A GIS-based Quantitative Prediction of Seafloor Massive Sulfide on Ultraslow-spreading Ridges: a Case Study of SWIR 48.7° E - 50.5° E
- ADS bibcode
- 2020AGUFMV007.0001L
- year
- 2020
- Listed Authors
- Liu, L.
- Tao, C.
- Shili, L., VI
- Listed Institutions
- Jilin University, Jilin, China
- Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China
- State Oceanic Administration, Key Laboratory of Submarine Geosciences, Second Institute of Oceangraphy, Hangzhou, China
Linked Authors [?]
Linked Institutions