The 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 by a large number of reference samples for 13 classes to generate the Iran-wide land cover map.
伊朗全境的土地覆盖图是通过在谷歌地球引擎云平台内处理哨兵图像生成的。为此,处理了2500多张哨兵一号和11000多张哨兵二号图像,生成了2017年的单一马赛克数据集。然后,通过大量的参考样本对13个类别进行基于对象的随机森林分类方法的训练,以生成伊朗范围内的土地覆盖图。
Dataset Availability
2017-01-01T00:00:00 - 2018-01-01T00:00:00
Dataset Provider
K. N. Toosi University of Technology LiDAR Lab
Collection Snippet
ee.Image("KNTU/LiDARLab/IranLandCover/V1")
Bands Table
Name | Description | Resolution |
---|---|---|
classification | Classification | 10 meters |
Class Table: classification
Value | Color | Color Value | Description |
---|---|---|---|
1 | #000000 | Urban | |
2 | #006eff | Water | |
3 | #41a661 | Wetland | |
4 | #ff7f7f | Kalut (yardang) | |
5 | #bee8ff | Marshland | |
6 | #ff00c5 | Salty Land | |
7 | #ff0000 | Clay | |
8 | #00734c | Forest | |
9 | #732600 | Outcrop | |
10 | #ffaa00 | Uncovered Plain | |
11 | #d3ffbe | Sand | |
12 | #446589 | Farm Land | |
13 | #cccccc | Range Land |
数据说明:This work "Iran Land Cover Map v1 13-class (2017)" by Arsalan Ghorbanian, Mohammad Kakooei, Meisam Amani, Sahel Mahdavi, Ali Mohammadzadeh, Mahdi Hasanlou is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0)
引用:Ghorbanian, A., Kakooei, M., Amani, M., Mahdavi, S., Mohammadzadeh, A., & Hasanlou, M. (2020). Improved land cover map of Iran using Sentinel imagery within Google Earth Engine and a novel automatic workflow for land cover classification using migrated training samples. ISPRS Journal of Photogrammetry and Remote Sensing, 167, 276-288. doi:10.1016/j.isprsjprs.2020.07.013
代码:
var dataset = ee.Image("KNTU/LiDARLab/IranLandCover/V1");
var visualization = {
bands: ['classification']
};
Map.setCenter(54.0, 33.0, 5);
Map.addLayer(dataset, visualization, "Classification");