Investigating Temporal Patterns and Spatial Correlation in RSI

Alinune Musopole (Autor)

Buch | Softcover

76 Seiten

2016
Scholar's Press (Verlag)
9783659843426 (ISBN)

Infos

The world today is data-centric. The challenge that we have in such a world is extracting as much information from the data as the data contain. The challenge is made even worse when technology comes into the equation. Technology has led to the collection, storage, retrieval and analysis of data. With technology, it is possible to collect large volumes of data (such as remote sensing images, RSI, obtained both in space and time at a high frequency). Handling such kind of data becomes a challenge. This work partly presents one of the methods through which large volumes of data can be handled. The application of mathematical sciences in various disciplines is fascinating. Using mathematical sciences, methods for handling challenges in various sectors, such as environmental sector, are developed. Thus this work also presents one rare method that is used in analysing variation in terms of periodicity in multiple time series of, for example, climate data (this kind of data is mostly characterised by periodicity).

Autor

Alinune Musopole is a holder of MSc in Environmental Statistics from the University of Glasgow. Environmental challenges that we are facing and the many applications of mathematical sciences in the environmental sector effected his interest in conducting environment-related studies. He has published work relating to this sector.

Produkt-Details

• Erscheinungsdatum: 29.10.2016
• Sprache: englisch
• Maße: 150 x 220 mm
• Gewicht: 130 g
• Themenwelt: Mathematik / Informatik ► Mathematik
• Schlagworte: climate change • Functional Data • Principle Periodic Components • Remote Sensing
• ISBN-13: 9783659843426 / 9783659843426
• Zustand: Neuware