Concept of Assessment of Age-Friendly Residential Areas (AFRA): A Case Study of Gdańsk, Poland

Abstract

(1) Background: Local governments are facing a considerable challenge to accurately verify cities, as well as to diagnose the condition of housing estates in the context of their friendliness to life of older people in order to be able to pursue a sustainable pro-ageing policy. In response to these needs, universal methodology for identifying age-friendly residential areas (AFRA) in cities was developed and tested. Thus, the main objective of the research was to develop an innovative methodological approach to the AFRA assessment, taking into account integrated functional-spatial and aesthetic indicators with particular emphasis on the ways of presenting results. (2) Methods: The methodology was based on the general, international assumptions of “ageing in place”, “age-friendly city”, “active ageing”, and an in-depth analysis of contemporary trends in this field, using international guidelines and recommendations, as in the case of survey data from the target international population and information provided by experts. (3) Results: The overall result of the project is a universal methodology for diagnosing housing estates in cities, taking into account infrastructural and landscape determinants in terms of their friendliness to older people, including a presentation of the usefulness of GIS tools to create thematic maps visualising the degree of friendliness. (4) Conclusions: This innovative approach to AFRA visualisation will expand the knowledge about the possibilities of diagnosing age-friendly spaces in the city that are conducted at the level of the city’s settlement units. The developed list of criteria influencing the friendliness of housing estates for older citizens can be useful for public entities in creating city and housing planning policies for private entities to manage their own investment plans and implement the concept of on-site ageing in their planning and for real estate agents to explore the real estate market for the needs of older clients.

1. Introduction

According to the World Health Organisation (WHO) [1], the coming decades are expected to see an increase in the number of people over the age of 60, aging in place, and the necessity for local authorities to provide adequate healthcare and meet other needs of the older population. The issue of an aging society directly or indirectly affects the entire population, and it is crucial that this issue is considered in the context of urban spaces, as advocated by the WHO [2]. An urban space that meets the needs of older adults is one that is adapted to their requirements, especially by eliminating age-related barriers, thus becoming “friendly” [3]. According to the Human Rights in the City Agenda provided by the WHO [4], everyone should feel comfortable in the city, which is highlighted in the Age-Friendly Cities document [2]. A friendly urban space should encompass eight aspects of city life that overlap and interact with each other, namely, outdoor spaces and public buildings, transportation, housing, social participation, respect and social inclusion, civic participation and employment, communication and information, and community support and health services. Respect and social inclusion are reflected in the accessibility of buildings and spaces and in the opportunities the city offers older people to participate in social life, entertainment, or employment. Social participation, in turn, not only affects social inclusion but also access to information [2]. However, none of the above guidelines indicate the significance of the landscape as a factor in the friendliness of residential areas. As noted by Handler [5], the friendliness of urban spaces depends on the structure of the city, the attractiveness of the landscape, and the level of infrastructure. A comprehensive composition of these elements is key to achieving an age-friendly space.

Therefore, effective methods of identifying such residential areas in cities are necessary, highlighting infrastructure and landscape preferences. Previous studies, such as those by Fitzgerald and Car [6] or Plouff and Kalache [7], described spaces conducive to residents, including “age-friendly”, “liveable communities”, “lifelong neighbourhoods”, and “communities for all ages” [3]. The landscape of age-friendly residential areas was not valorised. Earlier analyses of age-friendly cities were conducted by Gonyea and Hudson [8], focusing on social integration, while Wong and Shaw [9] focused on spatial activity, offering a methodological approach to measuring segregation. Infrastructure solutions create opportunities for active engagement of older adults in the entire urban space [10,11,12,13,14]. Case studies on active aging, for instance, by Dawidowicz et al. [15], establish priorities and preferences regarding spatial distances, along with methods and tools for visualising places of active aging [16] and studies on the needs of older people for safe infrastructure [17]. Moreover, scientific activities focus on architectural solutions that facilitate the lives of older people and identify areas adapted to their needs [18,19], as well as on child-friendly architectural solutions [20,21]. Little or limited attention is paid to research on the aesthetics of the landscape as seen through the eyes of older adults, which is an important additional element of the solutions introduced. An aesthetic landscape contributes to a sense of security, identification with the place of residence, rest, and the creation of reality [2,22,23]. Landscape is perceived as a visual phenomenon, composed of many layers (components). It is characterised by a composition that forms an integral whole also in an aesthetic sense [24,25]. Assessing the aesthetics of a landscape requires seeing the phenomenon as a whole. This is the reason for using, for the purposes of analysis, a definition of an aesthetic nature: “A landscape is the external (visual) expression of the current (analysed) state of the geographical environment, in which the processes taking place create the characteristic features that define the type of landscape and state” [26]. The landscape is an essential and integral part of urban space. It serves as a backdrop and stage for everyday life, perceived more or less consciously. The more distinctive and characteristic it is, the more noticeable and the stronger the emotions associated with it. In the urban environment, the aesthetics of the landscape are increasingly linked to the safety and functionality of spaces. Therefore, determining older adults’ preferences regarding the significance of landscape values in residential areas is important. When it comes to studying the impact on people, including seniors, green spaces are of great aesthetic and utilitarian importance in urbanised areas. Greenery in space creates an aesthetic feeling. It is the colour of balance, renewal, and tranquillity, which is conducive to promoting relaxation and unwinding. Greenery has a beneficial effect not only on mental condition and well-being, but also on people’s physical health [27,28]. Hence, an approach to assessing urban AFRA with aesthetic indicators would also be of universal relevance to other social groups. Defining the landscape-friendliness of a residential area requires an assessment of space, which can be done by considering a list of indicators of a landscape-friendly residential area. Given the need to fill the research gap, the main aim of the study was to develop an innovative methodological approach to the age-friendly residential areas (AFRA) assessment in the city in terms of functional-spatial and aesthetic (landscape) determinants, with particular emphasis on the ways of presenting results. The dedicated AFRA approach is in line with individual, bottom-up, and local needs, recommended by Lin et al. [29], among others. Preliminary analysis allowed for the formulation of the research hypothesis that spatial visualisation of AFRA on thematic maps is a significant element in the process of identifying residential areas friendly to older adults. So far, such an approach to the identification of residential areas friendly to an aging population, that integrates planning and aesthetic indicators in the public open spaces of residential neighbourhoods, has not been developed or applied in such a comprehensive scope that will enable the automation of diagnostics in the future.

The proposed methodology extends the WHO research on age-friendly urban settlements by combining infrastructural and landscape aspects [1,29]. The methodology test presents the possibilities of using free GIS software e.g., QGIS 3.28.10 to develop AFRA thematic maps in the city. This research is current and relevant, taking into account the provision of health and well-being at every age and creating safe and sustainable settlements [30,31,32].

Preliminary literature research and knowledge of the tested space enabled the formulation of the following research hypotheses: (1) the methodological assessment of AFRA will differ from the assessment of quality of life in residential areas made by the general population (older people have different needs than the general population); (2) the availability of various functional facilities is significant in the process of assessing the level of AFRA of the public open space of the residential complex; (3) the impact of a given factor on the area of the entire housing complex appears to be significant.

The applied research approach allowed the authors to answer the following research question: does an approach focused on separate assessment of the friendliness of functional-spatial and aesthetic factors yield the same results in the overall assessment of the friendliness of individual residential areas?

2. Materials and Methods

2.1. Research Framework and Assumptions

To develop the AFRA assessment methodology, theoretical and empirical analyses were conducted. The methodology was based on the general, international assumptions of “ageing in place” [33], “age-friendly city” [34,35], and “active ageing” [36], as well as an in-depth analysis of contemporary trends in this field, using international guidelines and recommendations for age-friendly policies as in the case of survey data from the target international population over 55 years old [37] and information provided by experts. WHO [2] classification of age structure divided into 4 age groups of seniors was taken into account in the surveys: (I) 55–59 years—pre-old age (pre-senior), (II) 60/65–74 years—early old age (young-old), (III) 75–89 years—old age proper (old-old), (IV) 90+ years—oldest-old (lifelong). In addition, identification of AFRA must be performed at the local level, since many aspects of ageing in place depend on local conditions, i.e., economic conditions—income levels of the older population [38], local policies [39], and local community features [40], including patterns of family life [41,42].

Taking the above assumptions into account the study consisted of several stages. The research task plan is presented in Figure 1.

In the first stage, a literature review was conducted to identify functional-spatial and aesthetic factors based on scientific publications and documents that have a significant impact on the quality of life of older adults in residential public open spaces (1). Then, in the practical stage, indicators of friendliness for older people were developed and hierarchically evaluated with the participation of experts (2), and the AFRA assessment methodology was developed (3). An agglomeration city was selected as the study area (4), and data were obtained from various sources such as maps, aerial photographs, and public databases (5). A field inventory (6) and cartographic inventory (7) were also conducted, as well as spatial analyses (8). Finally, the estates and the city were assessed according to the adopted methodology (9), and the results were verified through quality-of-life studies and a repeat survey among older citizens (10).

This approach enabled a comprehensive assessment of age-friendliness in the studied estates and throughout the city. Any city can be diagnosed with the proposed method because it does not contain limitations resulting from the city’s area, its location, and number of inhabitants, as well as its economic status.

2.2. AFRA Indicators

The rankings of functional-spatial and aesthetics groups of indicators were established using a mixed approach based on the analysis of literature concerning the needs of older people in the aspect of residential space, especially on the results from an international study [37], European Union (EU) legal regulations, strategic documents, and with the participation of experts. These rankings were established through a survey conducted among seniors from Europe. They were divided into a total of 12 categories, described by 34 corresponding factors. For these factors, indicator values reflecting their age-friendliness were determined.

In the group of functional-spatial factors, 8 categories/functions were identified (F1—transportation-communication, F2—recreational-rest, F3—commercial-service, F4—cultural-educational, F5—information, F6—protective, F7—urban planning parameters, F8—neighbourhood function) and 21 corresponding factors (Figure 2), and in the group of aesthetics factors, 4 categories (K1—green-blue infrastructure, K2—urban layouts, K3—appearance of spatial objects, K4—orderliness and cleanliness of the surroundings) with a total of 13 factors (Figure 3).

Each of the adopted indicators was analysed in terms of supporting the well-being and quality of life of older adults. For instance, building intensity (F7A) in urban planning parameters (Category VII) affects accessibility to essential services and social interaction. High density often means amenities like grocery stores and healthcare facilities are within walking distance, which is crucial for older adults with limited mobility. Similarly, biologically active areas (F7B) were examined for their contribution to mental and physical health. Green spaces provide opportunities for exercise and a serene environment, reducing stress and promoting social interaction, thereby combating loneliness and isolation.

Likewise, the analysis considered aesthetic factors. Historical spatial arrangements (K2C) in urban layouts (K2) were evaluated for their impact on emotional well-being. Heritage architecture fosters a sense of continuity and connection with the past, evoking personal memories and enhancing identity for older adults. Familiar and comforting settings provided by these environments are particularly beneficial for those experiencing cognitive decline or feelings of isolation. The indicator values were then used to assess residential estates in a specific case study.

2.2.1. Assessment of AFRA Indicators from the Functional-Spatial and Landscape (Aesthetics) Categories

The rankings of functional-spatial and aesthetics groups of indicators were established using a mixed approach based on the analysis of literature concerning the needs of older people in the aspect of residential space, especially on the results from an international study [37], EU legal regulations, strategic documents, and with the participation of experts. A survey of the literature has shown that the integration of architecture with an aesthetically pleasing landscape and natural environment is crucial for sustainable development, human health, and well-being, as well as environmental protection and biodiversity [43]. In the architectural and urban context, this means designing buildings and spaces that minimise negative impacts on the environment and create a beautiful natural–anthropogenic composition [44]. Aesthetically pleasing landscaping, including greenery, flowers, and water features, can significantly improve the mood of residents. Contact with nature reduces stress and improves concentration and overall mental state [45]. Aesthetically designed spaces help reduce levels of cortisol, the stress hormone [46]. Hence, the AFRA assessment approach must include planning (Figure 4) and aesthetic (Figure 5) indicators together.

The indicator values reflecting their friendliness towards older people were determined. These values were assigned using an expert method, in a four-person group of individuals over the age of 55, referred to as competent judges. These experts specialised in spatial planning, urban planning, architecture, and landscape architecture. Such a selection of an interdisciplinary group of experts ensures a high level of correctness in the assessment of the collected data and allows for the introduction of weights differentiating the impact of individual factors on the functional, spatial attractiveness and landscape values. Their task was to determine the ranges in which the analysed factors should be perceived as beneficial, average, or unfavourable. In creating the AFRA rating scale, which was to be derived from the survey and easily implemented in QGIS 3.28.10 software, it was not decided to use the extensive ICF Qualifier scale [47]. The methodological assumptions adopted that the assessment scale would be three-level (or in some cases two-level) to simplify the diagnostic algorithm, thereby facilitating the automation of space evaluation. Parameters for unfavourable (0 points), average/neutral (1 point), and favourable factors (2 points), or respectively unfavourable (0 points) and favourable (1 point) (depending on the adopted scale), were selected to identify the best and weakest solutions within the AFRA model. The results for functional-spatial indicators are presented in

Table A1. Functional-spatial indicators.

Category of Factors	Factors	Elements		Indicator
			0–2 Scale	0—Unfavourable	1—Average	2—Favourable
			0–1 Scale	0—Unfavourable	-	1—Favourable
(F1) Transportation-communication function	(F1A) General parking places	1. Availability of parking spaces		<1 parking space per dwelling in the estate	1–1.5 parking spaces per dwelling in the estate	>1.5 parking spaces per dwelling in the estate
		2. Proportion of parking area to the total building area
	(F1B) Parking places designated for disabled persons	1. Availability of parking spaces for disabled persons		<4% of the total parking space area designated for disabled people	4–5% of the total parking space area designated for disabled people	>5% of the total parking space area designated for disabled people
	(F1C) Pavements, stairs, ramps without barriers adapted to various levels of older adults’ abilities	1. Widths of pedestrian pathways		Neglected pavements and numerous barriers hindering the movement of people with varying degrees of mobility in the case of most pedestrian and mixed-use paths within the estate (max. 50%)	Well-maintained pavements and few barriers hindering the movement of people with varying degrees of mobility in at least half of the pedestrian and mixed-use paths within the estate (50–75%)	No or few barriers hindering the movement of people with varying degrees of mobility in the vast majority of pedestrian and mixed-use paths within the estate (75–100%)
		2. Barrier-free communication routes (no thresholds, curbs, uneven ground)
		3. Surfaces with anti-slip systems
	(F1D) Readability of communication layouts	1. Separation of communication routes (pedestrian, bicycle, vehicle)		Lack of clear separation of traffic flows	Separated routes for pedestrian and vehicular traffic	Separated and marked routes for pedestrian, bicycle, and car traffic
	(F1E) Accessibility of public transport and taxi stands	1. Bus stops adapted to various levels of abilities		Access to a stop within a max radius of 300 m on max 50% of the estate’s area. Frequency of service every 60 min during the day	Access to a stop within a max radius of 300 m on 50–75% of the estate’s area. Frequency of service every 30 min during the day	Access to a stop within a max radius of 300 m on at least 75% of the estate’s area. Frequency of service every 15 min during the day
		2. Taxi stands located in easily accessible places for persons with varying levels of abilities
		3. Clear communication systems
		4. Readable architecture
		5. Lighting of pedestrian crossings
(F1) Transportation-communication function	(1F) Readability of spatial layouts	1. Easy orientation in space		<50% of the estate area with legible spatial layouts	-	>50% of the estate area with legible spatial layouts
		2. Clear communication systems
		3. Readable architecture
	(F1G) Lighting of communication routes	1. Lighting systems ensuring good visibility after dark		The number of street lamps and other lighting not providing adequate illumination for most of the estate area or its absence within the estate	The number of street lamps and other lighting providing adequate illumination for at most half of the estate area	The number of street lamps and other lighting providing adequate illumination for the majority of the estate area
		2. Lighting of pedestrian crossings
(F2) Recreational-rest function	(F2A) Passive rest areas	1. Dedicated small architectural elements and facilities (benches, gazebos, etc.)		Distance to passive recreation spots above 500 m on >75% of the estate’s area	Distance to passive recreation spots 200–500 m on >75% of the estate’s area	Distance to passive recreation spots below 200 m on >75% of the estate’s area
		2. Walking areas (squares, parks, green spaces)
	(F2B) Active rest areas	1. Dedicated sports and recreational infrastructure (sports fields, outdoor gyms, walking areas, cycle paths, etc.)		Distance to active recreation spots above 1000 m on >75% of the estate	Distance to active recreation spots 500–1000 m on >75% of the estate	Distance below 500 m on >75% of the estate
(F3) Commercial-service function	(F3A) Primary healthcare locations	1. Clinics (outpatient care, primary healthcare, rehabilitation)		Distance above 1000 m on >75% of the estate	Distance 500–1000 m on >75% of the estate	Distance below 500 m on >75% of the estate
	(F3B) Places to purchase basic necessities	1. Grocery stores		Distance above 500 m on >75% of the estate	Distance 200–500 m on >75% of the estate	Distance below 200 m on >75% of the estate
		2. Department stores
		3. Pharmacies
	(F3C) Restaurants/bars	1. Eateries with varying price ranges and menus		Distance above 1000 m on >75% of the estate	Distance 500–1000 m on >75% of the estate	Distance below 500 m on >75% of the estate
(F3) Commercial-service function	(F3D) Security and public order services (response speed and ability for personal and telephone contact)	1. Police, Municipal Guard		Response time > 30 min.	Response time 15–30 min.	Response time < 15 min.
		2. Fire Service
		3. Emergency Services
	(F3E) Public toilets and cleanliness of the estate	1. Access to toilets outside the residence		Limited access to public toilets or their absence in the estate. Waste collection less than twice a week	Access to public toilets within the estate. Waste collection at least twice a week	Access to public toilets within the estate. Daily (or every 2 days) waste collection by cleaning companies
		2. Regular waste collection by cleaning companies
(F4) Cultural-educational function	(F4A) Cultural-educational facilities	1. Community clubs and cultural centres		Distance above 1000 m on >75% of the estate	Distance 500–1000 m on >75% of the estate	Distance below 500 m on >75% of the estate
		2. Libraries
		3. Museums, galleries, art and craft studios
		4. Cinemas and theatres
	(F4B) Sacred facilities	1. Temples		Distance above 1000 m on >75% of the estate	Distance 500–1000 m on >75% of the estate	Distance below 500 m on >75% of the estate
		2. Chapels and other elements of small sacred architecture
		3. Cemeteries
(F5) Information function	(F5A) Clear signage adapted to the abilities of older adults	1. A uniform system of address markings (street names, building numbers) and building functions (bakery, post office, shop, restaurant, public toilet, library, etc.) and direction signs/indicators		Lack of signage (or only 1 of 3) on main streets	Some signage present (2 of 3) on main streets	Address and directional signs and audible signals present on main streets
		2. Auditory signals (communication, public utility buildings, residential buildings—intercoms, etc.) and devices for the hearing impaired
		3. Clear messages regarding public transport movement
(F6) Protective function	(F6A) Places of safe shelter and infrastructure elements providing safety in emergency situations (e.g., shelters, flood protection, shelters, evacuation points)	1. Accessibility of places of safe shelter and infrastructure elements providing safety in emergency situations		Distance above 1000 m on <50% of the estate		Distance 500–1000 m on 50–75% of the estate	Distance below 500 m on >75% of the estate
(F7) Urban planning parameters	(F7A) Building intensity.	1. Density of development		Building density > 1.5		Building density 1.0–1.5	Building density < 1.0
		2. Height of buildings
	(F7B) Biologically active area	1. The percentage of biologically active area in the total area of the estate		<25% biologically active area of the total estate area		25–35% biologically active area of the total estate area	>35% biologically active area of the total estate area
(F8) Neighbourhood function	(F8A) Neighbourhood function (function of land adjacent to the estate)	1. The type of function of lands neighbouring the estate		Industrial function; services and trade causing inconvenience, generating heavy traffic (e.g., station, railway traffic, hypermarkets); mines; gravel pits; wastelands (e.g., marshes, peat bogs, dunes, rubbish dumps, etc.)		Agricultural lands	Residential function; non-intrusive services and trade; forests and wooded areas; recreation (flowing and standing waters); green areas, including allotment gardens

Source: own elaboration.

and for aesthetics indicators in

Table A2. Aesthetics indicators.

Category of Factors	Factors	Elements		Indicator
			0–2 Scale	0—Unfavourable	1—Average	2—Favourable
			0–1 Scale	0—Unfavourable	-	1—Favourable
(K1) Green-blue infrastructure (areas with various forms of greenery—isolation greenery, recreational greenery, function-defining greenery, and water bodies)	(K1A) Low greenery	1. Dominant low greenery (lawns, flower beds, borders, gardens, shrubs)		Within 50 m of the building <30% of the area occupied by low greenery	Within 50 m of the building 30–50% of the area occupied by low greenery	Within 50 m of the building >50% of the area occupied by low greenery
	(K1B) Tall greenery	1. Composition of tall greenery that does not cast shade on buildings		>0.3 trees per building within <10 m of the building. or <1 tree/building in the estate area	-	Absence of tall greenery or <0.3 trees per building within <10 m of the building. or ≥1 tree per building in the estate area. or Forest on >10% of the estate area
	(K1C) Aesthetic (well-maintained) places for recreation and relaxation (passive and active) (RP)	1. Benches and resting places		Lack of aesthetically pleasing places for recreation and relaxation	Presence of aesthetically pleasing places for recreation and relaxation (at least 30% of the residential area is dedicated to recreation and relaxation, and up to 50% of these spaces are aesthetically pleasing)	Presence of aesthetically pleasing places for recreation and relaxation (at least 30% of the residential area is dedicated to recreation and relaxation, and more than 50% of these spaces are aesthetically pleasing)
		2. Walking paths, avenues
		3. Park layouts, green spaces, squares
		4. Sports facilities (sports fields, cycle paths, outdoor gyms, ice rinks) and playgrounds
	(K1D) Water bodies	1. Natural and artificial water bodies (ponds, lakes, rivers, and other streams and reservoirs)		Absence of water bodies within the estate	-	Presence of water bodies within the estate
(K2) Urban layouts	(K2A) Logic of the layout	1. Simple and understandable layout of streets and alleys that facilitates navigation		Lack of logic in the layout and legible and uniform address signage in <30% of the estate area	30–50% of the estate area has logical spatial layouts and legible and uniform address signage	50% of the estate area has logical spatial layouts and legible and uniform address signage
		2. Legible and uniform address signage
(K2) Urban layouts	(K2B) View corridors (open layouts providing observations of the near and distant surroundings)	1. View corridors of the immediate surroundings		No visible thoroughfare through the housing estate	There is one visible thoroughfare running through the housing estate	There are multiple visible thoroughfares running through the housing estate
		2. View corridors of the distant perspective
	(K2C) Historical spatial arrangements (heritage architecture with natural surroundings)	1. Architectural monuments		<5% of the estate area occupied by heritage objects	5–10% of the estate area occupied by heritage objects	>10% of the estate area occupied by heritage objects
		2. Historic park layouts
		3. Narrow streets with townhouses
(K3) Appearance of spatial objects	(K3A) Façades of buildings and other construction objects	1. Subdued colour scheme of buildings and condition of façades		Well-maintained, clean, and with subdued colours on <50% of the estate area	-	Well-maintained, clean, and with subdued colours on >50% of the estate area
		2. Traditional architectural forms
		3. Harmony of building compositions
		4. Spacious building entrances
		5. Well-maintained façades and architectural details
	(K3B) Harmonious architecture	1. Uniform stylistic approach of urban spatial units		Mixed architectural styles within the estate	Large-panel building construction within the estate. Uniform style	Modern or heritage buildings within the estate
	(K3C) Harmonious (stylistically integrated) accompanying infrastructure (recreational, transportation, technical)	1. Small accompanying architecture—benches, shelters, canopies, street lamps, etc.		Non-uniform style of structures within the estate	-	Uniform style of structures within the estate
		2. Squares, playgrounds, exercise facilities, etc.
(K3) Appearance of spatial objects	(K3D) Landscape dominant	1. Anthropogenic dominant		Absence of a dominant feature within the neighborhood		Absence of a dominant feature within the neighborhood
		2. Natural dominant.
		3. Anthropogenic and natural sub-dominants
		4. Landscape accents
	(K3E) Objects and elements reducing the aesthetic values of the landscape	1. Damage (acts of vandalism)—graffiti, physical damage		Presence of damaged and neglected structures within the estate. Presence of inconsistent structures within the estate	-	Absence of damaged and neglected structures within the estate. Absence of inconsistent structures within the estate
		2. Worn and unrepaired development elements
		3. Objects inconsistent with surrounding anthropogenic and natural elements
(K4) Orderliness and cleanliness of the surroundings	(K4A) Well-maintained and clean estate elements	1. Maintained proper cleanliness and aesthetics of anthropogenic and natural elements in private and shared (public) areas		Estate cleanliness not maintained	-	Estate cleanliness maintained

Source: own elaboration.

. This construction of the score table allows for determining the range of the applied scale and the maximum value that a selected residential estate can achieve based on the assessment (21 in the functional-spatial category and 13 in the aesthetics category).

The adopted indicators from the functional-spatial group, as well as the aesthetics group, are described in detail and can be found in Table A1 and Table A2.

2.2.2. Data Acquisition, Selection for Analysis, and Cartographic and Field Inventory

The diagnosis of the space was based on a mixed approach: cartographic and field inventory. Cartographic inventory was conducted through the modelling of the landscape and infrastructure using maps and numerical terrain models from Geographic Information Systems (GIS). This method significantly speeds up the measurement procedure and acquires data for large areas, often inaccessible during field inventory. Spatial analyses were performed using ArcGIS Pro 3.1.3 and QGIS 3.28.10 software. Only publicly available data sources were used, such as Orthophotomap, BDOT10k, and OpenStreetMap, datasets provided by national institutions following the Open Data policy, as well as integrated public spatial data registers: cadastre, planning documents, geodetic registration of utility networks (GESUT), and situational-height map. In the selected area, certain information was missing, such as the availability of parking spaces for people with disabilities. Therefore, vectorisation based on high-resolution and current orthophoto maps available in geoportals was necessary. In some cases, GIS tools were insufficient, so field inventory was required.

Table 1. Data selection for the analysis of functional-spatial factors.

Functional-Spatial Factors	Data Sources
	Orthophotomap	OpenStreetMap	BDOT10k	Google Maps	Situational-Height Map	Planning Documents	Other Spatial Data Registers	Geodetic Registrer of Utility Networks	Cartographic Inventory	Google Street View	Field Inventory
F1A	x	x	x						x
F1B	x	x		x					x		x
F1C	x										x
F1D	x			x	x				x		x
F1E	x			x
F1F											x
F1G	x							x		x	x
F2A	x	x	x						x
F2B	x	x	x						x
F3A		x		x					x
F3B		x		x					x
F3C		x		x					x
F3D		x					x
F3E				x			x		x
F4A		x		x					x
F4B		x		x
F5A										x	x
F6A		x	x					x	x
F7A		x	x
F7B		x	x
F8A	x	x	x			x			x

Source: own elaboration. The code extensions can be found in Figure 4 and Figure 5.

and

Table 2. Data selection for analysis of aesthetics factors.

Aesthetics Factors	Data Sources
	Orthophotomap	OpenStreetMap	BDOT10k	Google Maps	Situational-Height Map	Planning Documents	Other Spatial Data Registers	Geodetic Register of Utility Networks	Cartographic Inventory	Google Street View	Field Inventory
K1A		x	x						x
K1B		x	x				x				x
K1C		x	x
K1D		x	x
K2A	x	x									x
K2B	x	x									x
K2C	x	x									x
K3A										x	x
K3B										x	x
K3C										x	x
K3D	x	x	x							x	x
K3E										x	x
K4A							x			x	x

Source: own elaboration. The code extensions can be found in Figure 4 and Figure 5.

show which GIS resources were used for functional-spatial and aesthetics indicators, including data from cartographic and field inventories.

The assessment of the accessibility of parking spaces for people with disabilities (indicator F1B) in the district of Przymorze Małe (19) in Gdansk required data from BDOT10k. Based on these data, the location of all parking spaces in the Przymorze Małe district in Gdansk was identified. Using the orthophoto map and Street View images, parking spaces designated for people with disabilities were identified. Figure 6 illustrates the distribution of designated parking spaces for people with disabilities.

The assessment of Green-Blue Infrastructure (K1B, Tall greenery) in the Przymorze Małe (19) district in Gdańsk required data from BDOT10k (PTLZ tree layer, PTRK shrubs). Based on these data, the location of trees and shrubs within the Przymorze Małe district in Gdańsk was identified. Using orthophoto maps, Street View images, and field inventory, the condition of tall vegetation was assessed. Figure 7 illustrates the distribution of trees in the neighbourhood.

Functional-spatial indicators from F2A to F8A (except F5A) could be determined using GIS tools without the need for field inventory. However, aesthetics indicators from K2A to K4A, K1B and functional-spatial from F1B to F1G (except F1E) required field inventory. The entire field inventory also included taking photographic documentation, which was useful in the process of ranking individual factors in the estate space (Table 2).

In Figure 8, an example rating scale for indicator (1F) readability of spatial layouts is presented: a well-maintained sidewalk easy to navigate without barriers received a favourable rating, while an unmaintained or dirt path received an unfavourable rating. Indicator (K1A) low greenery received the highest rating for well-maintained low greenery, and the lowest rating for the absence of greenery.

2.2.3. Spatial Analyses

The calculation of AFRA indicators for the study area required conducting detailed spatial analyses in GIS software e.g., ArcGIS Pro 3.1.3 and QGIS 3.28.10, utilising various functions and tools available in the program. Key functions that were used to determine the indicators included distance analysis and the creation of buffer zones, which proved crucial for determining indicators 2A, 2B, 3A, 3B, and 3C. Distance analysis allowed for precisely determining the degree of area accessibility for residents, considering the location of recreational spots, public transport stops, and other significant points. Meanwhile, creating buffer zones helped identify areas within a specific distance from key points, which was essential in analysing the accessibility of various services and infrastructure.

Additionally, attribute calculations were used to determine the percentage of the estate area meeting specific distance criteria, which was particularly significant for indicators 4A and 4B. During this stage of the study, over 150 GIS layers were generated. For example, the layer concerning parking spots included 2779 records, and the building layer 68,210 records.

A commonly used tool during the analysis was the use of spatial queries, which allowed for the identification of areas with limitations, e.g., where there was a lack of greenery or too little greenery relative to the set criteria (indicators K1A, K1B). This entire process required significant effort in the pilot stage of the developed algorithm and involvement but allowed for obtaining accurate data about the study area.

2.2.4. Assessment Procedure for the Age-Friendliness of Residential Estates

The assessment of the friendliness of the city’s residential estates consisted of the following stages:

(1)

Identification of residential estates or parts of estates uniform in terms of buildings in the city. Let $O=\{O_1,O_2,\dots ,O_n\}$ be the set of estates or their parts.

(2)

Preliminary assessment of individual estates (or their parts) using the table concerning AFRA indicators (presented in Table A1 and Table A2). Let $W_i$ denote the score for the estate $O_i$ based on the analysis of these indicators.

(3)

Assessment of the friendliness of the estates:

(a)

Calculation of the weighted average of points for the functional-spatial group $S_{F-P}$ and the aesthetics group $S_K$, adopting the estate areas $P_i$ as weights:

$$S_{F-P}=\frac{\sum _n^{i=1}{P}_i·W_{i\left(F-P\right)}}{{{\sum }_n^{i=1}P}_i}$$

(1)

$$S_K=\frac{\sum _n^{i=1}{P}_i·W_{i\left(K\right)}}{{{\sum }_n^{i=1}P}_i}$$

(2)

where

• $W_{i(F-P)}$ is the number of points for a given estate for the functional-spatial group;
• $W_{i\left(K\right)}$ is the number of points for a given estate for the aesthetics category;
• $P_i$ is the area of the estate;
• $n$ is the number of estates.

(b)

Comparison with the standard in each category. Then, comparing the weighted average with the maximum indicator value in each category, thereby obtaining an assessment of the age-friendliness of the entire city in terms of the given group of functional-spatial factors $S_{I_{F-P}}$ or aesthetics factors $S_{I_K}$:

$$S_{I_{F-P}}=\frac{S_{F-P}}{max\left(W_{i\left(F-P\right)}\right)}·100\%$$

(3)

$$S_{I_K}=\frac{S_K}{max\left(W_{i\left(K\right)}\right)}·100\%$$

(4)

where

• $max\left(W_{i\left(F-P\right)}\right)$ is the maximum number of points for the functional-spatial group;
• $max\left(W_{i\left(K\right)}\right)$ is the maximum number of points for the aesthetics group.

(c)

Calculating the weighted sum of points obtained for each spatial unit analysed, separately within functional-spatial and landscape indicators, adopting the importance of chosen factors for older adults (as in Figure 2 and Figure 3):

$$S_{F-P_{II}}=\frac{\sum _n^{i=1}{V}_{i(F-P)}·W_{i\left(F-P\right)}}{{{\sum }_n^{i=1}V}_{i(F-P)}}$$

(5)

$$S_{K_{II}}=\frac{\sum _n^{i=1}{V}_{i\left(K\right)}·W_{i\left(K\right)}}{{{\sum }_n^{i=1}V}_{i\left(K\right)}}$$

(6)

where

• $V_{i(F-P)}$ is the importance of chosen functional-spatial factors (presented in Figure 2);
• $V_{i\left(K\right)}$ is the importance of chosen aesthetics factors (presented in Figure 3);
• $n$ is the number of estates.

(d)

Comparing the obtained result for each estate (or its part) with the maximum possible score in each group (functional-spatial $S_{I_{F-P_{II}}}$ and aesthetics $S_{I_{K_{II}}}$ separately):

$$S_{I_{F-P_{II}}}=\frac{S_{F-P_{II}}}{max(W_{i\left(F-P\right)}·V_{i\left(F-P\right)})}·100\%$$

(7)

$$S_{I_{K_{II}}}=\frac{S_K}{max(W_{i\left(K\right)}·V_{i\left(K\right)})}·100\%$$

(8)

where

• $max(W_{i\left(F-P\right)}·V_{i\left(F-P\right)})$ is the maximum number of points for the functional-spatial group;
• $max(W_{i\left(K\right)}·V_{i\left(K\right)})$ is t the maximum number of points for the aesthetics group.

(e)

Determining the overall age-friendliness of a residential estate $A_i$ as the arithmetic mean of friendliness in terms of functionality and aesthetics:

$$A_i=\frac{S_{I_{F-P_{II}}}+S_{I_{K_{II}}}}{2}$$

(9)

(4)

Determining the age-friendliness of the city (separate and overall) as the weighted average of the friendliness of individual estates, with the areas of the respective spatial units $P_i$ as weights:

$$A=\frac{{\sum }_n^{i=1}{A}_i·P_i}{{\sum }_n^{i=1}{P}_i}$$

(10)

In the final stage of the procedure, instead of using the classical arithmetic mean, which may have limited informative value in the case of heterogeneous sets, the weighted average was applied. In this method, weights were assigned based on the area of each of the analysed residential estates (or their parts), following the Thiessen approach. Thiessen used this form of spatial division to determine average values on the studied area, typically scattered with irregular objects [48].

2.3. Study Area

The AFRA assessment procedure was conducted for Gdańsk, Poland, in Europe. It is a voivodeship city (the capital of Pomeranian Voivodeship), located in the northern part of the country, on the coast of the Baltic Sea (Figure 9).

In 2022, Gdańsk covered an area of 683 km² and had a population of 486,345, of which 53% were women. The population density was 1829.3 people per km². The median age of residents was 41.0 years. Older adults (aged 55 and over) constituted 30% of the community, with a demographic dependency ratio of 31.2. Among this social group, men accounted for 42%, and women 58%. The population structure by gender and age is shown in Figure 10. The population forecast for Gdańsk (Statistics Poland, 2017) predicts that the number of post-working-age individuals will steadily increase, reaching 121.2 thousand people by 2030. Among people with disabilities (14% of the city’s population), 60% are of post-working age (65% women, 35% men). The largest group of older adults live in the northern part of the city. These statistics show how large a group of older adults requires special adjustments to the urban space to meet their needs, especially in terms of mobility around the city.

The city of Gdańsk is divided into 35 city districts, which were the subject of analysis. Districts in Gdańsk vary in terms of architecture, infrastructure, character, and size. The city has a rich history and a diverse urban landscape, which translates into unique features of individual districts and estates. In Gdańsk, there are both modern estates with new residential buildings and prefabricated technology (large panel buildings), as well as older districts with a rich history and brick townhouse constructions. The size of Gdańsk’s districts also varies. The smallest, such as district number 32 (Wzgórze Mickiewicza), covers only 51 hectares, while the largest, district number 31 (Wyspa Sobieszewska), spans as much as 3579 hectares. Differences can also exist in terms of access to infrastructure, cultural attractions, or living standards.

In 2021, a detailed study of the quality of life of Gdańsk residents [51] was conducted, involving a representative sample of 1509 adult residents. The analysis aimed to understand the satisfaction level with various aspects of city life, rated on a six-point scale. The study covered areas such as overall quality of life in districts, road infrastructure, commercial and service network, public transport functioning (SKM, PKM, trams, buses), communication links, sense of security, natural environment, recreational and sports infrastructure, job satisfaction, health level and medical services, financial situation, housing conditions, beach infrastructure, and public space. The analysis showed that the overall quality of life in the city was rated at 3.78 out of 6 points. The assessment results indicated significant variations between different areas/districts of the city. Primarily, the eastern districts received the lowest ratings, ranging from 3 to 3.3 points. The next set of districts was rated between 3.3 to 3.6 points, mainly located in the western part of the city and adjacent to districts with lower ratings (Figure 11). Meanwhile, the central districts and the southern part of the city received the highest ratings, fluctuating between 3.6 and 4.0 points. The absence of districts with the highest rating may suggest that even in areas that were well-rated, there are certain aspects to improve.

3. Results

The testing of the AFRA assessment methodology was conducted in two stages: the assessment of functional-spatial layouts and the aesthetics assessment. The results were then combined to obtain an overall assessment of the estates, and these results were validated by comparing them to a separate assessment of the overall quality of life in residential areas in Gdańsk.

3.1. Assessment of AFRA Functional-Spatial Layouts

Appropriate indicator values for each factor were assigned to individual estates, under Table A1, as shown in

Table 3. Results from the age-friendliness assessment of estates in terms of functional-spatial factors (F1A–F3E factors).

Statistic	F1A	F1B	F1C	F1D	F1E	F1F	F1G	F2A	F2B	F3A	F3B	F3C	F3D	F3E
Minimum	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0
Maximum	2.0	0.0	2.0	2.0	2.0	1.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	1.0
Median	0.0	0.0	1.0	2.0	1.0	1.0	1.0	1.0	2.0	1.0	0.0	1.0	1.0	1.0
Average	0.5	0.0	0.9	1.6	1.0	0.7	1.3	0.8	1.3	0.8	0.5	1.0	1.0	1.0

Source: own elaboration. The code extensions can be found in Figure 4 and Figure 5.

and

Table 4. Results from the age-friendliness assessment of estates in terms of functional-spatial factors (F4A–F8A factors).

Statistic	F4A	F4B	F5A	F6A	F7A	F7B	F8A
Minimum	0.0	0.0	0.0	0.0	0.0	0.0	0.0
Maximum	2.0	2.0	2.0	1.0	2.0	2.0	2.0
Median	1.0	1.0	1.0	0.0	0.0	2.0	1.0
Average	0.7	0.8	1.2	0.2	0.5	1.9	1.1

Source: own elaboration. The code extensions can be found in Figure 4 and Figure 5.

. Maps of estate friendliness for individual indicators were also prepared.

The spatial analysis of estates for older adults revealed diversity in terms of functional-spatial aspects, with some areas requiring additional investments, especially in the context of older adults’ needs, while others are at a satisfactory level. Shortcomings of the estates are related to parking spaces, especially for disabled persons (indicator F1B), and general parking spaces (indicator F1A) (see Table 3).

The studied estates are characterised by a high level of biologically active surface area (F7B). These estates feature abundant low and tall greenery. They possess legible communication layouts (F1D) and illuminated communication paths (F1G). These estates have places for active rest, such as gyms and sports fields (F2B), which were rated as high or medium. In Gdańsk, certain deficiencies related to the presence of public toilets have been noticed, as well as complaints regarding the frequency of waste collection (F3E)—the indicator illustrating this infrastructure was set at a medium level. The actions of public safety services (F3D) are at a medium level, which may represent a significant area for improvement. These estates lack places ensuring safety in emergency situations, such as shelters (F6A) (Table 4). Most estates in the city are characterised by excessive building density (F7A), both in newer and older estates. The results of all indicators are presented in Figure 12.

3.2. AFRA Landscape Assessment

The process described in Section 2.2.4 was repeated for aesthetics indicators (

Table 5. Results from the age-friendliness assessment of estates in terms of aesthetics factors (K1A–K4A factors).

Statistic	K1A	K1B	K1C	K1D	K2A	K2B	K2C	K3A	K3B	K3C	K3D	K3E	K4A
Minimum	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
Maximum	2.0	1.0	2.0	1.0	2.0	0.0	2.0	1.0	2.0	1.0	2.0	1.0	1.0
Median	2.0	0.0	1.0	1.0	2.0	0.0	0.0	1.0	1.0	1.0	1.0	0.0	1.0
Average	1.5	0.4	1.2	0.9	1.3	0.0	0.7	0.8	0.8	0.9	1.3	0.5	0.9

Source: own elaboration.

).

During the landscape assessment of residential estates, certain imperfections and deficiencies were identified in terms of landscape factors. Many estates exhibit dense construction, resulting in a lack of attractive view corridors, especially from a further perspective (K2B) (Table 5). Monuments and historical spatial layouts (K2C) are predominantly concentrated in the city centre, constituting a significant landscape attraction. Spatial dominants (K3B) are present in half of the city’s estates. Access to water bodies (K1D), modern spatial layouts (K2A), and building façades with subdued colours (K3A) and tall greenery (K2B) are attractive for most estates.

Harmonious accompanying infrastructure is often uniform for selected estates or their parts (K3C). A relatively small number of objects and elements that could lower the aesthetic values of the landscape (K3E) were also noted. Furthermore, the cleanliness of the estate was considered to be maintained at a high level (K4A), constituting a positive element of the landscape assessment.

It is worth noting that despite certain imperfections, there are areas where the landscape of residential estates is favourably presented, attracting attention with its aesthetics and harmony of infrastructure. Results for the landscape indicators are presented in Figure 13.

3.3. Assessment of Estate Age-Friendliness

The age-friendliness of the estates in the city of Gdańsk was determined based on the methodology defined in Section 2.2 in two general steps:

(a)

Determining the particular age-friendliness of the residential areas in the city in terms of functional-spatial (Figure 14a) and aesthetic parameters (Figure 14b).

The grouped AFRA assessment took into account the values of the obtained parameters (Section 4), as well as their weights, which were established based on the significance level of these factors as determined by older adults, as shown in Figure 2 and Figure 3.

(b)

Joint parametric AFRA assessment.

The overall age-friendliness of individual estates in the city was calculated as the arithmetic mean of the results obtained in the context of functional-spatial layouts and landscape aesthetics, and the final result of this assessment is presented in Figure 14c.

According to the presented Figure 14a, the estates most friendly to older adults in terms of functional-spatial aspects are located in the central and north-central part of the city, being its oldest part. Meanwhile, areas in the western and eastern parts of Gdańsk are rated as the least friendly. The best result was achieved by estate 33 (Zaspa-Młyniec—78%), created in the 1970s with characteristic artistic murals on the façades, and the worst—31 (Wyspa Sobieszewska—16%), a relatively young estate built with new technology. Regarding the landscape (Figure 14b), estates in the central-eastern part of the city, such as 21 (Rudniki—20%) and 13 (Olszynka—27%), are the least attractive. In contrast, central estates, like 17 (Piecki-Migowo—84%), and those in the east, like 31 (Wyspa Sobieszewska—89%), are rated the best. There are also differences between overall assessments and assessments of individual groups of factors, as shown in Figure 14c. For example, estates rated as unfriendly in terms of functional-spatial aspects often have favourable or average aesthetics ratings (e.g., 31 Wyspa Sobieszewska or 6 Kokoszki).

As the final step in the assessment of Gdańsk, its age-friendliness in terms of aesthetics and functional-spatial layouts was determined separately and as a joint assessment. This involved calculating the weighted average of the friendliness of individual estates, with their areas as weights. In this way, the city was assessed at 56% in the context of aesthetics factors and 34% in the context of functional-spatial factors, thus giving an overall city age-friendliness rating of 45%, which can be interpreted as an average AFRA level.

3.4. Validation

The last stage of work was the verification of the proposed methodology for its correctness and universality and the results of spatial analyses based on the comparison of the obtained results with the study on the quality of life in the city, conducted on behalf of the City of Gdańsk [51]. The results are presented in the chart in Figure 15. To make a comparison between the AFRA assessment of residential estates and the quality of life in Gdańsk (Figure 11), a uniform ranking scale from 0 to 100% was applied. This procedure allowed for a direct comparison of both sets of data, scaling the results to the same percentage range.

The analysis presented in Figure 15 shows that overall, the quality of life in the estates was rated higher than the assessment of these estates in terms of their functionality, spatial organisation, and landscape (AFRA).

The results are consistent for 10 estates that achieved a ranking in the range of 60 to 80% in both categories. However, for seven estates, discrepancies were observed where the quality of life on the estates ranged from 60 to 80%, while the assessment based on AFRA parameters only fluctuated in the range of 20–40%. Additionally, nine estates received an assessment in the range of 40 to 60% in terms of functional-spatial and aesthetics parameters, while simultaneously having a high quality of life rating of 60 to 80%.

4. Discussion and Conclusions

The presented approach shows how important the parametric assessment is, taking into account functional-spatial and landscape aspects together in the overall assessment of the age-friendliness of housing estates. As a result of AFRA’s aggregate evaluation, we received divergent results than in the calculation of individual categories, which means that they should be analysed together. The impact of deficiencies noticed in one group of factors, e.g., aesthetics, can be offset by factors positively received by older adults from another group (e.g., functional-spatial).

The obtained results can serve as an important starting point for further actions aimed at improving the quality of life of older adults in estates, considering their specific needs and limitations. Thanks to the developed methodology for assessing AFRA tested using the example of the city of Gdańsk, barriers in the categories of functional-spatial and landscape were identified that may limit the mobility of older adults and their access to services. This makes it possible to implement integrated actions in Gdańsk aimed at improving urban infrastructure, such as building sidewalks, ramps, elevators, resting places, or increasing the accessibility of public transport. The results of the spatial analysis provided valuable information for urban planners and city designers, which can be used to create more inclusive and sustainable urban spaces. Utilising these results allows for the design of neighbourhoods, parks, and other public spaces tailored to the needs of older adults, promoting their social integration and physical activity. Identified places that are potentially dangerous for older adults (e.g., poorly lit streets, damaged sidewalks, lack of pedestrian crossings) should be prioritised by public administration to improve safety. This may include improving road infrastructure, increasing the number of police patrols, or educational campaigns on safety. Adapting urban spaces to the needs of seniors can attract investments in the healthcare and senior services sectors. A senior-friendly environment can activate this demographic group to use local services and businesses, which in turn can positively impact the city’s economy. This innovative diagnostic approach, which includes functional-spatial and landscape indicators, will promote the sustainable development of the urban environment, as green spaces and well-designed, accessible infrastructures that serve older adults are often beneficial for other age groups as well, contributing to the overall improvement in quality of life in the city. Consequently, a senior-friendly city will foster intergenerational integration and contribute to increased social solidarity. Creating common spaces that are accessible to all age groups will promote cooperation and mutual support among residents. Such AFRA diagnostics will contribute to creating more accessible, safe, and sustainable cities that better meet the needs of all residents, especially older adults. This innovative approach then will benefit WHO stakeholders and urban institutions responsible for policy [2,52], because the AFRA diagnostic methodology is in line with goals of sustainable development, especially for panels 3 (ensure healthy lives and promote wellbeing for all at all ages), 11 (make cities and human settlements inclusive, safe, resilient, and sustainable), and 15 (protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss) [53].

Every city should aim to carry out an AFRA diagnosis before planning its land-use budget. The vector data layers of individual indicators created during the AFRA approach show the exact locations of places that are unsuitable or not fully adapted to the needs of older people.

The overall results across the entire social group show an assessment of residential estates concerning the quality of life significantly different from the studies with the AFRA methodology, confirming the conclusions that different social groups have different needs and preferences concerning living space. These should be individually conducted for specific age groups. Furthermore, when approaching the AFRA assessment, it is necessary to renew research on social preferences, as the needs of older adults change with the generational rotation, related to the reminiscence period of older adults and economic development.

A limitation of this method towards the full automation of AFRA assessment is the necessity of conducting field inventory, which supplements spatial data with qualitative data about the space, essential for landscape assessment. Considering the research development in automating landscape assessment [54,55,56], progress enabling the full automation of AFRA assessment is expected shortly.

In future studies, the authors plan to test the developed scale on residential estates for the AFRA assessment of cities in other countries. When verifying this assessment, the survey should be repeated in the social group in the selected area; however, the results might be distorted by emotional values and long-term attachment to a given area and habits. Social relationships and family bonds of older adults were not studied because they are difficult to define and quantify—they are not spatial data, so it is impossible to include this indicator in an automated algorithm. The scale was adapted to access spatial data, but as data availability online increases, this scale can easily be expanded and modified. However, it should be developed locally—every city has its specificity and cultural-historical heritage, from which local habits and values arise. Therefore, standardised scales provide a general view and knowledge about the quality of such estates, but immeasurable (local) elements also affect the assessment of these estates and the quality of life on them.

These results confirm the hypotheses set at the beginning: (1) the methodological assessment of AFRA will differ from the quality of life assessment in estates conducted by the general population (older adults have different needs than the general society); (2) the availability of various functional facilities matters in the process of assessing the AFRA level of the public open space of the estate; (3) the impact of a given factor on the surface of the entire housing complex appears to be significant.