Ebrahim GhaderpourUniversità degli Studi di Roma La Sapienza · Dipartimento di Scienze della Terra
Ebrahim Ghaderpour
Doctor of Philosophy
Guest Editor: Sustainability
https://www.mdpi.com/journal/sustainability/special_issues/840T99IU37
About
105
Publications
56,528
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Introduction
Dr. Ebrahim Ghaderpour is currently the Guest Editors of Special Issues in
Sustainability (MDPI):
https://www.mdpi.com/journal/sustainability/special_issues/840T99IU37
and Discover Applied Sciences (Springer Nature):
https://link.springer.com/collections/hejdcjdahe
Dr. Ghaderpour obtained his first Ph.D. degree in Theoretical and Computational Science in 2013 and obtained his second Ph.D. degree in Remote Sensing in 2018.
Additional affiliations
June 2021 - May 2022
May 2020 - present
Earth & Space Inc
Position
- CEO
Description
- We provide many tech services to various organizations including but not limited to geoscience, finance, healthcare, retail, energy, transportation, and education. Our team consists of highly skilled and knowledgeable experts with the mathematical, physical, and computational background. Data analytics, machine learning, and deep learning are the main theoretical and computational skills of our team which can help for a better understanding of physical phenomena around us.
July 2016 - April 2022
Education
September 2013 - July 2018
September 2010 - November 2013
September 2007 - November 2009
Publications
Publications (105)
Snow cover has a key role in balancing the Earth’s surface temperature and can help
in filling rivers and reservoirs. In this study, 8-day MOD10A2 images are employed to monitor the spatiotemporal changes in snow cover in the Sefid-Rud basin and its eleven sub-basins during 2000–2019. The non-parametric Mann–Kendall (MK) test and its associated Sen...
Land surface temperature (LST) is an important factor in land monitoring studies, but due to the presence of clouds, dust and sensor issues, there are missing values. The aims of this research are to determine the optimal parameters for the reconstruction of Landsat-LST images, required in many applications, by the harmonic analysis of time series...
The control design of wheeled mobile robots is often accomplished based on the robot’s kinematics which imposes critical challenges in the motion tracking control of such systems. In the related literature, most works designed dynamic controllers based on the terms of voltage or torque; however, the velocity is often utilized in industrial and comm...
Human activity recognition is known as the backbone of the development of interactive systems, such as computer games. This process is usually performed by either vision-based or depth sensors. So far, various solutions have been developed for this purpose; however, all the challenges of this process have not been completely resolved. In this paper...
The availability of continuous spatiotemporal land surface temperature (LST) with high resolution is critical for many disciplines including hydrology, meteorology, ecology, and geology. Like other remote sensing data, satellite–based LST is also encountered with the cloud issue. In this research, over 5000 daytime and nighttime MODIS–LST images ar...
In this paper, a model free control method for a class of discrete time nonlinear systems is introduced. A type-3 fuzzy system estimates the unknown parameters required by the control system. The control system only uses the input and output data of the plant and therefore does not need to know its mathematical equations. On the other hand, the phe...
Ensuring the reliability of wind energy conversion systems (WECSs) is a crucial task for maximizing energy capture from the wind. A detailed model incorporating mechanical and electrical components is essential for accurately diagnosing system errors and assessing their impact on subsystems. Additionally, a fault detection and isolation system is n...
This study presents a novel methodology to enhancing the sustainability of urban infrastructure such as urban buildings, cultural heritage, bridges, roads, railways, etc. using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique from sentinel-1 C-band SAR datasets from 2018 to 2022 in Ravenna, Italy. Geological un...
Dear Colleagues,
We are pleased to invite you to contribute to a Special Issue titled "Advancing Sustainable Development through AI" in the Sustainability journal. As the world faces the pressing challenges of climate change, resource depletion, and social inequality, the role of AI in driving sustainable development has become increasingly signif...
The use of linear array pushbroom images presents a new challenge in photogrammetric applications when it comes to transforming object coordinates to image coordinates. To address this issue, the Best Scanline Search/Determination (BSS/BSD) field focuses on obtaining the Exterior Orientation Parameters (EOPs) of each individual scanline. Current so...
Detecting anomalies in videos poses a significant challenge due to the unbounded, infrequent, ambiguous, and irregular nature of abnormal events in real-world scenes. Recently, transformers have shown remarkable modeling capabilities for sequential data. As a result, we endeavor to leverage transformers for video anomaly detection. This paper prese...
Monitoring slow-moving landslides is a crucial task for socioeconomic risk prevention and/or mitigation. Persistent scatterer interferometric synthetic aperture radar (PS-InSAR) is an advanced remote sensing method for monitoring ground deformation. In this research, PS-InSAR time series derived from COSMO-SkyMed (descending orbit) and Sentinel-1 (...
An active disturbance rejection control (ADRC) has been developed for stabilizing electric vehicle (EV) systems without the need for model identification. The proximal policy optimization (PPO) algorithm, along with actor and critic neural networks, has been used to fine-tune the adjustable parameters of the ADRC controller to achieve optimal perfo...
This article aimed to map Cropping Intensity Patterns (CIPs) in the southwest region of Iran using Google Earth Engine and monthly composites of Sentinel-2 and Landsat-8/9 data. To detect CIPs with high inter- and intra-class variability of crops, a heterogeneous Stack ensemble of machine learning model was developed. The model incorporated the Min...
Climate change and human activities have increased the
frequency of wildfires and landslides. Burned areas, like
those on Ischia Island after the August 28, 2023, wildfire,
are highly susceptible to landslides due to historical ground
deformation and post-fire vegetation loss, exacerbated by
subsequent rainfall. This study aims to assess these risk...
Detecting slow-moving landslides is a crucial task for mitigating potential risk to human lives and infrastructures. In this research, Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) time series, provided by the European Ground Motion Service (EGMS), for the province of Frosinone in Italy are employed, and Sequential Turnin...
Chaos theory offers a new way to investigate variations in financial markets data that cannot be obtained with traditional methods. The primary approach for diagnosing chaos is the existence of positive small Lyapunov views. The positive Lyapunov index indicates the average instability and the system’s chaotic nature. The negativity indicates the a...
Persistent Scatterers Interferometric Synthetic Aperture Radar (PS-InSAR) is an advanced satellite remote sensing technique which allows an effective monitoring of ground movement. In this work, PS-InSAR time series as well as precipitation and temperature time series in a region in Catania, Italy are utilized during 2018-2022, and their possible i...
In this paper, the mathematical derivation of the underlying probability distribution function for the normalized least-squares wavelet spectrogram is presented. The impact of empirical and statistical weights on the estimation of the spectral peaks and their significance are demonstrated from the statistical point of view both theoretically and pr...
Frequency regulation in Multi-region Interconnected Power Systems (MIPS), incorporating wind turbine systems, energy storage units, and demand response, is a challenging control problem. The problem involves maintaining grid stability, integrating variable renewable energy sources, enhancing grid resilience, optimizing energy storage and demand res...
In the midst of a global health crisis, it is of utmost importance for healthcare technologies to possess the capability to regulate and monitor the physiological variables of patients remotely and automatically. The effective control of mean arterial pressure (MAP) in a closed-loop manner is particularly critical for individuals who are critically...
Land Surface Temperature (LST) is an important climate factor for understanding the relationship between the land surface and atmosphere. Furthermore, LST is linked to soil moisture and evapotranspiration, which can potentially alter the severity and regime of wildfires, landslide-triggering precipitation thresholds, and others. In this paper, the...
Wildfires present substantial threats to ecosystems and human settlements which increase the importance of monitoring for timely detection and assessment. This study was performed on the Campania provinces—Salerno, Avellino, Benevento, Caserta, and Napoli in Italy—employing a multi-sensor remote sensing approach to elevate wildfire analysis. The fi...
Studying water level fluctuation is crucial for water resource management and infrastructures. Groundwater level variations are due to recharge and/or discharge of water from aquifer because of anthropogenic activities or natural processes, e.g., rainfalls, irrigations, etc. Such variations may have a direct impact on ground deformation in the form...
Thermal monitoring of different regions is usually limited to meteorological data in ground stations. Meteorological networks are limited in arid and semi-arid areas, where monitoring climatic conditions is not possible. The aim of this study is to estimate the land surface temperature (LST) hourly for Yazd-Ardakan plain by modeling the diurnal tem...
Recent advances in remote sensing technology allow rigorous monitoring of ground deformation and environment both in time and space. Thanks to artificial intelligence techniques and data processing platforms, such as Google Earth Engine (GEE) and QGIS, there are a lot of opportunities for researchers to analyze measurements acquired from various so...
Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) is an advanced technique enabling effective ground deformation monitoring. In this study, PS-InSAR time series of Sentinel-1 ascending and descending orbits for period 2015–2022 are utilized for an industrial zone in Sacco River Valley, Central Italy. The Sequential Turning Po...
The risks associated with ground displacements, such as landslides, subsidence, sinkholes, and liquefaction, are on the rise due to climate change. To effectively address these issues, it is crucial to enhance existing methodologies for fundamental tasks like data collection, monitoring, modeling, and prediction. Although remote sensing and Earth o...
Assessment and management of the uncertainties in the context of natural hazards have recently received an increasing attention in the disciplinary literature. Several approaches have been proposed for single proofs of concept in the past few decades. In fact, in real-world applications, a problem is usually confronted with multiple types of uncert...
Ground deformation monitoring is a crucial task in geohazard management to ensure the safety of lives and infrastructure. Persistent scatterer interferometric synthetic aperture radar (PS-InSAR) is an advanced technique for measuring small displacements on the Earth's surface. Estimated PS-InSAR time series acquired by Sentinel-1 satellites provide...
The use of wheeled mobile robots (MRs) with symmetrical structure in engineering is rapidly increasing, with applications in various fields, such as industry, agriculture, forestry, healthcare, mining, rehabilitation, search and rescue, household tasks, remote locations, and entertainment. As MRs become more common, researchers are focusing on deve...
The accurate mapping of crop types is crucial for ensuring food security. Remote Sensing (RS) satellite data have emerged as a promising tool in this field, offering broad spatial coverage and high temporal frequency. However, there is still a growing need for accurate crop type classification methods using RS data due to the high intra-and inter-c...
We presented a fast and robust time series trend turning point detection model for detecting the dates and velocities of potential slow-moving landslides.
Time series analysis of Interferometric Synthetic Aperture Radar (InSAR) data is a crucial step for monitoring the displacement of the Earth's surface. The Persistent Scatterer InSAR (PS-InSAR) is a multi-temporal InSAR method that provides the displacement time series that can be used for studying ground deformation. From a hazard-assessment persp...
The paper studies the control of wheeled land mobile robots (MRs) using nonlinear equations and non-holonomic dynamic constraints. Due to the complex and unpredictable nature of the environments in which these robots operate, designing a controller for them is a challenging task. Uncertainties in the system further compound the problem. To tackle t...
Land surface temperature (LST) is a significant environmental factor in many studies. LST estimation methods require various parameters, such as emissivity, temperature, atmospheric transmittance and water vapor. Uncertainty in these parameters can cause error in LST estimation. The present study shows how the moderate resolution imaging spectrorad...
River flow monitoring is a critical task for land management, agriculture, fishery, industry, and others. Herein, a robust least-squares triple cross-wavelet analysis is proposed to investigate possible relationships between river flow, temperature, and precipitation in the time-frequency domain. The Athabasca River Basin (ARB) in Canada is selecte...
In dry regions, gardens and trees within the urban space are of considerable significance. These gardens are facing harsh weather conditions and environmental stresses; on the other hand, due to the high value of land in urban areas, they are constantly subject to destruction and land use change. Therefore, the identification and monitoring of gard...
Non-holonomic wheeled robots (NWR) comprise a type of robotic system; they use wheels for movement and offer several advantages over other types. They are efficient, highly, and maneuverable , making them ideal for factory automation, logistics, transportation, and healthcare. The control of this type of robot is complicated, due to the complexity...
In Italy, most of the destructive landslides are triggered by rainfall, particularly in central Italy. Therefore, effective monitoring of rainfall is crucial in hazard management and ecosystem assessment. Global precipitation measurement (GPM) is the next-generation satellite mission, which provides the precipitation measurements worldwide. In this...
Internet of Things (IoT) and mobile edge computing (MEC) architectures are common in real-time application scenarios for improving the reliability of service responses. Energy conservation (EC) and energy harvesting (EH) are significant concerns in such architectures due to the self-sustainable devices and resource-constraint edge nodes. The densit...
Land cover and climate monitoring is a crucial task in agriculture, forestry, hazard management, and ecosystems assessment. In this paper, normalized difference vegetation index (NDVI), land surface temperature (LST), and land cover products by the moderate resolution imaging spectroradiometer (MODIS) as well as precipitation were utilized to monit...
This document illustrates the monthly average and gradient geospatial maps of MODIS NDVI at 250 m, MODIS LST at ∼5.5 km, and GPM precipitation at ∼11 km resolution for Italy during 2000-2021. This document also illustrates the LST (daytime, diurnal, nighttime) time series for all months and ecoregions with their ALLSSA trends. Then it illustrates t...
Understanding the land surface temperature (LST) trends is crucial for policymakers and stakeholders to develop adaptation and mitigation strategies suitable for a sustainable environment coping in the face of climate change. This article presents a systematic review of the studies related to delineating spaceborne sensor based LST trends, includin...
We are pleased to announce that our Special Issue in #Land (MDPI) entitled "Ground Deformation Monitoring via Remote Sensing Time Series Data" is now open for submission: https://www.mdpi.com/journal/land/special_issues/2A61OI7856
Monitoring ground deformation is a crucial task in geohazard management to ensure the safety of lives and infrastructu...
GIS-based kinematic stability analysis in rock slopes is a rare practice in geological engineering despite its immense potential to delineate unstable zones in a mountainous region. In this article, we have used a GIS-based modified technique to assess the efficiency of kinematic analysis in predicting shallow landslides in the rock slopes of the H...
Electroencephalogram (EEG) is often corrupted with artifacts originating from sources like the eyes and muscles. Hybrid artifact removal methods often require human intervention for the adjustment of different parameters. We propose a robust method that can automatically detect and remove eye-blink and muscular artifacts from EEG using k-nearest ne...
Emotion plays a vital role in understanding the affective state of mind of an individual. In recent years, emotion classification using electroencephalogram (EEG) has emerged as a key element of affective computing. Many researchers have prepared datasets, such as DEAP and SEED, containing EEG signals captured by the elicitation of emotion using au...
Spatiotemporal changes in land surface temperature (LST) over South Asia were estimated using MODIS (moderate resolution imaging spectroradiometer) data from 2000 to 2021. We calculated the monthly and annual LST trends and magnitudes by applying the Mann–Kendall test and Sen's slope estimator at both ecoregion and pixel level. More ecoregions expe...
For the first time, a novel concept of merging computational intelligence (the type-2 fuzzy system) and control theory (optimal control) for regulator and reference tracking in doubly fed induction generators (DFIGs) is proposed in this study. The goal of the control system is the reference tracking of torque and stator reactive power. In this case...
Supplementary Information for the article entitled: "Long Term Trend Analysis of River Flow and Climate in Northern Canada" https://doi.org/10.3390/hydrology9110197
Changes in water resources within basins can significantly impact ecosystems, agriculture, and biodiversity, among others. Basins in northern Canada have a cold climate, and the recent changes in climate can have a profound impact on water resources in these basins. Therefore, it is crucial to study long term trends in water flow as well as their i...
Monitoring spatiotemporal changes in climate and vegetation coverage are crucial for various purposes, including water, hazard, and agricultural management. Climate has an impact on vegetation, however, studying their relationship is challenging. We implemented the Least-Squares Wavelet (LSWAVE) software for investigating trend, coherency, and time...
This file is the Supplementary Materials associated with article entitled: "Wavelet-based spatiotemporal analyses of climate and vegetation for the Athabasca river basin in Canada" DOI: 10.1016/j.jag.2022.103044
The linear parameter-varying (LPV) models have broad applications in advanced mathematics and modern control systems. This paper introduces a new method for controlling the LPV systems. This method includes the gain-scheduled state-feedback technique and a fuzzy system to calculate the state-feedback gain. The main goal of the control system is to...
Electroencephalogram (EEG) artifacts such as eyeblink, eye movement, and muscle movements widely contaminate the EEG signals. Those unwanted artifacts corrupt the information contained in the EEG signals and degrade the performance of qualitative analysis of clinical applications and as well as EEG-based brain-computer interfaces (BCIs). The applic...