Description: Zonal interpolation is a method used in spatial data analysis that allows for estimating values at unknown points within defined areas, known as zones. This approach is based on the premise that values of a geographical phenomenon are more similar to each other when they are closer in space. Zonal interpolation is commonly used in geographic information systems (GIS) and in environmental data modeling, where the goal is to predict or estimate characteristics in areas where direct measurements have not been taken. This method can be applied to different types of data, such as temperature, precipitation, or soil quality, and relies on existing data to generate estimates at intermediate locations. The main features of zonal interpolation include its ability to efficiently handle spatial data and its flexibility to adapt to different types of analysis, making it a valuable tool for researchers and professionals in fields such as geography, ecology, and urban planning.
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