Forest Cover Classification by Optimal Segmentation of High Resolution Satellite Imagery
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, So-Ra | - |
dc.contributor.author | Lee, Woo-Kyun | - |
dc.contributor.author | Kwak, Doo-Ahn | - |
dc.contributor.author | Biging, Greg S. | - |
dc.contributor.author | Gong, Peng | - |
dc.contributor.author | Lee, Jun-Hak | - |
dc.contributor.author | Cho, Hyun-Kook | - |
dc.date.accessioned | 2021-09-07T15:46:51Z | - |
dc.date.available | 2021-09-07T15:46:51Z | - |
dc.date.created | 2021-06-14 | - |
dc.date.issued | 2011-02 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/113179 | - |
dc.description.abstract | This study investigated whether high-resolution satellite imagery is suitable for preparing a detailed digital forest cover map that discriminates forest cover at the tree species level. First, we tried to find an optimal process for segmenting the high-resolution images using a region-growing method with the scale, color and shape factors in Definiens (R) Professional 5.0. The image was classified by a traditional, pixel-based, maximum likelihood classification approach using the spectral information of the pixels. The pixels in each segment were reclassified using a segment-based classification (SBC) with a majority rule. Segmentation with strongly weighted color was less sensitive to the scale parameter and led to optimal forest cover segmentation and classification. The pixel-based classification (PBC) suffered from the. salt-and-pepper effect. and performed poorly in the classification of forest cover types, whereas the SBC helped to attenuate the effect and notably improved the classification accuracy. As a whole, SBC proved to be more suitable for classifying and delineating forest cover using high-resolution satellite images. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.subject | REMOTE-SENSING IMAGERY | - |
dc.subject | OBJECT-BASED CLASSIFICATION | - |
dc.subject | LAND-USE CLASSIFICATION | - |
dc.subject | CONTEXTUAL CLASSIFICATION | - |
dc.subject | ACCURACY | - |
dc.subject | IDENTIFICATION | - |
dc.subject | INFORMATION | - |
dc.subject | ALGORITHMS | - |
dc.subject | MODELS | - |
dc.title | Forest Cover Classification by Optimal Segmentation of High Resolution Satellite Imagery | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Woo-Kyun | - |
dc.contributor.affiliatedAuthor | Kwak, Doo-Ahn | - |
dc.identifier.doi | 10.3390/s110201943 | - |
dc.identifier.scopusid | 2-s2.0-79952074186 | - |
dc.identifier.wosid | 000287735400043 | - |
dc.identifier.bibliographicCitation | SENSORS, v.11, no.2, pp.1943 - 1958 | - |
dc.relation.isPartOf | SENSORS | - |
dc.citation.title | SENSORS | - |
dc.citation.volume | 11 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 1943 | - |
dc.citation.endPage | 1958 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Instruments & Instrumentation | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
dc.subject.keywordPlus | REMOTE-SENSING IMAGERY | - |
dc.subject.keywordPlus | OBJECT-BASED CLASSIFICATION | - |
dc.subject.keywordPlus | LAND-USE CLASSIFICATION | - |
dc.subject.keywordPlus | CONTEXTUAL CLASSIFICATION | - |
dc.subject.keywordPlus | ACCURACY | - |
dc.subject.keywordPlus | IDENTIFICATION | - |
dc.subject.keywordPlus | INFORMATION | - |
dc.subject.keywordPlus | ALGORITHMS | - |
dc.subject.keywordPlus | MODELS | - |
dc.subject.keywordAuthor | digital forest cover map | - |
dc.subject.keywordAuthor | high resolution | - |
dc.subject.keywordAuthor | satellite image | - |
dc.subject.keywordAuthor | pixel-based classification | - |
dc.subject.keywordAuthor | segment-based classification | - |
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