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Google Earth Engine tool to generate multi-modal and multi-temporal datasets, including spatially and temporally aligned Sentinel-1 SAR data, Sentinel-2 multispectral data, weather and DEM-based data. A supplementary material for Paluba et al. 2024: "Identification of Optimal Sentinel-1 SAR Polarimetric Parameters for Forest Monitoring in Czechia
The repository contains MATLAB and Python-based code for rainfall erosivity estimation and assessment of multiple datasets, and merging them into a single dataset.
Catalog-independent Wflow SBM hydrological model for the Upper Niger Basin. Complete ETL pipeline from raw ERA5/SRTM to runnable Julia simulation. Includes documented error resolutions and reusable patterns for building Wflow-sbm model.
A statistical downscaling pipeline using machine learning (XGBoost, Random Forest) to predict fine-grained Land Surface Temperature (LST) on 10-meter grids. Integrates Landsat 8/9, Sentinel-2 imagery, OpenStreetMap features, and ERA5-Land climate data across Vienna, Barcelona, and Hong Kong to map urban heat islands.
This repository contains all the data and scripts to explore the greenness response of the vegetation from the Forest Floristic Inventory of Santa Catarina to seasonal variations in rainfall and temperature.
Herramienta de Hydro-Intelligence para balances hídricos globales. Usa Google Earth Engine (GEE) y Python para procesar series CHIRPS (0.05°) y ERA5-Land. Implementa un buffer de 5.5 km de diámetro para coincidir con la resolución nativa del píxel (Escala 1:1), garantizando precisión en el cálculo de P, ETP.
Climate, hazard and accidentology visualisation project for the Mont Blanc massif, combining ERA5 temperature analysis, geospatial processing and Quarto web design.