Process-based image analysis for agricultural mapping: A case study in Turkgeldi region, Turkey
The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose becaus...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Damla Uca Avci, Z. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015transfer abstract |
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| Schlagwörter: |
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| Umfang: |
10 |
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| Übergeordnetes Werk: |
Enthalten in: Posttranscriptional actions of triiodothyronine on - Bargi-Souza, Paula ELSEVIER, 2018, including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU), Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:56 ; year:2015 ; number:8 ; day:15 ; month:10 ; pages:1635-1644 ; extent:10 |
| Links: |
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| DOI / URN: |
10.1016/j.asr.2015.07.021 |
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| Katalog-ID: |
ELV023495944 |
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| 520 | |a The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. | ||
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10.1016/j.asr.2015.07.021 doi GBVA2015008000020.pica (DE-627)ELV023495944 (ELSEVIER)S0273-1177(15)00523-2 DE-627 ger DE-627 rakwb eng 520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl Damla Uca Avci, Z. verfasserin aut Process-based image analysis for agricultural mapping: A case study in Turkgeldi region, Turkey 2015transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. Image processing Elsevier Crop mapping Elsevier Object-based classification Elsevier Sunar, Filiz oth Enthalten in Elsevier Science Bargi-Souza, Paula ELSEVIER Posttranscriptional actions of triiodothyronine on 2018 including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU) Amsterdam [u.a.] (DE-627)ELV000905844 volume:56 year:2015 number:8 day:15 month:10 pages:1635-1644 extent:10 https://doi.org/10.1016/j.asr.2015.07.021 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.89 Endokrinologie VZ AR 56 2015 8 15 1015 1635-1644 10 045F 520 |
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10.1016/j.asr.2015.07.021 doi GBVA2015008000020.pica (DE-627)ELV023495944 (ELSEVIER)S0273-1177(15)00523-2 DE-627 ger DE-627 rakwb eng 520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl Damla Uca Avci, Z. verfasserin aut Process-based image analysis for agricultural mapping: A case study in Turkgeldi region, Turkey 2015transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. Image processing Elsevier Crop mapping Elsevier Object-based classification Elsevier Sunar, Filiz oth Enthalten in Elsevier Science Bargi-Souza, Paula ELSEVIER Posttranscriptional actions of triiodothyronine on 2018 including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU) Amsterdam [u.a.] (DE-627)ELV000905844 volume:56 year:2015 number:8 day:15 month:10 pages:1635-1644 extent:10 https://doi.org/10.1016/j.asr.2015.07.021 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.89 Endokrinologie VZ AR 56 2015 8 15 1015 1635-1644 10 045F 520 |
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10.1016/j.asr.2015.07.021 doi GBVA2015008000020.pica (DE-627)ELV023495944 (ELSEVIER)S0273-1177(15)00523-2 DE-627 ger DE-627 rakwb eng 520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl Damla Uca Avci, Z. verfasserin aut Process-based image analysis for agricultural mapping: A case study in Turkgeldi region, Turkey 2015transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. Image processing Elsevier Crop mapping Elsevier Object-based classification Elsevier Sunar, Filiz oth Enthalten in Elsevier Science Bargi-Souza, Paula ELSEVIER Posttranscriptional actions of triiodothyronine on 2018 including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU) Amsterdam [u.a.] (DE-627)ELV000905844 volume:56 year:2015 number:8 day:15 month:10 pages:1635-1644 extent:10 https://doi.org/10.1016/j.asr.2015.07.021 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.89 Endokrinologie VZ AR 56 2015 8 15 1015 1635-1644 10 045F 520 |
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10.1016/j.asr.2015.07.021 doi GBVA2015008000020.pica (DE-627)ELV023495944 (ELSEVIER)S0273-1177(15)00523-2 DE-627 ger DE-627 rakwb eng 520 620 520 DE-600 620 DE-600 610 570 VZ 44.89 bkl Damla Uca Avci, Z. verfasserin aut Process-based image analysis for agricultural mapping: A case study in Turkgeldi region, Turkey 2015transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. Image processing Elsevier Crop mapping Elsevier Object-based classification Elsevier Sunar, Filiz oth Enthalten in Elsevier Science Bargi-Souza, Paula ELSEVIER Posttranscriptional actions of triiodothyronine on 2018 including COSPAR information bulletin : the official journal of the Committee on Space Research (COSPAR), a scientific committee of the International Council of Scientific Unions (ICSU) Amsterdam [u.a.] (DE-627)ELV000905844 volume:56 year:2015 number:8 day:15 month:10 pages:1635-1644 extent:10 https://doi.org/10.1016/j.asr.2015.07.021 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.89 Endokrinologie VZ AR 56 2015 8 15 1015 1635-1644 10 045F 520 |
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Damla Uca Avci, Z. |
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process-based image analysis for agricultural mapping: a case study in turkgeldi region, turkey |
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Process-based image analysis for agricultural mapping: A case study in Turkgeldi region, Turkey |
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The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. |
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The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. |
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The need for timely, accurate, and interoperable geospatial information is steadily increasing. In this context, process-based image processing systems will be the initial segment for future’s automatic systems. A process-based system is believed to be a good approach for agricultural purpose because agricultural activities are carried out according to a periodic (annual) cycle. Therefore, a process-based image analysis procedure was designed for routine crop classification for an agricultural region in Kırklareli, Turkey. The process tree developed uses a multi-temporal image data set as an input and gives the final crop classification as an output by using an incremental rule set. The test data set was composed of five images of Satellite Pour l’Observation de la Terre 4 (SPOT 4) data acquired in 2007. |
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