{"name": "GEE GPR Phenology", "package_name": "GEEGPRPheno", "description": "A QGIS plugin for Sentinel-2 biophysical variable retrieval, temporal gap filling, and land surface phenology analysis using Gaussian Process Regression.", "about": "GEE GPR Phenology implements a complete workflow for Sentinel-2 BOA/L2A imagery, including spectral GPR prediction, temporal gap filling with an RBF kernel, double logistic fitting, and land surface phenology metrics such as SOS, EOS, POS and LOS. Since version 1.5.0, the plugin includes automatic layer loading with QGIS symbology and groups, PDF/CSV reports, heterogeneous raster grid correction for LSP processing, duplicate-date handling, and multilingual support in Spanish, English and Portuguese. Version 1.5.18 resolves the Qt6 compatibility findings reported by the QGIS Plugin Repository by using scoped QGIS enum members with QGIS 3 fallbacks and a Qt5/Qt6-compatible dialog execution method. Version 1.5.17 removed subprocess-based dependency installation, replaced silent exception handling with explicit debug logging, and retained manual dependency instructions. The official contact email remains jfloresr@unal.edu.co. All mathematical, modelling, GPR, gap-filling, phenology, Sentinel-2 index, model data, and Processing algorithm logic remains unchanged. Note for QGIS 4.0.x / Python 3.12: in some installations, functional libraries such as rasterio may not be available in the QGIS Python environment by default. If rasterio is missing, GEE download may work but raster harmonization, gap filling, GPR raster prediction, or LSP processing can stop with ModuleNotFoundError. Use the plugin Info tab to view manual dependency instructions, or install rasterio in the QGIS Python environment before running those workflows. For security, the plugin never executes pip, ensurepip, shell commands, or other external processes. QGIS 3.x testing remains the recommended production path until all required Python wheels are confirmed in the target QGIS 4 environment. This release does not change the mathematical or modelling logic.", "homepage": "https://github.com/jf-floresriera/GEE_GPR_Phenology", "repository": "https://github.com/jf-floresriera/GEE_GPR_Phenology", "tracker": "https://github.com/jf-floresriera/GEE_GPR_Phenology/issues", "author": "Adapted for QGIS by Jesus Enrique Flores Riera", "tags": ["time series", "remote sensing", "vegetation", "sentinel-2", "gap filling", "lai", "phenology", "gpr", "land surface phenology", "biophysical"], "downloads": 423, "latest_version": "1.5.18", "versions": [{"version": "1.5.18", "experimental": false, "qgis_min": "3.0.0", "qgis_max": "4.99.0", "downloads": 115, "uploaded_by": "jf-floresriera", "upload_datetime": "2026-08-03T12:46:04.833731"}, {"version": "1.5.14", "experimental": false, "qgis_min": "3.0.0", "qgis_max": "4.99.0", "downloads": 149, "uploaded_by": "jf-floresriera", "upload_datetime": "2026-07-08T12:11:50.461897"}, {"version": "1.5.13", "experimental": false, "qgis_min": "3.0.0", "qgis_max": "4.99.0", "downloads": 12, "uploaded_by": "jf-floresriera", "upload_datetime": "2026-07-08T12:07:13.634034"}, {"version": "1.5.12", "experimental": false, "qgis_min": "3.0.0", "qgis_max": "4.99.0", "downloads": 16, "uploaded_by": "jf-floresriera", "upload_datetime": "2026-07-08T11:54:11.517950"}, {"version": "1.5.6", "experimental": false, "qgis_min": "3.16.0", "qgis_max": "3.99.0", "downloads": 130, "uploaded_by": "jf-floresriera", "upload_datetime": "2026-06-10T08:31:06.937353"}]}