‘Participatory data’ and the formulation of Tourism Development Area Management Plans in Samoa

Developing agriculture to better serve tourism markets in the Pacific is knowledge intensive. The first step is to determine the tourism market’s demands for agricultural produce and then to match this with what is available from local production. But much of this information is not currently readily available.

Bridging this information gap was a key objective of the recent Agribusiness Forum: Linking the agrifood sector to the tourism-related markets coordinated by CTA and the Pacific Islands Private Sector Organisation (PIPSO) with support from the Secretariat of the Pacific Community (SPC), the Pacific Agriculture Policy Programme (PAPP) and the intra-ACP Agricultural Policy Programme (Intra-ACP APP). This event, held in Fiji from 1 to 3 July 2015, brought together experts from government agencies, farmers’ organisations, community-based organisations, remote sensing and research bodies to identify the data gaps and discuss how to go forward.

Giving a community perspective, Amia Luatua from the Samoa Tourism Authority, shared Samoa’s work on tourism planning, showing how communities have used participatory 3D modelling (P3DM) to collect data that have been used to inform tourism developments.

Participatory Data: Public or Private?

Participatory 3D modelling (P3DM) is a community-based process centred, which integrates local spatial knowledge with data on elevation of the land and depth of the sea to produce physical 3D models. Residents of a given area assemble a 3D model of the territory they rely on for their livelihoods and cultural practices. P3DM is used for a number of purposes and addresses a range of issues including spatial planning, land tenure, climate change adaptation, intergenerational knowledge exchange, building community identity, documenting local knowledge for advocacy purposes, and more.

P3DM has been used mostly in developing countries in rural areas. A P3DM exercise covering an area of 1000 km2 at a 1:10000-scale lasts approximately 10 days and involves 50-100 knowledge holders. The resulting 3D map stores a huge amount of geo-located data, matching a well-defined legend. The legend - developed by the local communities - includes point, line and polygon data; it reflects local and traditional knowledge of all sectors of society, including women and elders. Free Prior Informed Consent (FPIC) obtained, data displayed on the 3D model are imported into GIS environments and further analysed and compared with other data sets. Depending on the scale used, a P3DM exercise may generate up to 80 layers of information including land cover, resource use and tenure, social infrastructure, settlements, sites of cultural significance and more. Some data may be considered as sensitive by the knowledge holders and treated as confidential (i.e. removed from the model or stored as classified layers in a GIS). Custodians of data (usually NGOs operating on behalf of communities) should manage these according on ethical principles and agreed procedures.

P3DM works best at 1:5000 – 1:10000 scale or larger. The larger the scale (1:5000 is larger than 1:10,000), the more detailed and diversified the input of the knowledge holders will be. As a consequence, P3DM can be applied on moderately large areas (1000-4000 km2) at a time, although repeated exercises may result in the full coverage of small island nations. In countries covering large portion of the Earth, P3DM can and should be applied on selected “hot spots” to address specific issues.

As a follow-up to the 2006 “Mapping for Change” Conference which took place in Nairobi, the Community of Practice devoted to the improvement of Participatory GIS (PGIS) practice, developed guidelines on “Practical ethics for PGIS practitioners, facilitators, technology intermediaries and researchers” available 12 languages.

Data generation is part of the P3DM process, but not its end. Evidence has proved that as a result of the process, knowledge holders gain a deeper understanding of their bio-physical and social environments, heightened awareness on the importance of sound and climate-smart resource management and more. Data are usually generated to serve the process as the communities (all generations) learn by doing and to empower knowledge holders in interfacing with higher authorities.
Sharing of data is strategic and meant to serve purposes set by the knowledge holders. On the other hand the process allows for traditional and scientific knowledge systems to come together and make use of or build on the best of the two “worlds”.