4,491 to 4,500 of 4,524 Results
Nov 14, 2018Patrick MARTIN
Dataverse for raw data from Sarawak 2017 research project on peatland dissolved organic matter transport to sea. Data in this dataverse have been submitted to Biogeosciences Discussion as: P Martin et al. (2018) Distribution and cycling of terrigenous dissolved organic carbon in... |
Nov 14, 2018Marine biogeochemistry group
Research topics: My research interest focus on the cycling of carbon, nitrogen, and phosphorus in the marine environment. The cycling of these elements is an essential part of the global climate system, and is also critical in supporting healthy marine ecosystems. My research con... |
Nov 14, 2018
Dataverse for marine biogeochemistry research group at ASE (PI Dr. Patrick Martin) |
Nov 10, 2018 - Drivers of Fire Activity Sumatra
Lee, Ser Huay Janice Teresa, 2018, "R code for data analysis", https://doi.org/10.21979/N9/A0LK3I, DR-NTU (Data), V1
R code for running GLMM and BRT analysis |
Nov 10, 2018 -
R code for data analysis
Plain Text - 4.7 KB -
MD5: bb08d7eb8e38dfaec665eb52ebe609ae
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Nov 10, 2018 -
R code for data analysis
Plain Text - 11.4 KB -
MD5: c8be94a5d30e3410d38b642447a5e2be
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Nov 10, 2018 - Drivers of Fire Activity Sumatra
Lee, Ser Huay Janice Teresa, 2018, "CSV files for GLMM and BRT analysis", https://doi.org/10.21979/N9/O48JED, DR-NTU (Data), V1, UNF:6:WPoLaRMWotlbETEKmNo/cg== [fileUNF]
CSV files for conducting GLMM analysis using regencies as units and BRT analysis using pixels (1km) as units. |
Nov 10, 2018 -
CSV files for GLMM and BRT analysis
Tabular Data - 17.8 MB - 19 Variables, 225710 Observations - UNF:6:RLvhNW+GJpaAtza0dw/PrA==
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Nov 10, 2018 -
CSV files for GLMM and BRT analysis
Tabular Data - 8.5 KB - 22 Variables, 40 Observations - UNF:6:3CSK2fZ51Iy0Wezd7b+0Qg==
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Nov 10, 2018 - Drivers of Fire Activity Sumatra
Lee, Ser Huay Janice Teresa, 2018, "Spatial layers for pixel analysis", https://doi.org/10.21979/N9/FLZGE5, DR-NTU (Data), V1
Spatial layers in the form of tif files for pixel analysis. Each file represents a layer for each predictor variable. Details on how each layer was derived can be found in the Supporting Information of the article Sze et al. (accepted). |
