Guinea is confronted to the increasing risks of bushfires that destroy thousands of hectares of vegetation cover every year. Very little research is devoted to the variability of those fires, which makes it a serious threat to both wildlife and human habitats. The current study investigates the spatial and temporal distribution of bushfires in the period from 2003 to 2016. The method used is the geospatial technology: we first filter pixels corresponding with active light supplied by MODIS images (Moderate Resolution Imaging Spectroradiometer) and estimate their densities following the square meshing procedure. Burned areas are deducted from the estimated pixel densities by calculations. The results highlight great occurrence of fires: 4 to 48 pixels of active fire per year and per 100 km² depending on the location; 2 to 5 million hectares per year of burned areas (20,000 to 50,000 sqkm). Almost 8 to 24% the size of the whole country. The prefectures of Beyla, Siguiri, Kouroussa, Kankan, Dinguiraye, Mali and Tougué are the most exposed areas. Every year, fire activities are observed as from October and between May and June. They are however mitigated according to the regions (or the geographical domains). Summits of bushfires activities are generally reached between December and January.
Let R be a commutative ring and M an unital R-module.In this paper we introduce the concept of S-quasi-Dedekind modules as a generalisation of small quasi-Dedekind modules, and gives some of their properties, characterizations and exemples. Another hand we study the relationships of S-quasi-Dedekind modules with some classes of modules and their endomorphism rings.
This study investigates the variability and the predictability of bush fire on inter-annual and multi-year timescales in Guinea (latitudes 7° 05 and 12° 51 N and longitudes 7° 30 and 15° 10 W). Using Moderate Resolution Imaging Spectroradiometer (MODIS) with a spatial resolution of 231 m × 231 m and 16 days composite temporal resolution between 2001 and 2016, two brush fire hazard indices are calculated based on the NDVI variability. Results show that both indices could be considered as good indicators of NDVI deficiency corresponding to the drought of vegetation. Multiple linear regression model using these risk indices as predictors and burned areas as predictands has shown a non-significant model skill of 0.33 (lower than the significant threshold equals to 0.42), at the inter-annual scale, while at the multi-year timescale (>5 years), the model's skill rise up to 0.89. These indices can therefore be used as predictors of Guinea burned areas on multi-year timescale. This novel finding improved our understanding on the forecasting of burned area in Guinea, and could therefore help for successful adaptation strategies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.