Automated Author ProfileSongwut Petcharoen
Songwut Petcharoen
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: 1.2 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The objective of this study was to assess risk area and its severity classification of forest fire covering the area of Kuan Krang swamp forest using the application of geographic information system (GIS) based on forest fire influencing factors. These factors included land uses, soil types, distance to streams, distance to roads and distance to communities. Each factor was assigned for weighting and rating scales following the literature data, interview data of representative from the Forest Fire Control Station at Kuan Kreng and hotspot (fire) data collected from 2001 to 2013. A GIS-based multi-criteria techniques using weighted overlay method was used to classify risk level of forest fires. The level of risk was divided into 3 types: high, medium and low risks. Results indicated that the most important factor for the forest fires of Kuan Kreng was land use. The degraded swamp forest was found to be the most vulnerability area for the origin of forest fires. The highest risk areas of forest fires in Kuan Kreng were found at Amphoe Cha Uat and Amphoe Ron Phibun, Nakhon Si Thammarat and Amphoe Khuan Khanun, Phattalung.
Authors
- Thongchai Kanabkaew ;
- Jantira Rattanarat ;
- Songwut Petcharoen
The objective of this study was to assess risk area and its severity classification of forest fire covering the area of Kuan Krang swamp forest using the application of geographic information system (GIS) based on forest fire influencing factors. These factors included land uses, soil types, distance to streams, distance to roads and distance to communities. Each factor was assigned for weighting and rating scales following the literature data, interview data of representative from the Forest Fire Control Station at Kuan Kreng and hotspot (fire) data collected from 2001 to 2013. A GIS-based multi-criteria techniques using weighted overlay method was used to classify risk level of forest fires. The level of risk was divided into 3 types: high, medium and low risks. Results indicated that the most important factor for the forest fires of Kuan Kreng was land use. The degraded swamp forest was found to be the most vulnerability area for the origin of forest fires. The highest risk areas of forest fires in Kuan Kreng were found at Amphoe Cha Uat and Amphoe Ron Phibun, Nakhon Si Thammarat and Amphoe Khuan Khanun, Phattalung.
Authors
- Thongchai Kanabkaew ;
- Jantira Rattanarat ;
- Songwut Petcharoen