İran genelindeki arazi örtüsü haritası, Google Earth Engine Cloud platformunda Sentinel görüntüleri işlenerek oluşturuldu. Bu amaçla, 2017 yılı için tek bir mozaik veri kümesi oluşturmak üzere 2.500'den fazla Sentinel-1 ve 11.000'den fazla Sentinel-2 görüntüsü işlendi. Ardından, İran genelindeki arazi örtüsü haritasını oluşturmak için 13 sınıfın çok sayıda referans örneğiyle nesne tabanlı bir Random Forest sınıflandırma yöntemi eğitildi.
Bantlar
Bantlar
Ad
Piksel Boyutu
Açıklama
classification
10 metre
Sınıflandırma
classification Class Table
Değer
Renk
Açıklama
1
#000000
Şehir
2
#006eff
Su
3
#41a661
Sulak arazi
4
#ff7f7f
Kalut (yardang)
5
#bee8ff
Marshland
6
#ff00c5
Salty Land
7
#ff0000
Kil
8
#00734c
orman
9
#732600
Outcrop
10
#ffaa00
Uncovered Plain
11
#d3ffbe
Kum
12
#446589
Tarım Arazisi
13
#cccccc
Range Land
Kullanım Şartları
Kullanım Şartları
Arsalan Ghorbanian, Mohammad Kakooei, Meisam Amani, Sahel Mahdavi, Ali Mohammadzadeh, Mahdi Hasanlou tarafından oluşturulan "Iran Land Cover Map
v1 13-class (2017)" adlı çalışma, Creative
Commons Attribution 4.0 Uluslararası Lisansı (CC BY 4.0) ile lisanslanmıştır.
Alıntılar
Alıntılar:
Ghorbanian, A., Kakooei, M., Amani, M., Mahdavi, S., Mohammadzadeh, A., &
Hasanlou, M. (2020). Google Earth Engine'deki Sentinel görüntülerini kullanarak İran'ın geliştirilmiş arazi örtüsü haritası ve taşınan eğitim örneklerini kullanarak arazi örtüsü sınıflandırması için yeni bir otomatik iş akışı. ISPRS Journal of
Photogrammetry and Remote Sensing, 167, 276-288.
doi:10.1016/j.isprsjprs.2020.07.013
İran genelindeki arazi örtüsü haritası, Google Earth Engine Cloud platformunda Sentinel görüntüleri işlenerek oluşturuldu. Bu amaçla, 2017 yılı için tek bir mozaik veri kümesi oluşturmak üzere 2.500'den fazla Sentinel-1 ve 11.000'den fazla Sentinel-2 görüntüsü işlendi. Ardından, nesne tabanlı bir rastgele orman sınıflandırma yöntemi eğitildi.
[null,null,[],[[["\u003cp\u003eThis dataset provides a 13-class land cover map of Iran for the year 2017, created using Sentinel-1 and Sentinel-2 imagery processed in Google Earth Engine.\u003c/p\u003e\n"],["\u003cp\u003eThe classification was performed using an object-based Random Forest method trained with a large number of reference samples.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is available at a 10-meter resolution and includes classes like urban, water, wetland, forest, and farmland.\u003c/p\u003e\n"],["\u003cp\u003eThe data is provided by the K.N. Toosi University of Technology LiDAR Lab and is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).\u003c/p\u003e\n"],["\u003cp\u003eUsers can access and analyze this dataset through the Google Earth Engine platform.\u003c/p\u003e\n"]]],["The K. N. Toosi University of Technology LiDAR Lab produced a 13-class land cover map of Iran for 2017, using over 13,500 Sentinel-1 and Sentinel-2 images processed in Google Earth Engine. An object-based Random Forest classification method was applied, with reference samples to identify categories like urban, water, forest, and more. The map is accessible via Earth Engine with the snippet `ee.Image(\"KNTU/LiDARLab/IranLandCover/V1\")`, under a CC BY 4.0 license.\n"],null,["# Iran Land Cover Map v1 13-class (2017)\n\nDataset Availability\n: 2017-01-01T00:00:00Z--2018-01-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [K. N. Toosi University of Technology LiDAR Lab](https://en.kntu.ac.ir/laser-scanners-laboratory/)\n\nTags\n:\n [landcover](/earth-engine/datasets/tags/landcover) [landuse-landcover](/earth-engine/datasets/tags/landuse-landcover) \n iran \nkntu \n\n#### Description\n\nThe Iran-wide land cover map was generated by processing Sentinel imagery\nwithin the Google Earth Engine Cloud platform. For this purpose, over 2,500\nSentinel-1 and over 11,000 Sentinel-2 images were processed to produce a single\nmosaic dataset for the year 2017. Then, an object-based Random Forest\nclassification method was trained by a large number of reference samples for 13\nclasses to generate the Iran-wide land cover map.\n\n### Bands\n\n**Bands**\n\n| Name | Pixel Size | Description |\n|------------------|------------|----------------|\n| `classification` | 10 meters | Classification |\n\n**classification Class Table**\n\n| Value | Color | Description |\n|-------|---------|-----------------|\n| 1 | #000000 | Urban |\n| 2 | #006eff | Water |\n| 3 | #41a661 | Wetland |\n| 4 | #ff7f7f | Kalut (yardang) |\n| 5 | #bee8ff | Marshland |\n| 6 | #ff00c5 | Salty Land |\n| 7 | #ff0000 | Clay |\n| 8 | #00734c | Forest |\n| 9 | #732600 | Outcrop |\n| 10 | #ffaa00 | Uncovered Plain |\n| 11 | #d3ffbe | Sand |\n| 12 | #446589 | Farm Land |\n| 13 | #cccccc | Range Land |\n\n### Terms of Use\n\n**Terms of Use**\n\nThis work \"Iran Land Cover Map\nv1 13-class (2017)\" by Arsalan Ghorbanian, Mohammad Kakooei, Meisam Amani,\nSahel Mahdavi, Ali Mohammadzadeh, Mahdi Hasanlou is licensed under the [Creative\nCommons Attribution 4.0 International License (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)\n\n### Citations\n\nCitations:\n\n- Ghorbanian, A., Kakooei, M., Amani, M., Mahdavi, S., Mohammadzadeh, A., \\&\n Hasanlou, M. (2020). Improved land cover map of Iran using Sentinel imagery\n within Google Earth Engine and a novel automatic workflow for land cover\n classification using migrated training samples. ISPRS Journal of\n Photogrammetry and Remote Sensing, 167, 276-288.\n [doi:10.1016/j.isprsjprs.2020.07.013](https://doi.org/10.1016/j.isprsjprs.2020.07.013)\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.Image('KNTU/LiDARLab/IranLandCover/V1');\n\nvar visualization = {\n bands: ['classification']\n};\n\nMap.setCenter(54.0, 33.0, 5);\n\nMap.addLayer(dataset, visualization, 'Classification');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/KNTU/KNTU_LiDARLab_IranLandCover_V1) \n[Iran Land Cover Map v1 13-class (2017)](/earth-engine/datasets/catalog/KNTU_LiDARLab_IranLandCover_V1) \nThe Iran-wide land cover map was generated by processing Sentinel imagery within the Google Earth Engine Cloud platform. For this purpose, over 2,500 Sentinel-1 and over 11,000 Sentinel-2 images were processed to produce a single mosaic dataset for the year 2017. Then, an object-based Random Forest classification method was trained ... \nKNTU/LiDARLab/IranLandCover/V1, landcover,landuse-landcover \n2017-01-01T00:00:00Z/2018-01-01T00:00:00Z \n24.62 43.46 39.95 65.58 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://en.kntu.ac.ir/laser-scanners-laboratory/)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/KNTU_LiDARLab_IranLandCover_V1)"]]
