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P. J. Pinter

Publications and source records attributed to P. J. Pinter.

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Surface energy balance estimates at local and regional scales using optical remote sensing from an aircraft platform and atmospheric data collected over semiarid rangelands

Remotely sensed data in the visible, near-infrared, and thermal-infrared wave bands were collected from a low-flying aircraft during the Monsoon '90 field experiment. Monsoon '90 was a multidisciplinary experiment conducted in a semiarid watershed. It had as one of its objectives the quantification of hydrometeorological fluxes during the “monsoon” or wet season. The remote sensing observations along with micrometeprological and atmospheric boundary layer (ABL) data were used to compute the surface energy balance over a range of spatial scales. The procedure involved averaging multiple pixels along transects flown over the meteorological and flux (METFLUX) stations. Average values of the spectral reflectance and thermal-infrared temperatures were computed for pixels of order 10 −1 to 10 1 km in length and were used with atmospheric data for evaluating net radiation ( R n ), soil heat flux ( G ), and sensible ( H ) and latent ( LE ) heat fluxes at these same length scales. The model employs a single-layer resistance approach for estimating H that requires wind speed and air temperature in the ABL and a remotely sensed surface temperature. The values of R n and G are estimated from remote sensing information together with near-surface observations of air temperature, relative humidity, and solar radiation. Finally, LE is solved as the residual term in the surface energy balance equation. Model calculations were compared to measurements from the METFLUX network for three days having different environmental conditions. Average percent differences for the three days between model and the METFLUX estimates of the local fluxes were about 5% for R n , 20% for G and H , and 15% for LE . Larger differences occurred during partly cloudy conditions because of errors in interpreting the remote sensing data and the higher spatial and temporal variation in the energy fluxes. Minor variations in modeled energy fluxes were observed when the pixel size representing the remote sensing inputs changed from 0.2 to 2 km. Regional scale estimates of the surface energy balance using bulk ABL properties for the model parameters and input variables and the 10-km pixel data differed from the METFLUX network averages by about 4% for R n , 10% for G and H , and 15% for LE . Model sensitivity in calculating the turbulent fluxes H and LE to possible variations in key model parameters (i.e., the roughness lengths for heat and momentum) was found to be fairly significant. Therefore the reliability of the methods for estimating key model parameters and potential errors needs further testing over different ecosystems and environmental conditions.

Water Resources Research

Spectral estimates of net radiation and soil heat flux

Conventional methods of measuring surface energy balance are point measurements and represent only a small area. Remote sensing offers a potential means of measuring outgoing fluxes over large areas at the spatial resolution of the sensor. The objective of this study was to estimate net radiation (R n ) and soil heat flux (G) using remotely sensed multispectral data acquired from an aircraft over large agricultural fields. Ground-based instruments measured R n and G at nine locations along the flight lines. Incoming fluxes were also measured by ground-based instruments. Outgoing fluxes were estimated using remotely sensed data. Remote R n , estimated as the algebraic sum of incoming and outgoing fluxes, slightly underestimated R n measured by the ground-based net radiometers. The mean absolute errors for remote R n minus measured R n were less than 7%. Remote G, estimated as a function of a spectral vegetation index and remote R n , slightly overestimated measured G; however, the mean absolute error for remote G was 13%. Some of the differences between measured and remote values of R n and G are associated with differences in instrument designs and measurement techniques. The root mean square error for available energy (R n - G) was 12%. Thus, methods using both ground-based and remotely sensed data can provide reliable estimates of the available energy which can be partitioned into sensible and latent heat under nonadvective conditions.

Remote Sensing of Environment

Plant stress detection by remote measurement of fluorescence

Chlorophyll fluorescence of mature lemon trees was measured with a Fraunhofer line discriminator (FLD). An increase in fluorescence was correlated with plant water stress as measured by stomatal resistance and twig water potential.

Applied Optics