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- Author: Maycol Zaraza Aguilera
- Publisher: Our Knowledge Publishing
- ISBN-10: 6202837640
- ISBN-13: 9786202837644
- Format: 15.2 x 22.9 x 0.4 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Application for analyzing time series of satellite images (e-book) (used book) | bookbook.eu
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Description
Climate predictions support risk management and natural disaster prevention. They also provide the necessary support to make decisions about the management and planning of climate-sensitive activities to cope with potential natural disasters. In turn, monitoring and predictions of the vegetative state of crops, pastures, forests and so on support food security, taking into account that farmers can adapt their planting dates, plant the best combination of crops and choose those that are resistant to disease and adapted to the conditions in certain months of the year. Through the developed application it is possible to make predictions or estimated values of meteorological variables and indexes, for a certain day, without being limited either by the temporal resolution of remote sensors or by the availability of climate stations on land, since through the time series of images it is possible to define a pattern of behavior and thus be able to make predictions through a regression model estimated of such behavior.
EXTRA 10 % discount with code: EXTRA
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- Author: Maycol Zaraza Aguilera
- Publisher: Our Knowledge Publishing
- ISBN-10: 6202837640
- ISBN-13: 9786202837644
- Format: 15.2 x 22.9 x 0.4 cm, softcover
- Language: English English
Climate predictions support risk management and natural disaster prevention. They also provide the necessary support to make decisions about the management and planning of climate-sensitive activities to cope with potential natural disasters. In turn, monitoring and predictions of the vegetative state of crops, pastures, forests and so on support food security, taking into account that farmers can adapt their planting dates, plant the best combination of crops and choose those that are resistant to disease and adapted to the conditions in certain months of the year. Through the developed application it is possible to make predictions or estimated values of meteorological variables and indexes, for a certain day, without being limited either by the temporal resolution of remote sensors or by the availability of climate stations on land, since through the time series of images it is possible to define a pattern of behavior and thus be able to make predictions through a regression model estimated of such behavior.
Reviews