Micro-classification of orchards and agricultural croplands by applying object based image analysis and fuzzy algorithms for estimating the area under cultivation
Remote sensing technology is one of the most efficient and innovative technologies for agricultural land use/cover mapping. In this regard, the object-based Image Analysis (OBIA) is known as a new method of satellite image processing which integrates spatial and spectral information for satellite im...
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Kharazmi University
2018-03-01
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| Series: | تحقیقات کاربردی علوم جغرافیایی |
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| Online Access: | http://jgs.khu.ac.ir/article-1-2735-en.pdf |
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| author | Bakhtiar Feizizadeh Ali KHedmat Zadeh Mohammad Reza Nikjoo, |
| author_facet | Bakhtiar Feizizadeh Ali KHedmat Zadeh Mohammad Reza Nikjoo, |
| author_sort | Bakhtiar Feizizadeh |
| collection | DOAJ |
| description | Remote sensing technology is one of the most efficient and innovative technologies for agricultural land use/cover mapping. In this regard, the object-based Image Analysis (OBIA) is known as a new method of satellite image processing which integrates spatial and spectral information for satellite image process. This approach make use of spectral, environmental, physical and geometrical characteristics (e.g. texture, shape) together images contexts for modeling of land use/cover classes. The main objective of this study is to classify micro land use/cover of Meyandoab County by applying appropriate and effective algorithms and parameters in the object based approach. For this goal, Quick Bird and Aster satellite images were used within the integrated approach for processing and land use modeling. Accordingly, the land use map was classified in 9 class based on spectral and spatial characteristics. In order to perform OBIA, the segmentation was applied in the scale of 10, shape parameter of 0.7 as well as the compactness of 0.3. In terms of the classification task, fuzzy based algorithm and operators (AND, OR) was applied to detriment the membership functionality of segments for each class as well as classifying the related objects. We also applied textures, geometric, NDVI, GLCM, brightness algorithms based on fuzzy operators and assign class algorithm. In order to applying the validation of results, the accuracy assessment step was performed and the finally overall accuracy of 93.6 was obtained for the derived map. The Kappa coefficient was also detriment to be 0.92. The area under cultivation included respectively for lands of wheat and barley, prunes and plums, apples, vineyards and alfalfa hay2622.42, 4505, 4354.55, 4457.85, 14110.58 hectares. |
| format | Article |
| id | doaj-art-f9f3c02b7d0042e798c33e0f5acc6912 |
| institution | Kabale University |
| issn | 2228-7736 2588-5138 |
| language | fas |
| publishDate | 2018-03-01 |
| publisher | Kharazmi University |
| record_format | Article |
| series | تحقیقات کاربردی علوم جغرافیایی |
| spelling | doaj-art-f9f3c02b7d0042e798c33e0f5acc69122025-01-31T17:24:18ZfasKharazmi Universityتحقیقات کاربردی علوم جغرافیایی2228-77362588-51382018-03-011848201216Micro-classification of orchards and agricultural croplands by applying object based image analysis and fuzzy algorithms for estimating the area under cultivationBakhtiar Feizizadeh0Ali KHedmat Zadeh1Mohammad Reza Nikjoo,2 Assistant Professor of Remote Sensing, Tabriz University . MSc student of Remote Sensing, Tabriz University Associate professor of geomorphology at Tabriz University. Remote sensing technology is one of the most efficient and innovative technologies for agricultural land use/cover mapping. In this regard, the object-based Image Analysis (OBIA) is known as a new method of satellite image processing which integrates spatial and spectral information for satellite image process. This approach make use of spectral, environmental, physical and geometrical characteristics (e.g. texture, shape) together images contexts for modeling of land use/cover classes. The main objective of this study is to classify micro land use/cover of Meyandoab County by applying appropriate and effective algorithms and parameters in the object based approach. For this goal, Quick Bird and Aster satellite images were used within the integrated approach for processing and land use modeling. Accordingly, the land use map was classified in 9 class based on spectral and spatial characteristics. In order to perform OBIA, the segmentation was applied in the scale of 10, shape parameter of 0.7 as well as the compactness of 0.3. In terms of the classification task, fuzzy based algorithm and operators (AND, OR) was applied to detriment the membership functionality of segments for each class as well as classifying the related objects. We also applied textures, geometric, NDVI, GLCM, brightness algorithms based on fuzzy operators and assign class algorithm. In order to applying the validation of results, the accuracy assessment step was performed and the finally overall accuracy of 93.6 was obtained for the derived map. The Kappa coefficient was also detriment to be 0.92. The area under cultivation included respectively for lands of wheat and barley, prunes and plums, apples, vineyards and alfalfa hay2622.42, 4505, 4354.55, 4457.85, 14110.58 hectares.http://jgs.khu.ac.ir/article-1-2735-en.pdfobject-based classification methodsaster and quick bird satellite imagesagricultural land use mapmeyandoab county |
| spellingShingle | Bakhtiar Feizizadeh Ali KHedmat Zadeh Mohammad Reza Nikjoo, Micro-classification of orchards and agricultural croplands by applying object based image analysis and fuzzy algorithms for estimating the area under cultivation تحقیقات کاربردی علوم جغرافیایی object-based classification methods aster and quick bird satellite images agricultural land use map meyandoab county |
| title | Micro-classification of orchards and agricultural croplands by applying object based image analysis and fuzzy algorithms for estimating the area under cultivation |
| title_full | Micro-classification of orchards and agricultural croplands by applying object based image analysis and fuzzy algorithms for estimating the area under cultivation |
| title_fullStr | Micro-classification of orchards and agricultural croplands by applying object based image analysis and fuzzy algorithms for estimating the area under cultivation |
| title_full_unstemmed | Micro-classification of orchards and agricultural croplands by applying object based image analysis and fuzzy algorithms for estimating the area under cultivation |
| title_short | Micro-classification of orchards and agricultural croplands by applying object based image analysis and fuzzy algorithms for estimating the area under cultivation |
| title_sort | micro classification of orchards and agricultural croplands by applying object based image analysis and fuzzy algorithms for estimating the area under cultivation |
| topic | object-based classification methods aster and quick bird satellite images agricultural land use map meyandoab county |
| url | http://jgs.khu.ac.ir/article-1-2735-en.pdf |
| work_keys_str_mv | AT bakhtiarfeizizadeh microclassificationoforchardsandagriculturalcroplandsbyapplyingobjectbasedimageanalysisandfuzzyalgorithmsforestimatingtheareaundercultivation AT alikhedmatzadeh microclassificationoforchardsandagriculturalcroplandsbyapplyingobjectbasedimageanalysisandfuzzyalgorithmsforestimatingtheareaundercultivation AT mohammadrezanikjoo microclassificationoforchardsandagriculturalcroplandsbyapplyingobjectbasedimageanalysisandfuzzyalgorithmsforestimatingtheareaundercultivation |