Mahdi Hasanlou

Verified

Mahdi verified their affiliation via an institutional email.

Learn more

Verified

Mahdi verified their affiliation via an institutional email.

Learn more

• Doctor of Philosophy
• Professor (Associate) at University of Tehran

Natural and man-made disasters take place around the world and cause significant financial and human losses. An accurate and fast post-disaster building damage mapping could play a crucial role in rapid rescue planning and operations. Remote sensing satellite images are the main source of building damage map generation. Usually, both pre-disaster a...

High-resolution remote sensing images capture intricate local structural features across a range of frequencies, causing significant challenges in producing reliable remote sensing and photogrammetry products, particularly in the fusion of multispectral images with panchromatic bands. Many existing methods suffer from spectral and spatial distortio...

The escalating concerns surrounding urban air pollution's impact on both the environment and human health have prompted increased attention from researchers, policymakers, and citizens alike. As such, this study addresses growing concerns about urban air pollution's impact on the environment and human health, emphasizing the need for early, high-re...

Natural disasters commonly occur in all regions around the world and cause huge financial and human losses. One of the main effects of earthquakes and floods is the destruction of buildings. Photogrammetric and remote sensing (RS) data track changes and detect damages in these events. Considering the evolution in deep learning (DL) techniques, the...

Soil organic carbon (SOC) is a crucial factor for soil fertility, directly impacting agricultural yields and ensuring food security. In recent years, remote sensing (RS) technology has been highly recommended as an efficient tool for producing SOC maps. The PRISMA hyperspectral satellite was used in this research to predict the SOC map in Fars prov...

Due to the complexity of the areas and the diversity of the objects, traditional Burned Area Mapping (BAM) methods cannot provide promising results. Moreover, these methods focus on additional processing to improve their results, which is time-consuming and complex. Therefore, an advanced framework is needed to achieve accurate results in burned ar...

3D building change detection (CD) methods detect more accurate multiple change maps than 2D ones. Recent technologies such as unmanned aerial vehicle (UAV) systems and dense image matching have made it much easier to obtain 3D data nowadays. Developing a solution which produces an accurate map of multiple building changes, including Unclassified,...

Timely and accurate building damage mapping is essential for supporting disaster response activities. While RS satellite imagery can provide the basis for building damage map generation, detection of building damages by traditional methods is generally challenging. The traditional building damage mapping approaches focus on damage mapping based on...

Delineation of upwelled zones is critical for the economy and physical processes of the coastal areas. The upwelling process is accompanied by vertical water motion, resulting in a surface with lower water temperature and increased chlorophyll-a contents (Chl-a). Since such patterns can be monitored using remote sensing technologies, this research...

Agricultural land management relies heavily on accurate and timely estimation of uncultivated land. Geographical heterogeneity limits the ability of the model to map crops at large scales. This is because the spectral profile of a crop varies spatially. In addition, the generation of robust deep features from remotely sensed SAR data sets is limite...

An accurate and fast assessment of damaged buildings following a disaster is critical for planning rescue and reconstruction efforts. The damage assessment by traditional methods is time-consuming and with limited performance. In this paper, we propose an end-to-end deep-learning network named Building Damage Detection Network-plus (BDD-Net+). The...

Detailed wetland inventories and information about the spatial arrangement and the extent of wetland types across the Earth’s surface are crucially important for resource assessment and sustainable management. In addition, it is crucial to update these inventories due to the highly dynamic characteristics of the wetlands. Remote sensing technologie...

Change detection in urban areas can be helpful for urban resource management and smart city planning. The effects of human activities on the environment and ground have gained momentum over the past decades, causing remote sensing data sources analysis (such as satellite images) to become an option for swift change detection in the environment and...

Crop information and quality are not only fundamental for experts using spatial decision support systems but also have many applications in irrigation management, economic analysis for import or export, food safety, and achieving sustainable agriculture. Remote sensing is a cheap and fast way of reaching this goal. Full polarimetric SAR unlike opti...

In recent decades, global warming and sea level rise, population growth, and intensification of human activities, have directly affected the coasts and as such, their monitoring for the accretion and retreat are among the issues that are considered by the coastal countries. This study, compares two supervised classification algorithms for classifyi...

Roads are one of the essential transportation infrastructures that get damaged over time and affect economic development and social activities. Therefore, accurate and rapid recognition of road damage such as cracks is necessary to prevent further damage and repair it in time. The traditional methods for recognizing cracks are using survey vehicles...

Soil moisture content plays a pivotal role in biomass development of vegetation coverage at various growth stages. Moisture content of the soil is considered as a crucial parameter for agricultural studies which directly leads to higher fertility rate. Remote sensing techniques, specifically Synthetic Aperture Radar (SAR) sensors, provides suitable...

Timely and accurate mapping of crops is crucial for agriculture management, policy-making, and food security. Due to the differences in the product calendars of various crops, it is possible to classify them by investigating the remote sensing Vegetation Indices (VIs) during crop growth season. This study developed a VI-based mapping approach to sp...

This paper presents a deep learning approach for swift detection of COVID-19 in chest CT scan images in order to facilitate treatment planning and reduce the burden on hospital resources and staff workload. The detection procedure starts with a pre-processing step, which involves noise removal and resizing, and the pre-processed images are fed to V...

Floods are one of the most destructive natural disasters, causing financial and human losses every year. As a result, reliable Flood Susceptibility Mapping (FSM) is required for effective flood management and reducing its harmful effects. In this study, a new machine learning model based on the Cascade Forest Model (CFM) was developed for FSM. Sate...

Due to the natural conditions and inappropriate management responses, large part of plains and forests in Iran have been burned in recent years. Given the increasing availability of open-access satellite images and open-source software packages, we developed a fast and cost-effective remote sensing methodology for characterizing burned areas for th...

Rice is one of the most essential and strategic food sources globally. Accordingly, policymakers and planners often consider a special place in the agricultural economy and economic development for this essential commodity. Typically, a sample survey is carried out through field observations and farmers’ consultations to estimate annual rice yield....

Estimating ocean surface winds from space is an essential field in remote sensing research, with applications such as hurricane forecasting, wind energy mapping, estimation of oil spill drift patterns, validation and development of numerical weather forecasting models (NWP), and several other applications. In this study, using meteorological buoys...

Accurate and timely mapping of wildfire burned areas is crucial for post-fire management, planning, and next subsequent actions. The monitoring and mapping of the burned area by traditional and common methods are time-consuming and challenging while is vital to propose an advanced burned area detection framework for achieving reliable results. To t...

Detecting changes in urban areas have always been an important element of urban planning and resource management. With the widening impacts of human activities on the ground terrain and landscapes, in recent decades the analysis of remote sensing data, including satellite images, has become a method of choice for rapid tracking of changes in the gr...

Wildfires are considered as one of the most disturbing factors in forest areas and high-density vegetation regions. The mapping of wildfires is particularly important for fire prediction and burned biomass estimation. Therefore, accurate and timely mapping of burned areas is of great importance and has a key role in disaster management. Estimation...

A shoreline is defined as the line of contact between the sea and land. Shoreline shifting as one of the most critical environmental challenges directly influences the inhabitant life in the coastal cities. Due to global warming, the sea level has risen over the past centuries and threatens coastal infrastructures. Therefore, coastal management for...

The coastline is considered as the boundary between water and land. coasts are one of the most important environmental effects that directly affect human life. Rising sea levels due to global warming have made coastal cities among the areas under threat. Therefore, management and planning to prevent coastal erosion is one of the important issues th...

Due to anthropogenic and natural activities, the land surface continuously changes over time. The accurate and timely detection of changes is greatly important for environmental monitoring , resource management and planning activities. In this study, a novel deep learning-based change detection algorithm is proposed for bi-temporal polarimetric syn...

Wildfires are one of the most destructive natural disasters that can affect our environment, with significant effects also on wildlife. Recently, climate change and human activities have resulted in higher frequencies of wildfires throughout the world. Timely and accurate detection of the burned areas can help to make decisions for their management...

Oil Spill (OS), as one of the main pollutions in the ocean, is a serious threat to the marine environment. Thus, timely and accurate OS Detection (OSD) is necessary for ocean management. In this regard, Remote Sensing (RS) plays a key role due to multiple advantages over large and remote ocean environments. In this study, a new OSD framework based...

The earth is constantly being changed by natural events and human activities that constantly threaten our environment. Therefore, accurate and timely monitoring of changes at the surface of the earth is of great importance for properly facing their consequences. This research presents a new hyperspectral change detection (HCD) framework based on a...

Soil moisture is an important parameter that directly impacts crop productivity. Microwave signals are highly sensitive to soil dielectric constant and so they are used to derive soil moisture. The potential of entropy and alpha (H / α) decomposition for moisture estimations at 0- to 5-cm soil depth was assessed. The H / α parameters were extracted...

Earth is constantly changing due to some natural events and human activities that threaten our environment. Thus, accurate and timely monitoring of these changes is of great importance for properly coping with their consequences. In this regard, this research presented a new framework for hyperspectral change detection (HCD) based on dynamic time w...

With uninterrupted space-based data collection since 1972, Landsat plays a key role in systematic monitoring of the Earth’s surface, enabled by an extensive and free, radiometrically consistent, global archive of imagery. Governments and international organizations rely on Landsat time series for monitoring and deriving a systematic understanding o...

Soil salinity is regarded as a crucial environmental indicator and has been identified as an essential factor contributing to land degradation, particularly in regions characterized by arid and semi-arid climates. The presence of this substantial environmental risk often destroys agricultural lands, a reduction in agricultural productivity, the dep...

Soil salinity, a significant environmental indicator, is considered one of the leading causes of land degradation, especially in arid and semi-arid regions. In many cases, this major threat leads to loss of arable land, reduces crop productivity, groundwater resources loss, increases economic costs for soil management, and ultimately increases the...

Timely and accurate change detection (CD) of Earth’s surface features is important for understanding interactions between human and natural phenomena. Remote sensing (RS) as the most important information resource plays a role key in monitoring and assessment of the environment. One of most applications of hyperspectral imagery is CD. The hyperspec...

Earth, as humans' habitat, is constantly affected by natural events, such as floods, earthquakes , thunder, and drought among which earthquakes are considered one of the deadliest and most catastrophic natural disasters. The Iran-Iraq earthquake occurred in Kermanshah Province, Iran in November 2017. It was a 7.4-magnitude seismic event that caused...

Estimating volumetric soil moisture (M v) and surface roughness (S) are the key parameters for numerous agricultural and hydrological applications. Although these two parameters can be effectively retrieved from synthetic aperture radar (SAR) data, the presence of vegetation can negatively affect the results. A method was proposed to accurately est...

Soil salinity is a widespread natural hazard that negatively influences soil fertility and crop productivity. Using the potential of earth observation data and remote sensing technologies provides an opportunity to address this environmental issue and makes it possible to identify salt-affected regions accurately. While most of the utilized methods...

In recent years, land surface temperature (LST) has become critical in environmental studies and Earth science. Remote sensing technology enables spatiotemporal monitoring of this parameter on large scales. This parameter can be estimated by satellite images with at least one thermal band. Sentinel-3 SLSTR data provide LST products with a spatial r...

Polarimetric decomposition extracts scattering features that are indicative of the physical characteristics of the target. In this study, three polarimetric decomposition methods were tested for soil moisture estimation over agricultural fields using machine learning algorithms. Features extracted from model-based Freeman–Durden, Eigenvalue and Eig...

The rich spectral data found in the hyperspectral data cube make them useful in real-world applications, such as target detection. Target pixels detection among an unknown background such as ground objects from hyperspectral data cube is of great interest for remote sensing community. The commonly used hyperspectral target detection methods often o...

Accurate information about the location, extent, and type of Land Cover (LC) is essential for various applications. The only recent available country-wide LC map of Iran was generated in 2016 by the Iranian Space Agency (ISA) using Moderate Resolution Imaging Spectroradiometer (MODIS) images with a considerably low accuracy. Therefore, the producti...

Timely and accurate change detection of Earth’s surface features is extremely important for understanding relationships and interactions between human and natural phenomena to promote better decision making. The bi-temporal hyperspectral imagery has a high potential for the detection of surface changes. However, the extraction of changes from bi-te...

The diversity of change detection (CD) methods and the limitations in generalizing these techniques using different types of remote sensing datasets over various study areas have been a challenge for CD applications. Additionally, most CD methods have been implemented in two intensive and time-consuming steps: (a) predicting change areas, and (b) d...

Sea Surface Salinity (SSS) is a pre-eminent parameter in oceanology causing extreme climate and weather events such as floods and droughts. Therefore, knowledge discovery of SSS is increasingly becoming a fundamental problem in recent years. However, not only the inadequacy of in-situ SSS data in large ocean basins are hampering conduction of detai...

Over the last decade, developments in hyperspectral sensors have caused an increase in the use of hyperspectral images (HSIs) due to fine spectral resolution, which has lead to the precise extraction and identification of the materials of the observed scene. Change detection (CD) is one of the most fundamental applications of remote sensing, which...

Policymaking and planning agricultural improvement require accurate and timely information and statistics. In Iran, collecting and acquiring agricultural statistics is often done in the traditional methods. Related studies have proved that these methods mostly contain some mistakes. Multi-temporal acquisition strategies of remotely sensed data prov...

The combined use of PolSAR and hyperspectral data can improve the classification accuracy. This paper proposes a new classification approach for combining use of PolSAR and hyperspectral image data sets. At the first step, polarization signature is generated from coherency matrix of PolSAR image data. In the second step, in order to improve spatial...

In recent years, forests in the north of the country have been attacked due to human interference. Increasing population and development of residential and agricultural areas have led to deforestation. Change detection is one of the most common methods for evaluating natural resources. The aim of this study is to monitor changes in forests of Goles...

Over the last few decades in coastal areas, the occurrence of Harmful Algal Blooms (HAB) has increased. The phenomenon is harmful to the health of coastal residents as well as marine organisms and can cause damage to the economy of the region. In this article, considering the need of a method for detecting red tide phenomenon using high spatial res...

Air pollution is one of the main problems in human and environmental health in big cities and in developing countries. The precise monitoring and predicting of air quality and the assessing of the amount of contaminants will reduce the risks to human and the environment health. The particulate materials in the atmosphere are divided into two PM2.5...

Time-series interferometric synthetic aperture radar (InSAR) has developed as an influential method to measure various surface deformations. One of the generations of time-series InSAR methodologies is Persistent Scatterer Interferometry (PSI) that focuses on targets with a high correlation over time. In this study, we have measured the surface def...

In recent years, the applications of interior and exterior model of buildings have been increased in the field of surveying and mapping. This paper presents a new method for extracting a two-dimensional (2D) floor plan of a building from Simultaneous localization and mapping (SLAM)-based point clouds. In the proposed algorithm, after preprocessing,...

Lakes play a pivotal role in the development of cities and have major impacts on the ecosystem balancing of the area. Remote sensing techniques and advanced modeling methods make it possible to monitor natural phenomena, such as lakes’ water level. The ecosystem of Urmia Lake is one of the most momentous ecosystems in Iran, which is almost close-en...

In recent years, the applications of interior and exterior model of buildings have been increased in the field of surveying and mapping. This paper presents a new method for extracting a two-dimensional (2D) floor plan of a building from Simultaneous localization and mapping (SLAM)-based point clouds. In the proposed algorithm, after preprocessing,...

Endmember extraction is a process to identify the hidden pure source signals from the mixture. Endmember finding has become increasingly important in hyperspectral data exploitation because endmembers can be used to specify unknown particular spectral classes. This paper evaluates the change detection problem in bi-temporal hyperspectral remote sen...

Coral reef communities face unprecedented pressures at local, regional and global scales as a consequence of climate change and anthropogenic disturbance. Remote sensing, from satellites or aircraft, is possibly the only means to measure the effects of such stresses at appropriately large spatial scales. Coral reefs are indicators of environmental,...

Change detection, which is a process of identifying changes occurred in a geographical area over the time, plays a key role in many applications including assessing natural disasters, monitoring crops, and managing water resources. In the past decades, many change detection techniques have been proposed. Hence, evaluating and analyzing of probabili...

The freely available global and near-global digital elevation models (DEMs) have shown great potential for various remote sensing applications. The Shuttle Radar Topography Mission (SRTM) data sets provide the near-global DEM of the Earth’s surface obtained using the interferometry synthetic aperture radar (InSAR). Although free accessibility and g...

The Zagros Mountains forests extend across 11 provinces in Iran and constitute approximately 40.0% of the country’s woodlands. These forests have important soil conservation and water regulation functions. Over the last decade, these forests have been declining in oak populations in many places, triggered by factors such as drought, pathogens like...

Abstract: Azar Oil Field is located in the east of the city of Mehran, Ilam. The tank of this oil field is shared by Iraq’s oil field whose name is Badra where oil extraction started in 2014, and they have maximized its oil exploration since 2017. Iran started oil exploration in 2017. In this study, we have estimated land surface deformation in Aza...

Urmia Lake is one of the most momentous ecosystems in Iran, which is exposed to complete drying. Thus, monitoring the variations of its water level is crucial to avoid this disaster. There are many parameters involved in this crisis, one of them is precipitation, which plays an important role in this regard, and besides, precipitation has several f...

The earth is continually being influenced by some actions such as flood, tornado and human artificial activities. This process causes the changes in land cover type. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes. Today’s remote sensing plays key role in geology and environmental monitoring by its...

The present study introduces distance based change detection (CD) algorithms in polarimetric synthetic aperture radar (PolSAR) data. PolSAR images, due to interactions between electromagnetic waves and target and because of the high spatial resolution, can be used to study changes in the Earth’s surface. The purpose of this paper is to use features...

One of the most important applications of remote sensing is change detection (CD). The accurate detection of changes is of great significance for the optimal management of available resources. This article presents an unsupervised ‘multiple-change detection’ method using multi-temporal hyperspectral imaging based on the integration of an unmixing t...

Polarization orientation angle (POA) shifts produced by topography variations lead to rotating polarization around the radar beam direction. In addition to slope topography, depolarization induced by volume scattering and orientation of dihedral target impact POA which is used for deorientation and, in some cases, topography measurement. Unlike deo...

Soil salinity is a widespread environmental hazard and the main causes of land degradation and desertification, especially in arid and semi-arid regions. The first step in finding such a solution is providing accurate information about the severity and extent of the salinity spread in affected areas; this can be done by mapping the electrical condu...

Soil salinity caused by climate change associated with rising sea level is considered as one of the most severe natural hazards that has a negative effect on agricultural activities in the coastal areas in most tropical climates. This issue has become more severe and increasingly occurred in the Mekong River Delta of Vietnam. The main objective of...

The SSM/I is a passive microwave sensor which has the capability of measuring the geophysical parameters which are used for research in the field of climate and hydrology in the world. In this paper, the SSM/I data along with ground measurements of snow depth at meteorological stations from the National Center of Environmental Information has been...

Seafloor topography certainly has an impact on ocean circulation in different ways. Due to this assumption, the sea surface currents calculated by optical flow (Horn–Schunck) and geostrophic currents methods are analyzed to observe this impact. Pair of sea surface temperature imageries, calculated sea surface height and sea level anomaly are showed...

Soil salinity is a major environmental threat, which has a negative impact on soil productivity and agricultural fields. One of the most promising methods for monitoring affected areas, which has special importance in land management studies, is through remote sensing technologies. While the potential of optical imagery in detecting saline soils is...

The conventional classifying methods use polarimetric information in the restrict number of polarization basis and frequency for polarimetric data classification. At the same time, different polarization and frequencies are sensitive to different surface scales and scattering mechanisms respectively. The combined use of different frequencies on the...

In this study, we focus the investigation of land subsidence in Azar oil field by small-baseline SAR interferometry analysis with Sentinel-1 satellite. Azar oil field is one of Iranian the oil fields. This oil field is located in the east of Mehran in Ilam. After extracting a large number of oil wells, heavy rainfall occurred and widespread and ext...

Matching in high-resolution synthetic aperture radar (SAR) images while being more complicated compared to optical images, is especially important due to its numerous applications. The main aim of current research is to determine improvement of SAR image matching process by deploying texture analysis using gray level's co-occurrence matrix (GLCM)....

Increasing the population and urban development is one of the most important human actions that cause changes on the face of the earth, especially in the developing countries, which is more. This process can cause devastating effects such as social, economic and biophysical. The harmful effects include; loss of agriculture lands, pasture and forest...

Wetlands are one of the important types of ecosystems that play a fundamental role in the environment and provide significant benefits due to the resources that they contain. Therefore, it is necessary to monitor the changes in these ecosystems. The alterations in Earth’s ecosystems caused by the natural activities, such as drought, as well as huma...

Introduction Urmia Lake is located in the North West of Iran and its area between 4750 to 6100 square kilometers at an altitude of 1250 meters above sea level. This lake is a permanent lake in Iran. In fact, Urmia Lake is one of the lowest parts of the catchment area North West of Iran. The total surface area of Urmia Lake is 51,876 km square, whic...

The Earth’s surface is constantly changing due to variations originating from the increasing human population. In the last decade, numerous methods were presented in the literature for change detection using multispectral image data. Owing to the increasing availability of hyperspectral images, these methods are now being applied to hyperspectral i...

The changes in the earth's surface significantly increase the natural disasters, resulting in severe damage to man-made objects, such as roads, buildings, bridges, and so on. Radar techniques have advantages such as lack of sensitivity to weather conditions, night and day, and cloud cover conditions which can be used to identify, alert, and mitigat...

Change detection (CD) is one of the most important uses of remote sensing, and it plays a key role in many applications. Satellite hyperspectral imagery has a high spectral resolution but low spatial resolution, which results in images with mixed pixels. To improve spatial resolution in hyperspectral images, multiresolution fusion techniques must b...

Earth as the human habit, has been affected by natural events, such as tornado and flood of thunder and drought. In addition, some human activities such as urban development and deforestation have made the changes in many ways. However, these changes are unintentional they constantly threaten out the environment. So, predicting these changes are re...

Monitoring and surveillance changes around the world need powerful methods, so detection, visualization, and assessment of significant changes are essential for planning and management. Incorporating polarimetric SAR images due to interactions between electromagnetic waves and target and because of the high spatial resolution almost one meter can b...

The recent development of satellite sea surface salinity (SSS) observations has enabled us to analyse SSS variations with high spatiotemporal resolution. In this regards, The Level3-version4 data observed by Aquarius are used to examine the variability of SSS in Gulf of Mexico for the 2012-2014 time periods. The highest SSS value occurred in April...

Soil salinity is one of the main causes of desertification and land degradation which has negative impacts on soil fertility and crop productivity. Monitoring salt affected areas and assessing land cover changes, which caused by salinization, can be an effective approach to rehabilitate saline soils and prevent further salinization of agricultural...

Numerical simulation results of wind wave in the Caspian Sea by using wind forcing data are presented. The numerical modeling which is applied in this study is based on numerical spectral wave model which is based on Navier-Stokes equations. It solves these equations through each of mesh elements. Moreover, in this model high-resolution unstructure...

Soil moisture is an important parameter that affects several environmental processes. This parameter has many important functions in numerous sciences including agriculture, hydrology, aerology, flood prediction, and drought occurrence. However, field procedures for moisture calculations are not feasible in a vast agricultural region territory. Thi...

Study of hydrological parameters of lakes and examine the variation of water level to operate management on water resources are important. The purpose of this study is to investigate and model the Urmia Lake water level changes due to changes in climatically and hydrological indicators that affects in the process of level variation and area of this...