The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor offers an improved combination of spectral, temporal, and spatial resolution for global fire detection compared to previous sensors. The MODIS Terra active fire product was analyzed to investigate the spatial and temporal occurrence of fires in croplands from 2001 to 2003. Monthly fire counts were analyzed globally, within several regions and for important crop‐producing countries. The annual global total number of fire counts ranged from 1,472,367 to 1,577,952 during the 3 years. Agricultural fires were found to account for 8–11% of the annual global fire activity during the 3 years, but the contribution of agricultural burning was significantly higher on a regional basis. The Russian Federation was the largest contributor to agricultural burning globally during the 3 years, producing 31–36% of all agricultural fires. The global spatial distribution of agricultural fires was fairly similar among the 3 years, but a notable interannual change was observed in the total number of global agricultural fire events. The majority of regions showed similar magnitude and seasonality in their year‐to‐year agricultural fire activity, but in some regions, significant differences were found. At the global scale, agricultural fire activity showed two peaks, the first occurring during April to May, and was associated primarily with burning in the croplands of Eastern Europe and European Russia, and the second in August from burning mainly in the croplands across central Asia and Asiatic Russia. This timing pattern was observed both in 2001 and 2002. The August 2003 fire peak was significantly affected by reduced agricultural fire activity in European Russia. The seasonal and interannual trends in agricultural fire activity are consistent with known national and regional agricultural practices and reported crop production estimates.

Acute poisoning with various substance is common everywhere. The earlier the initial resuscitations, gastric decontamination and use of specific antidotes, the better the outcome. The aim of this study was to characterize the poisoning cases admitted to the tertiary care hospital, Warangal district, Andhra Pradesh, Southern India. All cases admitted to the emergency department of the hospital between the months of January and December, 2007, were evaluated retrospectively. We reviewed data obtained from the hospital medical records and included the following factors: socio-demographic characteristics, agents and route of intake and time of admission of the poisoned patients. During the outbreak in 2007, 2,226 patients were admitted to the hospital with different poisonings; the overall case fatality rate was 8.3% (n = 186). More detailed data from 2007 reveals that two-third of the patients were 21–30 years old, 5.12% (n = 114) were male and 3.23% (n = 72) were female, who had intentionally poisoned themselves. In summary, the tertiary care hospitals of the Telangana region, Warangal, indicate that significant opportunities for reducing mortality are achieved by better medical management and further sales restrictions on the most toxic pesticides. This study highlighted the lacunae in the services of tertiary care hospitals and the need to establish a poison information center for the better management and prevention of poisoning cases.

The RUSLE-3D (Revised Universal Soil Loss Equation-3D) model was implemented in geographic information system (GIS) for predicting the soil loss and the spatial patterns of soil erosion risk required for soil conservation planning. High resolution remote sensing data (IKONOS and IRS LISS-IV) were used to prepare land use/land cover and soil maps to derive the vegetation cover and the soil erodibility factor whereas Digital Elevation Model (DEM) was used to generate spatial topographic factor. Soil erodibility (K) factor in the sub-watershed ranged from 0.30 to 0.48. The sub-watershed is dominated by natural forest in the hilly landform and agricultural land in the piedmont and alluvial plains. Average soil loss was predicted to be lowest in very dense forest and highest in the open forest in the hilly landform. Agricultural land-1 and agriculture land-2 to have moderately high and low soil erosion risk, respectively. The study predicted that 15% area has 'moderate' to 'moderately high' and 26% area has high to very high risk of soil erosion in the sub-watershed.

Climate change, particularly due to the changed precipitation trend, can have a severe impact on soil erosion. The effect is more pronounced on the higher slopes of the Himalayan region. The goal of this study was to estimate the impact of climate change on soil erosion in a watershed of the Himalayan region using RUSLE model. The GCM (general circulation model) derived emission scenarios (HadCM3 A2a and B2a SRES) were used for climate projection. The statistical downscaling model (SDSM) was used to downscale the precipitation for three future periods