2,541 to 2,550 of 9,496 Results
May 24, 2024 - UMR MIVEGEC
Kouassi, Arsène Adou; Taconet, Paul; Koné, Aboubacar; Koffi, Laurent Niamien; Catry, Thibault; Marti, Renaud; Dessay, Nadine; Delaitre, Eric; Fournet, Florence, 2023, "Land use land cover ultra-high-spatial-resolution digital maps (5-cm) for 4 urban districts of the city of Bouaké (Air France, Belleville, Koko, Sossoribougou), center Côte d'Ivoire, 2020", https://doi.org/10.23708/PUYNSG, DataSuds, V3, UNF:6:dyGQe7mTss4FO+8xYhWzng== [fileUNF]
This dataset provides ultra-high-spatial-resolution Land Use / Land Cover (LULC) digital maps of 4 urban districts of Bouaké, a city located in center Côte d’Ivoire (Ivory Coast). They were produced using images acquired by Unmanned Aerial Vehicles (UAVs) in 2020 at a spatial res... |
Plain Text - 3.6 KB -
MD5: 92cda516b4a2d7729660deef3b843226
Dataset citation and description |
May 21, 2024 - UMR GET
Xavier, Rodrigo; Fleischmann, Ayan; Gosset, Marielle; Maciel, Tarcísio; Do Nascimento, Leandro; Ramalho, Emiliano; Bicudo, Thiago, 2023, "Measuring Amazon rainfall intensity with sound recorders: data and code", https://doi.org/10.23708/I0QYNM, DataSuds, V2, UNF:6:cXAvk8vWVI++coJPWKSnaA== [fileUNF]
Many regions still lack a network of ground weather observations, hampering effective climate monitoring and disaster management. In the Amazon basin, this occurs due to its remoteness and the challenging measurement of rainfall within the forest. Innovative rainfall estimation m... |
Tabular Data - 15.9 MB - 517 Variables, 3027 Observations - UNF:6:am6cSO1jVKdN5mqReymvHA==
Test dataset |
Tabular Data - 32.4 MB - 517 Variables, 6308 Observations - UNF:6:IL4rv/Alts6mLKH6QrEMRA==
Test dataset |
Tabular Data - 363.7 MB - 516 Variables, 48208 Observations - UNF:6:jTD/itqKxc5wvbFtqhf0Gg==
Data used for training the models |
Adobe PDF - 28.2 KB -
MD5: 5a4a82a66d96b19d45701029d0e15e8a
Dataset citation, description and terms of use |
Jupyter Notebook - 270.6 KB -
MD5: 85a560f15d345d32ff0f0ec57edebb50
Jupyter Notebook |
May 16, 2024 - DYNADIV Team
Barnaud, Adeline; Veltman, Margaretha; Kaczmarek, Thomas; Argout, Xavier; Vigouroux, Yves; Berthouly-Salazar, Cecile; Billot, Claire, 2024, "High throughput genetic diversity analyses of neglected crops: training data, codes and materials (Africa)", https://doi.org/10.23708/ETC16I, DataSuds, V1, UNF:6:ON0wb/ZYjxl4qqjnr8NEPA== [fileUNF]
Marginal land is land that is of little agricultural value because crops produced there would be worth less than any rent paid for access to the area. Helping to develop such zones in Africa is a key goal for the EU-funded EWA-BELT project. The aim is to promote the sustainable i... |
May 16, 2024 -
High throughput genetic diversity analyses of neglected crops: training data, codes and materials (Africa)
Plain Text - 2.1 KB -
MD5: 0ad59fd46069aaec2008347fc45ec2ce
Dataset citation, description and terms of use. |
