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Hamid Ebrahimy
Hamid Ebrahimy
Researcher in Remote sensing and GIS, shahid beheshti university, Tehran, Iran.
Verified email at sbu.ac.ir
Title
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Year
Downscaling MODIS land surface temperature over a heterogeneous area: An investigation of machine learning techniques, feature selection, and impacts of mixed pixels
H Ebrahimy, M Azadbakht
Computers & Geosciences 124, 93-102, 2019
482019
A comparative study of land subsidence susceptibility mapping of Tasuj plane, Iran, using boosted regression tree, random forest and classification and regression tree methods
H Ebrahimy, B Feizizadeh, S Salmani, H Azadi
Environmental Earth Sciences 79 (10), 1-12, 2020
202020
Per-pixel land cover accuracy prediction: A random forest-based method with limited reference sample data
H Ebrahimy, B Mirbagheri, AA Matkan, M Azadbakht
ISPRS Journal of Photogrammetry and Remote Sensing 172, 17-27, 2021
132021
RUESVMs: An Ensemble Method to Handle the Class Imbalance Problem in Land Cover Mapping Using Google Earth Engine
A Naboureh, H Ebrahimy, M Azadbakht, J Bian, M Amani
Remote Sensing 12 (21), 3484, 2020
132020
Downscaling MODIS Land Surface Temperature Product Using an Adaptive Random Forest Regression Method and Google Earth Engine for a 19-Years Spatiotemporal Trend Analysis Over Iran
H Ebrahimy, H Aghighi, M Azadbakht, M Amani, S Mahdavi, AA Matkan
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2021
52021
Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth Engine
A Naboureh, A Li, H Ebrahimy, J Bian, M Azadbakht, M Amani, G Lei, ...
International Journal of Applied Earth Observation and Geoinformation 105 …, 2021
22021
Integration of Sentinel-1 and Sentinel-2 Data with the G-SMOTE Technique for Boosting Land Cover Classification Accuracy
H Ebrahimy, A Naboureh, B Feizizadeh, J Aryal, O Ghorbanzadeh
Applied Sciences 11 (21), 10309, 2021
12021
Effectiveness of the integration of data balancing techniques and tree-based ensemble machine learning algorithms for spatially-explicit land cover accuracy prediction
H Ebrahimy, B Mirbagheri, AA Matkan, M Azadbakht
Remote Sensing Applications: Society and Environment, 100785, 2022
2022
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