GHS built-up grid, derived from Landsat, multitemporal (1975-1990-2000-2014), R2018A
2018
- 18Citations
- 3Mentions
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations18
- Policy Citations18
- Policy Citation18
- Mentions3
- News Mentions2
- News2
- References1
- Wikipedia1
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Dataset Description
Multi-temporal information layer on the presence of built-up surfaces derived from global Landsat satellite data collected from 1975 to 2014, at the native spatial resolution varying from 80 meters (Landsat MSS sensor), 30 meters (Landsat TM sensor), and 15/30 meters (Landsat ETM sensor). The image data collections were prepared by the Global Land Survey (GLS1975, GLS1990, GLS2000) and by the JRC (Landsat 8 collection for 2014). The data was processed by fully automatic and reproducible methods based on statistical learning (Symbolic Machine Learning). No manual or ad-hoc rule-based editing of the results was applied in the post-processing. The product it is provided with a spatial resolution of 30 meters.
Bibliographic Details
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