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Rain Cell project in Mali Mar 4, 2021Rain Cell projects IRD has developed the RainCell app Bamako project, an Early Flood Warning System (EWS) for the city of Bamako. The project was carried out in partnership with the Civil Protection of Mali (DGPC ), MALI-METEO and the National Hydraulic Directorate (DNH ). Funded by the Korean Gree...
Rain Cell projects Mar 4, 2021 Rain Cell Africa aims to promote and develop an innovating estimation of rain based on cellular networks. It relies on commercial microwave links from cellular telephone networks to detect and quantify rainfall. The method exploits radio wave attenuation caused by rain. Based on...
MigrationDroughtMali_Datafile1_Dictionary.tab Mar 3, 2021 - Replication data for: Migration response to drought in Mali Tabular Data - 5.7 KB - 4 Variables, 60 Observations - UNF:6:b/feCJ40t/JuM3LiggT/bw== Documentation Description of all variables contained in file MigrationDroughtMali_Datafile1
MigrationDroughtMali_Datafile1.tab Mar 3, 2021 - Replication data for: Migration response to drought in Mali Tabular Data - 4.9 MB - 60 Variables, 20260 Observations - UNF:6:15i0nOxB3AWdGS9hEfXQ9g== DataGeospatial Contains all the variables used in regressions on net migration rates
MigrationDroughtMali_Datafile2_Dictionary.tab Mar 3, 2021 - Replication data for: Migration response to drought in Mali Tabular Data - 5.1 KB - 4 Variables, 36 Observations - UNF:6:CiuXd7zT3TpGrR562s48RA== Documentation Description of all variables contained in file MigrationDroughtMali_Datafile2
MigrationDroughtMali_Datafile2.tab Mar 3, 2021 - Replication data for: Migration response to drought in Mali Tabular Data - 13.2 MB - 36 Variables, 59220 Observations - UNF:6:2yWqqphRS8t2WfFn+BuAFg== Data Contains all the variables used in regressions on international emigration rates
Supplementary material1_R procedure_tracking data_Random forest & Speed model_Madagascar.pdf Mar 3, 2021 - Supplementary material - Methodological brief (including R code and data) for performing random forest and speed-based analysis of GPS boat tracking data Adobe PDF - 1.2 MB - MD5: 66207b93e4cd7478cb290c59948b9f03 Methodological brief or performing the random forest model and the speed threshold method
Supplementary material2_Data_gillnet.Rdata Mar 3, 2021 - Supplementary material - Methodological brief (including R code and data) for performing random forest and speed-based analysis of GPS boat tracking data Gzip Archive - 2.5 MB - MD5: d732ab135b3a841f97cb92ceada7b089 Sample data (GPS positions and covariates)
Supplementary material3_required packages.R Mar 3, 2021 - Supplementary material - Methodological brief (including R code and data) for performing random forest and speed-based analysis of GPS boat tracking data R Syntax - 224 B - MD5: 341826df631639b46a8c5528a5dd5c6d List of the required R packages
Supplementary material4_AUC function.R Mar 3, 2021 - Supplementary material - Methodological brief (including R code and data) for performing random forest and speed-based analysis of GPS boat tracking data R Syntax - 1.8 KB - MD5: b9d19bf2aeb6dc04373a4fbe332aaf90 R code of function used to perform the cross-validation procedure of the random forest algorithm

Rain Cell project in Mali

Mar 4, 2021Rain Cell projects

IRD has developed the RainCell app Bamako project, an Early Flood Warning System (EWS) for the city of Bamako. The project was carried out in partnership with the Civil Protection of Mali (DGPC ), MALI-METEO and the National Hydraulic Directorate (DNH ). Funded by the Korean Gree...

Rain Cell projects

Mar 4, 2021

Rain Cell Africa aims to promote and develop an innovating estimation of rain based on cellular networks. It relies on commercial microwave links from cellular telephone networks to detect and quantify rainfall. The method exploits radio wave attenuation caused by rain. Based on...

MigrationDroughtMali_Datafile1_Dictionary.tab

Mar 3, 2021 - Replication data for: Migration response to drought in Mali

Tabular Data - 5.7 KB - 4 Variables, 60 Observations -

Documentation

Description of all variables contained in file MigrationDroughtMali_Datafile1

MigrationDroughtMali_Datafile1.tab

Mar 3, 2021 - Replication data for: Migration response to drought in Mali

Tabular Data - 4.9 MB - 60 Variables, 20260 Observations -

DataGeospatial

Contains all the variables used in regressions on net migration rates

MigrationDroughtMali_Datafile2_Dictionary.tab

Mar 3, 2021 - Replication data for: Migration response to drought in Mali

Tabular Data - 5.1 KB - 4 Variables, 36 Observations -

Documentation

Description of all variables contained in file MigrationDroughtMali_Datafile2

MigrationDroughtMali_Datafile2.tab

Mar 3, 2021 - Replication data for: Migration response to drought in Mali

Tabular Data - 13.2 MB - 36 Variables, 59220 Observations -

Data

Contains all the variables used in regressions on international emigration rates

Supplementary material1_R procedure_tracking data_Random forest & Speed model_Madagascar.pdf

Mar 3, 2021 - Supplementary material - Methodological brief (including R code and data) for performing random forest and speed-based analysis of GPS boat tracking data

Adobe PDF - 1.2 MB -

Methodological brief or performing the random forest model and the speed threshold method

Supplementary material2_Data_gillnet.Rdata

Mar 3, 2021 - Supplementary material - Methodological brief (including R code and data) for performing random forest and speed-based analysis of GPS boat tracking data

Gzip Archive - 2.5 MB -

Sample data (GPS positions and covariates)

Supplementary material3_required packages.R

Mar 3, 2021 - Supplementary material - Methodological brief (including R code and data) for performing random forest and speed-based analysis of GPS boat tracking data

R Syntax - 224 B -

List of the required R packages

Supplementary material4_AUC function.R

Mar 3, 2021 - Supplementary material - Methodological brief (including R code and data) for performing random forest and speed-based analysis of GPS boat tracking data

R Syntax - 1.8 KB -

R code of function used to perform the cross-validation procedure of the random forest algorithm

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