Automated Author ProfileSilva, Camilo Vinícius Trindade
Silva, Camilo Vinícius Trindade
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
ABSTRACT. The intensification of anthropogenic activities on soils contributes to soil loss through erosion. Moreover, the pattern of soil loss in the Cobra River watershed, located in the semiarid region of Rio Grande do Norte, is related to the history of land use and occupation, mainly from agriculture and the red ceramic industry, as well as the climatic seasonality of the region. Thus, the objective of this work was to identify the pattern of soil loss from the Cobra River microbasin in the state of Rio Grande do Norte. For this, the following analyses were performed: a survey of land use class areas for the years 1987, 1997, 2007 and 2017 as part of the Mapbiomas project; estimation of basin soil loss for these years; and quantification of areas of erosion vulnerability classes for this period. QGIS software was used to treat georeferenced data. According to the results, the land cover classes in the rich Cobra River microbasin fluctuated over time. Potential soil loss from the watershed increased from 1987 to 2017, with an increase of approximately 20 million megagrams of potentially erodible soil. The study of soil loss in a microbasin located in the Brazilian semiarid region should consider the variation in land cover over time, climatic seasonality and anthropic activity. To this end, it is important to use geotechnology and geoprocessing techniques to conduct a more robust spatiotemporal analysis.
Authors
- Silva, Camilo Vinícius Trindade ;
- Andrade, Eunice Maia de ;
- Lemos Filho, Luis Cesar de Aquino ;
- Ribeiro Filho, Jacques Carvalho ;
- Oliveira Júnior, Hermínio Sabino de
ABSTRACT. The intensification of anthropogenic activities on soils contributes to soil loss through erosion. Moreover, the pattern of soil loss in the Cobra River watershed, located in the semiarid region of Rio Grande do Norte, is related to the history of land use and occupation, mainly from agriculture and the red ceramic industry, as well as the climatic seasonality of the region. Thus, the objective of this work was to identify the pattern of soil loss from the Cobra River microbasin in the state of Rio Grande do Norte. For this, the following analyses were performed: a survey of land use class areas for the years 1987, 1997, 2007 and 2017 as part of the Mapbiomas project; estimation of basin soil loss for these years; and quantification of areas of erosion vulnerability classes for this period. QGIS software was used to treat georeferenced data. According to the results, the land cover classes in the rich Cobra River microbasin fluctuated over time. Potential soil loss from the watershed increased from 1987 to 2017, with an increase of approximately 20 million megagrams of potentially erodible soil. The study of soil loss in a microbasin located in the Brazilian semiarid region should consider the variation in land cover over time, climatic seasonality and anthropic activity. To this end, it is important to use geotechnology and geoprocessing techniques to conduct a more robust spatiotemporal analysis.
Authors
- Silva, Camilo Vinícius Trindade ;
- Andrade, Eunice Maia de ;
- Lemos Filho, Luis Cesar de Aquino ;
- Ribeiro Filho, Jacques Carvalho ;
- Oliveira Júnior, Hermínio Sabino de