Fuzzy (probabilistic) maps of hydrogeomorphic (HGM) wetland types on 20 test sites in metropolitan France, produced using a data fusion approach.

Fuzzy (probabilistic) maps of hydrogeomorphic (HGM) wetland types on 20 test sites in metropolitan France, produced using a data fusion approach.

Fuzzy (probabilistic) maps of hydrogeomorphic (HGM) wetland types on 20 test sites in metropolitan France, produced using a data fusion approach.

A dataset was produced for 117 urban trees in four monospecific tree rows in the city of Rennes, northwestern France. The trees were measured in nine 2- to 3-day measurement sessions from Apr-Sep 2021. The dataset includes (i) leaf traits (i.e., contents of pigments, water and dry matter) measured in situ and in the laboratory; (ii) plant area density measured in situ under the canopy and (iii) georeferenced data that describe the location, geometry and species of the trees. The dataset provides an original overview of dynamics of the contents of pigments, water and dry matter for four tree species grown under urban conditions. It can be used for several purposes, such as identifying trees’ responses/behaviors in relation to their urban environment or climate conditions.The repository comprised 3 files : DATASET_PART1.csv : This file contains leaf trait measurementsDATASET_PART2.csv : This file contains plant area density measurements DATASET_PART3.gpkg : This file contains two spatial vector layers: (1) CROWN_EXTENT that is a polygon layer describing tree crowns and (2) TRUNK_LOCATION that is a point layer describing tree location.More details on the study site, protocols and data can be found in the following reference:Théo Le Saint, Jean Nabucet, Cécile Sulmon, Julien Pellen, Karine Adeline, Laurence Hubert-Moy, A spatio-temporal dataset for ecophysiological monitoring of urban trees, Data in Brief, Volume 57, 2024, 111010, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2024.111010.

A dataset was produced for 117 urban trees in four monospecific tree rows in the city of Rennes, northwestern France. The trees were measured in nine 2- to 3-day measurement sessions from Apr-Sep 2021. The dataset includes (i) leaf traits (i.e., contents of pigments, water and dry matter) measured in situ and in the laboratory; (ii) plant area density measured in situ under the canopy and (iii) georeferenced data that describe the location, geometry and species of the trees. The dataset provides an original overview of dynamics of the contents of pigments, water and dry matter for four tree species grown under urban conditions. It can be used for several purposes, such as identifying trees’ responses/behaviors in relation to their urban environment or climate conditions.The repository comprised 3 files : DATASET_PART1.csv : This file contains leaf trait measurementsDATASET_PART2.csv : This file contains plant area density measurements DATASET_PART3.gpkg : This file contains two spatial vector layers: (1) CROWN_EXTENT that is a polygon layer describing tree crowns and (2) TRUNK_LOCATION that is a point layer describing tree location.More details on the study site, protocols and data can be found in the following reference:Théo Le Saint, Jean Nabucet, Cécile Sulmon, Julien Pellen, Karine Adeline, Laurence Hubert-Moy, A spatio-temporal dataset for ecophysiological monitoring of urban trees, Data in Brief, Volume 57, 2024, 111010, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2024.111010.