The Strengthening capacities in the use of geospatial information for improved resilience in Asia-Pacific and Africa project aims to develop the capacities of eight national governments in Asia-Pacific and Africa (Nigeria, Uganda, Lao PDR, Bhutan, Bangladesh, Fiji, Solomon Islands and Vanuatu) by using geospatial information in decision-making to improve disaster risk management and natural resource management.
The baseline evaluation assessed the entry level project conditions to provide a baseline against which the project’s progress can be measured and evaluated. Specifically the evaluation validated and obtained baseline evidence on the project’s log frame indicators; validated the adequacy of the log frame and indicators, performance measures, means of verification and underlying assumptions; verified the project’s theory of change; and validated the project’s implementation strategy.
The evaluation followed a participatory approach where project stakeholders, and the primarily project team members and management-level representatives of the project’s focal agencies were engaged. Qualitative interviews with national stakeholders were used to develop a scorecard survey inspired by the Global Environment Facility capacity development interventions’ approach.
The evaluation encountered two limitations, namely; that the baseline evaluation was conducted during the inception phase with most national experts not yet recruited and the specific project interventions still under discussion, and that the evaluation could not obtain data for the Pacific islands on the digital socioeconomic and gender divide and for Vanuatu and Solomon Islands on the damaged caused by Cyclone Harold.
Key evaluation findings and conclusions
The evaluation produced the following key findings and conclusions: First, project countries have different national circumstances and applications for geospatial information and earth observation technologies. Therefore, specific activities in each country constitute separate projects, leading to different outputs, outcomes and potential impacts. Fiji, Vanuatu and the Solomon Islands have a designated authority/focal point for international funds, with the capacity to implement additional international funding for climate change adaptation and mitigation.
Second, the project’s strategy is the most effective means of delivering the intended benefits (increased capacity to use geospatial solutions). The expected social benefits will likely surpass the expected costs assumed by the beneficiary/ focal agencies. In that capacity, it also addresses technical issues, responding to specific capacity development demands by government organizations of the targeted countries.
Third, the strategy aligns with multiple national and sectoral development strategies, framed in the outcomes of UN conferences, including the International Conference on Small Island Developing States and the 2030 Agenda for Sustainable Development. Other related initiatives include the SERVIR interventions in Southeast Asia and South Asia and the JICA-funded project in Bhutan which are currently implemented and specifically directed towards developing the national spatial data infrastructure. Furthermore, the project also incorporated lessons learned from previous UNITAR-UNOSAT interventions. The evaluation found the project to be gender-targeted, aiming to achieve parity in access to capacity development.
Moreover, beneficiary organizations have sufficient budgetary allocation and institutional capacity and function explicit in national strategy documents to continue the application of technical solutions implemented through the project.
Last, the results chain is partially logically linked and based on sound assumptions. The original project’s logical framework impact indicators do not reflect, or cannot be attributed to, the project. Impact indicators can be better gauged by national capacity, measured as means of score cards or surveys.
Based on the findings and conclusions above, the evaluation produced three main recommendations, divided into sub-recommendations.
R1: The project’s log-frame outputs could be defined beyond “capacities developed” to match the specific national demand for geospatial products. The specific outputs e.g., “applications to evaluate climate risk in land parcels” or “satellite-based oil spill monitoring application” are needs identified by the national beneficiaries (government organizations) to minimize public sector costs and maximize social benefits from a potential market-driven upscale of the project’s outcomes.
R2: The project could strive to be gender responsive by promoting disaggregated data collection and dissemination, in all levels of the project.
a. Number of women/ other groups made vulnerable participating in training;
b. Number of women/ other groups made vulnerable participating in technical teams;
a. Number of women/other groups made vulnerable successfully completing the training
b. Number of project’s focal agencies that collect disaggregated data based on gender and other vulnerable groups
a. Disaggregated data are incorporated into decision-making processes. E.g., climate funding proposals address differential exposure, vulnerability, and impacts of hydrometeorological hazards on men, women, and vulnerable groups
R3: The logical framework must respond to realistic assumptions and logical connections between activities, outputs, and outcomes. Therefore, the results framework should:
a. Not include indicators of impacts not attributable to the project, such as disaster loss and damage changes, and only suggest contributions to these areas.
b. Include specific outputs related to the needs of the eight government organizations involved.
c. Reformulate the outcomes according to the intended use of the project’s outputs (organizational change).
L1: Access to project stakeholders is key for baseline evaluation consultations and measures.
L2: Projects that benefit countries from different regions with different needs require logical frameworks that account for those differences.
L3: It is useful to build new projects based on the lessons learned of previous projects.
L4: Identifying counterfactuals is a challenging task given the numerous differences and collecting data for counterfactuals remains more challenging than collecting data for target countries.
L5: Impact indicators need to be formulated in a way that the project can measure some contribution/attribution.