This repository contains the reproducible geospatial workflows developed by UMR for the RemoTrees project, an initiative funded by Horizon Europe to support innovative forest and climate monitoring. The workflows enable automated generation of site-level environmental metadata, in-situ structural tree metrics, and spatial domain selection for sensor deployment. The pipeline integrates multi-source environmental data (CHELSA, WRB, CORINE, NASADEM), airborne/UAV LiDAR (ALS/ULS), and Sentinel-2 L2A time series (reflectance, vegetation indices, biophysical/biochemical variables). Key outputs include ISO/INSPIRE-compliant metadata, canopy surface models, individual tree segmentation, and crown-level metrics aggregated into hexagonal H3 spatial domains. A multi-criteria spatial decision model supports the selection of representative trees and monitoring domains for RT sensor units (RT-S, RT-T, RT-R). The system is modular, scalable, and reproducible across biomes, with environments managed via `renv` (R) and `venv` (Python). PostgreSQL/PostGIS integration ensures centralized access to all validated metadata and spatial products.