Asian School of the Environment (ASE)

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3,641 to 3,650 of 4,574 Results

Lallemant_OE_2021_input_Gridded_Potential_Evapotranspiration.cpgz Aug 4, 2021 - Related data for: Nature-based solutions for flood risk reduction: A probabilistic modeling framework Gzip Archive - 13.1 MB - MD5: 647a7e0670e55e145b0455a15b7120ac Input: gridded potential evapotranspiration from WorldClim
Lallemant_OE_2021_inputs_exposure.cpgz Aug 4, 2021 - Related data for: Nature-based solutions for flood risk reduction: A probabilistic modeling framework Gzip Archive - 186.2 KB - MD5: 70028fa936fa73abb5ee109eac7f595b Inputs: Flood exposure data, including agriculture, buildings and population exposure.
Lallemant_OE_2021_inputs_hazard.cpgz Aug 4, 2021 - Related data for: Nature-based solutions for flood risk reduction: A probabilistic modeling framework Gzip Archive - 1.8 MB - MD5: 2e4e96f7d7b15e2eb656b9da67893e90 Inputs: Flood hazard data for Chindwin river basin, including precipitation, river discharge, and digital elevation model.
Lallemant_OE_2021_output_Floodmap_simulation_deforestation.cpgz Aug 4, 2021 - Related data for: Nature-based solutions for flood risk reduction: A probabilistic modeling framework Gzip Archive - 3.9 MB - MD5: 70fff188298cb5fc3c2353009d207ebb Output: 18 Flood Simulations, continued deforestation
Lallemant_OE_2021_output_Floodmap_simulation_forest_protection.cpgz Aug 4, 2021 - Related data for: Nature-based solutions for flood risk reduction: A probabilistic modeling framework Gzip Archive - 3.7 MB - MD5: 9d9b5ea6603b625115c3799d92ea5e52 Output: 18 Flood Simulations, forest protection
Nature-Based Solution for Flood Risk Reduction(Nanyang Technological University) Jul 24, 2021David Lallemant Flooding is the most frequent and damaging natural hazard globally. While nature-based solutions can reduce flood risk, they are not part of mainstream risk management. We develop a probabilistic risk analysis framework to quantify these benefits that i) accounts for frequent sma...
Informatics for Equitable Recovery(Nanyang Technological University) Jul 24, 2021David Lallemant Informatics for Equitable Recovery is a transdisciplinary research project that brings together data scientists, engineers, social scientists and civic organizations to improve post-disaster information systems and decision support tools. Example use cases for these information s...
David Lallemant(Nanyang Technological University) Jul 24, 2021 Research topics: • Disaster risk analysis • Reliability Analysis • Probabilistic methods • Statistical learning • Disaster impact and recovery For more information, visit our disaster-analytics.com webpage.
Appendix A.2 Data table.tab Jul 23, 2021 - Replication Data for: Biogeochemical cycling and environmental footprints of peatland-derived dissolved organic carbon in the Sunda Shelf Sea, Southeast Asia Tabular Data - 41.7 KB - 18 Variables, 171 Observations - UNF:6:8GW7YgfVPXXEwoSgftL7Mw==
Appendix B.5 Data table for Chapter 3.tab Jul 23, 2021 - Replication Data for: Biogeochemical cycling and environmental footprints of peatland-derived dissolved organic carbon in the Sunda Shelf Sea, Southeast Asia Tabular Data - 69.0 KB - 44 Variables, 131 Observations - UNF:6:K/CPyxA39kiywDm6GslKsg==

Lallemant_OE_2021_input_Gridded_Potential_Evapotranspiration.cpgz

Aug 4, 2021 - Related data for: Nature-based solutions for flood risk reduction: A probabilistic modeling framework

Gzip Archive - 13.1 MB -

Input: gridded potential evapotranspiration from WorldClim

Lallemant_OE_2021_inputs_exposure.cpgz

Aug 4, 2021 - Related data for: Nature-based solutions for flood risk reduction: A probabilistic modeling framework

Gzip Archive - 186.2 KB -

Inputs: Flood exposure data, including agriculture, buildings and population exposure.

Lallemant_OE_2021_inputs_hazard.cpgz

Aug 4, 2021 - Related data for: Nature-based solutions for flood risk reduction: A probabilistic modeling framework

Gzip Archive - 1.8 MB -

Inputs: Flood hazard data for Chindwin river basin, including precipitation, river discharge, and digital elevation model.

Lallemant_OE_2021_output_Floodmap_simulation_deforestation.cpgz

Aug 4, 2021 - Related data for: Nature-based solutions for flood risk reduction: A probabilistic modeling framework

Gzip Archive - 3.9 MB -

Output: 18 Flood Simulations, continued deforestation

Lallemant_OE_2021_output_Floodmap_simulation_forest_protection.cpgz

Aug 4, 2021 - Related data for: Nature-based solutions for flood risk reduction: A probabilistic modeling framework

Gzip Archive - 3.7 MB -

Output: 18 Flood Simulations, forest protection

Nature-Based Solution for Flood Risk Reduction(Nanyang Technological University)

Jul 24, 2021David Lallemant

Flooding is the most frequent and damaging natural hazard globally. While nature-based solutions can reduce flood risk, they are not part of mainstream risk management. We develop a probabilistic risk analysis framework to quantify these benefits that i) accounts for frequent sma...

Informatics for Equitable Recovery(Nanyang Technological University)

Jul 24, 2021David Lallemant

Informatics for Equitable Recovery is a transdisciplinary research project that brings together data scientists, engineers, social scientists and civic organizations to improve post-disaster information systems and decision support tools. Example use cases for these information s...

David Lallemant(Nanyang Technological University)

Jul 24, 2021

Research topics: • Disaster risk analysis • Reliability Analysis • Probabilistic methods • Statistical learning • Disaster impact and recovery For more information, visit our disaster-analytics.com webpage.

Appendix A.2 Data table.tab

Jul 23, 2021 - Replication Data for: Biogeochemical cycling and environmental footprints of peatland-derived dissolved organic carbon in the Sunda Shelf Sea, Southeast Asia

Tabular Data - 41.7 KB - 18 Variables, 171 Observations -

Appendix B.5 Data table for Chapter 3.tab

Jul 23, 2021 - Replication Data for: Biogeochemical cycling and environmental footprints of peatland-derived dissolved organic carbon in the Sunda Shelf Sea, Southeast Asia

Tabular Data - 69.0 KB - 44 Variables, 131 Observations -

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