Pilot study using SPOT satellite imagery over Apalachicola national forest to determine appropriate spatial scale for area-wide aggregation of surface fluxes

Summary High resolution radiances from SPOT satellite imagery converted to Normalized Difference Vegetation Indices (NDVI) over a 16×16 km² mixed ground cover study-area in the Apalachicola National Forest in northwest Florida, along with in situ measurements from a Bowen ratio surface flux monitoring system and physical modeling techniques, are used to determine the length manifold beyond which degraded resolution satellite imagery fails to capture flux variability over the scene. The investigation is relevant to an understanding of how bias error is generated in methods designed to produce scale-invariant surface flux estimates from satellite measurements. Error estimates are based on assigning characteristic NDVI values to the four predominant types of ground cover found within the study-area. An open site near the center of the study-area, which satisfies the conditions for surface flux monitoring, is used for obtaining input data for a biosphere-atmosphere exchange model designed to calculate representative fluxes for the different ground covers. Continuous 6-minute meteorological and surface flux measurements were made at the monitoring site for a period of 22 days. These measurements are used in conjunction with surface layer theory to provide surface layer profile estimates of wind speed, temperature, and relative humidity at the tops of the forested sites. The measured and derived meteorological parameters, together with representative biophysical parameters, are used as input to the biosphere-atmosphere exchange model. By representing sensible and latent heat flux distributions due to the variable ground cover with characteristic NDVI values at 20-m resolution, baseline area-wide sensible and latent heat flux quantities are calculated. Error-growth curves as a function of spatial resolution for the fluxes are found by degrading the resolution of the SPOT radiances used to calculate NDVI, and rationing the associated area-wide fluxes to the baseline values. The point at which an error-growth curve becomes invariant represents the edge of a length manifold beyond which the satellite input no longer contains information on surface flux variability, even though NDVI variability continues at all scales up to that of the complete SPOT scene. The error-growth curves are non-linear, with all the error build-up taking place between 20 m and 1.6 km. Decreasing the spatial resolution of the NDVI information down to or below 1.6 km, introduces bias errors in the area-wide surface flux estimates of 10% for sensible heat and 8% for latent heat. The underlying assumptions and modeling produce uncertainty in estimating the manifold limits, however, the principal objective is to show that in using satellite data for scale-invariant surface flux retrieval, there is an optimal spatial resolution factor that can be objectively quantified.With 10 Figures