AI SearchClassification technique for multi-temporal vegetation index data
Call Number: AIT Thesis no.CS-93-32 Material type:
TextSeries: Asian Institute of Technology. Thesis ; no. CS-93-32Publication details: Bangkok : Asian Institute of Technology, 1993Description: 55 leaves + 1 online resourceSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 1993 Summary: GVI data were used in this digital image processing study to classify the land cover and to monitor the vegetation dynamics for Asian region. Since this data has multi-bands, in order to reduce the redundancy, Principal Component Analysis was implemented for this multi-temporal data. Color composite images of monthly GVI data were to be useful for visual interpretation of seasonal dynamics. There was a correspondence between seasonal and regional variation of the monthly GVI data. The pattern classification was applied to monthly data for one-year, using the Clustering which is useful for global land cover classification without ground truth. All proposed methods have been applied to GVI images of Asia, and good results have been obtained. Here it is proved that the multi-temporal data can be a suitable method to define the class type and to detect the vegetation changes.
| Cover image | Item type | Current library | Home library | Collection | Shelving location | Call number | Materials specified | Vol info | URL | Copy number | Status | Notes | Date due | Barcode | Item holds | Item hold queue priority | Course reserves | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
22-AIT Thesis (Replacement)
|
Asian Institute of Technology Library AIT Publications | AIT Thesis no.CS-93-32 (Browse shelf(Opens below)) | 3 | Available | 30050120676647 | |||||||||||||
20-AIT Publication
|
Asian Institute of Technology Library AIT Publications | AIT Thesis no.CS-93-32 (Browse shelf(Opens below)) | 4 | Available | 30050211014773 | |||||||||||||
40-Archives
|
Asian Institute of Technology Library Archives | AIT Thesis no.CS-93-32 (Browse shelf(Opens below)) | Available | 30050120356877 |
A thesis submitted in partial fulfillment of the requirement for the degree of Master of Engineering
Thesis (M.Eng.) - Asian Institute of Technology, 1993
GVI data were used in this digital image processing study to classify the land cover and to monitor the vegetation dynamics for Asian region. Since this data has multi-bands, in order to reduce the redundancy, Principal Component Analysis was implemented for this multi-temporal data. Color composite images of monthly GVI data were to be useful for visual interpretation of seasonal dynamics. There was a correspondence between seasonal and regional variation of the monthly GVI data. The pattern classification was applied to monthly data for one-year, using the Clustering which is useful for global land cover classification without ground truth. All proposed methods have been applied to GVI images of Asia, and good results have been obtained. Here it is proved that the multi-temporal data can be a suitable method to define the class type and to detect the vegetation changes.
There are no comments on this title.