Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil

Brazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international market places. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast.

Habitat Fragmentation Effects on the Orchid Bee Communities in Remnant Forests of Southeastern Brazil

The effect of habitat fragmentation on the structure of orchid bee communities was analyzed by the investigation of the existence of a spatial structure in the richness and abundance of Euglossini species and by determining the relationship between these data and environmental factors. The surveys were carried out in four different forest fragments and one university campus. Richness, abundance, and diversity of species were analyzed in relation to abiotic (size of the area, extent of the perimeter, perimeter/area ratio, and shape index) and biotic characteristics (vegetation index of the fragment and of the matrix of each of the locations studied). We observed a highly significant positive correlation between the diversity index and the vegetation index of the fragment, landscape and shape index. Our analysis demonstrated that the observed variation could be explained mainly by the vegetation index and the size of the fragment. Variations in relative abundance showed a tendency toward an aggregated spatial distribution between the fragments studied, as well as between the sampling stations within the same habitat, demonstrating the existence of a spatial structure on a small scale in the populations of Euglossini. This distribution will determine the composition of species that coexist in the area after fragmentation. These data help in understanding the differences and similarities in the structure of communities of Euglossini resulting from forest fragmentation.

Assessing biophysical variable parameters of bean crop with hyperspectral measurements

Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture. Motivated by the increasing importance of hyperspectral remote sensing data, the need for research is important to define optimal wavebands to estimate biophysical parameters of crop. The use of narrow band vegetation indices (VI) derived from hyperspectral measurements acquired by a field spectrometer was evaluated to estimate bean (Phaseolus vulgaris L.) grain yield, plant height and leaf area index (LAI). Field canopy reflectance measurements were acquired at six bean growth stages over 48 plots with four water levels (179.5; 256.5; 357.5 and 406.2 mm) and tree nitrogen rates (0; 80 and 160 kg ha-1) and four replicates. The following VI was analyzed: OSNBR (optimum simple narrow-band reflectivity); NB_NDVI (narrow-band normalized difference vegetation index) and NDVI (normalized difference index). The vegetation indices investigated (OSNBR, NB_NDVI and NDVI) were efficient to estimate LAI, plant height and grain yield. During all crop development, the best correlations between biophysical variables and spectral variables were observed on V4 (the third trifoliolate leaves were unfolded in 50 % of plants) and R6 (plants developed first flowers in 50 % of plants) stages, according to the variable analyzed.

Mapeamento do índice de vegetação da diferença normalizada em lavoura de algodão

Os dados de sensoriamento remoto em campo podem fornecer informações detalhadas sobre a variabilidade de parâmetros biofísicos ligados à produtividade em grandes áreas e apresentam potencial para o monitoramento destes parâmetros, ao longo de todo o ciclo de desenvolvimento da cultura. Este trabalho objetivou mapear a variabilidade espacial do índice de vegetação da diferença normalizada (NDVI) e seus componentes, em duas lavouras comerciais de algodão (Gossipium hirsutum L.), utilizando sensor óptico ativo, em nível terrestre. Os dados foram coletados utilizando-se sensor instalado em um pulverizador autopropelido agrícola. Um receptor GPS foi acoplado ao sensor, para a obtenção das coordenadas dos pontos de amostragem. As leituras foram realizadas em faixas espaçadas em 21,0 m, aproveitando-se as passadas do veículo no momento da pulverização de agroquímicos, e os dados submetidos à análise estatística clássica e geoestatística. Mapas de distribuição espacial das variáveis foram elaborados pela interpolação por krigagem. Observou-se maior variabilidade espacial do NDVI e da reflectância espectral da vegetação na região do infravermelho próximo (IVP) (880 nm) e do visível (590 nm) na lavoura com maior estresse fisiológico, devido ao ataque do percevejo castanho [Scaptocoris castanea (Hem.: Cydnidae)], em relação à lavoura sadia.

Calibration of a Species-Specific Spectral Vegetation Index for Leaf Area Index (LAI) Monitoring: Example with MODIS Reflectance Time-Series on Eucalyptus Plantations

The leaf area index (LAI) is a key characteristic of forest ecosystems. Estimations of LAI from satellite images generally rely on spectral vegetation indices (SVIs) or radiative transfer model (RTM) inversions. We have developed a new and precise method suitable for practical application, consisting of building a species-specific SVI that is best-suited to both sensor and vegetation characteristics. Such an SVI requires calibration on a large number of representative vegetation conditions. We developed a two-step approach: (1) estimation of LAI on a subset of satellite data through RTM inversion; and (2) the calibration of a vegetation index on these estimated LAI. We applied this methodology to Eucalyptus plantations which have highly variable LAI in time and space. Previous results showed that an RTM inversion of Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared and red reflectance allowed good retrieval performance (R-2 = 0.80, RMSE = 0.41), but was computationally difficult. Here, the RTM results were used to calibrate a dedicated vegetation index (called "EucVI") which gave similar LAI retrieval results but in a simpler way. The R-2 of the regression between measured and EucVI-simulated LAI values on a validation dataset was 0.68, and the RMSE was 0.49. The additional use of stand age and day of year in the SVI equation slightly increased the performance of the index (R-2 = 0.77 and RMSE = 0.41). This simple index opens the way to an easily applicable retrieval of Eucalyptus LAI from MODIS data, which could be used in an operational way.

A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas

Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r(2) = 0.64 and r(2) = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r(2) = 0.76 and r(2) = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km(2) (r(2) = 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Re). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.

When Is the Best Moment to Assess the Ankle Brachial Index: Pre- or Post-Hemodialysis?

Background: Cardiovascular disease is an important cause of death in patients on dialysis. Peripheral arterial disease (PAD) is a prognostic factor for cardiovascular disease. The ankle brachial index (ABI) is a noninvasive method used for the diagnosis of PAD. The difference between ABI pre- and post-dialysis had not yet been formally tested, and it was the main objective of this study. Methods:The ABI was assessed using an automated oscillometric device in incident patients on hemodialysis. All blood pressure readings were taken in triplicate pre- and post-dialysis in three consecutive dialysis sessions (times 1, 2, and 3). Results: One hundred and twenty-three patients (85 men) aged 53 +/- 19 years were enrolled. We found no difference in ABI pre- and post-dialysis on the right or left side, and there was no difference in times 1, 2, and 3. In patients with a history of PAD, the ABI pre- versus post-dialysis were of borderline significance on the right side (p = 0.088). Conclusion: ABI measured pre- and post-dialysis presented low variability. The ABI in patients with a history of PAD should be evaluated with caution. The applicability of the current method in predicting mortality among patients on hemodialysis therefore needs further investigation. Copyright (C) 2012 S. Karger AG, Basel

Low pressure support changes the rapid shallow breathing index (RSBI) in critically ill patients on mechanical ventilation

Background: The rapid shallow breathing index (RSBI) is the most widely used index within intensive care units as a predictor of the outcome of weaning, but differences in measurement techniques have generated doubts about its predictive value. Objective: To investigate the influence of low levels of pressure support (PS) on the RSBI value of ill patients. Method: Prospective study including 30 patients on mechanical ventilation (MV) for 72 hours or more, ready for extubation. Prior to extubation, the RSBI was measured with the patient connected to the ventilator (Drager (TM) Evita XL) and receiving pressure support ventilation (PSV) and 5 cmH(2)O of positive end expiratory pressure or PEEP (RSBI_MIN) and then disconnected from the VM and connected to a Wright spirometer in which respiratory rate and exhaled tidal volume were recorded for 1 min (RSBI_ESP). Patients were divided into groups according to the outcome: successful extubation group (SG) and failed extubation group (FG). Results: Of the 30 patients, 11 (37%) failed the extubation process. In the within-group comparison (RSBI_MIN versus RSBI_ESP), the values for RSBI_MIN were lower in both groups: SG (34.79 +/- 4.67 and 60.95 +/- 24.64) and FG (38.64 +/- 12.31 and 80.09 +/- 20.71; p<0.05). In the between-group comparison, there was no difference in RSBI_MIN (34.79 +/- 14.67 and 38.64 +/- 12.31), however RSBI_ESP was higher in patients with extubation failure: SG (60.95 +/- 24.64) and FG (80.09 +/- 20.71; p<0.05). Conclusion: In critically ill patients on MV for more than 72h, low levels of PS overestimate the RSBI, and the index needs to be measured with the patient breathing spontaneously without the aid of pressure support.

Effects of excess body mass on strength and fatigability of quadriceps in postmenopausal women

Objective: Obesity is a major public health problem leading to, among other things, reduced functional capacity. Moreover, obesity-related declines in functional capacity may be compounded by the detrimental consequences of menopause. The aim of this study was to understand the potential effects of excess body mass on measures of functional capacity in postmenopausal women. Methods: Forty-five postmenopausal women aged 50 to 60 years were divided into two groups according to body mass index (BMI): obese (BMI, >= 30 kg/m(2); n = 19) and nonobese (BMI, 18.5-29.9 kg/m(2); n = 26). To determine clinical characteristics, body composition, bone mineral density, and maximal exercise testing was performed, and a 3-day dietary record was estimated. To assess quadriceps function, isokinetic exercise testing at 60 degrees per second (quadriceps strength) and at 300 degrees per second (quadriceps fatigue) was performed. Results: The absolute value of the peak torque was not significantly different between the groups; however, when the data were normalized by body mass and lean mass, significantly lower values were observed for obese women compared with those in the nonobese group (128% +/- 25% vs 155% +/- 24% and 224% +/- 38% vs 257% +/- 47%, P < 0.05). The fatigue index did not show any significant difference for either group; however, when the data were normalized by the body mass and lean mass, significantly lower values were observed for obese women (69% +/- 16% vs 93% +/- 18% and 120% +/- 25% vs. 135% +/- 23%, P < 0.01). Conclusions: Our results show that despite reduced muscle force, the combination of obesity and postmenopause may be associated with greater resistance to muscle fatigue.

Relationship between body mass index with dietary fiber intake and skinfolds-differences among bodybuilders who train during morning and nocturne period

Background: The prevalence of overweight individuals has increased in recent years. Moreover, the importance of a healthy diet is associated with the practice of physical activity and attempt to verify the achievement of physical exercise influences on food choice. However, it relationship between food intake and physical activity have not been studied. Aim: To evaluate if the period in which the trainings are conducted, morning and nocturne, interfere qualitatively and quantitatively in food consumption as well as verify possible associations between anthropometric profiles and dietary habits. Methods: We collected data from 33 adult volunteers, between men and women, practitioners of bodybuilding. Results: A total of 33 volunteers were interviewed (18 (54.5%) were men and 15 (45.5%) were women). Regarding anthropometric data, it turns out that that the volunteers of the two periods had similar characteristics, differentiating only weight. The consumption of nutritional supplements was observed in 30.77% of the practitioners in the morning period vs. 35% for the nocturne. Considering macronutrient intake, there was a significant difference in the consumption of protein between the periods. The consumption during nocturne period was greater (126 +/- 5% of the daily requirement) than the morning period (115.7 +/- 2%). As for micro-nutrients, calcium intake was greater among men when compared to women. There was a positive correlation between the BMI, and arm circumference for practitioners of the morning period. Conclusion: This study show that the practitioners who train in the morning have quietly better eating habits than those in the nocturne period, however both are inappropriate.

Validation and comparison of two soil-vegetation-atmosphere transfer models for tropical Africa

This study aims to compare and validate two soil-vegetation-atmosphere-transfer (SVAT) schemes: TERRA-ML and the Community Land Model (CLM). Both SVAT schemes are run in standalone mode (decoupled from an atmospheric model) and forced with meteorological in-situ measurements obtained at several tropical African sites. Model performance is quantified by comparing simulated sensible and latent heat fluxes with eddy-covariance measurements. Our analysis indicates that the Community Land Model corresponds more closely to the micrometeorological observations, reflecting the advantages of the higher model complexity and physical realism. Deficiencies in TERRA-ML are addressed and its performance is improved: (1) adjusting input data (root depth) to region-specific values (tropical evergreen forest) resolves dry-season underestimation of evapotranspiration; (2) adjusting the leaf area index and albedo (depending on hard-coded model constants) resolves overestimations of both latent and sensible heat fluxes; and (3) an unrealistic flux partitioning caused by overestimated superficial water contents is reduced by adjusting the hydraulic conductivity parameterization. CLM is by default more versatile in its global application on different vegetation types and climates. On the other hand, with its lower degree of complexity, TERRA-ML is much less computationally demanding, which leads to faster calculation times in a coupled climate simulation.

STRUCTURAL CHARACTERIZATION OF CANOPIES OF Eucalyptus spp. USING RADIOMETRIC DATA FROM TM/Landsat 5

Empirical approaches and, more recently, physical approaches, have grounded the establishment of logical connections between radiometric variables derived from remote data and biophysical variables derived from vegetation cover. This study was aimed at evaluating correlations of dendrometric and density data from canopies of Eucalyptus spp., as collected in Capao Bonito forest unit, with radiometric data from imagery acquired by the TM/Landsat-5 sensor on two orbital passages over the study site (dates close to field data collection). Results indicate that stronger correlations were identified between crown dimensions and canopy height with near-infrared spectral band data (rho(s)4), irrespective of the satellite passage date. Estimates of spatial distribution of dendrometric data and canopy density (D) using spectral characterization were consistent with the spatial distribution of tree ages during the study period. Statistical tests were applied to evaluate performance disparities of empirical models depending on which date data were acquired. Results indicated a significant difference between models based on distinct data acquisition dates.