Multisource classification for land-use mapping based on spectral, textural, and terrain information using landsat thematic mapper imagery: A Case Study of Semarang-Ungaran Area, Central Java
Automatic classification of remotely sensed digital data is recognised as a robust and efficient method for mapping various land-cover types over a large area. However when more abstract concept such as land-use is required the automatic classification methods cannot be fully useful. This is due to...
| Main Author: | |
|---|---|
| Format: | Article |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2003
|
| Subjects: |
| _version_ | 1797019463820771328 |
|---|---|
| author | Perpustakaan UGM, i-lib |
| author_facet | Perpustakaan UGM, i-lib |
| author_sort | Perpustakaan UGM, i-lib |
| collection | UGM |
| description | Automatic classification of remotely sensed digital data is recognised as a robust and efficient method for mapping various land-cover types over a large area. However when more abstract concept such as land-use is required the automatic classification methods cannot be fully useful. This is due to the fact that land-use is related to various landscape factors, and cannot be mapped merely based on its spectral reflectance. This study tried to develop a knowledge-based technique that incorporates textural and terrain information of the image scene into a spectral-based decision making process for land-use labelling. To do so. six reflective hands of Landsat Thematic Mapper (TM) covering Semarang-Ungaran area. Central Java, were used. In addition, all bands were then be filtered using the so-called textural filter, which can accentuate several statistical parameters within a given window. .1 variance parameter was chosen in order to extract heterogeneity within every 7x7 pixels. and the l'ariance values of the whole image dalaset were then stored as a set of texture-filtered bands. Three bands with the lowest 'between-band correlations' were chosen and added to the reflective bands. Based on the nine-layer image dataset, a standard multispectral classification using maximum likelihood algorithm was run. Parallel to this process, a visual interpretation using heads-up digitisation was carried out in order to generate a terrain unit map containing land characteristics relevant to spatial distribution of the land-use in the study area. Finally. the terrain unit map was superimposed with the tentative land-corer map derived from the multispectral classification process. A final land-use map was generated from the nnthisource data integration, controlled by a formalised knowledge about ecological relationship between land-cover. land-use, and land characteristics exist in the field. It was found that the overall accuracy level of the final land-use map is higher as compared to the result generated from six-band classification. However, the use of textural filter also created an 'edge-effect', which shows misclassified pixels alongside the borders of particular land-use categories. The edge-effect also leads to lower accuracy levels for the corresponding land-use categories. In addition, based on the research findings, further research agenda was also set up.
Keywords: textural information, multisource classification, knowledge-based technique, land-use mapping |
| first_indexed | 2024-03-05T23:09:02Z |
| format | Article |
| id | oai:generic.eprints.org:26365 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T19:00:08Z |
| publishDate | 2003 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:263652014-06-18T00:30:22Z https://repository.ugm.ac.id/26365/ Multisource classification for land-use mapping based on spectral, textural, and terrain information using landsat thematic mapper imagery: A Case Study of Semarang-Ungaran Area, Central Java Perpustakaan UGM, i-lib Jurnal i-lib UGM Automatic classification of remotely sensed digital data is recognised as a robust and efficient method for mapping various land-cover types over a large area. However when more abstract concept such as land-use is required the automatic classification methods cannot be fully useful. This is due to the fact that land-use is related to various landscape factors, and cannot be mapped merely based on its spectral reflectance. This study tried to develop a knowledge-based technique that incorporates textural and terrain information of the image scene into a spectral-based decision making process for land-use labelling. To do so. six reflective hands of Landsat Thematic Mapper (TM) covering Semarang-Ungaran area. Central Java, were used. In addition, all bands were then be filtered using the so-called textural filter, which can accentuate several statistical parameters within a given window. .1 variance parameter was chosen in order to extract heterogeneity within every 7x7 pixels. and the l'ariance values of the whole image dalaset were then stored as a set of texture-filtered bands. Three bands with the lowest 'between-band correlations' were chosen and added to the reflective bands. Based on the nine-layer image dataset, a standard multispectral classification using maximum likelihood algorithm was run. Parallel to this process, a visual interpretation using heads-up digitisation was carried out in order to generate a terrain unit map containing land characteristics relevant to spatial distribution of the land-use in the study area. Finally. the terrain unit map was superimposed with the tentative land-corer map derived from the multispectral classification process. A final land-use map was generated from the nnthisource data integration, controlled by a formalised knowledge about ecological relationship between land-cover. land-use, and land characteristics exist in the field. It was found that the overall accuracy level of the final land-use map is higher as compared to the result generated from six-band classification. However, the use of textural filter also created an 'edge-effect', which shows misclassified pixels alongside the borders of particular land-use categories. The edge-effect also leads to lower accuracy levels for the corresponding land-use categories. In addition, based on the research findings, further research agenda was also set up. Keywords: textural information, multisource classification, knowledge-based technique, land-use mapping [Yogyakarta] : Universitas Gadjah Mada 2003 Article NonPeerReviewed Perpustakaan UGM, i-lib (2003) Multisource classification for land-use mapping based on spectral, textural, and terrain information using landsat thematic mapper imagery: A Case Study of Semarang-Ungaran Area, Central Java. Jurnal i-lib UGM. http://i-lib.ugm.ac.id/jurnal/download.php?dataId=9385 |
| spellingShingle | Jurnal i-lib UGM Perpustakaan UGM, i-lib Multisource classification for land-use mapping based on spectral, textural, and terrain information using landsat thematic mapper imagery: A Case Study of Semarang-Ungaran Area, Central Java |
| title | Multisource classification for land-use mapping based on spectral, textural, and terrain information using landsat thematic mapper imagery: A Case Study of Semarang-Ungaran Area, Central Java |
| title_full | Multisource classification for land-use mapping based on spectral, textural, and terrain information using landsat thematic mapper imagery: A Case Study of Semarang-Ungaran Area, Central Java |
| title_fullStr | Multisource classification for land-use mapping based on spectral, textural, and terrain information using landsat thematic mapper imagery: A Case Study of Semarang-Ungaran Area, Central Java |
| title_full_unstemmed | Multisource classification for land-use mapping based on spectral, textural, and terrain information using landsat thematic mapper imagery: A Case Study of Semarang-Ungaran Area, Central Java |
| title_short | Multisource classification for land-use mapping based on spectral, textural, and terrain information using landsat thematic mapper imagery: A Case Study of Semarang-Ungaran Area, Central Java |
| title_sort | multisource classification for land use mapping based on spectral textural and terrain information using landsat thematic mapper imagery a case study of semarang ungaran area central java |
| topic | Jurnal i-lib UGM |
| work_keys_str_mv | AT perpustakaanugmilib multisourceclassificationforlandusemappingbasedonspectraltexturalandterraininformationusinglandsatthematicmapperimageryacasestudyofsemarangungaranareacentraljava |