Mário Cunha

Airborne pollen concentration in the region of Braga, Portugal, and its relationship with meteorological parameters

The variation in airborne pollen concentrationof the Braga region (Portugal) was studied inspringtime, during the flowering of Vitisvinifera. The data set was obtained for twoconsecutive years (1999 and 2000), using aCour-type sampler.During this period, thirty-six taxa wereobserved in a total of 3,200 pollengrains m-3 of air (CPA). The main pollentypes observed were Olea, Poaceaea,nd Castanea, representing 74% of thepollen spectrum.The airborne pollen concentration (CPA) wassignificantly correlated with certainmeteorological parameters. Pollen concentrationwas positively correlated with temperature andwind direction (East and Northeast) andnegatively correlated with rainfall and numberof rainy days.

Using remote sensing energy balance and evapotranspiration to characterize montane landscape vegetation with focus on grass and pasture lands

Abstract Water and energy balance interactions with vegetation in mountainous terrain are influenced by topographic effects, spatial variation in vegetation type and density, and water availability. This is the case for the mountainous areas of northern Portugal, where ancestral irrigated meadows (lameiros) are a main component of a complex vegetation mosaic. The widely used surface energy balance model METRIC was applied to four Landsat images to determine the spatial and temporal distribution of the energy balance terms in the identified land cover types (LCT). A discussion on the variability of evapotranspiration (ET) through the various vegetation types was supported by a comparison between the respective crop coefficients and those available in the literature corresponding to the LCT, which has shown the appropriateness of METRIC estimates of ET. METRIC products derived from images of May and June – NDVI, surface temperature, net radiation, soil heat flux, sensible heat flux, and ET – were used to characterize the LCTs, through application of principal component analysis. Three principal components explained the variance of observed variables and their varimax rotated loadings allowed a good explanation of the behaviour of the explanatory variables in association with the LCTs. Information gained contributes to improve the characterization of the study area and may further support conservation and management of these mountain landscapes.

Image Processing of Artificial Targets for Automatic Evaluation of Spray Quality

A fully automatic methodology based on image processing is proposed to evaluate the quality of spray application sampled by water-sensitive papers (WSP). The methods proposed permit a computation of the fraction of spray coverage, an evaluation of the homogeneity of the spray spatial spread at various scales and directions, and extraction of stain and droplet size range and distribution. This allows the number of droplets per unit area and the standard droplet size spectra factors to be computed. The methods were tested with a number of test samples scanned at different resolutions, proving to be effective in situations where there is high spray coverage in the WSP, thus with considerable overlap between stains. The most suitable scanning resolution was found to be 600 dpi. The results obtained by the image processing methods were successfully compared with a manual (visual) counting of stains in a test sample.

Predicting Grapevine Water Status Based on Hyperspectral Reflectance Vegetation Indices

Several vegetation indices (VI) derived from handheld spectroradiometer reflectance data in the visible spectral region were tested for modelling grapevine water status estimated by the predawn leaf water potential (Ψpd). The experimental trial was carried out in a vineyard in Douro wine region, Portugal. A statistical approach was used to evaluate which VI and which combination of wavelengths per VI allows the best correlation between VIs and Ψpd. A linear regression was defined using a parameterization dataset. The correlation analysis between Ψpd and the VIs computed with the standard formulation showed relatively poor results, with values for squared Pearson correlation coefficient (r2) smaller than 0.67. However, the results of r2 highly improved for all VIs when computed with the selected best combination of wavelengths (optimal VIs). The optimal Visible Atmospherically Resistant Index (VARI) and Normalized Difference Greenness Vegetation Index (NDGI) showed the higher r2 and stability index results. The equations obtained through the regression between measured Ψpd (Ψpd_obs) and optimal VARI and between Ψpd_obs and optimal NDGI when using the parameterization dataset were adopted for predicting Ψpd using a testing dataset. The comparison of Ψpd_obs with Ψpd predicted based on VARI led to R2 = 0.79 and a regression coefficient b = 0.96. Similar R2 was achieved for the prediction based on NDGI, but b was smaller (b = 0.93). Results obtained allow the future use of optimal VARI and NDGI for estimating Ψpd, supporting vineyards irrigation management.

Measuring the impact of temperature changes on the wine production in the Douro Region using the short time fourier transform.

This paper investigates the cyclical behaviour of the wine production in Douro region during the period 1932–2008. In general, wine production is characterised by large fluctuations which are composed of short-term and/or long-term cycles. The aim of this paper is twofold: firstly, we decompose the wine productions variance in order to find the dominating production cycles, i.e we try to explain whether wine production follows more long-term or short-term cycles. In the next step, we try to explain those cycles using a dependent variable, namely the medium spring temperature (Tm_Sp) for the period 1967–2008. We estimated a Time-Varying Autoregressive Model, which could explain 75% of the production that is characterised by 4.8- and 2.5-year cycles. We use the Short Time Fourier Transform to decompose the link between wine production and temperature. When the temperature was incorporated, the R2 increased and the Akaike criterion value was lower. Hence, Tm_Sp causes a large amount of these cycles and the wine production variation reflects this relationship. In addition to an upward trend, there is a clearly identifiable cycle around the long-term trend in production. We also show how much of the production cycle and what cycle in particular is explained by the Tm_Sp. There is a stable but not constant link between production and the Tm_Sp. In particular, the temperature is responsible for 5.2- and 2.4-year cycles which has been happening since the 1980s. The Tm_Sp can also be used as an indicator for the 4.8- and 2.5-year cycles of production. The developed model suggests that stationarity is a questionable assumption, and this means that historical distributions of wine production are going to need dynamic updating.

Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data

A new procedure is proposed for estimating actual basal crop coefficients from vegetation indices (Kcb VI) considering a density coefficient (Kd) and a crop coefficient for bare soil. Kd is computed using the fraction of ground cover by vegetation (fc VI), which is also estimated from vegetation indices derived from remote sensing. A combined approach for estimating actual crop coefficients from vegetation indices (Kc VI) is also proposed by integrating the Kcb VI with the soil evaporation coefficient (Ke) derived from the soil water balance model SIMDualKc. Results for maize, barley and an olive orchard have shown that the approaches for estimating both fc VI and Kcb VI compared well with results obtained using the SIMDualKc model after calibration with ground observation data. For the crops studied, the correlation coefficients relative to comparing the actual Kcb VI and Kc VI with actual Kcb and Kc obtained with SIMDualKc were larger than 0.73 and 0.71, respectively. The corresponding regression coefficients were close to 1.0. The methodology herein presented and discussed allowed for obtaining information for the whole crop season, including periods when vegetation cover is incomplete, as the initial and development stages. Results show that the proposed methods are adequate for supporting irrigation management.

Dynamics of mountain semi-natural grassland meadows inferred from SPOT-VEGETATION and field spectroradiometer data

Permanent semi-natural grassland meadows (lameiros) are characteristic of the mountain rural landscapes in northeast Portugal and represent the main fodder resource for livestock production. Furthermore, these meadows are recognized for their environmental, historical, cultural and visual landscape value. A monitoring study based on remote-sensing data was implemented to understand the impacts of management practices on the lameiros vegetation dynamics and to analyse changes in vegetation dynamics over the period 1998–2008 in response to inter-annual climatic variability. Ten-day SPOT-VEGETATION (VGT) image composites from this period were used to examine the annual temporal profile using the normalized difference vegetation index (NDVI) and their relationship with ground-based observation of vegetation growth and reflectance inferred with a spectroradiometer. Results show that the NDVI profile fits well the characteristic vegetation growth dynamics and associated management practices in the region. For the period from July 2007 to December 2008, the variation in vegetation height explains 46 to 52% of the variation in NDVI derived respectively from spectroradiometer and VGT data. NDVI referring to dates of specific stages of the vegetation dynamics and management practices in lameiros was tested against climatic variables, for the period 1998–2008. More than 57% of the inter-annual variability of the average NDVI during the lameiros development period can be explained by the mean temperature, and 53% of the variability on the date of occurrence of maximum vegetation development (MVD) can be explained by the mean temperature during the spring period. These results support the analysis of lameiros responses to different scenarios of climate and water management and may support the implementation of more efficient farm activities.

Identification of potential land cover changes on a continental scale using NDVI time-series from SPOT VEGETATION

The identification of land cover changes on a continental scale is a laborious and time-consuming process. A new methodology is proposed based exclusively on SPOT VGT data, illustrated for the African Continent using GLC2000 as reference to select 26 distinct land cover types (classes). For each class, the normalized difference vegetation index (NDVI) time-series are extracted from SPOT VGT images and a hierarchical aggregation is done using two different methods: one that preserves the initial signatures throughout the hierarchical process, and another that recalculates the signatures for each aggregation level. The average classification agreement was above 89% using 26 classes. Reducing the number of classes improves classification agreement. In order to study the influence of temporal variability in the classification results, the methodology was applied on data from 1999, 2001, 2008, and 2010. With 26 classes, the best average classification agreement obtained was 94.5% with annual data, against 74.1% with interannual data.

Influence of meteorological parameters on Olea flowering date and airborne pollen concentration in four regions of Portugal

For calculating the total annual Olea pollen concentration, the onset of the main pollen season and the peak pollen concentration dates, using data from 1998 to 2004, predictive models were developed using multiple regression analysis. Four Portuguese regions were studied: Reguengos de Monsaraz, Valença do Douro, Braga and Elvas. The effect of some meteorological parameters such as temperature and precipitation on Olea spatial and temporal airborne pollen distribution was studied. The best correlations were found when only the pre‐peak period was used, with thermal parameters (maximum temperature) showing the highest correlation with airborne pollen distribution. Independent variables, selected by regression analysis for the predictive models, with the greatest influence on the Olea main pollen season features were accumulated number of days with rain and rainfall in the previous autumn, and temperatures (average and minimum) from January through March. The models predict 59 to 99% of the total airborne pollen concentration recorded and the initial and peak concentration dates of the main Olea pollen season.

Ultrastructure and germination of Vitis vinifera cv. Loureiro pollen.

Summary.The cultivar Loureiro of Vitis vinifera is one of the most economically important, recommended in almost the totality of the Região Demarcada dos Vinhos Verdes. In vineyards, the grape productivity of this cultivar is normal while in others it is extremely low. The aim of this work was to study the morphology and germination of Vitis vinifera cv. Loureiro pollen with high and low productivity. The pollen grain was examined under light, transmission and scanning electron microscopy. Typically V. vinifera pollen present three furrows but in the cultivar Loureiro we found tricolporated and acolporated (without furrows or pores) pollen grains. Both pollen types present generative and vegetative cells with the usual aspect and a dense cytoplasm rich in organelles. In the acolporated pollen a continuous exine layer and an irregular intine layer were observed. Differences were found in the starch accumulation, since only in tricolporated pollen abundant plastids filled with numerous starch granules were observed. To determine the causes of the low productivity of this cultivar we tested pollen viability by the fluorochromatic reaction and pollen germinability by in vitro assays. We observed that the acolporated pollen grain is viable, but no germination was recorded.