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.

Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

Re-Os isotope and highly siderophile element systematics of the Parana continental flood basalts (Brazil)

Basalts of the Parana continental flood basalt (PCFB) province erupted through dominantly Proterozoic continental crust during the Cretaceous. In order to examine the mantle source(s) of this major flood basalt province, we studied Os, Sr, Nd, and Pb isotope systematics, and highly siderophile element (HSE) abundances in tholeiitic basalts that were carefully chosen to show the minimal effects of crustal contamination. These basalts define a precise Re-Os isochron with an age of 131.6 +/- 2.3 Ma and an initial Os-187/Os-188 of 0.1295 +/- 0.0018 (gamma Os-187 = +2.7 +/- 1.4). This initial Os isotopic composition is considerably more radiogenic than estimates of the contemporary Depleted Mantle (DM). The fact that the Re-Os data define a well constrained isochron with an age similar to Ar-40/Ar-39 age determinations, despite generally low Os concentrations, is consistent with closed-system behavior for the HSE. Neodymium, Sr, and Pb isotopic data suggest that the mantle source of the basalts had been variably hybridized by melts derived from enriched mantle components. To account for the combined Os, Nd, Sr, and Pb isotopic characteristics of these rocks, we propose that the primary melts formed from metasomatized asthenospheric mantle (represented by arc-mantle peridotite) that underwent mixing with two enriched components, EM-I and EM-II. The different enriched components are reflected in minor isotopic differences between basalts from southern and northern portions of the province. The Tristan da Cunha hotspot has been previously suggested to be the cause of the Parana continental flood basalt magmatism. However, present-day Tristan da Cunha lavas have much higher Os-187/Os-188 isotopic compositions than the source of the PCFB. These data, together with other isotopic and elemental data, preclude making a definitive linkage between the Tristan plume and the PCFB. (C) 2012 Elsevier B.V. All rights reserved.