Analysis of energy fluxes and land surface parameters in a grassland ecosystem: a remote sensing perspective

A remote sensing‐based land surface characterization and flux estimation study was conducted using Landsat data from 1997 to 2003 on two grazing land experimental sites located at the Agricultural Research Services (ARS), Mandan, North Dakota. Spatially distributed surface energy fluxes [net radiation (R n), soil heat flux (G), sensible heat (H), latent heat (LE)] and surface parameters [emissivity (ε), albedo (α), normalized difference vegetation index (NDVI) and surface temperature (T sur)] were estimated and mapped at a pixel level from Landsat images and weather information using the Surface Energy Balance Algorithm for Land (SEBAL) procedure as a function of grazing land management: heavily grazed (HGP) and moderately grazed pastures (MGP). Energy fluxes and land surface parameters were mapped and comparisons were made between the two sites. Over the study period, H, ε and T sur from HGP were higher by 6.7%, 18.2% and 2.9% than in MGP, respectively. The study also showed that G, LE and NDVI were higher by 1.3%, 1.6% and 7.4% for MGP than in HGP, respectively. The results of this study are beneficial in understanding the trends of land surface parameters, energy and water fluxes as a function of land management.