The HEC-RAS 1D hydrological simulations for a 10-year return period storm (100 mm in 24 hours) demonstrated a notable decrease in flood hazard under the post-SPA scenario. Implementation of 720 m of primary drainage channels and slope-aligned secondary drains resulted in an overall 27% reduction in flood-prone surface area compared to the pre-SPA baseline as shown in Table 1 ([27]).

Table 1. Flood exposure reduction across 3 villages.

Source: Field Survey, 2025.

Across all villages, flood exposure declined by approximately 27%, protecting over 13,200 people residing in riparian zones exceeding the 0.3 m inundation depth threshold, corresponding to the residential structural damage benchmark ([16]).

The population comprised approximately 1800 households spread across the 3 villages with a household size ranging from 7 - 8 members. The most positively affected settlements were KKR and VWD with approximately 975 and 650 households respectively. The most significant improvements occurred near newly constructed trunk sewers in KKR ([27]; [11]). To include river proximity as a flood hazard factor, the river shapefile was converted into a feature layer. Euclidean distance from each cell to the nearest river was computed using the EucDistance tool, generating a continuous distance raster ([9]).

Raster Normalization—All continuous hazard factors were normalized to a 0 - 1 scale to allow for weighted overlay. A custom function calculated (value − min)/(max − min) for each raster. The following were factors normalized:

1) Flow accumulation-kept as is (higher accumulation = higher hazard).

2) Distance to river-inverted (1 − normalized distance) so closer proximity means higher hazard.

3) Slope-inverted (1 − normalized slope) so flatter areas mean higher hazard.

4) NDVI-inverted (1 − normalized NDVI) so low vegetation density means higher hazard. NDBI: kept as is (higher built-up index = higher hazard).

5) The process produced-Preprocessed hydrological layers (filled DEM, flow direction, flow accumulation), Normalized hazard factor rasters and Continuous flood hazard index raster. It further classified flood hazard maps as (low, medium, high zones) ready for visualization and further spatial analysis as shown in Table 2, Map 2 and Map3 below.

Source: Field Survey, 2025.

Map2. Flood risk time series for 1990, 2000, 2010 and 2020.

Table 2. Flood risk trends for 1990, 2000, 2010, 2020 and 2025.

Source: Field Survey, 2025.

Source: Field Survey, 2025.

Map3. Flood risk time series for 2025.

Table 3 and Table4 show Landsat 8-derived LST and NDVI indices, with the thermal classification revealing substantial spatial gains in vegetated cover and shading. Under the SPA scenario, tree-planting programs, reflective roof coatings, and pocket parks reduced high-risk heat zones (>34 ˚C) by 23% overall ([15]). Map4 and Map5 show the spatial distribution.

Table 3. Heat stress trends for 1990, 2000, 2010, 2020 and 2025.

VWD saw the greatest percentage reduction in heat-stressed areas. This is attributed to adoption of better building materials like masonry, concrete on roof slabs as compared to iron sheet roof, Glass and steel on doors and wider window openings as compared to KKR and KKN still Masonry is found to have less surface reflectance as compared to Iron sheets leading to a recording of reduced surface temperatures. However, absolute high temperatures still exceed 36.37 ˚C in certain dense clusters of all the 3 villages ([8]).

Source: Field Survey, 2025.

Map4. Heat waves time series for 1990, 2000, 2010 and 2020.

Source: Field Survey, 2025.

Map5. Heat waves time series for 2025.

Table 4. Heat wave across the 3 Villages.

Source: Field Survey, 2025.

NDVI change detection was performed through pixel-wise subtraction between NDVI rasters of consecutive years (e.g., 2000-1990, 2010-2000). Table 5 indicates Positive Values showing vegetation gain (regeneration or new greening) while Negative Values indicate vegetation loss (built-up expansion or degradation). Across all years, the minimum value is −0.5464 and the maximum value is 0.6479. Map 6 and Map7 show the spatial distribution.

Source: Field Survey, 2025.

Map6. NDVI dataset for 1990, 2000, 2010 and 2020.

Table 5. NDVI dataset for 1990, 2000, 2010, 2020 and 2025.

Source: Field Survey, 2025.

Source: Field Survey, 2025.

Map7. NDVI dataset for 2025.

The Normalized Difference Built-up Index (NDBI) was calculated to identify and analyze built-up areas using multispectral Landsat imagery. The method utilizes the spectral characteristics of built-up surfaces in the shortwave infrared (SWIR) and near-infrared (NIR) bands. Higher NDBI values indicate a greater likelihood of built-up surfaces (concrete, asphalt, rooftops).

Spatial changes in NDBI between years were interpreted as indicators of urban expansion or transformation as shown in Map 8, Map9 and Table 6 below.

Source: Field Survey, 2025.

Map8. NDBI dataset for 1990, 2000, 2010 and 2020.

Source: Field Survey, 2025.

Map9. NDBI dataset for 2025.

Table 6. NDBI dataset for 1990, 2000, 2010 and 2020.

Source: Field Survey, 2025.

When comparing the two key resilience indicators—extreme temperature exposure and flood risk—Viwandani (VWD) emerged as the most consistently resilient zone, showing strong capacity for heat mitigation and moderate improvements in flood risk reduction. In contrast, from Figure 2, Mukuru Kwa Reuben (KKR), which initially exhibited the highest vulnerability on both fronts, recorded the most substantial overall gains, particularly in lowering exposure to extreme temperatures and significantly reducing flood-related risks ([19]).

Source: [15].

Figure 2. Comparative Resilience gains for the 3 villages.

This 35-year longitudinal analysis reveals that integrated spatial planning under the Mukuru Special Planning Area (SPA) has delivered measurable improvements in climate resilience across Nairobi’s most vulnerable informal settlements. Empirical results show a 27% reduction in modeled flood exposure and a 23% decrease in high heat-stress zones, confirming that spatially targeted and participatory planning can yield substantial resilience gains even in high-density, low-income contexts. These improvements were primarily achieved through the combination of upgraded drainage systems, green infrastructure, reflective roofing, and targeted pollution source management, all coordinated within a multi-sectoral, community-driven governance framework ([19]; [15]).

The observed decline in flood exposure across Mukuru Kwa Njenga (KKN), Mukuru Kwa Reuben (KKR), and Viwandani (VWD) aligns closely with international evidence linking nature-based drainage systems and formalized stormwater infrastructure to reduced urban flood risks ([17]; [4]). According to the [17], sustainable urban drainage systems (SUDS) and integrated catchment management enhance adaptive capacity by restoring ecological functions while mitigating hazard exposure in flood-prone cities. The results from Mukuru corroborate these global findings—showing that drainage and slope-sensitive designs can function effectively even in spatially constrained settlements. The 27% average reduction in flood-prone surface area, as shown in Table 1, provides quantitative evidence that well-engineered drainage networks—when integrated with local terrain and hydrology—can yield equitable hazard mitigation benefits across multiple villages, not only in pilot areas. This confirms [21] and [23] findings that small-scale, decentralized drainage interventions can collectively transform informal settlement resilience when implemented under an inclusive planning framework.

Similarly, the thermal comfort improvements as shown in Figure 3, observed—particularly the 24.9% reduction in heat-stressed zones in Viwandani (VWD)—underscore the efficacy of urban greening and reflective materials as adaptive cooling strategies. Literature consistently supports this outcome: [2] and [15] highlight that vegetation and improved roofing materials substantially lower localized surface temperatures in informal neighborhoods where conventional cooling technologies are absent. The inclusion of pocket parks, shade trees, and reflective roofing in the Mukuru SPA framework has thus mitigated the urban heat island (UHI) effect even in areas with minimal baseline vegetation cover. This mirrors global evidence from [27] and [9], who found that community-led greening initiatives and cool roofing programs reduce heat exposure while improving public health outcomes.

Source: [15].

Figure 3. Visual summary of spatial resilience assessment across Mukuru Villages.

Moreover, the results affirm that multi-hazard resilience—addressing both flooding and heat stress—can be achieved within a single integrated spatial planning framework rather than through fragmented, sector-specific projects. This supports the argument by [28] that urban resilience is maximized when infrastructure, social inclusion, and environmental management are addressed synergistically. The Mukuru SPA exemplifies this approach: it integrates community mapping ([16]), participatory design, and data-driven decision-making to identify local hazard zones and co-produce solutions. This approach aligns with the [8], which emphasizes locally led adaptation as a cornerstone for climate resilience in informal settlements.

For policymakers and urban planners, the Mukuru experience demonstrates that aligning public infrastructure investments with community-generated spatial data can produce measurable resilience dividends and foster social inclusion. [27] argues that co-production between government and community groups enhances both the efficiency and legitimacy of urban resilience initiatives. The 27% and 23% hazard reductions recorded in Mukuru therefore provide empirical backing for scaling integrated, participatory spatial planning across other high-risk informal settlements in Sub-Saharan Africa. Finally, for funding agencies, the findings underscore the importance of long-term financing mechanisms that sustain drainage maintenance, vegetation management, and data-driven monitoring beyond donor project cycles—echoing recommendations from [16] and [20].

In summary, this study provides robust evidence that inclusive, spatially targeted urban planning, when supported by participatory governance and geospatial analysis, can produce transformative improvements in climate resilience. The Mukuru SPA stands as a replicable model demonstrating how local-level interventions—if well-coordinated and scientifically grounded—can yield long-term, equitable adaptation outcomes in rapidly urbanizing African cities.

To build on the progress made through the Mukuru Special Planning Area (SPA) initiative and address remaining climate resilience gaps, three core recommendations are proposed. First, spatial inequalities in resilience outcomes must be addressed by prioritizing infrastructure investments in the most vulnerable areas, particularly Mukuru Kwa Njenga (KKN), where exposure to flooding and extreme temperatures remains significant. Findings from the International Growth Center agree with this report that where policymakers are content to retain land under residential use, participatory in-situ slum upgrading is a cost-effective solution that can enable informal settlements to incrementally transform into poor but highly livable neighbourhoods, integrating the city’s low-income workforce into the urban fabric ([6]). It further reports that where informal settlements are located on land that is either unsafe for habitation or needed for vital urban infrastructure, resettlement may be necessary. This solidifies the need to either relocate residents from riparian reserves and other vulnerable areas or strengthen infrastructural interventions ([7]).

Second, the integration of participatory spatial planning tools into formal urban governance structures is essential ([19]). The Mukuru SPA’s success demonstrates the value of community-generated data, thematic consortia, and open GIS platforms in delivering inclusive and adaptive urban planning Nairobi County should institutionalize these tools and processes, embedding them within its planning frameworks to ensure continuity and scalability. Community-based organizations (CBOs) should continue to play a central role in co-producing spatial knowledge and monitoring implementation to maintain accountability and local ownership. This agrees with the idea that community resilience is a dynamic process and that these dynamics are not necessarily reflecting community needs but may instead reflect adaptive capacities of CBOs and their networks ([17]). The ability to sustain adaptive activities is associated with a strong endogenous capacity as well as exogenous bonding capacity.

Developing localized adaptation sub-plans tailored to each village’s unique risk profile can ensure that interventions respond effectively to micro-level environmental challenges. These plans should be informed by high-resolution spatial data and community-led assessments to capture nuanced hazards that may be missed by satellite imagery alone. The Global center for adaptation in its study on locally led adaptation measures in Mukuru reports that you cannot plan without the people, if you plan without the people, you are planning to fail. Therefore, the community coordination consortium comprised of AMT, Muungano wa Wanavijiji (MWW) and Slum Dwellers International-Kenya (SDI-K) had to work closely with Mukuru residents to mobilize people to attend more than 250 neighborhood planning forums and 114 formal consultation meetings held by the different planning consortia ([6]). This solidifies the argument that Participator planning lead to locally-appropriate planning standards that make sense in the context of the vulnerabilities and resource constraints in such settlements.

Finally, to sustain and replicate the gains made through the SPA, long-term financing and policy alignment are critical. Establishing a dedicated fund for the maintenance of climate-resilient infrastructure—such as drainage systems and green corridors—will help preserve functionality beyond the lifespan of donor support. Moreover, aligning local interventions with national climate and urban development policies can strengthen coordination across sectors and levels of government ([19]). By embedding resilience metrics into official performance indicators, Nairobi County can institutionalize continuous monitoring and ensure that resilience-building remains a core element of urban development. The UN-Habitat reports that Urban policy and legislation are key in promoting sustainable informal settlements transformation by enabling institutions and creating mechanisms for cities to unlock funds for services and infrastructure in deprived areas ([3]). For instance, the Special Zones of Social Interest (ZEIS) established by the City Statute, Federal law in Brazil, enabled the recognition of land occupations that were a key entry point to land regularization and adaptation of planning and infrastructure standards to existing settlement patterns that avoided mass displacement. Strong policy frameworks from government institutions, therefore, are important to build equitable and resilient urban futures as part of an effective city wide planning.

This study provides compelling evidence that integrated spatial planning anchored in participatory processes and geospatial analysis—can significantly enhance climate resilience in informal settlements. Through a longitudinal, 35-year assessment of Nairobi’s Mukuru Special Planning Area (SPA), as shown in Map10, the research quantified the impacts of targeted infrastructure and environmental interventions on flood risk and urban heat exposure. Key findings indicate a 27% reduction in flood-prone surface area, protecting over 13,200 residents across Mukuru Kwa Njenga (KKN), Mukuru Kwa Reuben (KKR), and Viwandani (VWD), settling along the riparian reserve who had to be relocated. Thermal analysis revealed a 23% decrease in high heat-stress zones (>34 ˚C), with Viwandani achieving the highest reduction at 24.9%, primarily due to early implementation of green corridors and shaded public spaces.

Source: [15].

Map10. Flood prone areas before and after SPA status.

Notably, while all three villages recorded resilience gains, the outcomes varied spatially. KKR, despite being the most vulnerable initially, recorded the highest marginal improvements, while Viwandani maintained consistent resilience performance due to its proactive planning and strong community-based engagement. These disparities underscore the importance of spatially differentiated interventions, guided by localized risk assessments and community participation ([17]).

In summary, the Mukuru SPA showcases a replicable model for climate adaptation in informal urban areas. By integrating high-resolution spatial diagnostics, community-led mapping, and thematic infrastructure planning, it is possible to deliver measurable, equitable improvements in urban resilience. Scaling such approaches across other at-risk settlements in Sub-Saharan Africa offers a transformative pathway toward inclusive, climate-resilient urban futures.