Burnt area data, derived from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) imagery, are validated in 11 regions of arid and semi-arid Australia, using three separate Landsat-derived burnt area data sets. Mapping accuracy of burnt extent is highly variable between areas and from year to year within the same area. Where there are corresponding patches in the AVHRR and Landsat data sets, the fit is good. However, the AVHRR data set misses some large patches.

Baobab fruit are harvested and used throughout Africa as an important source of food and are sold to generate income. Commercial use is increasing rapidly as derivatives of the fruit such as baobab seed oil and fruit pulp are being exported to Europe and North America. The cash derived from the sale of fruit support thousands of rural people. This study examines baobab fruit yields in an area being harvested for commercial use.

The shortage of forest products and unsustainability of current land use practices experienced by many hillside farmers in the Caribbean is associated with increasing rates of conversion and degradation of remaining natural forests. This pressure could be alleviated by the establishment of trees in community/farm forests or more integrated agroforestry systems.

We measured bidirectional arthropod fluxes at 12 river reaches distributed across an urban‐rural gradient of riparian land use and land cover in the Scioto River system of Ohio (U.S.A.). For the terrestrial‐to‐aquatic arthropod flux (i.e. inputs of terrestrial arthropods to the river from the land), urban development was positively related to density of inputs but negatively related to biomass, partially explained by shifts in community composition and body size. Riparian grassland, typical of rural (i.e.

In order to investigate spatial and temporal characteristics of the purely grazing-based livestock husbandry system in southwestern Madagascar, individual animals from 12 cattle and 12 goat herds that were equally distributed across four villages were fitted with GPS tracking collars and their behaviour during pasturing was directly observed to identify seasonal variations in land use and movement patterns along the regional altitude and vegetation gradient.

Remote sensing is a useful technology for monitoring the spatial distribution and expansion of built-up and bare land areas. One effective approach, known as the normalized difference built-up index (NDBI), has been promoted for identifying built-up areas based on Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM+) data.

Rapid land ownership changes in the Northern Forest of the eastern United States have spurred development as well as conservation. Local people have experienced differing degrees of participation in land use decisions. We examine two conservation projects from the Northern Forest state of Maine. This paper presents the policy processes from these projects and an assessment of their impact on conflict and support for the project. One project was a top-down approach, and the second was a grassroots, private effort by local citizens to conserve forestland.

Endocrine-disrupting contaminant (EDC) loads in rivers, and the associated risk to wildlife, may be linked to different anthropogenic stressors occupying river catchments. The aims of this study were to evaluate seasonal and spatial variation in steroid estrogen loads, and (anti)estrogenic and (anti)androgenic activity in a river catchment (upper Olifants River, South Africa), subject to a diversity of anthropogenic impacts. In addition, Mozambique tilapia, Oreochromis mossambicus, was applied as African-endemic sentinel and source of in vivo biomarkers.

Land cover monitoring using remotely sensed data requires robust classification methods which allow for the accurate mapping of complex land cover and land use categories. Random forest (RF) is a powerful machine learning classifier that is relatively unknown in land remote sensing and has not been evaluated thoroughly by the remote sensing community compared to more conventional pattern recognition techniques. Key advantages of RF include: their non-parametric nature; high classification accuracy; and capability to determine variable importance.

Bashagard district is one of the important malaria endemic areas in southern Iran. From this region a total of 16,199 indigenous cases have been reported in recent years. The aim of this study was to determine the situation of the disease and provide the risk map for the area. ArcGIS9.2 was used for mapping spatial distribution of malaria incidence. Hot spots were obtained using evidence-based weighting method for transmission risk.