Barriers to fire spread in northern Australian tropical savannas, deriving fire edge metrics from long term high-frequency fire histories.

The savannas of northern Australia are amongst the most fire-prone landscapes in the world. However, over the last fifteen years, increasing effort has been put into reducing fire extent and severity using prescribed burning strategies early in the dry season. This study seeks to improve the application of strategic fire management by providing a more detailed understanding of the landscape features that impede fire spread in Australia's tropical savannas using long-term satellite-derived fire histories. Spatial analysis of fire edges in Kakadu National Park based on fine-scale (30 m) Landsat imagery found that most fires stopped along linear edges, which were primarily associated with known features (roads, rivers and cliffs). Further analysis found linear features with the highest stopping ability covered only 13% of the park but divided the whole park into smaller containment regions. The stopping power of each feature type was found to vary according to their width and to change during the fire season, results that could help plan strategic fuel reduction burns. Similar results were seen with the lower-resolution continental-scale MODIS satellite-derived edge data. The MODIS dataset provided a means for applying fire edge analysis to support planning in areas of northern Australia that lack fine scale fire history mapping.

Interactive, open source, travel time scenario modelling: tools to facilitate participation in health service access analysis.

BACKGROUND: Modelling travel time to services has become a common public health tool for planning service provision but the usefulness of these analyses is constrained by the availability of accurate input data and limitations inherent in the assumptions and parameterisation. This is particularly an issue in the developing world where access to basic data is limited and travel is often complex and multi-modal. Improving the accuracy and relevance in this context requires greater accessibility to, and flexibility in, travel time modelling tools to facilitate the incorporation of local knowledge and the rapid exploration of multiple travel scenarios. The aim of this work was to develop simple open source, adaptable, interactive travel time modelling tools to allow greater access to and participation in service access analysis. RESULTS: Described are three interconnected applications designed to reduce some of the barriers to the more wide-spread use of GIS analysis of service access and allow for complex spatial and temporal variations in service availability. These applications are an open source GIS tool-kit and two geo-simulation models. The development of these tools was guided by health service issues from a developing world context but they present a general approach to enabling greater access to and flexibility in health access modelling. The tools demonstrate a method that substantially simplifies the process for conducting travel time assessments and demonstrate a dynamic, interactive approach in an open source GIS format. In addition this paper provides examples from empirical experience where these tools have informed better policy and planning. CONCLUSION: Travel and health service access is complex and cannot be reduced to a few static modeled outputs. The approaches described in this paper use a unique set of tools to explore this complexity, promote discussion and build understanding with the goal of producing better planning outcomes. The accessible, flexible, interactive and responsive nature of the applications described has the potential to allow complex environmental social and political considerations to be incorporated and visualised. Through supporting evidence-based planning the innovative modelling practices described have the potential to help local health and emergency response planning in the developing world.

Free and simple GIS as appropriate for health mapping in a low resource setting: a case study in eastern Indonesia.

BACKGROUND: Despite the demonstrated utility of GIS for health applications, there are perceived problems in low resource settings: GIS software can be expensive and complex; input data are often of low quality. This study aimed to test the appropriateness of new, inexpensive and simple GIS tools in poorly resourced areas of a developing country. GIS applications were trialled in pilot studies based on mapping of health resources and health indicators at the clinic and district level in the predominantly rural province of Nusa Tenggara Timur in eastern Indonesia. The pilot applications were (i) rapid field collection of health infrastructure data using a GPS enabled PDA, (ii) mapping health indicator data using open source GIS software, and (iii) service availability mapping using a free modelling tool. RESULTS: Through contextualised training, district and clinic staff acquired skills in spatial analysis and visualisation and, six months after the pilot studies, they were using these skills for advocacy in the planning process, to inform the allocation of some health resources, and to evaluate some public health initiatives. CONCLUSIONS: We demonstrated that GIS can be a useful and inexpensive tool for the decentralisation of health data analysis to low resource settings through the use of free and simple software, locally relevant training materials and by providing data collection tools to ensure data reliability.

Hunting territories and land use overlap in sedentarised Baka Pygmy communities in southeastern Cameroon.

A significant number of Baka Pygmies in Cameroon have been sedentarised in roadside villages, in contrast to their nomadic hunter-gatherer existence of the past. Although this change in lifestyle has had important consequences on health, most Baka villages still supplement their diets from forest products, especially wild meat. We used a combination of participatory methods and monitoring of individual hunters to map hunting territories in 10 Baka villages in southeastern Cameroon. From these, we determined whether wild meat extraction levels per village were related to the size of hunting territories, measured habitat use by hunters and finally defined the overlap between hunting territories and extractive industries in the region. Mapped village hunting areas averaged 205.2 ± 108.7 km2 (range 76.8-352.0 km2); all villages used a total of 2052 km2. From 295 tracks of 51 hunters, we showed that hunters travelled an average of 16.5 ± 13.5 km (range 0.9-89.8 km) from each village. Home ranges, derived from kernel utilization distributions, were correlated with village offtake levels, but hunter offtake and distance travelled were not significantly related, suggesting that enough prey was available even close to the villages. Hunters in all village areas exhibited a clear bias towards certain habitats, as indicated by positive Ivlev's index of selectivity values. We also showed that all village hunting territories and hunter home ranges fall within mining and logging concessions. Our results are important for local understanding of forest land uses and to reconcile these with the other land uses in the region to better inform decisions concerning land use policy and planning.

Defining Remoteness from Health Care: Integrated Research on Accessing Emergency Maternal Care in Indonesia.

The causes of maternal death are well known, and are largely preventable if skilled health care is received promptly. Complex interactions between geographic and socio-cultural factors affect access to, and remoteness from, health care but research on this topic rarely integrates spatial and social sciences. In this study, modeling of travel time was integrated with social science research to refine our understanding of remoteness from health care. Travel time to health facilities offering emergency obstetric care (EmOC) and population distribution were modelled for a district in eastern Indonesia. As an index of remoteness, the proportion of the population more than two hours estimated travel time from EmOC was calculated. For the best case scenario (transport by ambulance in the dry season), modelling estimated more than 10,000 fertile aged women were more than two hours from EmOC. Maternal mortality ratios were positively correlated with the remoteness index, however there was considerable variation around this relationship. In a companion study, ethnographic research in a subdistrict with relatively good access to health care and high maternal mortality identified factors influencing access to EmOC, including some that had not been incorporated into the travel time model. Ethnographic research provided information about actual travel involved in requesting and reaching EmOC. Modeled travel time could be improved by incorporating time to deliver request for care. Further integration of social and spatial methods and the development of more dynamic travel time models are needed to develop programs and policies to address these multiple factors to improve maternal health outcomes.