Prediction of soil properties using a hyperspectral remote sensing method | |
Yu, Huan1,4; Kong, Bo2![]() | |
2018 | |
Source Publication | ARCHIVES OF AGRONOMY AND SOIL SCIENCE
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ISSN | 0365-0340 |
Volume | 64Issue:4Pages:546-559 |
Subtype | Article |
Contribution Rank | 2 |
Abstract | Quickly and accurately mapping soil properties is critical for agricultural, forestry and environmental management. In this study, a new hyperspectral remote sensing method of soil property prediction was developed and validated in Stipa purpurea dominated alpine grasslands located in Shenzha County of the Qiangtang Plateau, northwestern Qinghai-Tibet Plateau. Hyperspectral data were collected in a total of 67 sample points. At the same time, soil samples were obtained at the locations and soil properties including organic carbon, total nitrogen, total potassium and total phosphorus were measured. The correlations of the soil properties with original bands and enhanced spectral variables derived from both field and satellite hyperspectral data were analyzed. Regression models that explained the relationships were further developed to map the soil properties. The results showed that the stepwise regression models based on the satellite hyperspectral image derived enhanced spectral variables produced reasonable spatial distributions of the soil properties and the relative RMSE values of 68.9, 46.3, 31.4 and 45.5% for soil organic carbon, total nitrogen, total phosphorus and total potassium, respectively. Thus, this study implied that the hyperspectral data based method provided great potential to predict the soil properties. |
Keyword | Alpine grasslands correlation analysis hyperspectral data soil properties stepwise regression Stipa Purpurea |
DOI | 10.1080/03650340.2017.1359416 |
Indexed By | SCI |
WOS Keyword | ORGANIC-CARBON ; REFLECTANCE SPECTROSCOPY ; DROUGHT TOLERANCE ; NIR SPECTROSCOPY ; CLAY CONTENT ; FIELD ; GRASSLAND ; CHINA ; PATTERNS ; TEXTURE |
Language | 英语 |
WOS Research Area | Agriculture |
WOS Subject | Agronomy ; Soil Science |
WOS ID | WOS:000427050800008 |
Publisher | TAYLOR & FRANCIS LTD |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.imde.ac.cn/handle/131551/22842 |
Collection | 数字山地与遥感应用中心 |
Corresponding Author | Yu, Huan |
Affiliation | 1.Chengdu Univ Technol, Coll Earth Sci, Chengdu, Sichuan, Peoples R China; 2.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu, Sichuan, Peoples R China; 3.Southern Illinois Univ, Dept Geog & Environm Resources, Carbondale, IL USA; 4.Chengdu Univ Technol, Minist Land & Resources, Key Lab Geosci Spatial Informat Technol, Chengdu, Sichuan, Peoples R China |
Recommended Citation GB/T 7714 | Yu, Huan,Kong, Bo,Wang, Guangxing,et al. Prediction of soil properties using a hyperspectral remote sensing method[J]. ARCHIVES OF AGRONOMY AND SOIL SCIENCE,2018,64(4):546-559. |
APA | Yu, Huan,Kong, Bo,Wang, Guangxing,Du, Rongxiang,&Qie, Guangping.(2018).Prediction of soil properties using a hyperspectral remote sensing method.ARCHIVES OF AGRONOMY AND SOIL SCIENCE,64(4),546-559. |
MLA | Yu, Huan,et al."Prediction of soil properties using a hyperspectral remote sensing method".ARCHIVES OF AGRONOMY AND SOIL SCIENCE 64.4(2018):546-559. |
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