Sadegh Jamali

Has grant

Lecturer

Lund University

Sweden

Research Interests

Explore related searches

Professors in Sweden

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Dr. Sadegh Jamali is a Lecturer at Lund University in Sweden. His research areas focus on remote sensing, environmental monitoring, and machine learning applications in geospatial analysis. Recent publications include studies on earthquake-damaged building detection, rural flood mapping, and the impact of drought in northern forests utilizing satellite imagery. He is also involved in developing innovative methods for individual tree detection and urban land use classification.

Recent Grants

Grant: Close

EU Scholarship Award

Open Date: 2009-01-01

Close Date: 2011-01-01

Articles (15)

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Collaborators (7)

Cintia Bertacchi Uvo

Lund University

SWEDEN

View details

Saeid Homayouni

Associate Professor

Institut national de la recherche scientifique

CANADA

View details

Hossein Hashemi

Associate Professor

Lund University

SWEDEN

View details

Mahdi Farnaghi

University of Twente

NETHERLANDS

View details

Abdulhakim Abdi

Lund University

SWEDEN

View details

Jonas Ardö

Lund University

SWEDEN

View details

Lars Eklundh

Professor

Lund University

SWEDEN

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Sadegh Jamali

Research Interests

Explore related searches

Contact this professor

About

Recent Grants

Articles (15)

EDB-HSTEU-Net: Earthquake-damaged building detection using a novel hybrid swin transformer efficient U-Net (HSTEU-Net) and transfer learning techniques from post-event VHR remote sensing data

Unsupervised Rural Flood Mapping from Bi-Temporal Sentinel-1 Images Using an Improved Wavelet-Fusion Flood-Change Index (IWFCI) and an Uncertainty-Sensitive Markov Random Field (USMRF) Model

Best Scanline Determination of Pushbroom Images for a Direct Object to Image Space Transformation Using Multilayer Perceptron

Response and resilience to drought in northern forests revealed by Sentinel-2

Kernel-Based Early Detection of Forest Bark Beetle Attack Using Vegetation Indices Time Series of Sentinel-2

Mangrove plantation suitability mapping by integrating multi criteria decision making geospatial approach and remote sensing data

Detecting the Greatest Changes in Global Satellite-Based Precipitation Observations

Individual tree detection from unmanned aerial vehicle (UAV) derived point cloud data in a mixed broadleaf forest using hierarchical graph approach

Satellite-Observed Spatial and Temporal Sea Surface Temperature Trends of the Baltic Sea between 1982 and 2021

Urban land use and land cover classification with interpretable machine learning – A case study using Sentinel-2 and auxiliary data

Global Evaluation of SMAP/Sentinel-1 Soil Moisture Products

Performance Evaluation of Six Gridded Precipitation Products throughout Iran Using Ground Observations over the Last Two Decades (2000–2020)

Linear and Non-Linear Vegetation Trend Analysis throughout Iran Using Two Decades of MODIS NDVI Imagery

Application of Artificial Neural Networks for Mangrove Mapping Using Multi-Temporal and Multi-Source Remote Sensing Imagery

Spatial and Temporal Analysis of Surface Urban Heat Island and Thermal Comfort Using Landsat Satellite Images between 1989 and 2019: A Case Study in Tehran

Collaborators (7)

Cintia Bertacchi Uvo

Saeid Homayouni

Hossein Hashemi

Mahdi Farnaghi

Abdulhakim Abdi

Jonas Ardö

Lars Eklundh

Make your next move.