Hossein Bagheri

About Hossein Bagheri

Hossein Bagheri, With an exceptional h-index of 7 and a recent h-index of 6 (since 2020), a distinguished researcher at University of Isfahan, specializes in the field of Remote Sensing, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Google Earth Engine-based mapping of land use and land cover for weather forecast models using Landsat 8 imagery

Assessment of explainable tree-based ensemble algorithms for the enhancement of Copernicus digital elevation model in agricultural lands

Enhancing Crop Classification Accuracy through Synthetic SAR-Optical Data Generation Using Deep Learning

Estimation of PM2. 5 as a Harmful Environmental Hazard in Tehran by Fusion of MODIS Aerosol Products through a Machine Learning Approach.

Using deep ensemble forest for high-resolution mapping of PM2. 5 from MODIS MAIAC AOD in Tehran, Iran

Data level and decision level fusion of satellite multi-sensor AOD retrievals for improving PM2. 5 estimations, a study on Tehran

Segment-based fusion of multi-sensor multi-scale satellite soil moisture retrievals

Using deep generative models to estimate PM2. 5 concentration from satellite AOD data collected from Tehran, Iran

Hossein Bagheri Information

University

Position

___

Citations(all)

309

Citations(since 2020)

275

Cited By

89

hIndex(all)

7

hIndex(since 2020)

6

i10Index(all)

6

i10Index(since 2020)

5

Email

University Profile Page

Google Scholar

Hossein Bagheri Skills & Research Interests

Remote Sensing

Machine Learning

Top articles of Hossein Bagheri

Google Earth Engine-based mapping of land use and land cover for weather forecast models using Landsat 8 imagery

Ecological Informatics

2024/5/1

Hossein Bagheri
Hossein Bagheri

H-Index: 5

Assessment of explainable tree-based ensemble algorithms for the enhancement of Copernicus digital elevation model in agricultural lands

International Journal of Image and Data Fusion

2024/4/14

Enhancing Crop Classification Accuracy through Synthetic SAR-Optical Data Generation Using Deep Learning

ISPRS International Journal of Geo-Information

2023/11/2

Ali Mirzaei
Ali Mirzaei

H-Index: 12

Hossein Bagheri
Hossein Bagheri

H-Index: 5

Estimation of PM2. 5 as a Harmful Environmental Hazard in Tehran by Fusion of MODIS Aerosol Products through a Machine Learning Approach.

Geography & Environmental Hazards

2023/9/1

Ali Mirzaei
Ali Mirzaei

H-Index: 12

Hossein Bagheri
Hossein Bagheri

H-Index: 5

Using deep ensemble forest for high-resolution mapping of PM2. 5 from MODIS MAIAC AOD in Tehran, Iran

Environmental Monitoring and Assessment

2023/3

Hossein Bagheri
Hossein Bagheri

H-Index: 5

Data level and decision level fusion of satellite multi-sensor AOD retrievals for improving PM2. 5 estimations, a study on Tehran

Earth Science Informatics

2023/3

Ali Mirzaei
Ali Mirzaei

H-Index: 12

Hossein Bagheri
Hossein Bagheri

H-Index: 5

Segment-based fusion of multi-sensor multi-scale satellite soil moisture retrievals

Remote Sensing Letters

2022/12/2

Hossein Bagheri
Hossein Bagheri

H-Index: 5

Davood Akbari
Davood Akbari

H-Index: 3

Using deep generative models to estimate PM2. 5 concentration from satellite AOD data collected from Tehran, Iran

Scientific-Research Quarterly of Geographical Data (SEPEHR)

2022/8/23

Hossein Bagheri
Hossein Bagheri

H-Index: 5

A machine learning-based framework for high resolution mapping of PM2. 5 in Tehran, Iran, using MAIAC AOD data

Advances in space Research

2022/5/1

Hossein Bagheri
Hossein Bagheri

H-Index: 5

So2Sat LCZ42: A benchmark data set for the classification of global local climate zones [Software and Data Sets]

IEEE Geoscience and Remote Sensing Magazine

2020/2/26

See List of Professors in Hossein Bagheri University(University of Isfahan)