Classification System (BCCS) domains, the largest of which is a littoral cell (Domain 2-9) that is characterized by the cross-shore catenary sequence BesiRseDubo,foWmr,sl. The La Paloma Divergence Zone separates littoral cells in Domains 2-9 and 2-11. Rock promontory outcroppings are shown with light-orange caret symbols along the coast. All codifications can be keyed using Table 1, and morphometric analysis of the Rocha Department corresponds directly with Table 2.

Figure 2

The 176.2-km long coastal belt throughout the Rocha Department extends from the southern border of Brazil southward and includes the Rocha Super Domain with an archetype codification of Beach-Dune-Wetland-Lagoon (Be-Du-W-L). Red lines separate the individual domain segments that were classified throughout the department. This coastal belt is divided into 13 Biophysical Cross-shore Classification System (BCCS) domains, the largest of which is a littoral cell (Domain 2-9) that is characterized by the cross-shore catenary sequence BesiRseDubo,foWmr,sl. The La Paloma Divergence Zone separates littoral cells in Domains 2-9 and 2-11. Rock promontory outcroppings are shown with light-orange caret symbols along the coast. All codifications can be keyed using Table 1, and morphometric analysis of the Rocha Department corresponds directly with Table 2.

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Figure 3

The 109.8-km long Maldonado Department coastal belt is divided into 14 individual Biophysical Cross-shore Classification System (BCCS) domains, five super domains, and two divergence zones (designated by red hatching). Red lines separate the individual domain segments that were classified throughout the department. The Faro Divergence Zone separates littoral cells in Domains 3-2 and 3-4 within the Santa Monica Super Domain (Barrier-Beach-Rock-Dune-Wetland), and the Punte del Este Divergence Zone separates the littoral cell in Domain 3-8 within the Maldonado Super Domain (Beach-Rock-Upland-Dune-Upland-Developed). Both divergence zones have a codification sequence of RmeUDvur. Although Domains 3-3, 3-8, 3-9, and 3-13 all contain developed archetypes, the city of Maldonado (Domain 3-8) is the most highly developed urban area in the department. Rock promontory outcroppings are shown with light-orange caret symbols along the coast. All codifications can be keyed using Table 1, and morphometric analysis of the Maldonado Department corresponds directly with Table 3.

Figure 3

The 109.8-km long Maldonado Department coastal belt is divided into 14 individual Biophysical Cross-shore Classification System (BCCS) domains, five super domains, and two divergence zones (designated by red hatching). Red lines separate the individual domain segments that were classified throughout the department. The Faro Divergence Zone separates littoral cells in Domains 3-2 and 3-4 within the Santa Monica Super Domain (Barrier-Beach-Rock-Dune-Wetland), and the Punte del Este Divergence Zone separates the littoral cell in Domain 3-8 within the Maldonado Super Domain (Beach-Rock-Upland-Dune-Upland-Developed). Both divergence zones have a codification sequence of RmeUDvur. Although Domains 3-3, 3-8, 3-9, and 3-13 all contain developed archetypes, the city of Maldonado (Domain 3-8) is the most highly developed urban area in the department. Rock promontory outcroppings are shown with light-orange caret symbols along the coast. All codifications can be keyed using Table 1, and morphometric analysis of the Maldonado Department corresponds directly with Table 3.

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Figure 4

The 55.3-km long Canelones Department coastal belt is divided into five individual Biophysical Cross-shore Classification System (BCCS) domains and three super domains. The designated super domains (and their archetype sequences) from east to west are Jaurequiberry (Beach-Rock-Cliff-Dune-Upland-Developed), Atlantida (Beach-Dune-Upland-Developed), and Colonia (Beach-Rock-Dune-Upland-Developed). Red lines separate the individual domain segments that were classified, and all domains contain developed archetypes. Rock promontory outcroppings are called out with light-orange caret symbols along the coast. All codifications can be keyed using Table 1, and morphometric analysis of the Canelones Department corresponds directly with Table 4.

Figure 4

The 55.3-km long Canelones Department coastal belt is divided into five individual Biophysical Cross-shore Classification System (BCCS) domains and three super domains. The designated super domains (and their archetype sequences) from east to west are Jaurequiberry (Beach-Rock-Cliff-Dune-Upland-Developed), Atlantida (Beach-Dune-Upland-Developed), and Colonia (Beach-Rock-Dune-Upland-Developed). Red lines separate the individual domain segments that were classified, and all domains contain developed archetypes. Rock promontory outcroppings are called out with light-orange caret symbols along the coast. All codifications can be keyed using Table 1, and morphometric analysis of the Canelones Department corresponds directly with Table 4.

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Figure 5

The 74-km long Montevideo Department coastal belt is divided into 16 individual Biophysical Cross-shore Classification System (BCCS) domains and two super domains. The smaller (11.9 km) Playa Verde Super Domain (Beach-Upland-Developed) is east of the larger (62.1 km) Montevideo Super Domain (Rock-Upland-Developed). Red lines separate the individual domain segments that were classified. The Montevideo Department coastal belt is completely developed with natural cross-shore eco-geomorphological catenas characterized by rock, cliff, and upland archetypes with occasional beach archetypes that are isolated by headlands. Domain 5-10 is an example of an intensely developed coastal stretch surrounding a major harbor. The 17-km long Domain 5-16, which extends westward out of frame, is characterized by a Rig,seUDvag catenary sequence. Rock promontory outcroppings are shown with light-orange caret symbols along the coast. All codifications can be keyed using Table 1, and morphometric analysis of the Montevideo Department corresponds directly with Table 5.

Figure 5

The 74-km long Montevideo Department coastal belt is divided into 16 individual Biophysical Cross-shore Classification System (BCCS) domains and two super domains. The smaller (11.9 km) Playa Verde Super Domain (Beach-Upland-Developed) is east of the larger (62.1 km) Montevideo Super Domain (Rock-Upland-Developed). Red lines separate the individual domain segments that were classified. The Montevideo Department coastal belt is completely developed with natural cross-shore eco-geomorphological catenas characterized by rock, cliff, and upland archetypes with occasional beach archetypes that are isolated by headlands. Domain 5-10 is an example of an intensely developed coastal stretch surrounding a major harbor. The 17-km long Domain 5-16, which extends westward out of frame, is characterized by a Rig,seUDvag catenary sequence. Rock promontory outcroppings are shown with light-orange caret symbols along the coast. All codifications can be keyed using Table 1, and morphometric analysis of the Montevideo Department corresponds directly with Table 5.

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Figure 6

The 93.5-km long San Jose Department coastal belt, which faces the Río de la Plata Estuary, is divided into six individual Biophysical Cross-shore Classification System (BCCS) domains and four super domains (from east to west: Playa Pascual, Punta del Tigre, Libertad, and Ordeig). Red lines separate the individual domain segments that were classified throughout the department. The 60.6-km long Ordeig Super Domain takes up more than half of the San Jose Department coastal belt and is characterized by barrier beaches and islands that are backed landward by developed upland archetypes with residential and agricultural sub archetypes. All codifications can be keyed using Table 1, and morphometric analysis of the San Jose Department corresponds directly with Table 6.

Figure 6

The 93.5-km long San Jose Department coastal belt, which faces the Río de la Plata Estuary, is divided into six individual Biophysical Cross-shore Classification System (BCCS) domains and four super domains (from east to west: Playa Pascual, Punta del Tigre, Libertad, and Ordeig). Red lines separate the individual domain segments that were classified throughout the department. The 60.6-km long Ordeig Super Domain takes up more than half of the San Jose Department coastal belt and is characterized by barrier beaches and islands that are backed landward by developed upland archetypes with residential and agricultural sub archetypes. All codifications can be keyed using Table 1, and morphometric analysis of the San Jose Department corresponds directly with Table 6.

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Figure 7

The 157-km long Colonia Department coastal belt, which lies on the northern shore of the Río de la Plata Estuary, is divided into eight individual Biophysical Cross-shore Classification System (BCCS) domains and two super domains. Red lines separate the individual domain segments that were classified throughout the department. The 68-km long Rosario Super Domain (Beach-Dune-Upland-Developed) is characterized by beach-headland alongshore sequences that are interrupted by a developed headland at Juan Lacaze in Domain 7-2. The cross-shore catenary sequence in this domain reads Dvph,shBesiDuUDvag,re, emphasizing developed sub archetypes. Domain 7-6 in the Conchillas Super Domain (Wetland-Upland-Developed) is similar in that the cross-shore concatenation is initialized by developed archetypes in the cross-shore catenary sequence: DvphWfoUDvag,re. All codifications can be keyed using Table 1, and morphometric analysis of the Colonia Department corresponds directly with Table 7.

Figure 7

The 157-km long Colonia Department coastal belt, which lies on the northern shore of the Río de la Plata Estuary, is divided into eight individual Biophysical Cross-shore Classification System (BCCS) domains and two super domains. Red lines separate the individual domain segments that were classified throughout the department. The 68-km long Rosario Super Domain (Beach-Dune-Upland-Developed) is characterized by beach-headland alongshore sequences that are interrupted by a developed headland at Juan Lacaze in Domain 7-2. The cross-shore catenary sequence in this domain reads Dvph,shBesiDuUDvag,re, emphasizing developed sub archetypes. Domain 7-6 in the Conchillas Super Domain (Wetland-Upland-Developed) is similar in that the cross-shore concatenation is initialized by developed archetypes in the cross-shore catenary sequence: DvphWfoUDvag,re. All codifications can be keyed using Table 1, and morphometric analysis of the Colonia Department corresponds directly with Table 7.

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Table 1

Code definitions of archetypes and sub archetypes using bolded upper- and lowercase letters as primary archetype designators and lowercase alphabet subscripts as secondary sub archetype refinements to indicate the composition and nature of barriers, beaches, beach ridges, cliffs, developed (anthropogenically-influenced development), dunes, flats (and banks), lagoons, rock, uplands, and wetlands. This table is modified from Finkl and Makowski (2020a).

Code definitions of archetypes and sub archetypes using bolded upper- and lowercase letters as primary archetype designators and lowercase alphabet subscripts as secondary sub archetype refinements to indicate the composition and nature of barriers, beaches, beach ridges, cliffs, developed (anthropogenically-influenced development), dunes, flats (and banks), lagoons, rock, uplands, and wetlands. This table is modified from Finkl and Makowski (2020a).
Code definitions of archetypes and sub archetypes using bolded upper- and lowercase letters as primary archetype designators and lowercase alphabet subscripts as secondary sub archetype refinements to indicate the composition and nature of barriers, beaches, beach ridges, cliffs, developed (anthropogenically-influenced development), dunes, flats (and banks), lagoons, rock, uplands, and wetlands. This table is modified from Finkl and Makowski (2020a).
Table 1

(continued).

(continued).
(continued).
Table 2

Morphometric breakdown of super domains and divergence zone designations in the Rocha Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 2.

Morphometric breakdown of super domains and divergence zone designations in the Rocha Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 2.
Morphometric breakdown of super domains and divergence zone designations in the Rocha Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 2.
Table 3

Morphometric breakdown of super domains and divergence zone designations in the Maldonado Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 3.

Morphometric breakdown of super domains and divergence zone designations in the Maldonado Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 3.
Morphometric breakdown of super domains and divergence zone designations in the Maldonado Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 3.
Table 4

Morphometric breakdown of super domains and divergence zone designations in the Canelones Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 4.

Morphometric breakdown of super domains and divergence zone designations in the Canelones Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 4.
Morphometric breakdown of super domains and divergence zone designations in the Canelones Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 4.
Table 5

Morphometric breakdown of super domains and divergence zone designations in the Montevideo Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 5.

Morphometric breakdown of super domains and divergence zone designations in the Montevideo Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 5.
Morphometric breakdown of super domains and divergence zone designations in the Montevideo Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 5.
Table 6

Morphometric breakdown of super domains and divergence zone designations in the San Jose Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 6.

Morphometric breakdown of super domains and divergence zone designations in the San Jose Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 6.
Morphometric breakdown of super domains and divergence zone designations in the San Jose Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 6.
Table 7

Morphometric breakdown of super domains and divergence zone designations in the Colonia Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 7.

Morphometric breakdown of super domains and divergence zone designations in the Colonia Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 7.
Morphometric breakdown of super domains and divergence zone designations in the Colonia Department showing individual domain segment labels, alongshore lengths, Biophysical Cross-shore Classification System (BCCS) codifications (cf. Table 1), approximate percentage of department length, and the percentages of the entire Uruguayan coastal belt. Summary totals are accentuated by boldface type. The hyphenated numerical identifiers for the individual domain segment labels correspond directly to Figure 7.

Administratively, the Uruguay coastal belts are divided by six departments that are from north to south: Rocha, Maldonado, Canelones, Montevideo, San Jose, and Colonia. The extreme northern and southern coastal departments of Uruguay are generally undeveloped except for some small coastal villages and towns that are backed inland by wetlands and agriculture. The intervening coastal departments are largely developed with the greatest concentration of commercial and urban developed environments occurring in the Montevideo Department that has a population of about 3.5 million inhabitants. About 96% of the Uruguayan population is urban (3,337,671 people in 2020) (e.g., Worldometers, 2021).

Purpose and Goals

The Uruguayan coastal belt was selected as a test site for application of the BCCS (Biophysical Coastal Classification System) on a trailing continental margin where significant anthropogenic development occurred. The purpose of that selection was based on the fact that the BCCS, as originally constructed (e.g., Finkl and Makowski, 2020a,b,c) on the basis of interpretation of satellite images showing naturally occurring coastal areas. Originally, anthropogenically developed areas were specifically avoided to develop a scheme that included known eco-geomorphological biophysical units. The CBLC (Coastal Belt Linked Classification) (Finkl and Makowski, 2020d, 2021a) subsequently extended those natural coastal environments to include LMEs (Large Marine Ecosystems) (e.g., IOC-UNESCO, 2011; Sherman and Hempel, 2008) and ERs (Ecoregions) (e.g., Bailey, 1998; Dinerstein et al., 2017) for a more comprehensive classification of coastal belts.

The present study assesses the possibility or feasibility of including developed areas as part of the BCCS, not as an adjunct but as an integration of natural environments and anthropogenically-influenced coastal zones. Although not meaning to delve into urban classifications per se, the goal is to provide potential guidance into possibilities for incorporating coastal development into a more complete or comprehensive cross- and alongshore classification of coastal belts that are naturally occurring and anthropogenically modified. Approximately half of the Uruguayan coastal belts are developed, thereby providing an ideal scope for investigating various types of sub archetype unit classifications within a Developed archetype category.

The BCCS (Biophysical Coastal Classification System) methodological approach to cross- and alongshore classification, as discussed by Finkl and Makowski (2020a,b,c,d; 2021a,b), is based on the interpretation of satellite imagery. This procedure is adopted because remote sensing provides scope for all of the world's coastlines, as accessed, for example, in the Google Earth Pro platform. Although a plethora of satellite imagery that is amenable to coastal classification is available, this platform is suggested because the images are free of charge and worldwide coverage is provided at one electronic location. Zoom and measuring capabilities in Google Earth Pro and easy one-click access to views in Google Maps on the internet are additional advantages that facilitate operational procedures to obtain detailed views and geographical information. Due to limitations of publication page size and the amount of information that can be shown in a single figure, zooming in for detailed inspection of coastal features is a methodological necessity that is facilitated by including geographical coordinates for each image in figure captions. This procedure allows readers to inspect the satellite images and to compare suggested classificatory units with their own interpretations.

Background to Methods and Procedures

The basic methodology has been detailed in several publications that outline procedures for interpreting satellite images for the purpose of delineating cross-shore biophysical catenas that comprise sequences of eco-geomorphological units starting with marine ecosystems and moving landward to include terrestrial environments (e.g., Finkl and Makowski, 2020a,b,c,d). Because cross-shore catenary sequences have alongshore spread, it is possible to demarcate distance alongshore and thereby acquire an alongshore classification. The procedure for accomplishing this classificatory effort is based on the recognition of domains that have specific codifications (Table 1). The categories provided in this table are divided into cross-shore archetype and sub archetype descriptors that can be grouped in catenary sequences in the form of a descriptive shorthand code. Delineation of cross-shore codifications provides a basis for subdividing the coast into domains. Due to natural variability along the shore, domains have alongshore proximal and distal limits, the boundaries of which are determined by different adjacent catenary sequences. To concisely understand the complexity of alongshore variation of cross-shore sequences, super domains are used to generalize characterization of the coast into larger alongshore units as domains can be quite small.

Cartographic Symbols and Notations

Color-coded symbologies used to depict interpreted properties of the satellite images (Figures 2 through 7) are based in the first instance on the delineation of domains that are separated by thin, red lines that extend from the sea across the shore to variable distances inland. Upper- and lowercase yellow letters define the codified cross-shore catenary sequences, and each domain is identified by numerals that are color coded to the super domain to which they belong. Orange arrows point seaward to headlands and promontories that are too small to map at presentation scale. Large rocky promontories that separate littoral cells are identified by translucent red boxes that also receive domain numerals. Super domains are identified by colored bars that run parallel to the shore and are identified by name with letters matching the colored bar. All figures are presented using this methodological format.

Methodological Categories of Classification

In a word, the methods employed boil down to identifying domains that comprise specific codified sea to land sequences that have areal extent. For simplicity, domains can be grouped into super domains to provide a more generalized classification of coastal environments. In addition to the original eco-geomorphological units comprising the BCCS, new units are now suggested to help characterize developed shores. Possible sub archetypes that can be used in the classification of coasts fall under the developed archetype category and include agriculture, aquaculture, commercial, industrial, military, mining, ports and harbors, residential, shore protection, and urban. These suggested anthropogenic sub archetypes are undifferentiated but could be further divided in more detailed studies. Not all of the anthropogenic sub archetypes listed in Table 1 are used in the test example of the Uruguayan coast. For purposes of this assessment, however, the following seven sub archetypes were identified in the study area: agriculture, commercial, military, ports and harbors, residential, shore protection, and urban. No attempt has been made to define or quantify these kinds of units because they have been applied according to general parlance in the simplest instance.

The methodology applied in the study of the coast of Uruguay thus involved the recognition of natural and anthropomorphized environments, as interpreted from satellite imagery. Sub archetypes of the developed archetype category are intermixed with archetypes and sub archetypes used to identify natural environments to provide a complete catenary sequence that is dictated by the spatial occurrence of cross-shore units with alongshore spread. Table 1 shows the expansion of the concise codifications into explicit verbiage.

Results of this study applying the BCCS (Biophysical Coastal Classification System) along the coast of Uruguay and investigation of the possibility for including sub archetypes for developed shores are presented in six figures with corresponding tables. One interpretive figure for each department shows that spatial delineations of domains are defined by cross-shore catenary sequences that have alongshore spread. For easy reference, each domain is numbered with the first digit that corresponds to the figure number. Tables containing morphometric data are identified in a similar manner with Table 2, for example, corresponding to Figure 2. The results for each department are discussed in the following paragraphs, starting with the northern Rocha Department facing the open southern Atlantic Ocean and concluding with the southern Colonia Department that faces the Río de la Plata.

Rocha Department

The Rocha Department contains 13 domains (Figure 2) and one super domain that compose 176.2 km of the coastal belt (Table 2). Occupying about 26.5% of the Uruguayan coast, the super domain retains a summary Beach-Dune-Wetland-Lagoon catenary sequence. Most domains contain Beach-Dune (i.e. Domains 2-1, 2-2, 2-3, 2-12, 2-13) or Barrier-Beach-Dune (Domain 2-11) cross-shore sequences that are often interspersed by the occurrence of rock sub archetypes (i.e. 2-4, 2-5, 2-6, 2-7, 2-9, 2-9, 2-13). Wetlands are ubiquitous ecosystems that occur at variable distances inland from immediately landward of dune archetypes and continuing inland for the length of cross-shore transects that range up to 20 km or more in length. Lagoon sub archetypes are a prominent feature of several transects (i.e. Domains 2-2, 2-5, 2-8, 2-11, 2-13), the most notable of which include Laguna Negra (Domain 2-5), Laguna de Castillos (Domain 2-8), Laguna de Rocha (Domain 2-11), and Laguna Garzon (part of Domain 2-13). Strand plain beach ridge sub archetypes occur on inland margins of lagoons in Domains 2-7 and 2-11 that, respectively, compose 8.5 and 14.5 km of shore. Although rock outcrops and promontories are commonly found throughout this coastal belt, one headland is most prominent because it extends about 3.5 km seaward from the general line of the shore and is identified here as the La Paloma Divergence Zone (Domain 2-10) because it separates littoral zones to the north and south. The cross-shore Rock-Upland archetypical codification of this zone contains a minor degree of urbanization.

Maldonado Department

The coastal belt of the Maldonado Department (Figure 3) spans an alongshore distance of about 109.8 km (Table 3), composing about 16.5% of the whole Uruguayan coastal belt, and is characterized by five super domains (Santa Monica, San Carlos, Maldonado, Punta Ballena, and Piriapolis), all of which feature rock archetypes. Barrier, beach, and dune cross-shore archetypical sequences provide an overall impression of the coastal belt, even though rock archetypes are prevalent but mostly understated except for rocky headlands that jut into the ocean. The Piriapolis (30.7 km: Domains 3-12, 3-13, 3-14), San Carlos (23.1 km: Domains 3-5, 3-6, 3-7), and Punta Ballena (18 km: Domains 3-10, 3-11) are the longest super domains, followed by Maldonado (14 km: Domain 3-8) and Punta del Este (5.5 km: Domain 3-9). The short Faro Divergence Zone (3 km: Domain 3-3) is a major rocky headland backed by upland archetypes that are heavily urbanized. Wetland, lagoon, and flat sub archetypes variably occur in Domains 3-1, 3-2, 3-4 (Santa Monica Super Domain), 3-5, 3-6, 3-7 (San Carlos Super Domain), 3-10, and 3-11 (Punta Ballena Super Domain). Eroding low cliffs (bluffs), described by Alonso et al. (2014), that are about 2 m in height at the back beach occur in Domain 3-14 (Piriapolis Super Domain). Urbanization increases in this coastal belt compared with the Rocha Department, composing a total distance of about 34.5 km combined from Domains 3-3, 3-8, 3-9, and 3-13.

Canelones Department

Three super domains (Jaurequiberry, Atlantida, and Colonia Nicolich) compose the Canelones Department (Figure 4) coastal belt spanning a total distance of about 55.3 km (Table 4) and, respectively, account for about 7.2%, 62.8%, and 30% of the coastal belt. Beach-dune archetypes dominate the shore except for the numerous rocky headlands that separate littoral cells. Rock sub archetypes are common in Domains 4-1 and 4-3, whereas cliff sub archetypes occur in Domains 4-1 and 4-2. One of the more striking features of this coastal belt is the increase in coastal development that occurs in all five domains but which is increasing development in Domains 4-3, 4-4, and 4-5. Urban development here, as in the case of Ciudad de la Costa, extends about 4 km inland and grades to ex-urban uses and agriculture. All development sub archetypes are associated with uplands.

Montevideo Department

The 74-km long coastal belt in the Montevideo Department (Figure 5) is completely developed, composing 11.1% of the total Uruguayan coast (Table 5). All 16 domains contain developed sub archetypes, spanning the gamut from agriculture, commercial, military, ports and harbors, residential, shore protection works, and urban. The two super domains are differentiated on the basis of whether the coastal belt is dominated by littoral cells or rock sub archetypes where the Playa Verde Super Domain is characterized by a Beach-Upland-Developed cross-shore catenary sequence, whereas the Montevideo Super Domain features a Rock-Upland-Developed codification. Silica beach sub archetypes (Domains 5-1 and 5-2), which compose about 11.9 km of the Montevideo Department coastal belt, contain littoral cells that are backed landward by upland residential and urban sub archetypes that are, respectively, designated as Beach-Dune-Upland-Developed and Beach-Upland-Developed cross-shore catenary sequences. The remaining domains composing the Montevideo Super Domain feature rock sub archetypes, except Domain 5-8, where a Beach-Upland-Developed codification and Domain 5-10 occur that surrounds Montevideo Bay, which is a completely developed harborage with the explanatory cross-shore codification Dvco,ml,ph,sh that embraces commercial, military, port and harbor facilities, and shore protection that work as sub archetypes. Small cliff archetypes that range from about 2–4 m in height occur in Domains 5-12 and 5-14. Although small-pocket beach sub archetypes occur in Domains 5-11 through 5-16, they are usually not called out in the code sequences because rock sub archetypes impart the dominant characteristics of the shore, with exceptions of Domain 5-13 and Domain 5-15 where the beaches are, respectively, about 1 km and about 0.4 km long. Intensive coastal development of the type associated with the main capital area ends in Domain 5-12, whereas Domains 5-13 through 5-16 are characterized by cross-shore catenary sequences that are dominated by ex-urban residential and agricultural sub archetypes.

San Jose Department

The 93.5-km long San Jose Department (Table 6) contains four super domains viz. Playa Pascual (12 km: Du-U-Dv-W), Punta del Tigre (8.5 km: Be-Du-W-U-Dv), Libertad (12.4 km: Be-Du-Cl-U-Dv), and Ordeig (60.6 km: Ba-Be-Du-U-Dv) (Figure 6). This coastal belt, which occupies about 14% of the total Uruguayan coastal belt, is completely different from the preceding Montevideo coastal zone in that the developed sub archetypes are largely restricted to agriculture with scattered small residential developments. Beaches characterize the Playa Pascal, Punta del Tigre, and Libertad super domains, whereas the Ordeig Super Domain is characterized by coastal barriers (barrier islands and mainland barriers) (Domains 6-4, 6-5, and 6-5), beaches, and dunes. Undeveloped wetland forest and/or marsh sub archetypes occur in Domains 6-1 and 6-5. Low cliffs up to 5 m in height occur to the east of Ordeig in Domain 6-3 occupying about 12 km of shore.

Colonia Department

The 157-km long Colonia Department (Figure 7) contains two long super domains, Rosario and Conchillas, which are, respectively, 68- and 89-km long (Table 7). Facing the Rio de la Plata embayment, the turbid nearshore waters are backed by beach sub archetypes (Domains 7-1, 7-3, 7-4, and 7-5), beach ridge sub archetypes (Domain 7-7), waterfront developed zones (Domains 7-2 and 7-6), and forested wetland sub archetypes (Domain 7-8). Upland agriculture and residential developed sub archetypes (Dvag and Dvag,re) variously occur inland in all eight domains. The Colonia Department coastal belt, which composes about 23.5% of the total Uruguayan coast, is largely undeveloped from a residential point of view except for small urban clusters at Juan Lacaze, Col Del Sacramento, Carmelo, and port development at Conchillas. The remaining development takes the form of sparse settlements on agricultural land. Some coastal forested wetlands occur, for example, in Domains 7-3, 7-5, 7-6, 7-7, and 7-8, but they normally extend only somewhat less than 0.5 km inland. Forested wetland sub archetypes facing the estuary per se, which lies landward of the Rio de la Plata embayment, are not preceded seaward by beach, beach ridge, or developed sub archetypes. These eco-geomorphological features are more spatially contiguous with distance up the estuary.

The natural Uruguayan coastal belt shows great variation that ranges from rocky shores and promontories to extensive littoral compartments with headland bay beach eco-geomorphological formations. Interruptions of the natural scenic and undeveloped coastalscapes occur in association with urbanization in the broadest context of the term. Morphometric data is assembled by Uruguayan Departments in Tables 2 through 7 that in turn correspond to figures with the same numerical identifier in Figures 2 through 7. Spatial distributions and frequency of occurrence of cross-shore catenary sequences and general coastal morphology in relation to hard (rock) and soft (sedimentary) domains are discussed in terms of domains and super domains in the various Departments.

Anchor Points (Divergence Zones) and Littoral Cells

The morphology of the Uruguayan coastal belts can be partly comprehended by reference to broad scale geological features and lithology. Coastal morphometrics that are incorporated into cross-shore eco-geomorphological sequences can be largely explained according to the types of geological features that occur along the shore. Littoral cells occur all along the shore but are interspersed by rock outcrops of various sorts that have different surficial expression partly depending on their lithological compositions. The most extensive and continuous zones of Phanerozoic cover (mostly Cenozoic in age) occur along the NE and SW coastal belts viz. Rocha, Maldonado, San Jose, and Colonia departments. Canelones and Montevideo departments tend to exhibit longer stretches of rock outcrop along the shore. Maps from the following researchers were used to identify types of rock outcrops in the various departments of the Uruguayan coast (Masquelin et al., 2011; Oyhantçaba; Siegesmund, and Wemmer, 2010; Sánchez Bettucci, Peel, and Oyhantçabal, 2010). Where practical, specific types of lithologies are identified with domains in the following analysis that generally associates rock types with coastal morphological expression.

Geological Control of Coastal Belt Morphology

Although littoral cells are predominantly sedimentary, these coastal belts are frequently punctuated by rocky headlands and low-elevation promontories. A swarm of rocky headlands, for example, occurs in the Rocha Department in Domain 2-5 where outcrops of the Alguá/Pelotas Batholith separate headland bay beach sub archetypes, which are denoted in Figure 2 by orange arrows pointing seaward from the coast. Lithologically and morphologically similar outcrops occur in Domains 2-8 and 2-13. A larger rocky headland occurs in Domain 2-10 where the Rocha Formation, the Eastern Schist Belt (Masquelin et al., 2011), forms what is here referred to as the La Palma Divergence Zone. In the Maldonado Department coastal belt, the Cerro Olivo Complex granulite outcrops as a rocky headland sub archetype in Domain 3-9 (Figure 3), but westward coastal segments (Domains 3-10 to 3-14) are characterized by mixtures of rock outcrops that are characterized by granites, gneisses, and low-grade schists that sometimes contribute to the formation of gravel beaches (Isla and Espinosa, 2021). Domains 5-3 to 5-16 in the Montevideo Department (Figure 5) contain sporadic outcrops of volcano-sedimentary rocks that form headlands that separate cove and headland bay beaches outside of the harbor and where shore protection structures are not present. Coastal rock outcrops are minimal in the San Jose Department, which presents a mostly sedimentary coastal belt with few rocky headlands. The Colonia Department is similar, but minor outcrops of the Carap Granitic Complex and Campanero orthogneisses occur. Because these rock outcrops are minor and discontinuous, they are not listed in the cross-shore codifications. The predominant features of the Colonia coastal belt are associated with Cenozoic sediments that have moved alongshore as Holocene formerly riverine materials that today form beach sub archetypes.

Characterization of Coastal Belts

The coastal landscapes of the Rocha Department (Figure 2, Table 2) are diminutive continuations of contiguous beach-dune couplets, lagoon, and wetland archetypes in SE Brazil, as seen, for example, in the regions of Lagoa Mangueira, Lagoa Mirim, and Lagoa dos Patos in the State of Rio Grande do Sul. Microtidal (tidal range < 0.5 m) oceanic sandy beaches (e.g., Ortega et al., 2013) characterize most of the Rocha Super Domain and are typified by discussion of those, for example, in Domain 2-1, which lies about 3 km south of the border with Brazil, and Domain 2-9, which lies a couple kilometers NE of the La Paloma Divergence Zone. The Departments of Maldonado (Figure 3, Table 3) and Canelones (Figure 4, Table 4) present similar cross-shore catenary sequences where beach and rock archetypes are the predominate initial digital codifications of the codes. These first two or three digits in the cross-shore domanial codifications thus represent the character of the seaward margins of the coastal belts. Rock archetypes are absent from cross-shore catenary sequences in the departments of San Jose (Figure 6, Table 6) and Colonia (Figure 7, Table 7), where riverine and estuarine sediments (e.g., Alonso, Solari, and Teixeira, 2018) have accumulated alongshore of the Rio de la Plata Embayment where wave energy (e.g., Solari, Alonso, and Teixeira, 2018) is less than that of other coastal belts in departments that face the open Southern Atlantic Ocean, i.e. Rocha, Maldonado, and Canelones. Exceptions to these general observations concerning the overall characterization of Uruguayan coastal belts are associated with intense urbanization, as evidenced by the town of Maldonado (capital of the Maldonado Department) and the city of Montevideo (capital of Uruguay). Both of these urbanizations are associated with rocky headland and upland archetypes that permit development in an environment that is otherwise classified among various wetland sub archetypes.

Anthropogenic Archetypes and Sub Archetypes

The city of Montevideo, which composes nearly the whole coastal belt in the Montevideo Department (Figure 5, Table 5) as intensive urbanization (Domains 5-3 through 5-16, Montevideo Super Domain) or ex-urban residential development (Domains 5-1 and 5-2, Playa Verde Super Domain), accounts for 11.1% of the whole Uruguayan coastal belt (Figure 5, Table 5). Pocket and headland bay beaches, with or without back-beach dunes, occur in all domains except 5-7 through 5-10, where hardened shores with seawalls, revetments, and other shore protection structures prevent sediment accumulation. Harbor infrastructure around Montevideo Bay in Domain 5-10, which has an alongshore length of about 16.5 km, is mostly comprised by docks, seawalls, quays, piers, berths, and wharfs. The harbor is protected by jetties and breakwaters. Domain 5-10, which retains the Dvco,ml,ph,sh sub archetype codification, is the only developed archetype that is not conjoined with other archetypes or sub archetypes. Rock sub archetypes and undifferentiated upland archetypes are a signature of the Montevideo Super Domain because they occur in Domains 5-3 through 5-16, except being mostly excluded from Domain 5-10. Urban and residential sub archetypes to the east of Domain 5-10 are included in Domains 5-1 through 5-9 and are generally not present west of the harbor in Domains 5-13 to 5-16 that more closely reflect ex-urban and agricultural sub archetypes. The rocky-developed upland sub archetypes of the Montevideo Department thus stand in contrast to other departments along the Uruguayan coast.

Developed sub archetypes in the San Jose Department are mostly associated with agriculture with minor residential buildups as in Domains 6-1 and 6-6. The 60.6 km of barrier beaches compose about 65% of the coastal belt in the Ordeig Super Domain (Table 6). Mainland beaches in the Playa Pascul, Punta del Tigre, and Libertad super domains account for about 33.4 km, or 35%, of the Department. Undifferentiated dune archetypes are associated with all beaches, whereas mostly undeveloped marshy wetland sub archetypes are dominantly associated with Domains 6-1 and 6-2. All concatenations in the San Jose Department include agricultural (93.5 km) or residential (19.6 km) sub archetypes, clearly identifying this coastal belt as predominantly agrarian. The sedimentary cliffs in Domain 6-3 rise about 2–3 m above the beach berm, and, although low, they make a distinctive feature of the Libertad Super Domain.

Cross-shore catenary sequences on the Colonia Department are diverse because this coastal belt transitions from the open ocean to an embayment formed by the Rio de la Plata. Between the Rosario and Conchillas super domains, beach sub archetypes compose 57.8 km, whereas beach ridge strand plains compose 15 km (Table 7). Fluvial beaches occur in the vicinity of Carmelo, as described by Alonso, Solari, and Teixeira (2018) for beaches 50 km upstream near La Condordia. Here, the Río de la Plata has an average discharge of 5000 m3s–1, with peak discharges that can exceed 30,000 m3s–1 (Jaime and Menéndez, 2002), bringing fluvial sediments to the shores of the Colonia Department. Occupying about a quarter of the total Uruguayan coastal belt, the Colonia Department cross-shore codifications signal a distinctive type of coastal belt compared with the rest of the coast.

In this kind of effort, pros and cons that are associated with various procedures and methodologies always occur. The Uruguayan coastal belt was investigated with the express purpose of testing the possibility of incorporating into the BCCS (Biophysical Coastal Classification System) a new range of codifications that are associated with anthropogenic development. Prior developments and advances of the BCCS (Finkl and Makowski, 2020a,b,c,d; 2021a,b) eschewed developed coastal belts because the initial efforts focused on natural features. Investigation of natural coastal areas provided a basis for developing comprehension of cross-shore catenary sequences, but it soon became obvious that most coastal belts are conflicted by human action to the point where natural features become completely obliterated by anthropogenic development. Because the Uruguayan coastal belt provided a meld of natural vs. developed coastalscapes, with most of the coastal zone being urbanized (developed sub archetypes occur in all departments except Rocha), it provided a basis for testing and evaluating the possibility of including developed sub archetypes in the BCCS.

Interpretation of Coastal Belts in Satellite Imagery

A word of caution is worth mentioning because in this case the cross-shore coastal classification applied in the BCCS requires a minimum skill set that is oriented to cognitive recognition of natural and anthropomorphic features. A moderate level of interpretive skills is required to fully comprehend the complexities of satellite imagery that is obtained from Google Earth Pro. The good quality of the imagery combined with zoom capabilities greatly facilitates interpretive functions that are required for the formulation of codifications that compose cross-shore catenary sequences. Researchers are thus required, at a minimum, to be able to identify the kinds of archetypes and sub archetypes listed in Table 1. Automated computerized classifications, although useful under certain circumstances (see, e.g., Brock and Purkis [2009]; Finkl and Makowski [2014]; Hagenaars et al. [2017]; Luijendijk et al., [2018]), are not applicable to the BCCS methodology because cognitive mapping is the key component of cross-shore classification procedure.

It is suggested here that use of the Google Earth Pro platform is generally sufficient for most procedures that are required for image interpretation. Tools provided in the platform assist in providing geolocation data directly from the satellite images as well as providing access to place names and other features contained in Google Maps and Google Earth online. Mensuration on the satellite images using the Ruler tool is useful for determining elevation and distance. Using the Google Ruler tool, it was possible to ascertain a total length of 666 km, which was within 2 km of the official estimate of coastline length (668 km) published by the Uruguayan government. The zoom function was used to measure approximate straight-line distances along the shore. The close association between the shoreline lengths may be fortuitous because a true digitizing function is not available with this platform. In any case, determination of coastline length can always be problematic because it is scale dependent due to its fractal nature, as described by Mandelbrot (1967). The main point is that the Google Earth Pro platform provides reasonable accuracy for vertical and horizontal distances and that these values can be accessed with ease to advantage.

Categories of Developed Coastal Belts

One of the main purposes of this experiment was to discover whether it is possible to incorporate the BCCS cross-shore codifications that broadly reflect the nature of coastal belts that contain or are dominated by anthropological development. Coastal development is a broad term that incorporates a multitude of possibilities that occur in cross-shore catenary sequences, sometimes in association with natural eco-geomorphological features and sometimes within cityscapes that are completely devoid of natural features. The terms used in this classification test of the Uruguayan coastal belt, in specific reference to developmental sub archetypes, were applied in a very subjective manner based on interpretation of satellite imagery and some collateral data. All of the developed sub archetypes can be further subdivided, but for illustrative purposes they generally showed that it is possible to identify anthropological features that can be incorporated into the BCCS. That being said, it should be noted that subjective interpretation of terms such as “urban” and “residential” were just used to indicate the density or compactness of residential areas that also incorporated some degree of industrial or commercial development. “Residential” was mostly used to indicate comparatively low-density suburban and ex-urban development that on the margins of cities and towns gradually merged with the agriculture sub archetype where residences and outbuildings occurred on farms. Other sub archetypes such as commercial, military, ports and harbors, and shore protection works were most prevalent in the Montevideo Department where they occupied about 74 km of the coastal belt (Table 5) and were easily interpreted from the satellite imagery (Figure 5). Many examples of applications of land use classifications occur (e.g., Ai et al., 2020; O'Hara, 2003; Szuster, Qi, and Borger, 2011), the categories of which could be conjoined with the BCCS should that be desirable along intensely developed coastal belts, but the BCCS is not designed for auto classification. In the example of the Uruguayan coastal belt, the incorporation of developed sub archetypes was a feasibility test that showed potential for inclusion in the BCCS, as illustrated in Table 1.

Examination of the Uruguayan coastal belt identified developed and undeveloped coastal segments that provided opportunity to consider the possibility of incorporating developed sub archetypes in the BCCS (Biophysical Cross-shore Classification System) (Finkl and Makowski, 2020a,b,c). The inclusion of subjective terms such as residential, commercial, industrial, ports and harbors, and urban showed that BCCS archetype codifications could be expanded to include a new archetype designation for Developed (i.e., Anthropogenically-influenced Development) that was divided into several distinct sub archetypes. Application of cross-shore catenary sequences that include development codifications (sub archetype categories) expand the BCCS into a more comprehensive specialized coastal classification system that addresses natural and developed coastalscapes. Because so many of the world's coastal belts are developed to various degrees, it seems apropos to provide a two-pronged approach for designation of cross-shore catenary sequences that can now accommodate natural eco-geomorphological units along with artificial environments. The coast of Uruguay is in many ways characteristic of seashores around the world where human activity supersedes the natural environment. Modification of the BCCS to include anthropogenic development brings to the forefront its more catholic approach to the cross-shore classification of coastal belts.

Ai,
J.;
Zhang,
C.;
Chen,
L.,
and
Li,
D.,
2020
.
Mapping annual land use and land cover changes in the Yangtze estuary region using an object-based classification framework and Landsat time series data.
Sustainability
,
12
(
2
),
659
.
doi:10.3390/su12020659
Alonso,
R.;
López,
G.;
Mosquera,
R.;
Solari,
S.,
and
Teixeira,
L.,
2014
.
Coastal erosion in Balneario Solís, Uruguay.
Journal of Coastal Research, Special Issue No. 71
, pp.
48
54
.
Alonso,
R.;
Solari,
S.,
and
Teixeira,
L.,
2018
.
Erosion problem on a fluvial beach. The case study of “La Concordia” in the Uruguay River, Uruguay, South America.
Journal of Coastal Research, Special Issue No. 85
, pp.
131
135
.
Baigun,
C.;
Colautti,
D.C.,
and
Maiztegui,
T.,
2018
.
Río de la Plata (La Plata River) and Estuary (Argentina and Uruguay).
In
:
Finlayson,
C.M.;
Everard,
M.;
Irvine,
K.;
McInnes,
R.J.;
Middleton,
B.A.;
van Dam,
A.A.,
and
Davidson,
N.C.
(eds.),
The Wetland Book.
Dordrecht
,
Springer
: pp.
847
855
.
doi:10.1007/978-94-007-4001-3_243
Bailey,
R.G.,
1998
.
Ecoregions: The Ecosystem Geography of the Oceans and Continents.
New York
:
Springer
,
176
p.
Brock,
J.C.
and
Purkis,
S.J.,
12009
.
The emerging role of Lidar remote sensing in coastal research and resource management.
Journal of Coastal Research, Special Issue No. 53
, pp.
1
5
.
Dinerstein,
E.;
Olson,
D.;
Joshi,
A.;
Vynne,
C.;
Burgess,
N.D.;
Wikramanayake,
E.;
Hahn,
N.;
Palminteri,
S.;
Hedao,
P.;
Noss,
R.;
Hansen,
M.;
Locke,
H.;
Ellis,
E.C.;
Jones,
B.;
Barber,
C.V.;
Hayes,
R.;
Kormos,
C.;
Martin,
V.;
Crist,
E.;
Sechrest,
W.;
Price,
L.;
Baillie,
J.E.M.;
Weeden,
D.;
Suckling,
K.;
Davis,
C.;
Sizer,
N.;
Moore,
R.;
Thau,
D.;
Birch,
T.;
Potapov,
P.;
Turubanova,
S.;
Tyukavina,
A.;
de Souza,
N.;
Pintea,
L.;
Brito,
J.C.;
Llewellyn,
O.A.;
Miller,
A.G.;
Patzelt,
A.;
Ghazanfar,
S.A.;
Timberlake,
J.;
Klöser,
H.;
Shennan-Farpón,
Y.;
Kindt,
R.;
Barnekow Lilles,
J.-P.;
van Breugel,
P.;
Graudal,
L.;
Voge,
M.;
Al-Shammari,
K.F.,
and
Saleem,
M.,
2017
.
An ecoregion-based approach to protecting half the terrestrial realm.
BioScience
,
67
(
6
),
534
545
.
Finkl,
C.W.,
2004
.
Coastal classification: Systematic approaches to consider in the development of a comprehensive scheme.
Journal of Coastal Research
,
20
(
1
),
166
213
.
Finkl,
C.W.
and
Makowski,
C.
(eds.),
2014
.
Remote Sensing and Modeling: Advances in Coastal and Marine Resources.
Volume
9
,
Coastal Research Library
.
Cham: Switzerland
,
502
p.
Finkl,
C.W.
and
Makowski,
C.,
2019a
.
Coastal seafloor geomorphological features, classification.
In
:
Finkl,
C.W.
and
Makowski,
C.
(eds.),
Encyclopedia of Coastal Science.
Cham, Switzerland
:
Springer Nature, Encyclopedia of Earth Sciences Series
, pp.
540
549
.
Finkl,
C.W.
and
Makowski,
C.,
2019b
.
Nearshore geomorphological mapping.
In
:
Finkl,
C.W.
and
Makowski,
C.
(eds.),
Encyclopedia of Coastal Science.
Cham, Switzerland
:
Springer Nature, Encyclopedia of Earth Sciences Series
, pp.
1243
1265
.
Finkl,
C.W.
and
Makowski,
C.,
2020a
.
The Biophysical Cross-shore Classification System (BCCS): Defining coastal ecological sequences with catena codification to classify cross-shore successions based on interpretation of satellite imagery.
Journal of Coastal Research
,
36
(
1
),
1
29
.
Finkl,
C.W.
and
Makowski,
C.,
2020b
.
Latitudinal and situational zonation of shore-normal catenary sequences observed from satellite images using the biophysical cross-shore classification system (BCCS).
Journal of Coastal Research
,
36
(
2
),
1
14
.
Finkl,
C.W.
and
Makowski,
C.,
2020c
.
Lateral extrapolation of coastal catenary sequences using the Biophysical Cross-shore Classification System (BCCS) to create shore-parallel situational zonation mapping units.
Journal of Coastal Research
,
36
(
3
),
457
471
.
Finkl,
C.W.
and
Makowski,
C.,
2020d
.
Coastal Belt Linked Classification (CBLC): A system for characterizing the interface between land and sea based on large marine ecosystems, coastal ecological sequences, and terrestrial ecoregions.
Journal of Coastal Research
,
36
(
4
),
677
693
.
Finkl,
C.W.
and
Makowski,
C.,
2021a
.
Alongshore classification and super domain delineation of coastal belts based on interpretation of biophysical catenary sequences observed from satellite images.
Journal of Coastal Research
,
37
(
1
),
1
25
.
Finkl,
C.W.
and
Makowski,
C.,
2021b
.
Alongshore classification and morphometric analysis of coastal belts: The state of Oregon, USA.
Journal of Coastal Research
,
37
(
2
),
238
271
.
Finkl,
C.W.;
Makowski,
C.,
and
Vollmer,
H.,
2014
.
Advanced techniques for mapping biophysical environments on carbonate banks using Laser Airborne Depth Sounding (LADS) and IKONOS satellite imagery.
In
:
Finkl,
C.W.
and
Makowski,
C.
(eds.),
Remote Sensing and Modeling: Advances in Coastal and Marine Resources. Coastal Research Library (CRL)
, Volume
9
,
Dordrecht, The Netherlands
:
Springer
, pp.
31
63
.
Hagenaars,
G.;
de Vries,
S.;
Luijendijk,
A.P.;
de Boer,
W.P.,
and
Reniers,
A.J.H.M.,
2017
.
On the accuracy of automated shoreline detection derived from satellite imagery: A case study of the Sand Motor mega-scale nourishment.
Coastal Engineering
,
133
,
113
125
.
Intergovernmental Oceanographic Commission, United Nations Educational, Scientific and Cultural Organization (IOC-UNESCO),
2011
.
Methodology for the GEF Transboundary Waters Assessment Programme.
In:
United Nations Environment Programme (UNEP) and IOC-UNESCO Staff
(eds.),
Methodology for the Assessment of Large Marine Ecosystems
, Volume
5
.
Nairobi, Kenya
:
UNEP
,
115
p.
Isla,
F.I.
and
Espinosa,
M.,
2021
.
The gravels of the Rio de la Plata: The Holocene beaches of Bella Vista, Uruguay.
Journal of Coastal Research
,
37
(
5
),
987
992
.
Jaime,
P.R.
and
Menéndez,
A.N.,
2002
.
Análisis del régimen hidrológico de los ríos Paraná y Uruguay.
Instituto Nacional del Agua
,
Argentina
.
LHA-01-216-02 (in Spanish).
Kelletat,
D.H.;
Scheffers,
A.M.,
and
May,
S.M.,
2013
.
Coastal environments from polar regions to the tropics: A geographer's zonality perspective.
Geological Society (London), Special Publications
,
388
,
33
57
.
Klemas,
V.C.,
2014
.
Remote sensing of coastal ecosystems and environments.
In
:
Finkl,
C.W.
and
Makowski,
C.
(eds.),
Remote Sensing and Modeling
, Volume
9
.
Cham, Switzerland
:
Coastal Research Library
, pp.
3
30
.
Kottek,
M.;
Grieser,
J.;
Beck,
C.;
Rudolf,
B.,
and
Rubel,
F.,
2006
.
World map of the Köppen-Geiger climate classification updated.
Meteorologische Zeitschrift
,
15
(
3
),
259
263
.
Luijendijk,
A.;
Hagenaars,
G.;
Ranasinghe,
R.;
Baart,
F.;
Donchyts,
G.,
and
Aarninkhof,
S.,
2018
.
The state of the world's beaches.
Scientific Reports
,
8
,
6641
.
doi:10.1038/s41598-018-24630-6
Makowski,
C.,
2014
.
Development and Application of a New Comprehensive Image-Based Classification Scheme for Coastal and Benthic Environments along the Southeast Florida Continental Shelf.
Boca Raton, Florida
:
Ph.D. dissertation
,
303
p.
Makowski,
C.
and
Finkl,
C.W.,
2016
.
History of modern seafloor mapping.
In
:
Finkl,
C.W.
and
Makowski,
C.
(eds.),
Seafloor Mapping along Continental Shelves: Research and Techniques for Visualizing Benthic Environments.
Coastal Research Library
, Volume
13
,
Dordrecht, The Netherlands
:
Springer International Publishing
, pp.
1
47
.
Makowski,
C.;
Finkl,
C.W.,
and
Vollmer,
H.M.,
2015
.
Geospatially Integrated Seafloor Classification Scheme (G-ISCS): A new method for cognitively interpreting benthic biogeomorphological features.
Journal of Coastal Research
,
31
(
2
),
488
504
.
Makowski,
C.;
Finkl,
C.W.,
and
Vollmer,
H.M.,
2016
.
Classification of continental shelves in terms of geospatially integrated physio-graphic realms and morphodynamic zones.
Journal of Coastal Research
,
32
(
1
),
1
34
.
Makowski,
C.;
Finkl,
C.W.,
and
Vollmer,
H.M.,
2017
.
Geoform and landform classification of continental shelves using geospatially integrated IKONOS satellite imagery.
Journal of Coastal Research
,
33
(
1
),
1
22
.
Mandelbrot,
B.,
1967
.
How long is the coast of Britain? Statistical self-similarity and fractional dimension.
Science
,
156
(
3775
),
636
638
.
doi:10.1126/science.156.3775.636.
Masquelin,
H.;
D'Avila Fernandes,
L.A.;
Lenz,
C.;
Porcher,
C.C.,
and
McNaughton,
N.J.,
2011
.
The Cerro Olivo Complex: A pre-collisional Neoproterozoic magmatic arc in Eastern Uruguay.
International Geology Review.
doi:10.1080/00206814.2011.626597
Mianzan,
H.;
Lasta,
C.;
Acha,
E.;
Guerrero,
R.;
Macchi,
G.,
and
Bremec,
C.,
2001
.
The Río de la Plata Estuary, Argentina-Uruguay.
In
:
Seeliger,
U.
and
Kjerfve,
B.
(eds.),
Coastal Marine Ecosystems of Latin America.
Berlin
,
Springer: Ecological Studies (Analysis and Synthesis)
, Volume
144
, pp.
185
204
.
doi:10.1007/978-3-662-04482-7_14
O'Hara,
C.G.;
King,
J.S.;
Cartwright,
J.H.,
and
King,
R.L.,
2003
,
Multitemporal land use and land cover classification of urbanized areas within sensitive coastal environments.
IEEE Transactions on Geoscience and Remote Sensing
,
41
(
9
),
2005
2014
.
doi:10.1109/TGRS.2003.816573
Ortega,
L.;
Celentano,
E.;
Finkl,
C.,
and
Defeo,
O.,
2013
.
Effects of climate variability on the morphodynamics of Uruguayan sandy beaches.
Journal of Coastal Research
,
29
(
4
),
747
755
.
Oyhantçaba,
P.;
Siegesmund,
S.,
and
Wemmer,
K.,
2010
.
The Rio de la Plata Craton: A review of units, boundaries, ages and isotopic signature.
International Journal of Earth Sciences (Geologische Rundschau)
,
100
,
201
220
.
doi:10.1007/s00531-010-0580-8
Peel,
M.C.;
Finlayson,
B.L.,
and
McMahon,
T.A.,
2007
.
Updated world map of the Köppen-Geiger climate classification.
Hydrology and Earth System Science
,
4
(
2
),
1633
1644
.
Rasid,
H.
and
Pramanik,
M.A.K.,
1990
.
Visual interpretation of satellite imagery for monitoring floods in Bangladesh.
Environmental Management
,
14
(
6
),
815
821
.
Sánchez Bettucci,
L.;
Peel,
E.,
and
Oyhantçabal,
P.,
2010
.
Precambrian geotectonic units of the Río de La Plata craton.
International Geology Review
,
52
(
1
),
32
50
.
Schowengerdt,
R.A.,
1983
.
Techniques for Image Processing and Classification in Remote Sensing.
New York
:
Academic
,
248
p.
Sherman,
K.
and
Hempel,
G.
(eds.),
2008
.
The UNEP Large Marine Ecosystem Report: A Perspective on Changing Conditions in LMEs of the World's Regional Seas
.
UNEP Regional Seas Report and Studies 182.
Nairobi, Kenya
:
United Nations Environment Programme
,
872
p.
Solari,
S.;
Alonso,
R.,
and
Teixeira,
L.,
2018
.
Analysis of coastal vulnerability along the Uruguayan coasts.
Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85
, pp.
1536
1540
.
Szuster,
B.W.;
Chen,
Qi.,
and
Borger,
M.,
2011
.
A comparison of classification techniques to support land cover and land use analysis in tropical coastal zones.
Applied Geography
,
31
(
2
),
525
532
.
Wang,
M.;
Ahmadia,
G.N.;
Chollett,
I.;
Huang,
C.;
Fox,
H.;
Wijonarno,
A.,
and
Madden,
M.,
2015
.
Delineating biophysical environments of the Sunda Banda Seascape, Indonesia.
International Journal of Environmental Research and Public Health
,
12
(
2
),
1069
1082
.
doi:10.3390/ijerph120201069
Worldometers,
2021
.
Uruguay population.
worldometers.info/world-population/uruguay-population/