Andere Kunden interessierten sich auch für
![Drought-responsive transcript(s) profiling from the leaves of soybean]( "Drought-responsive transcript(s) profiling from the leaves of soybean")
Drought-responsive transcript(s) profiling from the leaves of soybean32,99 €![Protein Function Prediction from Protein Interaction Network]( "Protein Function Prediction from Protein Interaction Network")
Protein Function Prediction from Protein Interaction Network40,99 €![Computational Prediction of Protein-Protein Interaction]( "Computational Prediction of Protein-Protein Interaction")
Computational Prediction of Protein-Protein Interaction32,99 €![Comparing Prediction Accuracy For Machine Learning]( "Comparing Prediction Accuracy For Machine Learning")
Comparing Prediction Accuracy For Machine Learning36,99 €![Exploit Prediction and Vulnerability Clustering Using Text Mining]( "Exploit Prediction and Vulnerability Clustering Using Text Mining")
Exploit Prediction and Vulnerability Clustering Using Text Mining36,99 €![On the Potential of Flupyradifurone, a Butenolide Insecticide, for Drought Stress Attenuation in Spring Wheat (Triticum aestivum L.)]( "On the Potential of Flupyradifurone, a Butenolide Insecticide, for Drought Stress Attenuation in Spring Wheat (Triticum aestivum L.)")
On the Potential of Flupyradifurone, a Butenolide Insecticide, for Drought Stress Attenuation in Spring Wheat (Triticum aestivum L.)57,80 €![Comparative Analysis of Tea and Energy Drinks on Attention Span]( "Comparative Analysis of Tea and Energy Drinks on Attention Span")
Comparative Analysis of Tea and Energy Drinks on Attention Span22,99 €
Early days of technology employed traditional methods like rainfall distribution, duration of sunshine, and the related meteorological data to forecast a forthcoming event regarding drought. Recently, satellite remote sensing has been considered as an appropriate tool for deriving information in spatial and temporal domains by providing multi-spectral reflectance data at regular intervals. In this book, analysis of series of deviation of NDVI images, extraction of virtual drought objects from the series, and investigation for drought patterns from historical image for growing season was made. Subsequent to this, appropriate prediction model of these patterns was developed for early measures while within the same season. The virtual drought objects extracted from images over the growing season were found to exhibit a pattern for the historical drought years. It is understood that this work will give new views for ways in drought prediction for early warning and crop condition monitoring at near real-time for agricultural sectors.