Deriving Spatial Inputs for Forest Microclimate Modelling Using Remote Sensing Techniques

The creation of gaps in forest canopies can dramatically change the microclimate and soil water balance which strongly influences the process of regeneration and biodiversity within forest ecosystems. Hence, understanding the microclimatic conditions in canopy gaps is a prerequisite in developing and improving techniques for forest management and conservation practices. However, information is scarce on how the size and shape of gaps and their spatial distribution affects the microclimate and soil water balance across forest stands. In the present study we investigated the potential for retrieving forest gap and canopy attributes from LiDAR and multispectral sensors in order to provide new opportunities for modelling forest microclimates. A spatially explicit microclimate model (FORGAP-BD) was developed which could be driven using spatial inputs from remote sensing. The model was implemented for a study site in the broadleaved deciduous forest, Eaves Wood, UK in order to quantify the spatiotemporal dynamics of microclimates over an entire forest stand.