|
|
|||
|
||||
OverviewThis thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space. Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved. The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed ""big data."" The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation. Full Product DetailsAuthor: Nasrin NasrollahiPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 2015 ed. Dimensions: Width: 15.50cm , Height: 0.60cm , Length: 23.50cm Weight: 0.313kg ISBN: 9783319120805ISBN 10: 3319120808 Pages: 68 Publication Date: 27 November 2014 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
||||