Next Article in Journal
An Energy-Efficient Virtualization-Based Secure Platform for Protecting Sensitive User Data
Next Article in Special Issue
Ancient Irrigation Canals Mapped from Corona Imageries and Their Implications in Juyan Oasis along the Silk Road
Previous Article in Journal
Managing Carbon Footprints under the Trade Credit
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessArticle
Sustainability 2017, 9(7), 1246; doi:10.3390/su9071246

Mapping the Soil Texture in the Heihe River Basin Based on Fuzzy Logic and Data Fusion

1,2
,
1,2,3
,
1,2,4
and
1,2,*
1
Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Zhuzhou Electric Locomotive Research Institute Co., Ltd., China Railway Rolling Stock Corporation (CRRC), Zhuzhou 412001, China
4
CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
*
Author to whom correspondence should be addressed.
Received: 12 June 2017 / Revised: 10 July 2017 / Accepted: 11 July 2017 / Published: 17 July 2017
View Full-Text   |   Download PDF [3664 KB, uploaded 17 July 2017]   |  

Abstract

Mapping soil texture in a river basin is critically important for eco-hydrological studies and water resource management at the watershed scale. However, due to the scarcity of in situ observation of soil texture, it is very difficult to map the soil texture in high resolution using traditional methods. Here, we used an integrated method based on fuzzy logic theory and data fusion to map the soil texture in the Heihe River basin in an arid region of Northwest China, by combining in situ soil texture measurement data, environmental factors, a previous soil texture map, and other thematic maps. Considering the different landscape characteristics over the whole Heihe River basin, different mapping schemes have been used to extract the soil texture in the upstream, middle, and downstream areas of the Heihe River basin, respectively. The validation results indicate that the soil texture map achieved an accuracy of 69% for test data from the midstream area of the Heihe River basin, which represents a much higher accuracy than that of another existing soil map in the Heihe River basin. In addition, compared with the time-consuming and expensive traditional soil mapping method, this new method could ensure greater efficiency and a better representation of the explicitly spatial distribution of soil texture and can, therefore, satisfy the requirements of regional modeling. View Full-Text
Keywords: soil texture; soil land inference model; data fusion; arid region soil texture; soil land inference model; data fusion; arid region
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Lu, L.; Liu, C.; Li, X.; Ran, Y. Mapping the Soil Texture in the Heihe River Basin Based on Fuzzy Logic and Data Fusion. Sustainability 2017, 9, 1246.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top