1. Base geography

This frame defines the Metro Manila study area within which user-testing suitability is assessed. It establishes the spatial relationship between central Manila, western coastal districts, northern extensions, and eastern corridors so that later claims about density, access, and competitor activity can be interpreted as part of one connected urban system rather than as isolated neighborhood observations.

• The study area spans the core Metro Manila corridor where housing demand, access, and competitor activity can be compared within one connected urban system.
• The frame sets the geographic boundaries for evaluating candidate user-testing sites.
• All later accessibility and market signals are meaningful because they are located within this shared metro context.

2. Population density

This map shows population concentration at a metro-wide scale and begins the demand-side argument for microhousing. The strongest intensity appears concentrated in the western and central urban core, suggesting that demand pressure is not evenly distributed and that early testing should focus on the districts where dense residential life is already embedded in the city fabric.

• Population density is strongest in the western and central urban core, making those districts the most credible starting points for microhousing demand testing.
• Density provides the first screen for where user-testing demand is likely to be most visible.
• Metro-wide coverage is less useful than focusing on the densest urban bands.

3. Density by district

This district-level density view sharpens the broad metro pattern into a more actionable neighborhood screen. Instead of simply showing that Manila is dense, it highlights which barangays and local districts are packed tightly enough to justify fieldwork, survey distribution, and early supply-side investigation. At this stage, the goal is not only to find density, but to identify dense areas that also sit near business districts and university districts, since those overlapping conditions are more likely to support real demand for microhousing from workers, students, and other urban renters. The analysis begins to move from general demand potential toward specific location selection.

• District-level density reveals which specific barangays merit fieldwork, moving the analysis from metro-wide demand to actionable neighborhood prioritization.
• The target is not density alone, but density near both business districts and university districts.
• These overlaps help identify where demand for microhousing is more likely to be strong enough to justify user testing.

4. Transportation accessibility

This frame introduces mobility as a livability filter by overlaying bus and rail accessibility with jeepney-stop density. The analysis uses a 150-meter buffer for bus access and a 500-meter buffer for rail access. The shorter bus radius reflects the expectation that bus-stop utility is more immediate and street-dependent, while the larger rail radius reflects the greater catchment area people will tolerate for higher-capacity transit. Jeepney stops were not treated the same way because they are so prevalent across the metro that a buffer approach would overwhelm the map and flatten useful variation. Instead, jeepney access is evaluated through density, which better captures where coverage is truly concentrated. For microhousing, density alone is insufficient if residents cannot move through the city efficiently, so transportation access narrows the candidate set to places where smaller-format living is more likely to remain workable in everyday practice.

• Transportation access filters dense districts down to places where compact living is actually workable for everyday commuting and movement.
• Bus access is measured at 150 meters, while rail access is measured at 500 meters to reflect different transit catchment assumptions.
• Jeepney stops are assessed through density rather than buffers because their prevalence would otherwise obscure meaningful variation.

5. Hospital accessibility

This hospital-accessibility layer adds a second urban-service dimension to the suitability analysis. While hospital proximity is not the only service measure that matters, it acts as a useful proxy for broader neighborhood support and institutional coverage. Hospital accessibility is assessed through a 500-meter buffer radius, which provides a practical way to estimate whether basic healthcare access is available within everyday reach. At the same time, this measure has an important limitation: hospitals differ substantially in size, specialization, and service capacity, so proximity alone does not imply equivalent healthcare quality across all sites. When combined with transportation, the layer still helps distinguish dense but under-supported areas from places where compact urban living is more realistically sustainable.

• Hospital proximity adds a service-quality layer, helping distinguish neighborhoods that are merely dense from those that are realistically livable.
• The analysis uses a 500-meter hospital buffer to estimate whether healthcare access falls within practical reach.
• Hospital proximity is informative, but not all hospitals are equal in size or capacity, so this layer should be read as a proxy rather than a full quality measure.

6. Urban accessibility composite

This composite layer is the most operational map in the set because it brings the main accessibility and demand signals into a single site-selection view. The layer is built through an intersect analysis of the transportation and hospital buffers, while jeepney access is left as a density layer so that the map continues to show where that form of mobility is most concentrated. That accessibility structure is then read together with population density and the presence of both business and university districts. The goal is to pinpoint places where the strongest overlap of accessibilities, demand, and district relevance suggests a suitable location for user testing a microhousing platform.

• The composite layer is the clearest site-selection tool because it identifies where density and urban accessibility overlap most strongly.
• The core composite comes from intersecting transportation and hospital buffers while preserving jeepney density as a separate spatial signal.
• The strongest candidate sites are where accessibility, population density, and proximity to both business and university districts overlap most clearly.

7. Competitor listings

This frame introduces observed market behavior by plotting two different competitor types across the study area. The yellow triangles denote a domestic competitor platform operating in the same sector with a similar platform model, while the red circles denote an international competitor, Airbnb, that serves a meaningfully different market from microhousing. The contrast matters. Airbnb activity appears concentrated nearer to higher-end and more expensive business districts and is less visible in the kinds of areas where microhousing demand would likely be strongest. By comparison, the domestic competitor shows a more concentrated listing pattern west of Makati City and near Manila Bay, just above the airport, making it more relevant as a benchmark for where similar demand may already be active.

• Yellow triangles represent a domestic competitor with a platform model closer to Roomie's market context.
• Red circles represent Airbnb, which maps a different and more expensive segment than microhousing.
• The domestic competitor's concentration west of Makati and near Manila Bay is more informative for microhousing-relevant user-testing demand.

8. Competitor listing density

This final density view focuses more closely on the domestic competitor's listings rather than treating all competitor points equally. The main concentration appears west of Makati City and along the Manila Bay corridor just above the airport, which suggests that this area is already active enough to be a practical candidate for user testing. At the same time, the analysis also shows that areas north of that corridor appear even stronger on some of Roomie's own demand-side signals: population density is higher, the composite accessibility layer is more prevalent, and competitor attention appears less concentrated. That contrast is useful because it suggests two different kinds of testing logic: one site where comparable market activity is already visible, and another where underlying suitability may be strong even before competitors have focused heavily on it.

• The domestic competitor is heavily concentrated west of Makati and near Manila Bay above the airport, making that corridor a credible user-testing site.
• North of that corridor, population density and composite accessibility appear even stronger while competitor concentration is less intense.
• That northern zone may therefore be another viable testing location, especially if Roomie wants to test demand in a less saturated competitive pocket.