Showing papers by "Scott J. Goetz published in 1995"

Effects of spatial variability in topography, vegetation cover and soil moisture on area-averaged surface fluxes: A case study using the FIFE 1989 data

Abstract: A modified version of the simple biosphere model (SiB) of Sellers et al. (1986) was used to investigate the impact of spatial variability in the fields of topography, vegetation cover, and soil moisture on the area-averaged fluxes of sensible and latent heat for an area of 2×15 km (the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) testbed area) located within the FIFE area. This work builds on a previous study of Sellers et al. (1992a) but makes use of a superior data set (FIFE 1989 rather than FIFE 1987) and has a sharper focus on the nonlinear effects of soil wetness on evapotranspiration. The 2×15 km testbed area was divided into 68×501 pixels of 30×30 m spatial resolution, each of which could be assigned topographic, vegetation condition, and soil moisture parameters from satellite and in situ observations gathered in FIFE-89. One or more of these surface fields was area averaged in a series of simulation runs to determine the impact of using large-area means of these initial/boundary conditions on the area-integrated (aggregated) surface fluxes. Prior to these simulations some validation work was done with the model. The results of the study can be summarized as follows: (1) SiB was initialized with satellite and airborne remotely sensed data for vegetation condition and soil wetness, respectively. The surface fluxes calculated by SiB compared well with surface-based and airborne flux observations. (2) Analyses and some of the simulations indicated that the relationships describing the effects of moderate topography on the surface radiation budget are near linear and thus largely scale invariant. The relationships linking the simple ratio (SR) vegetation index, the canopy conductance parameter ∇F, and the canopy transpiration flux are also near linear and similarly scale invariant to first order (see also Sellers et al., 1992a). Because of this it appears that simple area-averaging operations can be applied to these fields with relatively little impact on the calculated surface heat fluxes. (3) The relationships linking surface and root-zone soil wetness to the soil surface and canopy transpiration rates are nonlinear. However, simulation results and observations indicate that soil moisture variability decreases significantly as the study area dries out, which partially cancels out the effects of these nonlinear functions. (4) The near-infrared surface reflectance ρN estimated from atmospherically corrected satellite data may be a better predictor of vegetation condition than a two-band vegetation index, such as the SR, at least for the grasslands represented in the FIFE area. These results support the use of simple averages of topographic and vegetation parameters to calculate surface energy and heat fluxes over a wide range of spatial scales, from a few meters up to many kilometers. Although the relationships between soil moisture and evapotranspiration are nonlinear for intermediate soil wetnesses, the dynamics of soil drying act to progressively reduce soil moisture variability and thus the impacts of these nonlinearities on the area-averaged surface fluxes. These findings indicate that we can use mean values of topography, vegetation condition, and soil moisture to calculate the surface-atmosphere fluxes of energy, heat, and moisture at larger length scales to within an acceptable accuracy for climate-modeling work.

Surface temperature retrieval in a temperate grassland with multiresolution sensors

Abstract: Radiometric surface temperatures retrieved at various spatial resolutions from aircraft and satellite measurements at the FIFE site in eastern Kansas were compared with near-surface temperature measurements to determine the accuracy of the retrieval techniques and consistency between the various sensors. Atmospheric characterizations based on local radiosonde profiles of temperature, pressure, and water vapor were used with the LOWTRAN-7 and MODTRAN atmospheric radiance models to correct measured thermal radiances of water and grassland targets for atmospheric attenuation. Comparison of retrieved surface temperatures from a helicopter-mounted modular multispectral radiometer (MMR) (∼5-m “pixel”), C-130 mounted thematic mapper simulator (TMS) (NS001, ∼20-m pixel), and the Landsat 5 thematic mapper (TM) (120-m pixel) was done. Differences between atmospherically corrected radiative temperatures and near-surface measurements ranged from less than 1°C to more than 8°C. Corrected temperatures from helicopter-MMR and NS001-TMS were in general agreement with near-surface infrared radiative thermometer (IRT) measurements collected from automated meteorological stations, with mean differences of 3.2°C and 1.7°C for grassland targets. Much better agreement (within 1°C) was found between the retrieved aircraft surface temperatures and near-surface measurements acquired with a hand-held mast equipped with a MMR and IRT. The NS001-TMS was also in good agreement with near-surface temperatures acquired over water targets. In contrast, the Landsat 5 TM systematically overestimated surface temperature in all cases. This result has been noted previously but not consistently. On the basis of the results reported here, surface measurements were used to provide a calibration of the TM thermal channel. Further evaluation of the in-flight radiometric calibration of the TM thermal channel is recommended.

Monitoring primary production from Earth observing satellites

Abstract: Satellite remotely sensed observations provide a unique capacity to monitor biospheric activity at regional and global scales. Spectral vegetation indices from these observations capture the heterogeneity of growth patterns across the Earth's surface including the significant decline in vegetation activity above 50°N latitude. Conversion of these observations to meaningful assessments of vegetation growth, particularly changes within and between years, requires more than a simple linear transform between the spectral vegetation index and forest production. Although satellite observations of vegetation indices are essential, appropriate environmental variables and models are also necessary. The approach is illustrated by a study of the southern Boreal forest in northern Minnesota. A conceptual and methodological framework for monitoring primary production from remotely sensed observations alone is proposed and results of its application in the Global Production Efficiency Model (GLO-PEM) for global boreal forests are discussed.