Relating MODIS vegetation index time-series with structure, light absorption and stem production of fast-growing Eucalyptus plantations

By allowing the estimation of forest structural and biophysical characteristics at different temporal and spatial scales, remote sensing may contribute to our understanding and monitoring of planted forests. Here, we studied 9-year time-series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on a network of 16 stands in fast-growing Eucalyptus plantations in Sao Paulo State, Brazil. We aimed to examine the relationships between NDVI time-series spanning entire rotations and stand structural characteristics (volume, dominant height, mean annual increment) in these simple forest ecosystems. Our second objective was to examine spatial and temporal variations of light use efficiency for wood production, by comparing time-series of Absorbed Photosynthetically Active Radiation (APAR) with inventory data. Relationships were calibrated between the NDVI and the fractions of intercepted diffuse and direct radiation, using hemispherical photographs taken on the studied stands at two seasons. APAR was calculated from the NDVI time-series using these relationships. Stem volume and dominant height were strongly correlated with summed NDVI values between planting date and inventory date. Stand productivity was correlated with mean NDVI values. APAR during the first 2 years of growth was variable between stands and was well correlated with stem wood production (r(2) = 0.78). In contrast, APAR during the following years was less variable and not significantly correlated with stem biomass increments. Production of wood per unit of absorbed light varied with stand age and with site index. In our study, a better site index was accompanied both by increased APAR during the first 2 years of growth and by higher light use efficiency for stem wood production during the whole rotation. Implications for simple process-based modelling are discussed. (C) 2009 Elsevier B.V. All rights reserved.

Comparison of AutoSetä and polysomnography for the detection of apnea-hypopnea events

The use of the flow vs time relationship obtained with the nasal prongs of the AutoSetä (AS) system (diagnosis mode) has been proposed to detect apneas and hypopneas in patients with reasonable nasal patency. Our aim was to compare the accuracy of AS to that of a computerized polysomnographic (PSG) system. The study was conducted on 56 individuals (45 men) with clinical characteristics of obstructive sleep apnea (OSA). Their mean (± SD) age was 44.6 ± 12 years and their body mass index was 31.3 ± 7 kg/m2. Data were submitted to parametric analysis to determine the agreement between methods and the intraclass correlation coefficient was calculated. The Student t-test and Bland and Altman plots were also used. Twelve patients had an apnea-hypopnea index (AHI) <10 in bed and 20 had values >40. The mean (± SD) AHI PSG index of 37.6 (28.8) was significantly lower (P = 0.0003) than AHI AS (41.8 (25.3)), but there was a high intraclass correlation coefficient (0.93), with 0.016 variance. For a threshold of AHI of 20, AS showed 73.0% accuracy, 97% sensitivity and 60% specificity, with positive and negative predictive values of 78% and 93%, respectively. Sensitivity, specificity and negative predictive values increased in parallel to the increase in AHI threshold for detecting OSA. However, when the differences of AHI PSG-AS were plotted against their means, the limits of agreement between the methods (95% of the differences) were +13 and -22, showing the discrepancy between the AHI values obtained with PSG and AS. Finally, cubic regression analysis was used to better predict the result of AHI PSG as a function of the method proposed, i.e., AHI AS. We conclude that, despite these differences, AHI measured by AutoSetä can be useful for the assessment of patients with high pre-test clinical probability of OSA, for whom standard PSG is not possible as an initial step in diagnosis.