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Soil quality assessment in Yellow River Delta: Establishing a minimum data set and fuzzy logic model
Wu, Chunsheng; Liu, Gaohuan; Huang, Chong; Liu, Qingsheng
2019-01-15
Source PublicationGEODERMA
ISSN0016-7061
Volume334Pages:82-89
Corresponding AuthorLiu, Gaohuan(liugh@lreis.ac.cn)
AbstractThe Yellow River Delta has abundant land resources, but the land exhibits heavy degeneration because of long-term exposure to harsh natural conditions and improper human activities, and the soil quality is poor in some areas. All these factors have adversely affected agricultural development and ecological protection in the Yellow River Delta. This study selected multiple physical and chemical indicators and used principal component analysis (PCA) to construct a minimum data set (MDS) to determine a comprehensive set of indicators for assessing soil quality in the Yellow River Delta. Moreover, a fuzzy logic model was used to assess soil quality and analyze the spatial distribution of the primary land use types in different soil quality grades. The results indicate that the MDS includes six soil indicators: total nitrogen (TN), available phosphorus (AP), available potassium (AK), soil organic matter (SOM), soil salinity (SS) and pH. According to the spatial distribution maps of the indicators, SS gradually declined from the coast to the inland areas, while TN and AP had opposite characteristics. AK and pH were evenly distributed around the study area, and SOM was highest in the center and gradually declined toward the edge of the study area. The soil quality was higher in inland areas than in coastal areas, and most of the study area was classified as grade III. Most of the farmland, forest, and garden plots were distributed in high-grade soil levels, but some of these plots were distributed in areas classified as grades V or VI. Many areas with high soil quality were unused, which indicated that the land resources of the study area should be planned reasonably.
KeywordYellow River Delta Minimum data set Principal component analysis Soil quality assessment Fuzzy logic model
DOI10.1016/j.geoderma.2018.07.045
WOS KeywordGEOGRAPHICALLY WEIGHTED REGRESSION ; PRODUCTION SYSTEMS ; LAND ; CHINA ; INDICATORS ; INDEX ; DEGRADATION ; RANGELANDS ; FARMLAND ; WASTE
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41661144030] ; National Natural Science Foundation of China[41561144012]
Funding OrganizationNational Natural Science Foundation of China
WOS Research AreaAgriculture
WOS SubjectSoil Science
WOS IDWOS:000447116100011
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/52828
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLiu, Gaohuan
AffiliationChinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Wu, Chunsheng,Liu, Gaohuan,Huang, Chong,et al. Soil quality assessment in Yellow River Delta: Establishing a minimum data set and fuzzy logic model[J]. GEODERMA,2019,334:82-89.
APA Wu, Chunsheng,Liu, Gaohuan,Huang, Chong,&Liu, Qingsheng.(2019).Soil quality assessment in Yellow River Delta: Establishing a minimum data set and fuzzy logic model.GEODERMA,334,82-89.
MLA Wu, Chunsheng,et al."Soil quality assessment in Yellow River Delta: Establishing a minimum data set and fuzzy logic model".GEODERMA 334(2019):82-89.
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