A novel remote sensing monitoring index of salinization based on three-dimensional feature space model and its application in the Yellow River Delta of China
文献类型：期刊论文
| 作者 | Guo, Bing6,7,8,9,10; Lu, Miao5; Fan, Yewen4; Wu, Hongwei10; Yang, Ying3; Wang, Chenglong1,2 |
| 刊名 | GEOMATICS NATURAL HAZARDS & RISK
 |
| 出版日期 | 2023-12-31 |
| 卷号 | 14期号:1页码:95-116 |
| ISSN号 | 1947-5705 |
| 关键词 | Soil salinization 3-D feature space Landsat images spatial distribution vegetation index |
| DOI | 10.1080/19475705.2022.2156820 |
| 通讯作者 | Lu, Miao(lumiao@caas.cn) ; Fan, Yewen(fyw@whu.edu.cn) |
| 英文摘要 | Previous studies were mostly conducted based on two-dimensional feature space to monitor salinization, while studies on dense long-term salinization monitoring based on three-dimensional feature space have not been reported. Based on Landsat TM/ETM+/OLI images and three-dimensional feature space method, this study introduced six typical salinization surface parameters, including NDVI, salinity index, MSAVI, surface albedo, iron oxide index, wetness index to construct eight different feature space monitoring index. The optimal soil salinization monitoring index model was proposed base on field observed data and then the evolution process of salinization in Yellow River Delta (YRD) were analyzed and revealed during 1984-2022. The salinization monitoring index model of MSAVI-Albedo-I-Fe2O3 feature space had the highest accuracy with R-2 = 0.93 and RMSE = 0.678g/kg. The spatial distribution of salinization in YRD showed an increasing trend from inland southwest to coastal northeast and the salinization intensity showed an increasing trend during 1984-2022 due to the implements of agricultural measures such as planting salt-tolerant crops, microbial remediation and fertility improvement. The rate of salinization deterioration in the northeast part was greater than others. Zones of salinization improvement were mainly located in cultivated land of the southwest parts. |
| WOS关键词 | SOIL SALINIZATION ; VEGETATION ; SALINITY ; ACCUMULATION ; XINJIANG ; NPP |
| 资助项目 | Natural Science Foundation of Shandong Province[ZR2021MD047] ; National Natural Science Foundation of China[42101306] ; Open fund of Key Laboratory of National Geographic Census and Monitoring, MNR[2020NGCM02] ; Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources[KF-2020-05-001] ; Agricultural Science and Technology Innovation Program[CAAS-ZDRW202201] |
| WOS研究方向 | Geology ; Meteorology & Atmospheric Sciences ; Water Resources |
| 语种 | 英语 |
| 出版者 | TAYLOR & FRANCIS LTD |
| WOS记录号 | WOS:000899389800001 |
| 资助机构 | Natural Science Foundation of Shandong Province ; National Natural Science Foundation of China ; Open fund of Key Laboratory of National Geographic Census and Monitoring, MNR ; Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources ; Agricultural Science and Technology Innovation Program |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/188244]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Lu, Miao; Fan, Yewen |
| 作者单位 | 1.Chinese Acad Surveying & Mapping, Beijing, Peoples R China 2.Beijing Geo Vis Technol CO LTD, Chinese Acad Surveying & Mapping, Beijing, Peoples R China 3.Shenzhen Data Management Ctr Planning & Nat Resour, Shenzhen, Peoples R China 4.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & Re, Wuhan, Peoples R China 5.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Key Lab Agr Remote Sensing, Minist Agr & Rural Affairs, Beijing, Peoples R China 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 7.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing, Peoples R China 8.Minist Nat Resources, Key Lab Natl Geog Census & Monitoring, Wuhan, Peoples R China 9.Minist Nat Resources, Key Lab Urban Land Resources Monitoring & Simulat, Shenzhen, Peoples R China 10.Shandong Univ Technol, Sch Civil Architectural Engn, Zibo, Shandong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Guo, Bing,Lu, Miao,Fan, Yewen,et al. A novel remote sensing monitoring index of salinization based on three-dimensional feature space model and its application in the Yellow River Delta of China[J]. GEOMATICS NATURAL HAZARDS & RISK,2023,14(1):95-116. |
| APA | Guo, Bing,Lu, Miao,Fan, Yewen,Wu, Hongwei,Yang, Ying,&Wang, Chenglong.(2023).A novel remote sensing monitoring index of salinization based on three-dimensional feature space model and its application in the Yellow River Delta of China.GEOMATICS NATURAL HAZARDS & RISK,14(1),95-116. |
| MLA | Guo, Bing,et al."A novel remote sensing monitoring index of salinization based on three-dimensional feature space model and its application in the Yellow River Delta of China".GEOMATICS NATURAL HAZARDS & RISK 14.1(2023):95-116. |
入库方式： OAI收割
来源：地理科学与资源研究所
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