{"doi":"10.1109/icdma.2013.282","title":"Selecting Proper Method for Groundwater Interpolation Based on Spatial Correlation","abstract":null,"journal":"2013 Fourth International Conference on Digital Manufacturing & Automation","year":2013,"id":599067,"datarank":0.4566783656585135,"base_score":3.044522437723423,"endowment":3.044522437723423,"self_citation_contribution":0.4566783656585135,"citation_network_contribution":0.0,"self_endowment_contribution":0.4566783656585135,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":20,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1535370,"name":"Zhang Hanting","orcid":null,"position":1,"is_corresponding":false},{"id":1535371,"name":"Qian Hui","orcid":null,"position":2,"is_corresponding":false},{"id":1535372,"name":"Wu Jianhua","orcid":null,"position":3,"is_corresponding":false},{"id":1535373,"name":"Zhang Xuedi","orcid":null,"position":4,"is_corresponding":false},{"id":168388,"name":"Chen Jie","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Selecting Proper Method for Groundwater Interpolation Based on Spatial Correlation","abstract":"Interpolation technique is often used in analyzing groundwater flow and physiochemical parameter distribution. In order to select an optimal interpolation method to describe the spatial distribution of groundwater properties, the spatial correlations of parameters such as groundwater level, salinity and nitrate were studies, based on which the inverse distance weighting (IDW) and Kriging interpolation methods were compared by the semivariable function of ArcGIS. The results show that when the data of samples have high spatial correlation, Kriging is a reliable method for interpolation, IDW method is more suitable for data of weak spatial correlation. Furthermore, IDW focuses on the values of neighboring locations with special distance while Kriging puts emphasis on the whole trend.","is_dataset_classified":null,"base_score":3.044522437723423,"endowment":3.044522437723423,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21097893","pmcid":null,"openalex_id":"https://openalex.org/W2021907765","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2019,"count":1},{"year":2020,"count":1},{"year":2021,"count":4},{"year":2022,"count":4},{"year":2023,"count":3},{"year":2024,"count":3},{"year":2025,"count":2},{"year":2026,"count":2}],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://xplorestaging.ieee.org/ielx7/6597026/6597910/06598206.pdf?arnumber=6598206","host_type":"publisher"},{"url":"https://doi.org/10.1109/icdma.2013.282","host_type":""}],"fields_of_study":["Grey System Theory Applications","Regional Economic and Spatial Analysis","Environmental and Agricultural Sciences"],"mesh_terms":[],"keywords":["Kriging","Inverse distance weighting","Multivariate interpolation","Interpolation (computer graphics)","Spatial correlation","Groundwater","Geostatistics","Weighting","Spatial distribution","Spatial analysis","Correlation coefficient","Spatial variability","Mathematics","Soil science","Statistics","Computer science","Bilinear interpolation","Environmental science","Geology","Artificial intelligence","Geotechnical engineering"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Clean water and sanitation"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-28T17:43:25.701172Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}