Chapter 2. Characteristics of the Study Area,Data Utilized,and Modeling Approach

Summary

A wildfire hazard and risk model was developed in a week-long workshop to test the feasibility of using existing resource data and combined expert assessment to help address the increasing concern over wildfires in the Western United States. The goal was to utilize readily-available resource data, translated into a GIS format, to develop and illustrate relative hazard and risk assessments in a format that would be useful to decision makers. This paper discusses the characteristics of the study area, the data that were assembled, and the methods utilized. The results of the hazard and risk assessments are discussed in the papers that follow.     

Mapping landscapes: Integrating GIS and social science methods to model human-nature relationships in Southern Cameroon

Participatory mapping and GIS are both necessary to model the interactions between humans and their environment. A case study from the forest margin in the Congo Basin demonstrates how data from participatory community mapping and other social science methods can be prepared for quantitative modelling. This approach bridged the gap between spatial modelling data and social decision-making in space by elaborating a geographically consistent social representation of the landscape and giving a geographical base to the connection between land use, its cultural representation, and its social management. This was achieved through an iterative process of GIS cartography, using feedback from village informants and field checking, to transpose the spatial references from participatory mapping sketches into reliable geographic locations. As well as demonstrating the utility of such data for modelling, this work clarified the distribution of land rights among the six main owner-clans spread through the eight hamlets in the watershed. The ‘basin’ of spatial resources and its relation to the rules of land use and natural resource management were defined for each clan. Land-use systems at the forest-agriculture interface in the study area proved to be complex, strongly driven by social rules and influenced by history and settlement strategies. These social and historical aspects established the framework within which communities make current decisions and interventions. The authors thank the people of Akok for their collaboration and hospitality. Village technician Michel Engueng and village contact Adolphe Ze facilitated and assisted this work. Our thanks also to Julie Mbazo’o and Remy Assoumou, both members of the ‘social side’ working group of the FLORES modelling team. Christopher Legg’s contribution to the discussion of this work through his constant reviewing of the CamFlores model is gratefully recognized. Finally, thanks to the whole CIFOR-ACM team for numerous scientific and methodological inputs. The Italian Foreign Ministry funded the work of Valentina Robiglio (APO-GIS specialist) through an APO contract with IITA. The European Union (Tropical Forestry budget line DG VIII) contributed to the CIFOR’s research program on the ‘Adaptive Collaborative Management of Forests’ (ACM) in Africa, and to the Alternative to Slash and Burn (ASB) program in Cameroon on ‘Environmental Services and Rural Livelihoods’ through the World Agroforestry Centre.     

Fire models and methods to map fuel types: The role of remote sensing

Understanding fire is essential to improving forest management strategies. More specifically, an accurate knowledge of the spatial distribution of fuels is critical when analyzing, modelling and predicting fire behaviour. First, we review the main concepts and terminology associated with forest fuels and a number of fuel type classifications. Second, we summarize the main techniques employed to map fuel types starting with the most traditional approaches, such as field work, aerial photo interpretation or ecological modelling. We pay special attention to more contemporary techniques, which involve the use of remote sensing systems. In general, remote sensing systems are low-priced, can be regularly updated and are less time-consuming than traditional methods, but they are still facing important limitations. Recent work has shown that the integration of different sources of information and methods in a complementary way helps to overcome most of these limitations. Further research is encouraged to develop novel and enhanced remote sensing techniques.