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The fraction of intercepted photosynthetic active radiation (fPAR) is a key variable used by the Monteith model to estimate the net primary productivity (NPP). This variable can be assessed by vegetation indices (VIs) derived from spectral remote sensing data but several factors usually affect their relationship. The objectives of this work were to analyse the fPAR dynamics and to describe the relationships between fPAR and several indices (normalized difference vegetation index (NDVI), optimized soil adjusted vegetation index (OSAVI), Green NDVI (GNDVI), visible atmospherically resistant index (VARI) green, VIgreen and red edge position (REP)) under different water and nutrient treatments for two species with different canopy architectures. Two C3 grass species with differences in leaf orientation (planophile and erectophile) were cultivated from seeds in pots. Four treatments were applied combining water and nitrogen availability. Every week, canopy reflectance and fPAR were measured. Aerial biomass was clipped to estimate final above-ground production for each species and treatment. Starting from reflectance values, the indices were calculated. Planophile species have a steeper (but not significantly) slope in VIs-fPAR relationships than the erectophile species. Water and nutrient deficiencies treatment showed no relationship with fPAR in any spectral index in the erectophile species. In the other species, this treatment showed significant relationship according to the index used. Analysing each species individually, treatments did not modify slopes except in one case (planophile species between both treatments with high nitrogen but differing in water availability). Among indices, GNDVI was the best estimator of fPAR for both species, followed by NDVI and OSAVI. Inaccurate results may be obtained from commonly reported spectral relationships if plants' stress factors are not taken into account.

Spectral indices from remotely sensed data, such as the Normalized Difference Vegetation Index (NDVI), are often used to estimate biophysical characteristics of vegetation. The objective of this study is to evaluate the effect of senescent leaves on the estimation of the fraction of photosynthetically active radiation absorbed by the green elements of the canopy (fAPAR g ) from NDVI measurements. An experiment was conducted under controlled conditions over grass canopies. Both NDVI and fAPAR g were measured when the cover fraction by senescent leaves was changed. The results demonstrated that the effect of senescent leaves was significant on NDVI values. A similar effect was observed on the fAPAR g values. In these conditions, simple models were developed to relate the fAPAR g to NDVI values when the cover fractions of the senescent leaves vary. When combining these models, a linear relationship was found between NDVI and fAPAR g , which was in good agreement with our experimental observations. Complement...

In this paper a method for cloud cover assessment at night-time (when only thermal infrared data are available) is presented. It is based on the analysis of long wave radiation transfer processes in partially cloudy areas, which led to the formulation of a simplified model of the surface–cloud–atmosphere system. The model was implemented in an operational and iterative algorithm to solve the radiative equations. The algorithm was validated using ground data collected at four meteorological stations in Argentina during November 1997 and May–June 1998, which were compared to cloudiness derived from National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer thermal data. Differences between observed and calculated cloudiness were within ±1 okta in 78% of the cases studied, giving a bias of +0.5 oktas and a standard deviation of ±1.0 oktas in cloudiness estimation.

The objective of this study was to explore the use of multi-temporal Landsat TM data from the same growing season for the classification of land cover types in the south-western portion of the Argentine Pampas. Investigations were made on how many dates are necessary to obtain an accurate classification and, given a fixed number of dates, which is the particular combination of dates that yield the best results. Additionally, the effect of using the NDVI instead of all the bands available on the classification accuracy and the use of a moving window filter over the classified image were tested. Scenes acquired in spring, early summer, late summer and early fall of the 1996-1997 growing season were used. Land cover information for the same period was collected from farms and ranches and this information was included in a GIS. Supervised classifications were performed using all the 15 possible ways to combine the four dates. At least two scenes are needed for a satisfactory classification. These scenes must ...

We used multiple regression analysis to relate evapotranspiration (ET), computed from a water balance technique, to both thermal infrared and normalized difference vegetation index data obtained from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board on the National Oceanic and Atmospheric Administration (NOAA) satellite. This approach, based on only remotely sensed data, provided a reliable estimate of ET over the Pampas, the main agricultural region of Argentina. The relationship between spectral data and ET was more sensitive to the dates than to the sites used to generate the models.