The Applicability of Remote Sensing Models of Soil Salinization Based on Feature Space
文献类型：期刊论文
| 作者 | Liu, Jing1,3,5; Zhang, Li3,5; Dong, Tong3,5; Wang, Juanle1; Fan, Yanmin3,5; Wu, Hongqi3,5; Geng, Qinglong2; Yang, Qiangjun4; Zhang, Zhibin3,5 |
| 刊名 | SUSTAINABILITY
 |
| 出版日期 | 2021-12-01 |
| 卷号 | 13期号:24页码:16 |
| 关键词 | salinization feature space remote sensing inversion coastal areas arid areas applicability |
| DOI | 10.3390/su132413711 |
| 通讯作者 | Fan, Yanmin(ymfantt@126.com) ; Wu, Hongqi(hqwu7475@126.com) |
| 英文摘要 | Soil salinization is a major challenge for the sustainable use of land resources. An optimal remote sensing inversion model could monitor regional soil salinity across diverse geographical areas. In this study, the feature space method was used to study the applicability of the inversion model for typical salt-affected soils in China (Yanqi Basin (arid area) and Kenli County (coastal area)), and to obtain soil salinity grade distribution maps. The salinity index (SI) surface albedo (Albedo)model was the most accurate in both arid and coastal regions with overall accuracy reaching 93.3% and 88.8%, respectively. The sensitivity factors for the inversion of salinity in both regions were the same, indicating that the SI-Albedo model is applicable for monitoring salinity in arid and coastal areas of China. We combined Landsat 8 Operational Land Imager image data and field data to obtain the distribution pattern of soil salinity using the SI-Albedo model and proposed corresponding countermeasures for soil salinity in the Yanqi Basin and Kenli County according to the degree of salinity. This study on soil salinity in arid and coastal areas of China will provide a useful reference for future research on soil salinity both in China and globally. |
| WOS关键词 | SALINITY ; XINJIANG |
| 资助项目 | Strategic Priority Research Program (Class A) of the Chinese Academy of Sciences[XDA19040501] ; National Natural Science Foundation of China[31560340] |
| WOS研究方向 | Science & Technology - Other Topics ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000737485200001 |
| 出版者 | MDPI |
| 资助机构 | Strategic Priority Research Program (Class A) of the Chinese Academy of Sciences ; National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/169198]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Fan, Yanmin; Wu, Hongqi |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Xinjiang Acad Agr Sci, Inst Soil & Fertilizer & Agr Water Conservat, Urumqi 830000, Peoples R China 3.Key Lab Grassland Restorat & Environm Informat, Urumqi 830000, Peoples R China 4.China Geoengn Corp, Beijing 100101, Peoples R China 5.Xinjiang Agr Univ, Coll Resources & Environm, Urumqi 830000, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Jing,Zhang, Li,Dong, Tong,et al. The Applicability of Remote Sensing Models of Soil Salinization Based on Feature Space[J]. SUSTAINABILITY,2021,13(24):16. |
| APA | Liu, Jing.,Zhang, Li.,Dong, Tong.,Wang, Juanle.,Fan, Yanmin.,...&Zhang, Zhibin.(2021).The Applicability of Remote Sensing Models of Soil Salinization Based on Feature Space.SUSTAINABILITY,13(24),16. |
| MLA | Liu, Jing,et al."The Applicability of Remote Sensing Models of Soil Salinization Based on Feature Space".SUSTAINABILITY 13.24(2021):16. |
入库方式： OAI收割
来源：地理科学与资源研究所
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