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UMR ISTerre(CNRS, Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, IRD, Univ. Gustave Eiffel)
UMR ISTerre logo
Mar 25, 2024
The Institute of Earth Sciences (ISTerre) is a joint research unit of the CNRS, Grenoble-Alpes University, the University of Savoie Mont Blanc, the IRD, and Gustave Eiffel University. ISTerre is a leading laboratory for Grenoble’s Universe Sciences Observatory (OSUG) whose resear...
Base cartographique Sphaera(IRD - Institut de Recherche pour le Développement)
Base cartographique Sphaera logo
Mar 25, 2024
La base de données Sphaera repose sur 4 000 références cartographiques rassemblées dans 714 jeux de données couvrant une vaste zone géographique, plus particulièrement le domaine tropical, (cartes, notices de cartes, atlas, ouvrages), sur de nombreux thèmes (agronomie, archéologi...
Mar 22, 2024 - UMR LEMAR
Sané, Babacar; Diouf, Malick; Jean, Fréderic; Kerhervé, Malika; Flye-Sainte-Marie, Jonathan; Houmenou, Abdou Karim; Thomas, Yoann, 2024, "Gonad histological analysis of Senilia senilis sampled in the Sine Saloum inverse estuary in Senegal between march 2021 and march 2022", https://doi.org/10.23708/VQHAZB, DataSuds, V1, UNF:6:F8uDwbq/ISTm9wrdeI/tgg== [fileUNF]
Understanding the reproductive biology of a species is an important means of determining the renewal capacity of natural stocks, especially in the case of heavily exploited species. It is a fundamental element in supporting the implementation of management measures. Here, we stud...
Plain Text - 1.7 KB - MD5: b8581b9e3e22d8c19c11fe94458f8d8d
Documentation
ReadMe file - data citation, description and terms of use.
Tabular Data - 23.7 KB - 15 Variables, 200 Observations - UNF:6:MEN4Up4jbYyjPMDHIAKVKw==
Data
Histological analysis data for Senilia senilis in Senegal (2021-2022).
Mar 18, 2024 - UMR AMAP
Rodda, Suraj Reddy; Fararoda, Rakesh; Jha, Nidhi; Réjou-Méchain, Maxime; Couteron, Pierre; Gopalakrishnan, Rajashekar; Barbier, Nicolas; Alfonso, Alonso; Bako, Ousmane; Bassama, Patrick; Behera, Debabrata; Bissiengou, Pulcherie; Biyiha, Hervé; Brockelman Y., Warren; Chanthorn, Wirong; Chauhan, Prakash; Dadhwal, Vinay Kumar; Dauby, Gilles; Deblauwe, Vincent; Dongmo, Narcis; Droissart, Vincent; Jeyakumar, Selvaraj; Jha, Chandra Shekar; Kandem, Narcisse Guy; Katembo, John; Kougue, Ronald; Leblanc, Hugo; Lewis, Simon; Libalah, Moses; Manikandan, Maya; Martin-Ducup, Olivier; Mbock, Germain; Memiaghe, Hervé; Mofack, Gislain; Mutyala, Praveen; Narayanan, Ayyappan; Nathalang, Anuttara; Oum Ndjock, Gilbert; Ngoula, Fernandez; Nidamanuri, Rama Rao; Pélissier, Raphaël; Saatchi, Sassan; Sagang, Le Bienfaiteur; Salla, Patrick; Simo-Droissart, Murielle; B. Smith, Thomas; Sonké, Bonaventure; Stevart, Tariq; Tjomb, Danièle; Zebaze, Donatien; Zemagho, Lise; Ploton, Pierre, 2024, "South Asian and Central African maps from: LiDAR-based reference aboveground biomass maps for tropical forests of South Asia and Central Africa", https://doi.org/10.23708/H2MHXF, DataSuds, V2, UNF:6:pUYwyUIpsRWmCnpBju2KxQ== [fileUNF]
The dataset contains forest aboveground biomass prediction maps derived from field inventory plot and UAV or airborne LiDAR data over five sites in South Asia and eight sites in Central Africa, together with prediction uncertainty maps. Maps are provided at 100 x 100 m and 40 x 4...
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