Automated Author Profile

San-Juan-Heras, Raul

Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria

Current S-Index

3.6

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.8

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

73.1%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Soil grid data for agricultural fields in Spain for STEROPES (EJP Soil) project (ECe, texture, soil organic carbon, pH)

Soil data collected in an agricultural area with vegetable crops in Spain (Campo de Cartagena). The data refers to soil properties of 141 soil samples collected at a depth of 0-10 cm, considering a regular sampling grid, in different commercial fields with varying soil salinity. The samples were collected at a period when the soil was bare, during two consecutive summers, following the harvest of the annual crops, and pictures of the soil surface were taken for eventual correction of corresponding remote sensing imaging. The data includes: soil organic carbon (SOC) (Walkley-Black method), soil water content, electric conductivity of the saturated soil paste (ECe), EC1:5, soil texture, stone content and pH1:2.5.  The data may be representative of the soil conditions of the area, which is an intensive productive agricultural low land, potentially prone to the development of soil salinity as a result of the rise of saline groundwater and/or irrigation. The data can be used to establish relations between soil salinity (ECe) and other soil properties as well as build prediction models of the soil properties from remote sensing namely, for developing models for SOC prediction under the STEROPES project (WP3, WP5 and WP6).The aim of the collected dataset was to be able to analyze the influence of soil salinity in SOC prediction from remote sensing. Data in the form of MS Excel file (xlsx).

Authors

  • Gabriel, Jose Luis ;
  • San-Juan-Heras, Raul ;
  • Delgado, Maria del Mar ;
  • Lazaro, Alberto ;
  • Rodríguez-Martín, José Antonio
0 Citations0 Mentions73% FAIR1.8 Dataset Index
10.5281/zenodo.14104482November 2024

Soil grid data for agricultural fields in Spain for STEROPES (EJP Soil) project (ECe, texture, soil organic carbon, pH)

Soil data collected in an agricultural area with vegetable crops in Spain (Campo de Cartagena). The data refers to soil properties of 141 soil samples collected at a depth of 0-10 cm, considering a regular sampling grid, in different commercial fields with varying soil salinity. The samples were collected at a period when the soil was bare, during two consecutive summers, following the harvest of the annual crops, and pictures of the soil surface were taken for eventual correction of corresponding remote sensing imaging. The data includes: soil organic carbon (SOC) (Walkley-Black method), soil water content, electric conductivity of the saturated soil paste (ECe), EC1:5, soil texture, stone content and pH1:2.5.  The data may be representative of the soil conditions of the area, which is an intensive productive agricultural low land, potentially prone to the development of soil salinity as a result of the rise of saline groundwater and/or irrigation. The data can be used to establish relations between soil salinity (ECe) and other soil properties as well as build prediction models of the soil properties from remote sensing namely, for developing models for SOC prediction under the STEROPES project (WP3, WP5 and WP6).The aim of the collected dataset was to be able to analyze the influence of soil salinity in SOC prediction from remote sensing. Data in the form of MS Excel file (xlsx).

Authors

  • Gabriel, Jose Luis ;
  • San-Juan-Heras, Raul ;
  • Delgado, Maria del Mar ;
  • Lazaro, Alberto ;
  • Rodríguez-Martín, José Antonio
0 Citations0 Mentions73% FAIR1.8 Dataset Index
10.5281/zenodo.14104483November 2024