Participatory Geographical Information System (PGIS) and drivers of Mangrove forests loss and their implications on the people’s livelihoods

Abstract

Tanzania’s coastal communities, including the people of Zanzibar, largely depend on mangroves for fishing, wood for construction and for fuel. The increasing threat of mangroves disappearance due to anthropogenic and climate change factors would therefore affect the livelihood of coastal communities living in close proximity to the said forests.

In the last decade, there has been a strong drive towards integrating Geographical Information System (GIS) into community-cantered initiatives, particularly to deal with spatial information gathering and forest planning. Despite the increased use of participatory GIS methods in the developed and developing world, little has been published in Africa on the innovation because of cost and low accuracy levels of PGIS compared with conventional GIS. Moreover, most studies conducted on PGIS and forest management have been at the national and regional levels. This situation demonstrates the need for local scale studies on PGIS and the contribution of anthropogenic and climatic factors on mangrove forest loss.

A number of studies have been conducted in Zanzibar on GIS and PGIS and forest planning and management. Majority of the research activities have been focusing on farming strategies, landscape characterization and community stakeholders’ knowledge in landscape assessments. However, studies on mangrove forest loss have been few. Majority of these few studies conducted in Zanzibar have relied on conventional GIS and non-spatial participatory approaches. These techniques often show the status of the situation but such tools can hardly capture the reasons and the manner in which the situation occurs. Participatory GIS is highly needed to provide more precise information about all aspects of mangrove forests loss. Moreover, most PGIS studies conducted in Zanzibar, like in other developing countries, have only involved local communities during data collection. This approach has increased the many questions on the authenticity of PGIS output. This study therefore will involve local people in data processing and analysis, which is a new dimension in the PGIS application.

In this research local knowledge will be collected through traditional public meeting, GPS transect walks and mapping exercise using the most recent digital geo-referenced aerial photographs (2015, 0.5m pixel size). Kernel density and hotspot techniques will be used to analyse information from community mapping while supervised classification technique will be used to analyse satellite images so as to inform on the status and trend of mangrove forest.