Global-PCG-10: a 10 m global map of plastic-covered greenhouses derived from Sentinel-2 in 2020
文献类型：期刊论文
| 作者 | Niu, Bowen2; Feng, Quanlong2; Qiu, Bingwen1; Su, Shuai2; Zhang, Xinmin2; Cui, Rongji2; Zhang, Xinhong2; Sun, Fanli2; Yan, Wenhui2; Zhao, Siyuan2 |
| 刊名 | EARTH SYSTEM SCIENCE DATA
 |
| 出版日期 | 2025-10-01 |
| 卷号 | 17期号:10页码:5065-5088 |
| ISSN号 | 1866-3508 |
| DOI | 10.5194/essd-17-5065-2025 |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | Plastic-covered greenhouse (PCG) is widely used in agricultural production due to its temperature control, water conservation, and wind protection characteristics, significantly enhancing crop yields and economic benefits. However, its long-term and extensive use can lead to environmental issues, such as the accumulation of local toxic gases and the degradation of soil physicochemical properties. Therefore, obtaining a comprehensive distribution of PCGs is essential. To monitor PCGs on a large scale, this study developed a novel approach for producing the first global 10 m PCG dataset (Global-PCG-10) with high-quality. Firstly, the globe was divided into multiple 5 degrees grids, and grids for classification were organized based on global cropland layer. Then, multi-temporal Sentinel-2 data and initial labels of PCGs were obtained through Google Earth Engine (GEE) to create a training set for deep learning. Next, initial labels were optimized with the active learning strategy combined with the deep learning model, APC-Net. Finally, the PCG classification results were predicted, spatially analyzed, and compared with publicly released land use and land cover (LULC) datasets. Experimental results indicate that the proposed Global-PCG-10 dataset (Niu et al., 2024) has a high overall accuracy of 98.04 % +/- 0.12 %. The global area of PCGs is 14 259.85 km(2), and 69.24 % of PCGs are located in Asia, covering around 9874.51 km(2). China has the largest PCG area of 8224.90 km(2), accounting for 57.67 % of the globe and 83.29 % of Asia. Comparisons with other LULC datasets revealed that PCGs, which should be classified as cropland, are often misclassified as bareland, impervious surfaces, ice/snow, etc. |
| URL标识 | 查看原文 |
| WOS关键词 | FINE CLASSIFICATION-SYSTEM ; SERIES LANDSAT IMAGERY ; SPATIAL-RESOLUTION ; SEMANTIC SEGMENTATION ; DATASET ; CHINA ; INDEX ; TIME ; AREA ; MULTISOURCE |
| WOS研究方向 | Geology ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:001585814100001 |
| 出版者 | COPERNICUS GESELLSCHAFT MBH |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217442]  |
| 专题 | 区域可持续发展分析与模拟院重点实验室_外文论文 |
| 通讯作者 | Feng, Quanlong |
| 作者单位 | 1.Fuzhou Univ, Acad Digital China Fujian, Key Lab Spatial Data Min & Informat Sharing, Minist Educ, Fuzhou 350116, Fujian, Peoples R China; 2.China Agr Univ, Coll Land Sci & Technol, Beijing 100193, Peoples R China; 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 4.Wageningen Univ & Res, Lab Geoinformat Sci & Remote Sensing, NL-6708 PB Wageningen, Netherlands; 5.Chinese Acad Sci, Aerosp Informat Res Inst, Natl Engn Res Ctr Geoinformat, Beijing 100101, Peoples R China; 6.Southwest Jiaotong Univ, Fac Geosci & Engn, Chengdu 611756, Peoples R China; 7.Shandong Jianzhu Univ, Sch Surveying & Geoinformat, Jinan 250101, Shandong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Niu, Bowen,Feng, Quanlong,Qiu, Bingwen,et al. Global-PCG-10: a 10 m global map of plastic-covered greenhouses derived from Sentinel-2 in 2020[J]. EARTH SYSTEM SCIENCE DATA,2025,17(10):5065-5088. |
| APA | Niu, Bowen.,Feng, Quanlong.,Qiu, Bingwen.,Su, Shuai.,Zhang, Xinmin.,...&Zhu, Dehai.(2025).Global-PCG-10: a 10 m global map of plastic-covered greenhouses derived from Sentinel-2 in 2020.EARTH SYSTEM SCIENCE DATA,17(10),5065-5088. |
| MLA | Niu, Bowen,et al."Global-PCG-10: a 10 m global map of plastic-covered greenhouses derived from Sentinel-2 in 2020".EARTH SYSTEM SCIENCE DATA 17.10(2025):5065-5088. |
入库方式： OAI收割
来源：地理科学与资源研究所
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