| Author | Sarn Aksaranugraha |
| Call Number | AIT Thesis no.RS-09-19 |
| Subject(s) | Remote sensing
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| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Remote Sensing and Geographic Information System |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. RS-09-19 |
| Abstract | Remote Sensing (RS) is a modern way of collecting information of an object or phenomenon without accessing and disturbing the area. The frequent use of RS data is to monitor the vegetation growth by analyzing the dynamic of the data time series. The dynamic data in time series is widely known as Normalized Difference Vegetation Index (NDVI), which depends on the satellite’s return period . Even though the RS data is very useful for analyzing vegetation growth, because the sensor measures from a long way above the earth’s surface, cloud is one of the factors which contaminate the quality of the time series data. The widely used algorithm to remove cloud contamination is local maximum fitting (LMF). However, LMF algorithm takes very long processing time. Graphic processing unit (GPU) is a compute device, which is capable of data - parallel computation used in many scientific fields to compute highly intense algorithms. This is because of its flexibility for both graphic and non - graphic computations. Therefore, GPU is introduced in this study to reduce the processing time of LMF. |
| Year | 2009 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. RS-09-19 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Honda, Kiyoshi |
| Examination Committee(s) | Ohira, Wataru;Aoki, Takayuki;Dailey, Mathew N.;Voratas Kachitvichyanukul |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2009 |