Understanding the usage of land use and land cover classifiers in scientific research
Vitor da Silva Gonçalves et al.
What the paper says
assess the primary methods utilized in land use and land cover classification research to determine the most frequently applied techniques and potential trends Methodology/Approach: a bibliometric study was carried out in the Scopus scientific article databases, counting the use of classification methods between 2012 and 2022. The obtained data was converted into SQL database tables and processed using queries, looking for articles whose abstracts contains keywords related to land cover and land use methods. Findings: a general growth trend in the studies of this area was discovered, with an increase in the use of machine learning-based methodologies and stabilization in the use of other methods. Statistical methods were also heavily used, while others were used less frequently. Research Limitation/implication: it’s important to note that keywords present in abstract sections does not necessarily correspond to the mentioned methods being applied in the studies. This leads to some expected degree of imprecision, but the data remains a reasonable representation of the popularity of each method. Originality/Value of paper: considering that the scientific literature lacks a quantitative understanding of the usage of land use and land cover classifiers, this work aims to fill that gap by providing usable data.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.00 × 0.4 = 0.00 |
| M · momentum | 0.20 × 0.15 = 0.03 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.