Spatially continuous data of environmental variables are often required for environmental
sciences and management. However, information for environmental variables is usually …

Spatial interpolation methods have been applied to many disciplines. Many factors affect the
performance of the methods, but there are no consistent findings about their effects. In this …

Spatial continuous data (spatial continuous surfaces) play a significant role in planning, risk
assessment and decision making in environmental management. They are, however …

Crop yield forecast models for barley, canola and spring wheat grown on the Canadian
Prairies were developed using vegetation indices derived from satellite data and machine …

The deterioration of urban air quality is considered worldwide one of the primary
environmental issues and scientific evidence associates the exposure to ambient air …

Spatial interpolation of precipitation data is of great importance for hydrological modelling.
Geostatistical methods (kriging) are widely applied in spatial interpolation from point …

Abstract Changes in climate have caused impacts on ecosystems on all continents scale,
and climate change is also projected to be a stressor on most ecosystems even at the rate of …

We compare versions of six interpolation methods for the interpolation of daily precipitation,
mean, minimum and maximum temperature, and sea level pressure from station data over …

The differences in spatial patterns of drought over a range of time scales were analysed by
the Standardized Precipitation Index (SPI). In a climatic area with a wide range of …

Monthly or annual 5 km× 5 km gridded datasets covering the UK are generated for the 1961–
2000 period, for 36 climatic parameters. As well as the usual elements of temperature …