Exploratory Spatial Data Analysis

A novel spatial prediction method integrating Exploratory Spatial Data Analysis into Random Forest for large scale daily air temperature mapping

Accurately predicting spatially-continuous daily air temperature (Ta) is critical for agriculture, environmental management, and ecology. While meteorological stations provide precise Ta data, their spatial coverage is limited. Remotely-sensed Land Surface Temperature (LST), often fused with meteorological data, offers broader spatial coverage but struggles due to complex relationships between Ta and LST, influenced by factors like topography and human activities.

Categories:
Weather
329 Views

A novel spatial prediction method integrating Exploratory Spatial Data Analysis into Random Forest for large scale daily air temperature mapping

Accurately predicting spatially-continuous daily air temperature (Ta) is critical for agriculture, environmental management, and ecology. While meteorological stations provide precise Ta data, their spatial coverage is limited. Remotely-sensed Land Surface Temperature (LST), often fused with meteorological data, offers broader spatial coverage but struggles due to complex relationships between Ta and LST, influenced by factors like topography and human activities.

Categories:
Weather
216 Views