Digital technologies are transforming how we assess the long-term impacts of transport infrastructure. Long before economic trends appear in official statistics, satellite imagery, geospatial data, and artificial intelligence (AI) can reveal where communities are growing, agriculture is expanding, and commercial activity is increasing.
Along the Enga Highway corridor in Papua New Guinea, these technologies helped demonstrate how rehabilitating a deteriorating and unreliable road with climate-resilient engineering strengthened connectivity, supported trade, and enabled community development over more than a decade.
To evaluate these outcomes, we partnered with Rural Senses, a company that specializes in conducting impact assessments of projects in developing countries. The assessment combined Earth Observation, AI, geospatial data, and field research to understand how climate-resilient infrastructure has shaped local communities and economies over time.
Several technologies played important roles in both delivering the highway project and measuring its long-term impacts.
The use of Full Depth Reclamation and pavement stabilization strengthened the existing road structure, improving durability, reducing future maintenance, and increasing resilience to climate-related deterioration.
Satellite-based Earth Observation was used to track changes along the highway corridor over time. By comparing historical and current imagery, researchers identified settlement growth, agricultural expansion, and increasing commercial activity. This provided an objective and cost-effective way to monitor development across a large and remote region.
All interviews were geo-tagged using GPS coordinates collected during fieldwork. This enabled the evaluation team to verify respondent locations, map the distribution of beneficiaries, and analyse how impacts varied between communities, strengthening both data quality and geographic accuracy.
AI supported the design of the impact assessment by reviewing evidence from comparable road rehabilitation projects worldwide. These insights informed the Theory of Change, stakeholder mapping, and the selection of indicators used to assess the project’s social, economic, and environmental outcomes.
AI-supported tools enabled interviews to be conducted in local languages, allowing respondents to engage in more natural conversations than traditional surveys. This improved participation and produced richer qualitative insights. Following data collection, AI-assisted transcription, translation, and coding significantly reduced processing time while preserving the depth of stakeholder perspectives.
Machine learning and AI-assisted analytical tools identified recurring themes, analysed sentiment, and assessed stakeholder perceptions of the highway’s impact on daily life, access to services, and economic activity. These techniques enabled the evaluation team to efficiently analyse large volumes of qualitative data and uncover patterns that would have been difficult to identify manually.
While technology strengthened every stage of the assessment, it was only part of the solution. The success of the evaluation relied equally on local knowledge, experienced field teams, and meaningful engagement with communities along the highway. Technology identified patterns and processed large volumes of data, but the local researchers and project team provided the context needed to understand why changes had occurred and how they affected people’s lives.
By combining quantitative surveys, qualitative interviews, satellite observations, and administrative data, the assessment measured changes in mobility, healthcare access, education, market participation, transport services, and local economic activity. Collecting both before-and-after evidence and asking stakeholders to explain the reasons behind observed changes also enabled the team to explore causality, not simply whether conditions improved, but the extent to which those improvements resulted from the highway rehabilitation.
This blended approach demonstrates that robust technology delivers the greatest value when combined with local expertise and direct engagement in the field.
The assessment found that the climate-resilient rehabilitation of the Enga Highway generated substantial and lasting benefits for communities along the corridor. Stakeholders reported improved mobility, more reliable transport services, better access to healthcare and education, stronger market participation, and increased economic opportunities.
These findings were reinforced by satellite observations, which showed expanding settlements, increased agricultural activity, and growing commercial development along the corridor. Together, the evidence demonstrates how resilient infrastructure, supported by both advanced technology and strong local engagement, can drive sustained community and economic development over time.
Rural Senses is a team of impact experts that provides state-of-the-art technologies and methodologies to measure, manage, and communicate impact. With an extensive global network of data collectors, Rural Senses is equipped to conduct surveys and gather valuable data in diverse rural and urban areas across the globe.
Infrastructure doesn’t just move vehicles — it transforms lives, livelihoods, and entire communities. Because to build better infrastructure, we first need to understand what truly matters.
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