Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.3390/rs61110813 |
Modeling and Mapping of Soil Salinity with Reflectance Spectroscopy and Landsat Data Using Two Quantitative Methods (PLSR and MARS) | |
Nawar, Said1,2; Buddenbaum, Henning3; Hill, Joachim3; Kozak, Jacek1 | |
通讯作者 | Nawar, Said |
来源期刊 | REMOTE SENSING
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ISSN | 2072-4292 |
出版年 | 2014 |
卷号 | 6期号:11页码:10813-10834 |
英文摘要 | The monitoring of soil salinity levels is necessary for the prevention and mitigation of land degradation in arid environments. To assess the potential of remote sensing in estimating and mapping soil salinity in the El-Tina Plain, Sinai, Egypt, two predictive models were constructed based on the measured soil electrical conductivity (ECe) and laboratory soil reflectance spectra resampled to Landsat sensor’s resolution. The models used were partial least squares regression (PLSR) and multivariate adaptive regression splines (MARS). The results indicated that a good prediction of the soil salinity can be made based on the MARS model (R-2 = 0.73, RMSE = 6.53, and ratio of performance to deviation (RPD) = 1.96), which performed better than the PLSR model (R-2 = 0.70, RMSE = 6.95, and RPD = 1.82). The models were subsequently applied on a pixel-by-pixel basis to the reflectance values derived from two Landsat images (2006 and 2012) to generate quantitative maps of the soil salinity. The resulting maps were validated successfully for 37 and 26 sampling points for 2006 and 2012, respectively, with R-2 = 0.72 and 0.74 for 2006 and 2012, respectively, for the MARS model, and R-2 = 0.71 and 0.73 for 2006 and 2012, respectively, for the PLSR model. The results indicated that MARS is a more suitable technique than PLSR for the estimation and mapping of soil salinity, especially in areas with high levels of salinity. The method developed in this paper can be used for other satellite data, like those provided by Landsat 8, and can be applied in other arid and semi-arid environments. |
英文关键词 | soil salinity reflectance spectra Landsat PLSR MARS Egypt |
类型 | Article |
语种 | 英语 |
国家 | Poland ; Egypt ; Germany |
收录类别 | SCI-E |
WOS记录号 | WOS:000345530700026 |
WOS关键词 | YELLOW-RIVER DELTA ; ADAPTIVE REGRESSION SPLINES ; SALT CONTENT ; IMAGING SPECTROSCOPY ; HARRAN PLAIN ; INDICATORS ; VEGETATION ; SIMULATION ; SPECTRA ; REGION |
WOS类目 | Remote Sensing |
WOS研究方向 | Remote Sensing |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/184694 |
作者单位 | 1.Jagiellonian Univ, Inst Geog & Spatial Management, PL-30387 Krakow, Poland; 2.Suez Canal Univ, Fac Agr, Ismailia 41522, Egypt; 3.Univ Trier, D-54286 Trier, Germany |
推荐引用方式 GB/T 7714 | Nawar, Said,Buddenbaum, Henning,Hill, Joachim,et al. Modeling and Mapping of Soil Salinity with Reflectance Spectroscopy and Landsat Data Using Two Quantitative Methods (PLSR and MARS)[J],2014,6(11):10813-10834. |
APA | Nawar, Said,Buddenbaum, Henning,Hill, Joachim,&Kozak, Jacek.(2014).Modeling and Mapping of Soil Salinity with Reflectance Spectroscopy and Landsat Data Using Two Quantitative Methods (PLSR and MARS).REMOTE SENSING,6(11),10813-10834. |
MLA | Nawar, Said,et al."Modeling and Mapping of Soil Salinity with Reflectance Spectroscopy and Landsat Data Using Two Quantitative Methods (PLSR and MARS)".REMOTE SENSING 6.11(2014):10813-10834. |
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