Automated Author ProfileZhao, Chenchen
Beijing Normal University
Zhao, Chenchen
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: 4.8 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
DMSP-OLS provides the longest observations of NTL information, from 1992 to 2013, an unparalleled dataset for studying historical artificial lights. Version 4 of the DMSP-OLS Nighttime Lights Time Series is widely used ( Image and data processing by NOAA's National Geophysical Data Center. DMSP data collected by US Air Force Weather Agency ). However, it suffers from three main problems: inter-annual inconsistency, saturation, and blooming effect.We used a series of methods to mitigate the impact and improve data quality. After processing, we get consistent and corrected nighttime light dataset (CCNL).The version 1 products span the globe from 75N latitude to 65S. The products are produced in 30 arc resolution and are made available in GeoTIFF format. Pixel Unit: 'DN'(Digital Number).Each GeoTIFF filename has 4 filename fields that are separated by an underscore "_". A filename extension follows these fields. The fields are described below using this example filename:CCNL_DMSP_1992_V1Field 1: CCNL(Consistent and Corrected Nighttime Light dataset)Field 2: Platform "DMSP"Field 3: Year “1992”Field 4: version “V1”
Authors
- Zhao, Chenchen ;
- Cao, Xin ;
- Chen, Xuehong ;
- Cui, Xihong
DMSP-OLS provides the longest observations of NTL information, from 1992 to 2013, an unparalleled dataset for studying historical artificial lights. Version 4 of the DMSP-OLS Nighttime Lights Time Series is widely used ( Image and data processing by NOAA's National Geophysical Data Center. DMSP data collected by US Air Force Weather Agency ). However, it suffers from three main problems: inter-annual inconsistency, saturation, and blooming effect.We used a series of methods to mitigate the impact and improve data quality. After processing, we get consistent and corrected nighttime light dataset (CCNL).The version 1 products span the globe from 75N latitude to 65S. The products are produced in 30 arc resolution and are made available in GeoTIFF format. Pixel Unit: 'DN'(Digital Number).Each GeoTIFF filename has 4 filename fields that are separated by an underscore "_". A filename extension follows these fields. The fields are described below using this example filename:CCNL_DMSP_1992_V1Field 1: CCNL(Consistent and Corrected Nighttime Light dataset)Field 2: Platform "DMSP"Field 3: Year “1992”Field 4: version “V1”
Authors
- Zhao, Chenchen ;
- Cao, Xin ;
- Chen, Xuehong ;
- Cui, Xihong