PREDICTING PLANT PRESENCE/ABSENCE ACROSS LANDSCAPES: A MORPHOMETRICALLY BASED MODEL USING PUBLICLY AVAILABLE DATA AND THE GEOWALL

Photosythetically-active radiation (PAR) is the most important energy source for all green plants in aquatic and terrestrial ecosystems. The amount of photosynthesis and a corresponding plant biomass increase is proportional to PAR. Spatial distribution and the amount of plant biomass are important because that determines the microbiological and geochemical heterogeneity across ecosystems.

We have developed an algorithm that predicts the spatial distribution of PAR and corresponding plant biomass across landscapes using only the time of the year and the local topography. This algorithm will be superimposed over an entire watershed drainage area to predict plant presence or absence across landscapes. Prediction results can be instrumental in guiding studies in landscape sustainability.

This algorithm was developed within the GIS software MicroDEM and uses freely available digital elevation data from the USGS or higher resolution airborne LIDAR data. At each point in the DEM, the algorithm first computes the horizon for each azimuth. Then for each day of the year, the algorithm computes the sun position as a function of time and determines when the sun first appears over the horizon and when it disappears below the horizon. The resulting duration of direct solar illumination can be compared to the duration of daylight from standard predictions of sunrise and sunset, which do not consider terrain blocking, and displayed as maps showing the degree of terrain blocking. We create a map for each day of the year and an annual average, stored as standard GIS grids. The predictions are visualized using the programs Walkabout and Fledermaus and displayed on the GeoWall. We can also display graphs for each location showing the duration of direct illumination throughout the year, which may have complex relationships as terrain blockage changes with seasonal changes in solar position.

With bare earth USGS DEMs the results do not consider shading from vegetation, but LIDAR data with both bare earth and first return canopy top can consider this additional complexity.