NDVI time series
Detecting leaf pulvinar movements on NDVI time series of desert trees: a new approach for water stress detection.
... the NDVI, has proved to be useful for assessing Tamarugo’s water condition ...Nevertheless, time series of NDVI have not been directly related to GW depletion yet and to do so, the effect of ...
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Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data
... underestimated NDVI values (Gu, 2006; Hird and Mc- Dermid, ...noise-free NDVI time series following the main assumption that vegetation follows a continuous sequence drawn by in- crease, peak ...
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Historical Fire Detection of Tropical Forest from NDVI Time-series Data: Case Study on Jambi, Indonesia
... In this paper, the application of outlier detection using X12-ARIMA for exploring historical evidence of forest fire was investigated. It seems that part of Jambi natural forest have been suffering from encroachment ...
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Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5
... from time series of soil erosion and sediment yield, which are scarce and difficult to obtain in most cases (Oliveira et ...of time (and a larger area) might be estimated correctly on the basis of ...
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ANALYSIS OF THE PHENOLOGY DYNAMICS OF BRAZILIAN CAATINGA SPECIES WITH NDVI TIME SERIES
... Landsat series are identical, it was not necessary to make adjustments in the NDVI values of one sensor in relation to the ...the NDVI calculation all images had been previously recorded (fi rst ...
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A feature fusion based forecasting model for financial time series.
... Regarding prediction tools, some soft computing methods, such as Artificial Neural Networks (ANNs) and Support Vector Machine (SVM), have become popular methods for stock market forecasting due to their excellent ...
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Similarity estimators for irregular and age uncertain time series
... source of error in the linear CAR case. Both have small baseline bias for regular sam- pling. gXCF estimates coupling strength more effectively, however, for both age un- certainty and irregular sampling contributions of ...
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Sales forecast in an IT company using time series
... Network Time Series Forecasts (NNETAR), disponível na biblioteca forecast do R, recorrendo a um modelo NNAR(p,P,k), onde p corresponde ao número de observações como input, P se é sazonal ou não, onde P=1 ...
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Forecasting power of social media sentiment time series
... smaller time steps analyzing social media to get deeper knowledge about market ...short time triggers by applying similar ...of time and different securities, although sentiment data is in great ...
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Wavelet Cross-correlation in Bivariate Time-Series Analysis
... bivariate time-series analysis, the relation between two series can be ...one time series may be related to an other with a time offset (either to the past or to the future), it ...
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Modelling time series of counts: An inar approach
... in time se- ries analysis. In the context of time series of counts, [41] studies an automatic criterion for selecting the order of an INAR(p) model based on the corrected version of Akaike ...
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TSPO: an autoML approach to time series forecasting
... A time series is a sequence of historical measures of an observable variable y with an equal time interval [ 6 ...why time series are of ...to time series analysis: one is ...
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Tourism Time Series Forecast - Different ANN Architectures with Time Index Input
... The behaviour of the series indicates that there is seasonality (higher values during the summer months and lower values in winter). It is also clear that there is a progressive trend over the period in question. ...
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Time series forecasting for a call center in a Warsaw holding company
... study time series were mostly based on the idea of a deterministic world until 1927, when the first major breakthrough in the area of time series forecasting took place essentially thanks to ...
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Web-based Interface for Tailored Time Series Analysis and Visualization
... Making this process work in this fashion, is a more intuitive way to load the report, than to load it all at once, because the user understands at which state he’s in, since there is not an idle state, where no feedback ...
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On the extremes of randomly sub-sampled time series
... measurements. Missing values, however, are frequently encountered in time series analysis of wave measurements, mainly when waverider buoys are used for collecting data sets. The main reasons are damage by ...
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Simulating Price Interactions by Mining Multivariate Financial Time Series
... By projecting again the historical data over the UbiSOM we get a set of trajectories over the map that are used to generate these alternate time series. A trajectory is formed by project- ing two ...
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The PRIMAP-hist national historical emissions time series
... aggregate time series covers the union of all years of the individual gas or sector ...gory time series, they are interpolated to close gaps and extrapolated to fill missing data at the ...
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Output convergence in Mercosur: multivariate time series evidence
... Cavalcanti Ferreira; João Victor Issler; Samuel de Abreu Pessoa – Outubro de 2003 – 8 págs. SHOULD EDUCATIONAL POLICIES BE REGRESSIVE[r] ...
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