Determination of the Olive Trees with Object Based Classification of Pleiades Satellite Image
Identification of fruit trees and determination of their spatial distribution is an important task for several agricultural activities including fruit yield estimation, irrigation planning, disease management and supporting agricultural policies. This research aims to determine spatial distributio...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IJEGEO
2018-08-01
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| Series: | International Journal of Environment and Geoinformatics |
| Subjects: | |
| Online Access: | http://dergipark.gov.tr/download/article-file/504698 |
| _version_ | 1797915340856885248 |
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| author | Uğur Algancı Elif Sertel Şinasi Kaya |
| author_facet | Uğur Algancı Elif Sertel Şinasi Kaya |
| author_sort | Uğur Algancı |
| collection | DOAJ |
| description | Identification of fruit trees and determination of their spatial distribution is an important task for several
agricultural activities including fruit yield estimation, irrigation planning, disease management and supporting
agricultural policies. This research aims to determine spatial distribution of olive trees at parcel level by using
geographic object based image analysis (GEOBIA) and very high resolution satellite images. A pilot area
located in the Aegean region of Turkey was selected to conduct research considering the massive amount of
olive production within the area. GEOBIA based decision-tree classification was applied to accurately map
perennial crop parcel boundaries. After applying multi-resolution segmentation to create image objects,
thresholds determined from spectral properties of image objects were integrated into the decision tree to ensure
accurate mapping of olive trees. Accuracy assessment was conducted by comparing a highly accurate parcel
database with classification results and efficiency of parcel identification and areal information derivation were
evaluated. Our results indicated that, decision-tree oriented GEOBIA classification provided sufficient results
for determination of olive trees with 90 percent classification accuracy and differentiating them from nonvegetated
areas and annual crops. Area estimation and parcel detection performances of the method were also
acceptable by providing 0.11 and 0.08 relative errors respectively |
| first_indexed | 2024-04-10T12:40:10Z |
| format | Article |
| id | doaj.art-f777890259704a68854008f9cbfc4bb2 |
| institution | Directory Open Access Journal |
| issn | 2148-9173 2148-9173 |
| language | English |
| last_indexed | 2024-04-10T12:40:10Z |
| publishDate | 2018-08-01 |
| publisher | IJEGEO |
| record_format | Article |
| series | International Journal of Environment and Geoinformatics |
| spelling | doaj.art-f777890259704a68854008f9cbfc4bb22023-02-15T16:14:21ZengIJEGEOInternational Journal of Environment and Geoinformatics2148-91732148-91732018-08-015213213910.30897/ijegeo.396713Determination of the Olive Trees with Object Based Classification of Pleiades Satellite ImageUğur Algancı0Elif Sertel1Şinasi Kaya2Istanbul Technical University, Geomatics Engineering Department, 34469 Sarıyer Istanbul TRIstanbul Technical University, Geomatics Engineering Department, 34469 Sarıyer Istanbul TRIstanbul Technical University, Geomatics Engineering Department, 34469 Sarıyer Istanbul TRIdentification of fruit trees and determination of their spatial distribution is an important task for several agricultural activities including fruit yield estimation, irrigation planning, disease management and supporting agricultural policies. This research aims to determine spatial distribution of olive trees at parcel level by using geographic object based image analysis (GEOBIA) and very high resolution satellite images. A pilot area located in the Aegean region of Turkey was selected to conduct research considering the massive amount of olive production within the area. GEOBIA based decision-tree classification was applied to accurately map perennial crop parcel boundaries. After applying multi-resolution segmentation to create image objects, thresholds determined from spectral properties of image objects were integrated into the decision tree to ensure accurate mapping of olive trees. Accuracy assessment was conducted by comparing a highly accurate parcel database with classification results and efficiency of parcel identification and areal information derivation were evaluated. Our results indicated that, decision-tree oriented GEOBIA classification provided sufficient results for determination of olive trees with 90 percent classification accuracy and differentiating them from nonvegetated areas and annual crops. Area estimation and parcel detection performances of the method were also acceptable by providing 0.11 and 0.08 relative errors respectivelyhttp://dergipark.gov.tr/download/article-file/504698Area EstimationObject Based ClassificationOlive Tree IdentificationParcel Level AnalysisPleiades Satellite Image. |
| spellingShingle | Uğur Algancı Elif Sertel Şinasi Kaya Determination of the Olive Trees with Object Based Classification of Pleiades Satellite Image International Journal of Environment and Geoinformatics Area Estimation Object Based Classification Olive Tree Identification Parcel Level Analysis Pleiades Satellite Image. |
| title | Determination of the Olive Trees with Object Based Classification of Pleiades Satellite Image |
| title_full | Determination of the Olive Trees with Object Based Classification of Pleiades Satellite Image |
| title_fullStr | Determination of the Olive Trees with Object Based Classification of Pleiades Satellite Image |
| title_full_unstemmed | Determination of the Olive Trees with Object Based Classification of Pleiades Satellite Image |
| title_short | Determination of the Olive Trees with Object Based Classification of Pleiades Satellite Image |
| title_sort | determination of the olive trees with object based classification of pleiades satellite image |
| topic | Area Estimation Object Based Classification Olive Tree Identification Parcel Level Analysis Pleiades Satellite Image. |
| url | http://dergipark.gov.tr/download/article-file/504698 |
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