UMR AMAP

botAny and Modelling of Plant Architecture and vegetation

AMAP joint research unit (French acronym UMR) is an interdisciplinary laboratory that conducts basic research on plants and plant communities with the aim of predicting ecosystems responses to environmental forcing, in terms of the distribution/conservation of species and biodiversity, crop production, carbon storage in plant biomass, protection of the environment and the provision of ecosystem services. Our research concerns Mediterranean, temperate and tropical plant communities. It is cutting edge research in botany, plant ecology, agronomy, forestry and in computer science, applied statistics and mathematics.

AMAP BASES DE DONNEES

AMAPVox

ECOMED

Published in Recherche Data Gouv

Published in CIRAD Dataverse

Cas d'étude du projet ANR-BRIDGE

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1 to 10 of 63 Results

South Asian and Central African maps from: LiDAR-based reference aboveground biomass maps for tropical forests of South Asia and Central Africa Mar 18, 2024 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...
Cocoa tree point clouds obtained by terrestrial Lidar scanning in agroforestry systems in Cameroon Jan 31, 2024 - Published in CIRAD Dataverse Momo Takoudjou, Stéphane; Peynaud, Emilie, 2019, "Cocoa tree point clouds obtained by terrestrial Lidar scanning in agroforestry systems in Cameroon", https://doi.org/10.18167/DVN1/5HZB1F, CIRAD Dataverse This data set concerns a total of 55 cocoa trees grown in cocoa based agroforestry systems from Central region of Cameroon. The data collection campaign was carried out in the district of Bokito (4°34 latitude N and 11°07 longitude E), in the village of Yorro located in a forest-... This Dataset is harvested from CIRAD Dataverse. Clicking the link will take you directly to the source.
Maps of central African rainforest composition and vulnerability Nov 21, 2023 - Published in CIRAD Dataverse Maxime Réjou-Méchain; Frédéric Mortier; Jean-Francois Bastin; Guillaume Cornu; Nicolas Barbier; Nicolas Bayol; Fabrice Bénédet; Xavier Bry; Gilles Dauby; Vincent Deblauwe; Jean-Louis Doucet; Charles Doumenge; Adeline Fayolle; Claude Garcia; Jean-Paul Kibambe; Jean-Joël Loumeto; Alfred Ngomanda; Pierre Ploton; Bonaventure Sonke; Catherine Trottier; Ruppert Vimal; Olga Yongo; Raphael Pelissier; Sylvie Gourlet-Fleury, 2019, "Maps of central African rainforest composition and vulnerability", https://doi.org/10.18167/DVN1/UCNCA7, CIRAD Dataverse This is a dataset repository for the manuscript: Réjou-Méchain, M., Mortier, F., Bastin, J.-F., Cornu G., Barbier, N., Bayol, N., Bénédet, F., Bry, X., Dauby, G., Deblauwe, V., Doucet, J.-L., Doumenge, C., Fayolle, A., Garcia, C., Kibambe, J.-P., Loumeto, J.-J., Ngomanda, A., Plo... This Dataset is harvested from CIRAD Dataverse. Clicking the link will take you directly to the source.
Map of landform classes of the Congo Basin and adjacent regions at 900 m of spatial resolution Oct 26, 2023 - Published in CIRAD Dataverse Viennois, Gaëlle; Bétard, François; Freycon, Vincent; Barbier, Nicolas; Couteron, Pierre, 2024, "Map of landform classes of the Congo Basin and adjacent regions at 900 m of spatial resolution", https://doi.org/10.18167/DVN1/ZRFRGD, CIRAD Dataverse Map of landform classes of the Congo Basin and adjacent regions at 900 m of spatial resolution. This Dataset is harvested from CIRAD Dataverse. Clicking the link will take you directly to the source.
Code for: Spatial scenario of tropical deforestation and carbon emissions for the 21st century May 27, 2023 - Published in CIRAD Dataverse Vieilledent, Ghislain, 2024, "Code for: Spatial scenario of tropical deforestation and carbon emissions for the 21st century", https://doi.org/10.18167/DVN1/7N2BTU, CIRAD Dataverse This dataset includes the code used to produce the results of the following scientific article: Vieilledent G., C. Vancutsem, C. Bourgoin, P. Ploton, P. Verley and F. Achard. Spatial scenario of tropical deforestation and carbon emissions for the 21st century. bioRxiv. doi: 10.11... This Dataset is harvested from CIRAD Dataverse. Clicking the link will take you directly to the source.
Code and data for: Not all species will migrate poleward as the climate warms: the case of the seven baobab species in Madagascar Jan 18, 2023 - Published in CIRAD Dataverse Vieilledent, Ghislain; Tagliari, Mario M.; Danthu, Pascal; Leong Pock-Tsy, Jean-Michel; Cornu, Cyrille, 2024, "Code and data for: Not all species will migrate poleward as the climate warms: the case of the seven baobab species in Madagascar", https://doi.org/10.18167/DVN1/LIALRR, CIRAD Dataverse This repository includes code and data for the following article: TAGLIARI Mario M., Pascal DANTHU, Jean-Michel LEONG POCK TSY, Cyrille CORNU, Jonathan LENOIR, Vítor CARVALHO-ROCHA, Ghislain VIEILLEDENT. 2021. Not all species will migrate poleward as the climate warms: the case o... This Dataset is harvested from CIRAD Dataverse. Clicking the link will take you directly to the source.
Démarche qualité AMAP 2017 Jan 18, 2023 - Published in CIRAD Dataverse Perez, Jérôme, 2024, "Démarche qualité AMAP 2017", https://doi.org/10.18167/DVN1/ZPB36L, CIRAD Dataverse Document de mise en place de la démarche qualité dans la création des bases de données. This Dataset is harvested from CIRAD Dataverse. Clicking the link will take you directly to the source.
Native plants reported as threatened by identified alien plants in the global IUCN Red List Nov 9, 2022 Pouteau, Robin, 2022, "Native plants reported as threatened by identified alien plants in the global IUCN Red List", https://doi.org/10.23708/6ERBMY, DataSuds, V1, UNF:6:CMYlNd/qh6rEJxXLInXZpg== [fileUNF] This dataset includes 1,407 pairs of threatened native–invasive alien plants extracted from the IUCN Red List of Threatened Species (https://www.iucnredlist.org/). For each pair, the threat category of the threatened native species (NT, VU, EN, CR, EW, EX), its population trend (...
Projet ECOSFIX : interrogation de la base de données d'observations permettant de déterminer comment un type de forêt affecte les traits physiques et fonctionnels des racines. Apr 13, 2022 - AMAP BASES DE DONNEES Perez, Jerome, 2022, "Projet ECOSFIX : interrogation de la base de données d'observations permettant de déterminer comment un type de forêt affecte les traits physiques et fonctionnels des racines.", https://doi.org/10.23708/H7GYTB, DataSuds, V3, UNF:6:Rg4omgKiJ8nmN6yKTBKDlA== [fileUNF] Requêtes PostgreSQL développées dans le cadre du projet ECOSFIX pour créer la base de données et en extraire les échantillons, les mesures des rhizotrons, les sites, les caractéristiques de sols, les données météorologiques, les parcelles, les parcelles avec leurs sites et les fi...
Projet STABILITY : interrogation de la base de données d'observations sur l’utilisation de la végétation pour prévenir et lutter contre les glissements de terrain et l’érosion Apr 6, 2022 - AMAP BASES DE DONNEES Perez, Jerome, 2022, "Projet STABILITY : interrogation de la base de données d'observations sur l’utilisation de la végétation pour prévenir et lutter contre les glissements de terrain et l’érosion", https://doi.org/10.23708/KISGJY, DataSuds, V1, UNF:6:5F7M4/mecTgliXYhsT19Sw== [fileUNF] Requêtes PostgreSQL développées dans le cadre du projet STABILITY pour créer la base de données , extraire les types d'habitat, l'ensemble des localisations, aires, villes, continents, pays, districts, risques, sols, typologies racinaires, bibliographies, éco-ingéniérie, écologie...

South Asian and Central African maps from: LiDAR-based reference aboveground biomass maps for tropical forests of South Asia and Central Africa

Mar 18, 2024

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...

Cocoa tree point clouds obtained by terrestrial Lidar scanning in agroforestry systems in Cameroon

Jan 31, 2024 - Published in CIRAD Dataverse

Momo Takoudjou, Stéphane; Peynaud, Emilie, 2019, "Cocoa tree point clouds obtained by terrestrial Lidar scanning in agroforestry systems in Cameroon", https://doi.org/10.18167/DVN1/5HZB1F, CIRAD Dataverse

This data set concerns a total of 55 cocoa trees grown in cocoa based agroforestry systems from Central region of Cameroon. The data collection campaign was carried out in the district of Bokito (4°34 latitude N and 11°07 longitude E), in the village of Yorro located in a forest-...