A GIS-Based Approach for Use Recommendations and Limitations in Sustainable Coastal Planning in the Southeastern Margin of the Ría de Arosa (Pontevedra, Spain)

Abstract

The southeastern margin of the Ría de Arosa is a region of great ecological and social importance, characterized by increasing urban development, tourism pressures, and vulnerability to natural hazards, soil erosion, coastal flooding, and mass movements, where sustainable territorial planning poses significant challenges. This study combines Geographic Information Systems tools and quantitative and qualitative overlay techniques to integrate conservation quality and comprehensive risk maps. The main challenge addressed in this research is the integration of geospatial data and diverse natural risk factors. The result was a map of land use recommendations and limitations, and another of degree of land use limitation, which identify priority areas for conservation and zones suitable for the controlled development of recreational, agricultural, and industrial activities. The methodology employed allows for detailed modelling that is easily updated and applicable to other environments for territorial planning and natural resource conservation. Areas of special natural importance, such as Arosa Island and the El Grove Peninsula, stand out as optimal locations for sustainable recreational activities, while the northeastern coastal corridor, between Villanueva de Arosa and Cambados, shows suitability for anthropogenic development. This approach contributes to a balance between socioeconomic development and environmental protection, facilitating the implementation of sustainable planning and conservation strategies in highly fragile coastal areas.

1. Introduction

The natural and strategic characteristics, from an economic development perspective, make coastal areas places with high potential for the development of human activities [1,2,3]. They represent areas with significant natural interest, hosting unique ecosystems with high and rich biodiversity [2,4]. Additionally, the characteristics of their landscapes, represented by the interaction of abiotic elements (beaches, dunes, cliffs, and marshes) and biotic elements (flora and fauna), enhance the need for conservation and a sustainable use of the coastal environment together with the economic use of ecosystem services [5,6].

Historically, and increasingly over the past few decades, coastal areas have housed large population centres of high socioeconomic importance. The location and logistic, industrial, and productive opportunities (agriculture and fishing), along with the increase in tourism, concentrate nearly 11% of the world’s population in coastal areas (around 896 million people), according to 2020 data [7]. This upward trend in terms of population and economic activity development, which in many cases requires the development of infrastructure (buildings, factories, and communication routes), generates negative impacts related to the degradation of coastal ecosystems [8,9].

The current global dynamics show an increase in the likelihood of extreme weather events [2,5]. Coastal areas are therefore particularly sensitive to natural hazards such as storms, rising sea levels, or mass movements, all of which are becoming more severe [2,5,10]. This increase in coastal vulnerability to growing hazards related to global change results in a deterioration of the environment’s adaptive capacity [11,12,13]. Consequently, it exacerbates the economic impacts on agricultural (food security), energy, tourism, and urban activities, as well as on people or the natural environment [11,12,13,14,15]. Recognizing the external processes responsible for triggering natural hazards becomes a practice of special necessity and importance to reduce or mitigate the impact of these events, whether fully or partially [16,17,18]. The southeast margin of the Ría de Arosa represents an environment of high ecological importance, characterized by protected natural spaces (PNS) of the Umia-Grove Intertidal Complex, the Ons-Grove Complex, a set of geological interest sites (geosites), and extensive areas of high landscape quality [19,20]. Natural hazards, particularly coastal flooding, mass movements (e.g., landslides and rockfalls), or soil loss, are particularly relevant issues in this area due to its geographic configuration and the high population density recorded. In line with this fact, the degradation of its ecosystems, particularly wetlands, can directly affect the regenerative capacity of the coast and its resilience against extreme natural events or anthropogenic activities [11,12,13]. Consequently, it may jeopardize not only biodiversity but also the ecosystem services important to the local population.

The rapid advancement of digital tools in recent decades, especially Geographic Information Systems (GIS), has made these technologies essential for land-use planning and decision-making processes. GIS enables the rapid and cost-effective management of large volumes of geospatial information, allowing for its organization, visualization, querying, integration, and analysis [21]. This ability to model and visualize scenarios for territorial planning enhances the transparency and reproducibility of the resulting outputs [22].

Multi-Criteria Decision Analysis (MCDA) is a decision-support tool applicable to various contexts and particularly useful in spatial planning [23]. It provides a systematic approach for integrating multiple spatial data layers, each representing different suitability criteria, to produce a composite map indicating the degree of suitability of each evaluated parcel [23]. MCDA is especially effective in helping decision-makers analyze complex problems in a more visual, simple, and comprehensible way [24]. Recent studies addressing multi-risk assessments have successfully applied this and other similar methodologies, such as the Analytic Hierarchy Process (AHP), Equal Weighting Method (EWM), Weighted Overlay Analysis (WOA), and Boolean analysis [20,25,26,27,28,29,30].

This study aims to develop a methodology that, using various MCDA-related techniques, produces land use recommendation and limitation mapping (at 1:50,000 scale and 1 × 1 m pixel resolution). This map integrates areas of high conservation quality and zones of significant natural hazard, which are unsuitable for anthropogenic development. The resulting cartography can be considered a novel, high-resolution, easy-to-understand tool designed to support sustainable territorial planning in the early stages of project development. It serves as a preliminary diagnostic tool that allows for the detailed definition of conservation and management strategies in the study areas [31,32].

Furthermore, this study introduces a land use limitation degree mapping, a novel tool designed to identify parcels with significant restrictions due to environmental, risk-related, or legal factors. Through Boolean analysis, the overlaid information layers from the land use recommendation and limitation mapping are integrated. The resulting areas are classified according to the severity of the constraints (high, medium, or low), providing a solid basis for informed decision-making, sustainable planning, and conservation strategies. Based on the characteristics of each area, appropriate measures will be proposed to guide the development of specific activities, often highlighting the need for Strategic Environmental Assessments (SEA) or Environmental Impact Assessments (EIA) [33,34,35].

Although numerous studies have applied GIS and MCDA-based approaches to land-use planning [36,37,38], this research stands out by integrating conservation quality values and natural hazards, with high spatial resolution and up-to-date data. Therefore, the main objective is to develop an effective, easily replicable methodology for sustainable spatial planning that considers environmental protection and natural risk management, promoting responsible land use aligned with the ecological management priorities of the area.

Study Zone

The Ría de Arosa, located on the northwest coast of the Iberian Peninsula, is one of the largest and most important of the Rías Bajas in Galicia (Figure 1). This estuary is the result of the flooding caused by rising sea levels of ancient river valleys during the Quaternary period. It delineates its northern margin in the province of La Coruña and its southern margin in the province of Pontevedra. The entire study focuses on the southeast margin of the estuary, which encompasses approximately 9600 hectares and a stable population of 57,358 inhabitants, distributed among municipalities such as Cambados, El Grove, Villanueva de Arosa, Arousa, Sangenjo, and Portonovo. In this territory, the population density reaches 598 inhabitants per km², well above the national average (96 inhabitants per km²) (data from the National Institute of Statistics (INE), https://www.ine.es/, accessed on 25 October 2024). These figures do not account for the notable population increase during the summer months due to the tourist influx.

From a climatic perspective, the area is influenced by the moderating effect of the Atlantic Ocean, which favours mild and humid conditions throughout the year. It is classified as type Csb according to the Köppen classification [39]. The average temperature in summer is 19.3 °C, while in winter it drops to 9 °C. Precipitation is abundant, with an annual average of 1455 mm, especially intense during the autumn months when it exceeds 200 mm/month (information prepared by the State Meteorological Agency (AEMET), https://www.aemet.es/es/serviciosclimaticos/datosclimatologicos, accessed on 25 October 2024).

The region is part of the Iberian Massif, specifically the Galicia Trás-os-Montes Zone, belonging to the internal domain of the Variscan orogeny. In this area, Palaeozoic metasediments converge with granite outcrops, notably the Caldas de Reyes batholith [40]. The geomorphology of the area is characterized by a generally smooth relief, with significant granite and metamorphic outcrops forming ridges, summits, and hills [37]. The relief results from continuous modelling through weathering and differential erosion due to the interaction between climatic conditions, geology, and coastal action, leading to extensive peneplains, marine terraces, and residual landforms of varying dimensions, including inselbergs (granite domes), along with rocky outcrops and tors, especially in more evolved areas [41,42,43]. The coastline is shaped by depositional environments where beaches, dune systems, and marshes are found. In La Lanzada, a tombolo has formed, connecting the El Grove Peninsula with the Castrove Peninsula, upon which extensive dune fields develop. The coastal relief, combined with tidal activity and sedimentary dynamics, has favoured the formation of “rasas” or marine terraces. A total of 14 landscape units are defined in this region, all representative of the area based on their geomorphological characteristics and vegetation [20]. Around the study area and along the bay of Umia-Grove, there are two protected areas under the Natura 2000 Network: the Umia-O Grove Intertidal Complex (Special Protection Area for Birds (SPA)) and the Ons-O Grove Complex (Special Area of Conservation). Both safeguard the important wetland and intertidal ecosystems, enhancing the interest related to the local botany and fauna. The soils in the area vary according to the substrate type. Acidic and poorly developed soils, such as Leptosols and Umbrisols, develop over granite outcrops, while similar soils are found in metamorphic areas. In the coastal and marsh areas, Arenosols and Fluvisols predominate, derived from recent Quaternary deposits [44,45].

2. Materials and Methods

The methodology described here aims to develop land use recommendation and limitation mapping, as well as land use limitation degree mapping, for the southeastern margin of the Ría de Arosa (scale 1:50,000) (Coordinate system: Projected coordinates, ETRS89/UTM Zone 29N). To achieve this, comprehensive fieldwork was conducted, structured in various campaigns with specific objectives focused on improving the understanding of the physical environment and the external processes affecting it. This preliminary fieldwork was complemented by a photo-interpretation analysis of orthophotos (both historical aerial photographs from the American flight series (1956–1957), with an estimated spatial resolution between 0.5 and 1 m per pixel, and recent ones from the Spanish National Aerial Orthophotography Plan (PNOA), with a spatial resolution of 25 cm per pixel), along with an analysis of a high-resolution digital elevation model (DEM) (1 × 1 m pixel) produced from LIDAR satellite data. The integration of these sources allowed for a detailed recognition, greater accuracy in synthesis, and improved resolution of the thematic maps of the physical environment factors, which play a key role in this study.

Simultaneously with the field data collection, an exhaustive bibliographic and digital review was carried out, incorporating relevant thematic maps, such as the Spanish Forest Map (MFE) and the Land Occupation Information System of Spain (SIOSE). All this information was integrated into a rigorous and structured geodatabase.

Subsequently, spatial analysis was performed using a Geographic Information System (GIS) (ArcGIS Pro 3.4.2 ©) (Figure 2). This GIS methodology allows for the integration and overlay of the different thematic maps of the study area through spatial analysis techniques. It is based on a multi-criteria decision-making (MCDM) analysis through the combination of multiple layers of information, applying quantitative methods (Weighted Overlay Analysis—WOA) and qualitative methods (Qualitative Overlay Analysis—QOA) depending on the nature of the data.

By combining both cartographies, the land use recommendation and limitation mapping and the land use limitation degree mapping are produced. This methodological approach enables the development of a transparent and replicable process, facilitating its interpretation and application in various contexts. Its objective is to provide a clear and accessible tool for territorial planning, allowing the direct identification of priority areas for public agencies, environmental stakeholders, and the public, even for those without prior knowledge of environmental geology and geological hazard management.

2.1. Conservation Quality Mapping

The high level of knowledge of the inherent factors of the physical environment—abiotic (lithology and geomorphology), biotic (vegetation), landscape, and natural heritage—allows the development of Conservation Quality Mapping (CQM). This process employs a Weighted Overlay Analysis (WOA) method, which assigns a rank to each attribute and a weight to each factor according to its relevance, based on its uniqueness in the territory. This evaluation considers characteristics such as visual perception, naturalness, and heritage rank, which are closely related to the territory’s ability to absorb impacts.

1.

Conservation Quality of Geomorphological Domains: the geomorphological domains map simplifies the most representative morphological elements of the territory, facilitating the interpretation and manipulation of geoinformation [46]. This simplification process of the geomorphological map allows for the generation of polygons that better define the terrain’s relief characteristics. Based on these polygons, a more precise evaluation of this physical parameter can be made (Table 1).

Given the importance of geomorphology in shaping the landscape, this factor is considered one of the most significant when assessing conservation quality. The highest ranks are assigned to areas with greater topographic prominence, corresponding to summits, ridges, and hills where granite landforms such as domes or inselbergs are distinguished (rank 5). Areas with less pronounced topographic contrast receive lower conservation quality ranks. In the study area, the lowest ranks correspond to coastal morphogenetic system features (e.g., beaches, dunes, and marine terraces) (rank 2). Anthropized areas receive the lowest score, as no significant landforms are identified (rank 1).

Table 1. Assessment of Geomorphological Domains for Conservation Quality.

Geomorphological Domains	Weighting
Ridges, hills, inselbergs, and summits	5
Alluvial fans and slopes	4
Glacis and pediments	3
Marine terraces and surfaces	2
Dunes, beaches, marshes, and valley floors	2
Urban centres and anthropic infrastructures	1

Table 1. Assessment of Geomorphological Domains for Conservation Quality.

Geomorphological Domains	Weighting
Ridges, hills, inselbergs, and summits	5
Alluvial fans and slopes	4
Glacis and pediments	3
Marine terraces and surfaces	2
Dunes, beaches, marshes, and valley floors	2
Urban centres and anthropic infrastructures	1

2.

Conservation Quality of Lithological Domains: the geological formations of the territory are evaluated based on their perceptual relevance (e.g., relief and colour) and intrinsic characteristics (e.g., shape and resistance). These formations are scored on a scale from 1 to 4 and assigned a weight of 4 (Table 2), which is lower than the geomorphology factor due to its reduced influence on shaping the relief.

The highest ranks are given to granite lithologies, which are associated with the most representative granite landforms in the study area. Additionally, the chromatic and intrinsic characteristics (e.g., greater resistance to weathering) of early granitoids justify their maximum rank (4). Conversely, poorly consolidated or unconsolidated surface formations closely linked to the coastal morphostructural system receive the lowest rank (1) due to their minimal perception.

Table 2. Assessment of Lithological Domains for Conservation Quality.

Lithological Domains	Weighting
Early granites (enriched in feldspar phenocrysts)	4
Lete granites	3
Metamorphic rocks (slates and shales)	2
Conglomerates, gravel, sand, silt, and mud	1

Table 2. Assessment of Lithological Domains for Conservation Quality.

Lithological Domains	Weighting
Early granites (enriched in feldspar phenocrysts)	4
Lete granites	3
Metamorphic rocks (slates and shales)	2
Conglomerates, gravel, sand, silt, and mud	1

3.

Vegetation Conservation Quality: vegetation is a key factor in environmental conservation (weight 5) and is closely linked to naturalness (landscape visibility), scientific significance, and environmental and socioeconomic importance. In this study, the ecological importance of each vegetation unit is derived from the Spanish Forest Map (1:50,000 scale) (https://www.miteco.gob.es/es/biodiversidad/servicios/banco-datos-naturaleza/informacion-disponible/mfe50.html, accessed on 15 March 2025). This ecological importance is assessed based on two primary aspects: species composition and vegetation structure.

a.

The specific composition of the plant quality factor is studied based on two subfactors: plant grouping and plant diversity. The plant grouping of the plots is classified according to the type of formation: tree, shrub, mixed, or non-vegetated (Table 3). Diversity is assessed based on the greater or lesser number of plant species found in each plot (Table 4).

b.

Vegetation structure measures the plant density of each plot or the number of elements found within it. It is assessed based on the percentage of vegetation cover (FCC) (Table 5). The stratification or vertical structure of a plot is measured based on the visual impact of each plot (Table 6).

To obtain the Vegetation Conservation Quality (VCQ) result, a Weighted Overlay Analysis (WOA) is used for these four subfactors (Equation (1)):

VCQ = Plant grouping + Plant diversity + Vegetation density + Plant stratification

(1)

• The results are reclassified into five groups and scored from 1 to 5 based on their lowest or highest quality (Table 7).

Table 3. Assessment of the Plant Grouping for the Vegetation Quality Factor.

Plant Grouping	Weighting
Tree formations	5
Bush or shrub formations	4
Subshrub formations	3
Grasslands, crops, and fallow	2
Not vegetated	0

Table 3. Assessment of the Plant Grouping for the Vegetation Quality Factor.

Plant Grouping	Weighting
Tree formations	5
Bush or shrub formations	4
Subshrub formations	3
Grasslands, crops, and fallow	2
Not vegetated	0

Table 4. Assessment of plant diversity for the Vegetation Quality Factor.

Plant Diversity	Weighting
3 plant species	4
2 plant species	3
1 plant specie	2
No plant species	0

Table 4. Assessment of plant diversity for the Vegetation Quality Factor.

Plant Diversity	Weighting
3 plant species	4
2 plant species	3
1 plant specie	2
No plant species	0

Table 5. Assessment of plant density for the Vegetation Quality Factor.

% CCF	Weighting
>40	4
<40	2
0	0

Table 5. Assessment of plant density for the Vegetation Quality Factor.

% CCF	Weighting
>40	4
<40	2
0	0

Table 6. Assessment of plant stratification for the Vegetation Quality Factor.

Plant Stratification	Weighting
Woody strata (Tree formations)	4
Shrub strata (Shrub and subshrub formations)	3
Herbaceous strata (Grasslands, crops, and fallow)	2
Not vegetated	0

Table 6. Assessment of plant stratification for the Vegetation Quality Factor.

Plant Stratification	Weighting
Woody strata (Tree formations)	4
Shrub strata (Shrub and subshrub formations)	3
Herbaceous strata (Grasslands, crops, and fallow)	2
Not vegetated	0

Table 7. Assessment of the vegetation factor for Conservation Quality.

Vegetation Factor	Weighting
Very High	5
High	4
Medium	3
Low	2
Very Low	1

Table 7. Assessment of the vegetation factor for Conservation Quality.

Vegetation Factor	Weighting
Very High	5
High	4
Medium	3
Low	2
Very Low	1

4.

The landscape quality map is the result of a Weighted Overlay Analysis (WOA) process, which combines, through weighted summation, the information represented in multiple inherent layers of the biotic and abiotic physical environment (factors) to obtain a concrete result. It is generated from the combination of intrinsic and extrinsic quality maps and then reclassifies the results into five ranges from very low to very high [20] (

Table 8. Assessment of the Landscape Quality factor for Conservation Quality.

Landscape Quality	Weighting
Very High	5
High	4
Medium	3
Low	2
Very Low	1

).

5.

Natural Heritage Conservation Quality: the bioecological heritage of the area is represented by a Special Protection Area for Birds (SPA) (Complexo Intermareal Umia-O Grove) and a Special Area of Conservation (SAC) (Complexo Ons-O Grove), both designated under the Natura 2000 Network. The geological heritage consists of seven geosites [19], which have been evaluated based on their scientific, educational, and touristic attributes [47]. Areas containing geosites are assigned to a rank of 4, as they represent locations of high significance and unique landscape features. Protected natural areas are assigned a rank of 2, as they represent high ecological significance zones. However, in the study area, these correspond to coastal zones with low topographic prominence (Table 9).

The Weighted Overlay Analysis (WOA) of these various factors allows the identification of areas with significant natural relevance that should be recognized as priority zones for protection, geoconservation, monitoring, or rehabilitation (Equation (2)). This last intervention is only considered when active methods are required [48,49,50,51]. The resulting map is reclassified into five classes, ranging from very low to very high conservation quality.

CQM = (5 × Geomorphological domains factor) + (4 × Lithological domains factor) + (5 × Vegetation factor) + (5 × Landscape quality factor) + (4 × Natural heritage factor)

(2)

Table 9. Assessment of the natural heritage factor for conservation quality.

Natural Heritage	Weighting
GeoHeritage (geosites)	4
Biological Heritage (ZEPA and ZEC)	2
Other zones	0

Table 9. Assessment of the natural heritage factor for conservation quality.

Natural Heritage	Weighting
GeoHeritage (geosites)	4
Biological Heritage (ZEPA and ZEC)	2
Other zones	0

2.2. Comprehensive Risk Mapping

The detailed work carried out in the study area concerning the recognition of active processes, as well as the analysis of vulnerability and/or hazards related to a specific natural risk, has separately allowed for the identification of locations with the highest probability of occurrence of these phenomena. The purpose of the comprehensive risk mapping is to combine, through qualitative overlay, all the layers encompassing the different analyzed natural hazards and to display, using patterns and colours, the areas most affected by these risks. This way, it becomes possible to recognize areas with a high potential for socioeconomic losses and, more importantly, for loss of human lives. The mappings that are overlaid here include: coastal flooding risk mapping, real erosion risk mapping, mass movement risk mapping, and finally, natural hazard mapping [52,53,54,55].

2.2.1. Flood Risk Map

The results obtained in the study area are represented through the Flood Hazard Index (FHI) [56]. This analysis considered parameters, such as significant wave height (Fw), sea level change (Fsl), and the extreme tide range (Ftr), to estimate the hazard of flooding in different scenarios [56]. In this case, scenarios with a return period of twenty-five years (‘Xa’) and one hundred years (‘Xb’) are considered, which generate very high and high risk [52].

2.2.2. Real Erosion Risk Map

The real soil erosion map of the SE of the Ría de Arosa was created using the Revised Universal Soil Loss Equation (RUSLE) [57,58]. To calculate the rates of real erosion, values for rainfall erosivity (R-Factor), soil erodibility (K-Factor), slope length and steepness (LS-Factor), ground cover (C-Factor), and conservation practices (P-Factor) were used. Values above 50 t/ha/year (>3.85 mm/year) for soil loss (>high) [54] are extracted and used in comprehensive risk mapping.

2.2.3. Mass Movement Hazard Map

The risk from mass movements was assessed according to the guidelines established by the United Nations Office for Disaster Risk Reduction (UNDRR) [59]. The mass movement hazard map is generated through a combination matrix of the susceptibility map and the triggering values of the processes (rainfall and seismic). Susceptibility is the result of a bivariate statistical process [60,61] that combines inherent terrain elements with historically generated mass movements in the region. This results in a quantitative predictive model of the spatial probability of a region experiencing rock, debris, or soil displacement [62].

The evaluation of the surfaces is closely related to the geological, geomorphological, and land use characteristics of the studied area. For the triggering factors’ data, rainfall data are first taken from the model of the Centre for Studies and Experimentation of Public Works (CEDEX) regarding the impact of climate change on maximum precipitation in Spain (2021–2022) [63]. For seismic triggers, values from the Seismic Hazard Map of Spain (2015) are used, which provide maximum ground acceleration (PGA) data with a return period of 475 years [64].

These values were classified into four hazard categories (low to very high), focusing on the areas with the highest hazard range for this study [53].

2.2.4. Natural Hazard Map

The last map used is the natural hazard map [50]. This map combines lithological, geomorphological, geotechnical, and hydrological criteria. It is based on the prior creation of the geotechnical characterization map, which allows for a relationship between this mapping and the construction capabilities of the area [55]. This map shares similarities with the comprehensive risk mapping, as it sectorial represents the areas where one or more possible external geodynamic processes responsible for generating these potential natural hazards are recognized [55].

2.3. Land Use Recommendations and Limitations Mapping

Finally, both mappings (conservation quality mapping and comprehensive risk mapping), through qualitative overlay, allow for the joint recognition of areas where high conservation priority exist, where one or more possible geological hazards act, and where both combine. Green shades are used to highlight areas of high landscape quality, while different patterns in different colours (black, purple, or red) are applied to indicate geological hazards. This is all done to facilitate the reading of the final mapping.

2.4. Land Use Limitation Degree Mapping

Once the land use recommendations and limitations mapping are completed, the next objective is to determine the degree of territorial limitation based on the overlap of the two layers that comprise it. For this purpose, the land use limitation degree mapping is generated for the southeastern margin of the Ría de Arosa. This process involves a Boolean analysis through data combination geoprocessing based on specific conditions of the study area [21].

The goal of this method is to identify areas with high and very high conservation quality where natural hazards have also been detected. Both layers are reclassified to be treated as categorical layers, allowing the application of Boolean operations [21].

The following combination matrix shows the values assigned to areas that meet the predefined criteria: 1 for areas with high or very high conservation quality, 0 for areas without high or very high conservation quality, 1 for areas with natural hazard presence, and 0 for areas without natural hazard presence (

Table 10. Combination matrix for the analysis of the degree of land use limitation.

Conservation Quality	Natural Hazards Presence	Result (Land Use Limitation Degree)
1 (High and very high quality)	1 (Hazard present)	High limitation (Red zone)
1 (High and very high quality)	0 (No hazard)	Medium limitation (Yellow zone)
0 (No high and very high quality)	1 (Hazard present)	Medium limitation (Yellow zone)
0 (No high and very high quality)	0 (No hazard)	Low limitation (Green zone)

). This layer overlap results in a total of four different scenarios: 1-1, 1-0, 0-1, and 0-0.

The first scenario represents areas where high and very high conservation quality (1) and natural hazard presence (1) are identified. Using the Raster Calculator, the intersection of both layers is performed, and areas where the resulting value is equal to 2 are extracted. These areas are reclassified as high land-use limitation zones.

To identify areas where there is a natural hazard presence (1) but no high or very high conservation quality (0), the Raster Calculator is used to perform the intersection, assigning a “0” value to the conservation quality layer (“quality_file” == 0). Similarly, to obtain areas with high and very high conservation quality (1) but no natural hazard presence (0), the same procedure is applied by assigning a “0” value to the hazard layer (“hazards_file” == 0). These areas represent the medium land-use limitation degree.

Finally, low land-use limitation zones are identified by extracting areas where the intersection of both layers (“quality_file” and “hazards_file”) is equal to 0, indicating that no areas of high and very high conservation quality (0) or natural hazard presence (0) have been detected.

3. Results and Discussion

3.1. Conservation Quality of the SE Margin of the Ría de Arosa

The areas of greatest importance for conservation quality are obtained through the multi-criteria analysis WOA of the thematic quality maps indicated in the methodological section.

3.1.1. Quality of Geomorphological Domains

Based on the geomorphological domains thematic map (Figure 3A), the conservation quality of geomorphological domains map is developed (Figure 3B). High and very high conservation quality ranks of the geomorphological domains are associated with lithostructural relief morphologies (ridges, summits, and hills) and fluvial morphostructural system morphologies (alluvial fans and cones).

The southwestern margin of the Castrove Peninsula holds the highest conservation ranks due to the presence of pronounced residual metamorphic relief, which gradually becomes gentler through the occurrence of adjacent alluvial fan and cone systems. These overlapping alluvial fans are particularly well-represented along the southern edge of the Umia-Grove Bay.

The El Grove Peninsula also exhibits high conservation quality in its interior due to the presence of dome-shaped residual morphologies associated with immature stages of granite landform evolution. These features constitute one of the most characteristic elements of the relief around the Ría. The western margin of the peninsula displays more mature morphologies of the berrocal type.

High-quality zones associated with granite landforms are also found on Arosa Island and in the southeastern margin of the study area (north of Sangenjo).

Low values of this factor are observed in anthropized areas, both near and within urban centres. Similarly, low conservation quality is recorded on the La Lanzada tombolo and coastal sectors featuring beaches, dunes, abrasion platforms, or marine terraces. This is due to their low topographic prominence, especially when compared to the more pronounced morphologies mentioned above.

3.1.2. Quality of Lithological Domains

The lithological characteristics of the territory determine the development of the various morphologies described in the previous section, meaning that the presence of specific rock types directly influences the conservation features of the environment (Figure 4C).

The southeastern area, north of Sangenjo, exhibits the highest level of lithological quality factors, where granite domes associated with early leucocratic granitoids—which exhibit greater resistance to weathering—outcrop (Figure 4D). High lithological quality is also observed where the Caldas de Reyes granodiorite emerges, particularly in the El Grove Peninsula, Arosa Island, and La Toja Island.

In contrast, the presence of metamorphic rocks, which are less representative of the territory and have lower topographic prominence than granitoids, results in low lithological quality along the southwestern margin of the Castrove Peninsula, where metasediments of the Cabo d’Home-La Lanzada Complex are identified.

Finally, low ranks are also assigned to areas covered by poorly consolidated Quaternary surface formations, which exhibit very low topographic prominence.

3.1.3. Quality of Vegetation

The large expanse of vineyards and pastures results in a generally low vegetation quality (Figure 4A,B). High vegetation quality is associated with areas containing various woody species, which generate a visual impact that enhances the natural appearance of the landscape. These areas, dominated by eucalyptus, pine, and oak forests, are located in the core areas of the O Grove and Castrove Peninsulas, closely linked to crystalline rocks and residual lithostructural relief.

3.1.4. Landscape Quality

The landscape quality of the territory is closely related to the intrinsic characteristics described above (Figure 4C). It is generated through the analysis of the intrinsic and extrinsic landscape features of the area [20].

The highest landscape quality levels correspond to the elevated terrains, where residual relief morphologies are found on crystalline lithologies and where dense woody forests are present. High landscape quality is located within the O Grove Peninsula, the Castrove Peninsula, and on Arosa Island.

These zones are ranked low in terms of landscape quality, particularly those corresponding to coastal morphostructural systems around the La Lanzada tombolo, where beaches and dune fields are identified. Coastal margins featuring marshes, such as the mouth of the Umia River, as well as flat areas with marine platforms and terraces, also exhibit low landscape quality. Anthropized areas, where the natural landscape has been significantly altered, are assigned to the lowest level of landscape quality level.

3.1.5. Natural Heritage Quality

The natural heritage quality is derived from the integration and evaluation of bioecological and geological heritage (Figure 4D).

The bioecological heritage in the study area is represented by protected areas declared under the Natura 2000 Network: The Umia-O Grove Intertidal Complex and the Ons-O Grove Complex (Figure 1). The Umia-O Grove Intertidal Complex is designated as a protected wetland and classified as a Special Protection Area for Birds (SPA). It encompasses the entire coastal environment surrounding Umia-O Grove Bay, including significant areas such as the La Lanzada tombolo, La Toja Island, the mouth of the Umia River, and the alluvial fan and cone systems located in the northern part of the Castrove Peninsula. The southern margin of Arosa Island is also included within this wetland territory. The Ons-O Grove Complex, classified as a Special Area of Conservation (SAC), covers almost the same territory as the SPA described above. However, it also includes the western coast of the El Grove Peninsula and the southeastern area of the La Lanzada tombolo, extending to Fagilda Cape. This area is assigned a rank of 2.

Within the study area, seven sites of geological interest (geosites) have been identified. These sites have undergone a thorough assessment of their scientific (Vc), educational (Vd), and tourist (Vt) attributes, and have higher scores than other potential sites of interest (citation). This assessment is performed using various standardized parameters that display a weighting associated with each of the attributes to be scored [47]. Each of these geosites receives the highest score for natural heritage quality, as they represent sites of great importance for understanding the evolution of the coastal environment of the Arosa estuary.

3.1.6. Conservation Quality Mapping of SE Margin of the Ría de Arosa

This cartography aims to highlight areas within the territory where different strategies for their preservation and management are recommended (Figure 5). Within the entire region, certain areas stand out either due to the integration of multiple factors or because a specific factor is particularly prominent (Figure 6A–H).

Arosa Island emerges as a site of high natural, landscape, and heritage importance. This area combines high landscape quality with geological and natural heritage features, especially along the southern margin. It is particularly important to highlight this area as a geological site of interest due to its geodiversity and its high scientific, educational, and touristic significance.

In the El Grove Peninsula, there are many zones with high landscape quality and natural heritage significance. The inselbergs located in the interior of the peninsula, including the Monte de Siradella viewpoint, are classified as geosites due to their representativeness of granite landforms in the area (Figure 6A). Additionally, the topographic prominence of the slopes and the naturalness provided by the dense arboreal vegetation further enhance its landscape quality, making it a priority site for the development of geoconservation policies and activities.

The western sector of the peninsula, although it holds less geological interest, includes extensive areas belonging to the Natura 2000 Network wetlands. Furthermore, high landscape quality is observed, possibly influenced by the prominent granite domes and berrocal formations found in the area (Figure 6B). Compared to the interior zone, the urgency for geoconservation policies is lower due to the legal protection provided by the Natura 2000 Network (Figure 6C).

Other areas of high landscape quality, though less significant in terms of natural heritage, are associated with lithostructural reliefs found in the interior of the Castrove Peninsula. In these areas, adequate management would be advisable to ensure the proper development of infrastructure.

Most of the western coastal margin of the Castrove Peninsula features areas of interest for conservation measures (Figure 6D). Along the coastline, geosites have been identified that demonstrate geological processes, providing insights into the geological evolution of the coast. These include marine abrasion surfaces (terraces or marine platforms), dune systems, fossil beaches, and evidence of neotectonic processes related to coastline variation. Notable examples include La Lanzada Cape, Foxos Beach, Fagilda Cape, and Cabicastro Cape (Figure 6G). At these capes, the steep cliffs contribute to a high landscape quality, increasing their geological and scenic interest.

Finally, the La Lanzada tombolo and the alluvial fan and cone systems located in the southern part of Umia-Grove Bay exhibit high natural heritage significance (Figure 6C,H). The scientific, educational, and touristic significance (particularly high in the Lanzada area) justifies their classification as geosites. Additionally, these zones include extensive areas that belong to protected intertidal systems. As a result, these areas are considered less of a priority for conservation since they already fall under the legal protection of the Natura 2000 Network (Figure 6E,F). However, it would be advisable to promote these areas effectively, emphasizing their geological significance.

The conservation quality mapping proves highly useful in integrating various environmental attributes into a single layer that identifies and highlights areas that should be prioritized for preservation actions. The result shows a high level of consistency, as the zones with the highest conservation quality ratings coincide with key features of the territory, such as geological interest sites, protected natural areas, and areas of high landscape quality. This correlation supports the reliability of the final output. The applied multicriteria methodology (WOA) [20] has demonstrated its effectiveness in generating a conservation quality index through the weighted combination of intrinsic physical factors of the territory. This cartographic product emerges as a key preliminary tool to guide land use restrictions by indicating where environmental protection or management measures should be implemented or reinforced.

3.2. Limitations on the Use of the SE Margin of the Ría de Arosa

3.2.1. Coastal Flood Risk

The analysis of coastal flood risk using the Flood Hazard Index (FHI) method allowed for the identification of areas with higher and lower risk based on different time scenarios. The scenarios corresponding to 25 (Xa) and 100 (Xb) years present the highest danger [52], and these will be considered in the final map (Figure 7A).

Urban areas located along the coastal environments (El Grove, Arosa, Cambados, Villanueva de Arosa, or Portonovo) present the highest risk of a coastal flooding event. These areas involve a high population density, which is significantly greater than in the rest of the study area, with high danger values (e.g., the tombolo of La Lanzada or the mouth of the Umia River).

3.2.2. Real Erosion Risk

The real erosion map allows us to observe which areas present a greater problem regarding water-related erosive processes (Figure 7B) [54]. The study area does not show large zones with high values of water erosion (>50 t/ha/year). The dense vegetation distributed throughout the area and the predominance of gently sloping zones are factors that positively influence the reduction of these values. It is in the less vegetated areas with steeper slopes where the results indicate a more significant problem. Coastal areas featuring large cliffs, such as those found along the western coastline of the Castrove Peninsula, are a clear example of high erosion risk. Additionally, areas with sparse vegetation and poorly consolidated substrate also register high values of real erosion. The area of the tombolo of La Lanzada, which features significant dune systems, as well as beaches and wetland environments, clearly records values above 50 t/ha/year.

3.2.3. Mass Movement Hazard

The mass movement risk map, created through a correlation between the area’s susceptibility and its potential triggers (rainfall and seismic activity), identified that approximately 18.89% of the area is under high risk (Figure 7C) [53].

In these high-risk areas, territories dominated by residual granite and metamorphic landforms are primarily represented. Granitic areas with dome-like morphologies where abundant individual granite boulders or those forming part of a boulder field are recognized serve as a good example. Similarly, cliff areas are prone to experiencing mass movement processes, such as landslides, which affect the steep coastal zones.

3.2.4. Natural Hazard Map of the SE Margin of the Ría de Arosa

The natural hazard map reflects various problems that are recognized either individually or cumulatively in the study area (Figure 7D). These problems are geomorphological, lithological, hydrological, or geotechnical in nature. They represent the locations where these issues pose a significant concern. The most affected areas are those that exhibit a greater number of risks [55]. On one hand, the natural hazard map integrates the high coastal flood hazard zones described in Section 3.2.1. These areas, along with valley bottom sectors, characterize the hydrological problems associated with coastal flooding and waterlogging typical of valley bottoms following heavy rainfall events. Furthermore, a geotechnical characterization map is available, which identifies geomorphological, lithological, and geotechnical aspects related to the mechanical characteristics of the lithologies for construction in the study area. The coastal zones, where hydrological and geotechnical problems interact with geomorphological or lithological variables, show the greatest challenges in the territory. Thus, they are declared unsuitable for the development of anthropogenic infrastructure.

3.2.5. Comprehensive Risk Mapping of the SE Margin of the Ría de Arosa

This section integrates the various risks identified in Section 3.2 into a single, comprehensive mapping (Figure 8). The areas around the coastline are those that pose the greatest challenges, as it is here that a higher number of natural risks converge. Therefore, the limitations on land use must place special emphasis on these areas. The development of anthropogenic infrastructure for residential or industrial purposes would not be advisable without a thorough prior analysis.

Cliff sectors, particularly well represented along the western margin of the Castrove Peninsula, are among the most critical constraints. These areas feature steep slopes, low vegetation density, and are generally unsuitable for construction due to their instability and high susceptibility to erosion and landslides.

Coastal areas with gentler slopes, while less prone to landslides or surface erosion (depending on the consolidation of the substrate), present problems related to coastal flooding, especially in low-lying areas.

Furthermore, the southern margin of Umia-Grove Bay, characterized by active fan and alluvial cone systems, presents constraints due to the mobile nature of the substrate, which increases the risk from a geomorphological and geotechnical perspective. Finally, areas with residual relief, such as Monte Siradella or the northwest part of Arosa Island, are not recommended for construction. These areas have poor slope stability and can be affected by block falls and landslides, making them particularly susceptible to ground movement. The comprehensive risk mapping provides a unified view of the potential natural threats described in the study area [52,53,54,55], which is highly useful for identifying the most problematic zones where multiple hazards converge. This contributes positively to risk prevention strategies that should be considered during the pre-project planning phase. The qualitative overlay analysis of multiple layers (QOA) proves to be an appropriate and effective method for generating a comprehensive multi-hazard map [55]. It enables a holistic visualization (i.e., integrated and combined) of areas where several hazards coexist. This cartographic product translates technical hazard information into a planning tool that is both easily interpretable and aimed at minimizing potential impacts in the context of coastal development [7,8].

3.3. Recommendations and Limitations on Land Use

3.3.1. Land Use Recommendations and Limitations Mapping of the SE Margin of the Ría de Arosa

The land use recommendation and limitation mapping synthesize the conservation quality mapping and the comprehensive risk mapping into a single representation (Figure 9). This significantly enhances the usefulness of the result and its technical applicability. In a single map, it identifies both the areas that are optimal for certain land uses and those where land use should be totally or partially restricted. This approach ensures that the cartographic information is based on a critical interpretation of each input layer. It thus avoids the unjustified overprotection of areas where no apparent constraints exist, as well as the omission of limiting factors in zones that may otherwise seem suitable for development.

From a territorial planning perspective, the recommendation and restriction map provide direct support for decision-making by clearly indicating where activities (recreational, agricultural, or even controlled development) can be promoted, and where restrictions or additional assessments should be imposed. In this way, authorities can easily incorporate the results into spatial planning instruments, ensuring that socio-economic growth is directed toward areas with lower environmental conflict, while zones of high ecological value or risk receive the appropriate level of protection or caution.

3.3.2. Land Use Limitations Degree Mapping for the SE Margin of the Ría de Arosa

The overlap of the thematic layers that make up the land use recommendations and limitations mapping through the Boolean analysis combination matrix allows for the creation of land use limitation degree mapping (Figure 10). Three distinct scenarios are thus presented: high limitation degree, medium limitation degree, and low limitation degree.

• High limitation degree: These areas combine high or very high conservation quality with recognized natural hazards, making them especially vulnerable and highly restrictive for anthropogenic activities. Any proposed activity in these areas must strictly undergo a detailed and rigorous environmental impact assessment explicitly aimed at minimizing ecological disruption and hazards. Given their ecological sensitivity and natural risk, anthropogenic developments in these zones should only be approved under exceptional circumstances where environmental compatibility and hazard mitigation are unequivocally demonstrated. Otherwise, their conservation and protection should be prioritized as a primary recommendation. Due to the territorial context, spaces of a more recreational nature, such as adapted bathing areas, trails, rest areas, or viewpoints, may be established. Where the environmental impact study allows it, more invasive recreational activities, such as campsites with bungalows, motorcycle paths, or interpretation centres, could be developed. Potential locations for the development of such activities could be the tombolo of La Lanzada, the islands of Arosa and La Toja, the coastline around the Umia-Grove Bay, the marshes at the mouth of the Umia River, or the inland areas and coastal margins of the El Grove peninsula. Similarly, the western coastal sector of the Castrove peninsula, where successive geosites are recognized, would be an ideal area for the development of trails with interactive panels, promoting activities beneficial to the environment, such as geotourism.
• Medium limitation degree: These represent areas of the territory where high conservation quality and geological hazards do not co-occur, but at least one of them is present. In the case of the study area, this scenario primarily occurs in areas of low conservation quality where some hazard is recognized. Areas where only high conservation importance is identified and no geological hazards are present are very few and not considered sufficiently representative. Thus, both scenarios are described within the same context.
  This scenario is identified in coastal areas, where flood risks and erosion rates are high, but which lie outside of the protected spaces of the Natura 2000 network. These are areas considered unfavorable for most anthropogenic activities. In such areas where a specific project is to be developed, it is again recommended to carry out an Environmental Impact Assessment. Furthermore, corrective or rehabilitation measures should be implemented during the pre-project phase to mitigate or reduce the negative effects posed by use limitations. This is well represented by the entire coastal area connecting the municipalities of Cambados and Villanueva de Arosa. The northernmost flank of the El Grove peninsula, near the town of the same name, also presents a similar situation. Lastly, this scenario is recognized around beach areas along the southeastern margin of the Castrove peninsula extending to Portonovo and Sangenjo.
• Low limitation degree: These areas are characterized by low conservation quality and the absence of any recognized natural hazards. In these areas, the potential risk is lower, as no natural hazards are identified. The conditions are most favorable for the development of most anthropogenic activities. Agricultural or agronomic exploitations could take place in these areas. Where risks are lower or not recognized, activities such as urban expansion and industrial developments (industrial parks or factories) may be carried out. These locations are found in a large sector of the interior of the eastern margin, connecting the municipalities of Villanueva de Arosa and Cambados and continuing under the mouth of the Umia River, east of the Umia-Grove Bay. These areas are also recognized along the southern margin of the Castrove Peninsula, north of Portonovo. The El Grove peninsula concentrates optimal areas for anthropogenic activities on the interior margin of the town of El Grove and around the outskirts of the Mexilloneira beach.

As indicated at the beginning of this section, this tool classifies the territory into categories based on high, medium, or low land use constraints, allowing for a rapid understanding of potential restrictions in each parcel. It was developed to simplify the complex information represented in the land use recommendation and limitation mapping (Figure 9) by summarizing the combined data on conservation quality and natural hazards into three general levels.

The assignment of each constraint level is consistent with the data used and the logic of qualitative overlay: areas with high constraints correspond to sites where both high conservation value and natural hazards are present; medium-constraint areas show one of the two limiting factors (e.g., significant risk but low natural value or vice versa); and low-constraint areas lack distinctive environmental elements or clear hazard presence. The results align with the source data, indicating that this tool does not introduce additional information or anomalies.

The Boolean analysis carried out using the combination matrix [21] to determine land use limitation levels has proven to be highly effective. This approach simplifies the output while preserving the traceability of how each zone was categorized. Admittedly, grouping the results into three classes involves a certain degree of simplification, which can obscure some of the detail embedded in the process. However, we consider this approach appropriate for land-use planning purposes, as it opens new pathways for communicating complex spatial information. The resulting map is clear and accessible, allowing even non-specialist audiences to understand it with ease.

As shown, the land use limitation degree mapping is directly applicable to sustainable territorial planning and management: areas of high constraint may be designated for strict conservation or only light, non-intrusive uses; medium-constraint areas could support moderate uses or development subject to environmental assessment and mitigation measures; and low-constraint areas are the most suitable for urban growth or low-risk industrial projects. In this way, the gradient of restrictions offered by the map helps to balance development and conservation, serving as an objective reference for regulating land use according to each zone’s intrinsic capacity and vulnerability.

4. Conclusions

The multi-criteria decision-making analysis carried out on the southeastern margin of the Arosa Estuary, using the GIS techniques WOA, QOA, and a Boolean analysis with a combination matrix, has allowed the different layers of the conservation quality mapping to be linked with the comprehensive risk mapping. Thanks to this methodology, it has been possible to identify priority areas for conservation and those with significant restrictions due to natural risks. This methodological approach has facilitated effective modelling that is of high resolution, easy to update, and quick to implement. For these reasons, it can be considered a valuable tool that can be applied in various contexts and future environmental studies focused on sustainable territorial planning and the conservation of natural resources.

The areas of high conservation quality stand out as places to implement actions focused on recreational activities. Areas of special natural significance, such as the Island of Arosa or the inland and coastal zones of the El Grove and Castrove Peninsulas, are ideal for developing recreational areas such as swimming zones, resting places, picnic areas, and, where natural risks are not so high, campsites or interpretation centres. Implementing geotourism as a general tool for promoting the territory is a technique that has been developed in recent years and has been effective from the standpoint of social awareness and the maintenance of geologically interesting sites [19,49].

On the other hand, areas that present better conditions for the development of anthropogenic activities, such as agriculture, industry, or urban development, are associated with territories of low ecological and scenic importance and a lower propensity for natural risks. The inland corridor located in the northeastern coastal margin, which connects the municipality of Villanueva de Arosa with Cambados and extends to the marshland influence area at the mouth of the Umia River, is the most favourable territory for the development of anthropogenic activities.

The results obtained through this methodology have enabled the development of land use recommendation and limitation mapping that clearly and at high resolution integrate environmental, conservation, and risk-related criteria. This tool has proven to be highly useful in early planning phases, providing an objective and easily interpretable territorial diagnosis to guide decision-making and the prioritization of management strategies.

As in any applied research, the proposed approach presents certain limitations, particularly regarding the availability and quality of geospatial data. In this specific case, the study benefited from a strong background of previous research and detailed knowledge of the area, allowing for a high level of cartographic precision. However, replicating this methodology in other regions may require specific data collection campaigns or preliminary fieldwork, especially in contexts with limited spatial information.

These considerations open the door to future improvements, such as process automation, threshold optimization, and the implementation of more robust validation mechanisms, including sensitivity analysis, methodological comparisons, or validation through real-world data and expert review.

In addition, a complementary challenge toward enhancing the scalability of this work lies in the potential integration of the generated cartography with BIM methodologies. This connection would allow the territorial information to be transferred into three-dimensional models of the built environment, strengthening infrastructure design in line with the specific conditions of each area. Beyond its technical value, this integration offers a more holistic vision of the planning process, contributing a multidisciplinary approach that bridges spatial analysis with architecture, engineering, and built environment management. Recent studies have highlighted the potential of GIS–BIM integration as a tool to connect territorial-scale decisions with actionable solutions in the constructed environment [65].