Modelling Microclimates in Forests using Remotely Sensed Data

The focus of this study is to understand the spatio-temporal dynamics of the microclimatic conditions in gaps and the sub-canopy in broadleaved deciduous forests. This was achieved by applying a combination of numerical modelling and remote sensing techniques. A spatially explicit model of forest gap microclimate and soil water balance, FORGAP-BD (FORest GAP - Broadleaved Deciduous) was developed based on previous reviewed literatures and field measurements. The spatial input variables for FORGAP-BD model such as leaf area index, land surface elevation, gap and canopy properties and canopy radiation extinction coefficient were derived from LiDAR and multispectral remotely sensed data. The results demonstrated that FORGAP-BD driven by remotely-sensed inputs was able to accurately simulate the diurnal fluctuations and spatial distribution of solar radiation, air temperature, relative humidity, wind speed and soil water content across the broadleaved deciduous forests. Hence, the approach developed here provides the basis on which to assess the implications of forestry and conservation practices and natural or anthropogenic disturbances in temperate forest ecosystems.