Geospatial Data Cleaning
Geospatial Data Cleaning is a systematic process in mine survey data processing that identifies, corrects, and eliminates errors, inconsistencies, and inaccuracies in spatial datasets to ensure geometric and attribute-level integrity, thereby enhancing the reliability and usability of geospatial information for downstream analysis and decision-making.
10
Publications
223
Citations
37
Authors
18
Institutions
Publications per year
2017–2026
5
Parents
10
A Data Cleaning Method for Big Trace Data Using Movement Consistency
Xue Yang, Luliang Tang, Xia Zhang et al. · Sensors · 2018 · 17 citations · Full text
Computing, Geography, Geoinformatics +16
1–5 of 10
37
2
h-index
1
h-index
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, China
1 publications · 14 citations
1
h-index
1
h-index
1
h-index
1–5 of 37
18
Wuhan University
Wuhan, China
2 h-index
7 publications
107 citations
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Wuhan, China
2 h-index
6 publications
90 citations

The University of Texas at El Paso
El Paso, United States
2 h-index
8 publications
116 citations
University of Maryland, College Park
College Park, United States
1 h-index
3 publications
117 citations
International Institute for Sustainability
Rio de Janeiro, Brazil
1 h-index
1 publications
75 citations
University of California, Riverside
Riverside, United States
1 h-index
1 publications
75 citations

Royal Botanic Gardens, Kew
London, United Kingdom
1 h-index
1 publications
75 citations
George Mason University
Fairfax, United States
1 h-index
2 publications
28 citations
1–8 of 18
CAGEO · 1 publications · 10 citations
1
h-index
IV · 1 publications · 39 citations
1
h-index
1 publications · 17 citations
1
h-index
IJGI · 1 publications · 12 citations
1
h-index
1 publications · 75 citations
1
h-index
1–5