palubad
PhD candidate in Remote Sensing at Charles University in Prague, Czechia
Charles University, PraguePrague, Czechia
Pinned Repositories
Automatic-Forest-Classification-GEE
A Google Earth Engine tool for Automatic classification of forests using Sentinel-2 data. It also serves as supplementary material for the article by Onačillová, Krištofová & Paluba (2023): Automatic Classification of Forests using Sentinel-2 Multispectral Satellite Data and Machine Learning Methods in Google Earth Engine.
GEE-functions-codes
This repository contains GEE codes and functions that I have created in the course of my work in GEE and which I find useful for the wider GEE community.
LC-SLIAC
GEE codes to correct the radiometric effects (caused by the local incidence angle) in Sentinel-1 SAR data. Attachment for the article in Remote Sensing: Paluba et al. (2021): "Land Cover-Specific Local Incidence Angle Correction: A Method for Time-Series Analysis of Forest Ecosystems" (https://www.mdpi.com/1093660).
LST-downscaling-to-10m-GEE
A tool to downscale Landsat Land Surface Temperature to 10 m using Sentinel-2 data in GEE. Attachment for the article in Remote Sensing: Onačillová et al. 2021: Combining Landsat 8 and Sentinel-2 Data in Google Earth Engine to Derive Higher Resolution Land Surface Temperature Maps in Urban Environment. https://doi.org/10.3390/rs14164076
Precipitation_GEE
Precipitation dataset comparison in GEE. Supplementary material (code and data) for the article submitted for IGARSS 2024, entitled Evaluation of precipitation datasets available in Google Earth Engine on a daily basis for Czechia.
S1-BAP
A semi-automatic GEE tool to monitor burned area progression using Sentinel-1 SAR data. Attachment for the article in the IEEE JSTARS by Paluba D. et al. (2024): Tracking burned area progression in an unsupervised manner using Sentinel-1 SAR data in Google Earth Engine https://doi.org/10.1109/JSTARS.2024.3427382
S1BAM-IGARSS-2023
This code repository is an attachment for the IGARSS 2023 proceeding paper: Paluba D. et al. (2023): "Unsupervised Burned Area Mapping in Greece: Investigating the impact of precipitation, pre- and post-processing of Sentinel-1 data in Google Earth Engine".
TAT2023
Trans-Atlantic Training 2023 materials
palubad's Repositories
palubad/LST-downscaling-to-10m-GEE
A tool to downscale Landsat Land Surface Temperature to 10 m using Sentinel-2 data in GEE. Attachment for the article in Remote Sensing: Onačillová et al. 2021: Combining Landsat 8 and Sentinel-2 Data in Google Earth Engine to Derive Higher Resolution Land Surface Temperature Maps in Urban Environment. https://doi.org/10.3390/rs14164076
palubad/Automatic-Forest-Classification-GEE
A Google Earth Engine tool for Automatic classification of forests using Sentinel-2 data. It also serves as supplementary material for the article by Onačillová, Krištofová & Paluba (2023): Automatic Classification of Forests using Sentinel-2 Multispectral Satellite Data and Machine Learning Methods in Google Earth Engine.
palubad/S1-BAP
A semi-automatic GEE tool to monitor burned area progression using Sentinel-1 SAR data. Attachment for the article in the IEEE JSTARS by Paluba D. et al. (2024): Tracking burned area progression in an unsupervised manner using Sentinel-1 SAR data in Google Earth Engine https://doi.org/10.1109/JSTARS.2024.3427382
palubad/LC-SLIAC
GEE codes to correct the radiometric effects (caused by the local incidence angle) in Sentinel-1 SAR data. Attachment for the article in Remote Sensing: Paluba et al. (2021): "Land Cover-Specific Local Incidence Angle Correction: A Method for Time-Series Analysis of Forest Ecosystems" (https://www.mdpi.com/1093660).
palubad/S1BAM-IGARSS-2023
This code repository is an attachment for the IGARSS 2023 proceeding paper: Paluba D. et al. (2023): "Unsupervised Burned Area Mapping in Greece: Investigating the impact of precipitation, pre- and post-processing of Sentinel-1 data in Google Earth Engine".
palubad/Precipitation_GEE
Precipitation dataset comparison in GEE. Supplementary material (code and data) for the article submitted for IGARSS 2024, entitled Evaluation of precipitation datasets available in Google Earth Engine on a daily basis for Czechia.
palubad/GEE-functions-codes
This repository contains GEE codes and functions that I have created in the course of my work in GEE and which I find useful for the wider GEE community.
palubad/TAT2023
Trans-Atlantic Training 2023 materials
palubad/gee-teaching-cuni