DETEKSI UPWELLING CITRA SST MODIS MENGGUNAKAN FUZZY K-MEANS CLUSTERING
Indonesia has huge potential of marine fisheries, but the utilization has not been able significantly to give strength of economic growth and increases income of fishing communities because employment is very broad, especially for traditional fisherman. One of major problems that encountered in the...
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2013
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| _version_ | 1797034899046137856 |
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| author | , Rintania Elliyati Nuryaningsih, S.T , Prof. Adhi Susanto, M.Sc., Ph.D. |
| author_facet | , Rintania Elliyati Nuryaningsih, S.T , Prof. Adhi Susanto, M.Sc., Ph.D. |
| author_sort | , Rintania Elliyati Nuryaningsih, S.T |
| collection | UGM |
| description | Indonesia has huge potential of marine fisheries, but the utilization has not
been able significantly to give strength of economic growth and increases income
of fishing communities because employment is very broad, especially for
traditional fisherman. One of major problems that encountered in the utilization of
marine fishery resources in Indonesia is difficulty to determine areas with high
probability of fishing (fishing ground). This study aims to analyze the image of
sea surface temperatures (SST) and chlorophyll MODIS image with processing
techniques in order to obtain upwelling areas that have a high degree of potential
fishery.
Upwelling is a mass movement of water from the lower layer to the
surface, this movement will bring the mass of water which has a lower
temperature and high nutrients that will improve the watersfertility. The upwelling
area indicates the formation of potential fishing ground.Changes in water
conditions, including temperature and chlorophyll can be used to identify the
occurrence of upwelling through remote sensing technology. Based on SST ( Sea
Surface Temperature) and chlorophyll image of is known the value of the
distribution of sea surface temperature and chlorophyll concentrations, which then
processed using digital image processing techniques to detect the occurrence of
upwelling phenomena. Fuzzy K-Means clustering that run using Matlab program
is used to classify image feature extraction from SST MODIS image, and
determine the upwelling occurance well.
From this study the results showed that the Fuzzy C-Means clustering can
be used with either the SPL MODIS imagery to classify and detect the occurrence
of upwelling, after 2-4 weeks MODIS image of chlorophyll detected in areas of
upwelling analyzed shown to have high levels of chlorophyll. Detection of
upwelling can be used as an additional feature on the making of the map of
potential fishing. |
| first_indexed | 2024-03-13T23:19:26Z |
| format | Thesis |
| id | oai:generic.eprints.org:128040 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:19:26Z |
| publishDate | 2013 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1280402016-03-04T08:42:52Z https://repository.ugm.ac.id/128040/ DETEKSI UPWELLING CITRA SST MODIS MENGGUNAKAN FUZZY K-MEANS CLUSTERING , Rintania Elliyati Nuryaningsih, S.T , Prof. Adhi Susanto, M.Sc., Ph.D. ETD Indonesia has huge potential of marine fisheries, but the utilization has not been able significantly to give strength of economic growth and increases income of fishing communities because employment is very broad, especially for traditional fisherman. One of major problems that encountered in the utilization of marine fishery resources in Indonesia is difficulty to determine areas with high probability of fishing (fishing ground). This study aims to analyze the image of sea surface temperatures (SST) and chlorophyll MODIS image with processing techniques in order to obtain upwelling areas that have a high degree of potential fishery. Upwelling is a mass movement of water from the lower layer to the surface, this movement will bring the mass of water which has a lower temperature and high nutrients that will improve the watersfertility. The upwelling area indicates the formation of potential fishing ground.Changes in water conditions, including temperature and chlorophyll can be used to identify the occurrence of upwelling through remote sensing technology. Based on SST ( Sea Surface Temperature) and chlorophyll image of is known the value of the distribution of sea surface temperature and chlorophyll concentrations, which then processed using digital image processing techniques to detect the occurrence of upwelling phenomena. Fuzzy K-Means clustering that run using Matlab program is used to classify image feature extraction from SST MODIS image, and determine the upwelling occurance well. From this study the results showed that the Fuzzy C-Means clustering can be used with either the SPL MODIS imagery to classify and detect the occurrence of upwelling, after 2-4 weeks MODIS image of chlorophyll detected in areas of upwelling analyzed shown to have high levels of chlorophyll. Detection of upwelling can be used as an additional feature on the making of the map of potential fishing. [Yogyakarta] : Universitas Gadjah Mada 2013 Thesis NonPeerReviewed , Rintania Elliyati Nuryaningsih, S.T and , Prof. Adhi Susanto, M.Sc., Ph.D. (2013) DETEKSI UPWELLING CITRA SST MODIS MENGGUNAKAN FUZZY K-MEANS CLUSTERING. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=68366 |
| spellingShingle | ETD , Rintania Elliyati Nuryaningsih, S.T , Prof. Adhi Susanto, M.Sc., Ph.D. DETEKSI UPWELLING CITRA SST MODIS MENGGUNAKAN FUZZY K-MEANS CLUSTERING |
| title | DETEKSI UPWELLING CITRA SST MODIS MENGGUNAKAN FUZZY K-MEANS CLUSTERING |
| title_full | DETEKSI UPWELLING CITRA SST MODIS MENGGUNAKAN FUZZY K-MEANS CLUSTERING |
| title_fullStr | DETEKSI UPWELLING CITRA SST MODIS MENGGUNAKAN FUZZY K-MEANS CLUSTERING |
| title_full_unstemmed | DETEKSI UPWELLING CITRA SST MODIS MENGGUNAKAN FUZZY K-MEANS CLUSTERING |
| title_short | DETEKSI UPWELLING CITRA SST MODIS MENGGUNAKAN FUZZY K-MEANS CLUSTERING |
| title_sort | deteksi upwelling citra sst modis menggunakan fuzzy k means clustering |
| topic | ETD |
| work_keys_str_mv | AT rintaniaelliyatinuryaningsihst deteksiupwellingcitrasstmodismenggunakanfuzzykmeansclustering AT profadhisusantomscphd deteksiupwellingcitrasstmodismenggunakanfuzzykmeansclustering |