A Method to Improve the Performance of Raster Selection Based on a User-Defined Condition: An Example of Application for Agri-environmental Data
Autor: | François Pinet, Myoung-Ah Kang, Driss En-Nejjary |
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Rok vydání: | 2018 |
Předmět: |
Sequence
Data processing Computer science Process (engineering) 010401 analytical chemistry Climate change Value (computer science) 04 agricultural and veterinary sciences computer.file_format computer.software_genre 01 natural sciences 0104 chemical sciences Environmental data 13. Climate action 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Data mining Raster graphics computer Selection (genetic algorithm) |
Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030044466 |
DOI: | 10.1007/978-3-030-04447-3_13 |
Popis: | More and more environmental and agricultural data are now acquired with a high precision and temporal frequency. These data are often represented in the form of rasters and are useful for agricultural activities or climate change analyses. In this paper, we propose a new method to process very large raster. We present a new technique to improve the execution time of the selection and calculation of data summaries (e.g., the average temperature for a region) on a temporal sequence of rasters. We illustrate the use of our approach on the case of temperature data, which is important information both for agriculture and for climate change analyses. We have generated several data sets in order to analyze the influence of the different value properties on the process performance. One of our final goals is to provide information about the value conditions in which the proposed processing should be used. |
Databáze: | OpenAIRE |
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