Extracting soil salinization information with a fractional-order filtering algorithm and grid-search support vector machine (GS-SVM) model-Reference-Cited by-同舟云学术

Extracting soil salinization information with a fractional-order filtering algorithm and grid-search support vector machine (GS-SVM) model

Published:2019-08-14 Issue:3 Volume:41 Page:953-973
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Wang Xiaoping¹²,Zhang Fei²³,Kung Hsiang-te⁴,Johnson Verner Carl⁵,Latif Aamir⁶

Affiliation:

1. International Institute for Earth System Science, Nanjing University, Nanjing, PRC

2. Key Laboratory of Smart City and Environmental Modelling of Higher Education Institute, College of Resources and Environment Sciences, Xinjiang University, Urumqi, PRC

3. Key Laboratory of Oasis Ecology Ministry of Education, Xinjiang University, Urumqi, PRC

4. Department of Earth Sciences, The University of Memphis, Memphis, TN, USA

5. Department of Physical and Environmental Sciences, Colorado Mesa University, Grand Junction, CO, USA

6. Institute of Geographic Sciences and Natural Resources Research, University of Chinese Academy of Sciences, Beijing, PRC

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2019.1654142

Reference63 articles.

1. Assessing soil salinity using soil salinity and vegetation indices derived from IKONOS high-spatial resolution imageries: Applications in a date palm dominated region

2. Monitoring 2015 drought in West Java using Normalized Difference Water Index (NDWI)

3. Application of fractional-order differentiation in multispectral image fusion

4. Hybrid method for designing digital FIR filters based on fractional derivative constraints

5. Remote Sensing of Soil Alkalinity and Salinity in the Wuyu’er-Shuangyang River Basin, Northeast China

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