Ebrahim Ghaderpour

Ebrahim Ghaderpour
Sapienza University of Rome | la sapienza · Department of Earth Sciences

Doctor of Philosophy
Guest Editor: Sensors https://www.mdpi.com/journal/sensors/special_issues/A_TSA

About

44
Publications
31,993
Reads
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416
Citations
Introduction
Dr. Ebrahim Ghaderpour is currently the Guest Editors of two Special Issues: Sensors: https://www.mdpi.com/journal/sensors/special_issues/A_TSA Sustainability: https://www.mdpi.com/journal/sustainability/special_issues/sustai_artificalintelligence 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
The University of Calgary
Position
  • PostDoc Associate
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
The University of Calgary
Position
  • Instructor
Description
  • Taught 12 undergraduate courses
Education
September 2013 - July 2018
York University
Field of study
  • Earth and Space Science and Engineering (Geomatics)
September 2010 - November 2013
University of Lethbridge
Field of study
  • Theoretical and Computational Science
September 2007 - November 2009
Isfahan University of Technology
Field of study
  • Pure Mathematics

Publications

Publications (44)
Article
Surface water/ice dynamic monitoring is crucial for many purposes, such as water resource management, agriculture, climate change, drought, and flood forecasting. New advances in remote sensing satellite data have made it possible to monitor the surface water/ice dynamics both spatially and temporally. However, there are many challenges when using...
Article
Full-text available
Water resources are vital to the survival of living organisms and contribute substantially to the development of various sectors. Climatic diversity, topographic conditions, and uneven distribution of surface water flows have made reservoirs one of the primary water supply resources in Iran. This study used Landsat 5, 7, and 8 data in Google Earth...
Article
Full-text available
Electroencephalogram (EEG) signals may get easily contaminated by muscle artifacts, which may lead to wrong interpretation in the brain–computer interface (BCI) system as well as in various medical diagnoses. The main objective of this paper is to remove muscle artifacts without distorting the information contained in the EEG. A novel multi-stage E...
Article
Full-text available
The risk of forest and pasture fires is one of the research topics of interest around the world. Applying precise strategies to prevent potential effects and minimize the occurrence of such incidents requires modeling. This research was conducted in the city of Sanandaj, which is located in the west of the province of Kurdistan and the west of Iran...
Article
Full-text available
Emotion recognition using EEG has been widely studied to address the challenges associ- ated with affective computing. Using manual feature extraction methods on EEG signals results in sub-optimal performance by the learning models. With the advancements in deep learning as a tool for automated feature engineering, in this work, a hybrid of manual...
Article
Full-text available
Early detection of Basal Stem Rot (BSR) disease in oil palms is an important plantation management activity in Southeast Asia. Practical approaches for the best strategic approach toward the treatment of this disease that originated from Ganoderma Boninense require information about the status of infection. In spite of the availability of conventio...
Article
Full-text available
In many studies regarding the field of malaria, environmental factors have been acquired in single-time, multi-time or a short-time series using remote sensing and meteorological data. Selecting the best periods of the year to monitor the habitats of Anopheles larvae can be effective in better and faster control of malaria outbreaks. In this articl...
Article
Full-text available
Efficiently implementing remote sensing image classification with high spatial resolution imagery can provide significant value in land use and land cover (LULC) classification. The new advances in remote sensing and deep learning technologies have facilitated the extraction of spatiotemporal information for LULC classification. Moreover, diverse d...
Article
Full-text available
Change detection within unequally spaced and non-stationary time series is crucial in various applications, such as environmental monitoring and satellite navigation. The Jumps Upon Spectrum and Trend (JUST) is developed to detect potential jumps within the trend component of time series segments. JUST can simultaneously estimate the trend and seas...
Article
Full-text available
With the advent of the digital computer, time series analysis has gained wide attention and is being applied to many fields of science. This paper reviews many traditional and recent techniques for time series analysis and change detection, including spectral and wavelet analyses with their advantages and weaknesses. First, Fourier and least-square...
Article
Full-text available
This document is the Supplementary Materials for the article entitled: Application of the Least-Squares Wavelet software in hydrology: Athabasca River Basin Published in Journal of Hydrology: Regional Studies https://doi.org/10.1016/j.ejrh.2021.100847 It describes the LSWAVE software mathematically and demonstrates some of its advantages over th...
Article
Full-text available
Study region: Athabasca River Basin (ARB) in Alberta, Canada. Study focus: Understanding the historical streamflow variability within basins is crucial to reduce the effect of utmost events, such as drought and floods on agriculture, fishery, and other human activities. The Least-Squares Wavelet software (LSWAVE) is applied to estimate the trend a...
Article
Full-text available
Jump or break detection within a non-stationary time series is a crucial and challenging problem in a broad range of applications including environmental monitoring. Remotely-sensed time series are not only non-stationary and unequally spaced (irregularly sampled) but also noisy due to atmospheric effects, such as clouds, haze, and smoke. To addres...
Article
Full-text available
Extensive least-squares wavelet and cross-wavelet analyses are performed on the Very Long Baseline Interferometry (VLBI) baseline length and temperature time series for a network of four VLBI antennas located in different continents. These analyses do not rely on any pre-processing of the measurements including interpolations or gap-filling, and th...
Article
Full-text available
An extensive spectral analysis is performed on the light curve of dwarf nova V455 Andromedae (V455 And = HS 2331+3905) using the Least-Squares WAVElet software (LSWAVE) to highlight its robustness for analyzing astronomical time series. The V455 And properties are briefly reviewed, and the recent results are compared with the results obtained herei...
Article
Full-text available
Near-real-time disturbance detection within the remotely-sensed time series has become a crucial task in many environmental applications that can help policymakers and responsible authorities to make rapid decisions and proper actions. Although there are several techniques for the near-real-time monitoring of time series, their reliability in regio...
Article
Full-text available
Change detection within non-stationary and unequally spaced remote sensing time series has become a key methodology for a broad range of environmental applications. A new method of analysing vegetation variation over lands is proposed. Four regions in northern Tunisia with various characteristics are selected, and a non-stationary and unequally spa...
Conference Paper
Full-text available
Change detection within non-stationary and unequally spaced remote sensing time-series has become a key methodology for a broad range of environmental applications. A new method of analyzing vegetation variation over lands is proposed. Four study areas in the north of Tunisia with various characteristics are selected, and a non-stationary and unequ...
Article
Full-text available
The antileakage least-squares spectral analysis is a new method of regularizing irregularly spaced data series. This method mitigates the spectral leakages in the least-squares spectrum caused by non-orthogonality of the sinusoidal basis functions on irregularly spaced series, and it is robust when data series are wide-sense stationary. An appropri...
Patent
A refined average method is proposed to delineate unsupervised management zones in Precision Agriculture using multi-year satellite imagery. Furthermore, an elevation derived product is used to improve the zone maps.
Article
Full-text available
The least-squares wavelet analysis (LSWA) is a robust method of analyzing any type of time/data series without the need for editing and preprocessing of the original series. The LSWA can rigorously analyze any non-stationary and equally/unequally spaced series with an associated covariance matrix that may have trends and/or datum shifts. The least-...
Thesis
Full-text available
The Least-Squares Spectral Analysis (LSSA) is a robust method of analyzing unequally spaced and non-stationary data/time series. Although this method takes into account the correlation among the sinusoidal basis functions of irregularly spaced series, its spectrum still shows spectral leakage: power/energy leaks from one spectral peak into another....
Article
Full-text available
The least-squares wavelet analysis, an alternative to the classical wavelet analysis, was introduced in order to analyze unequally spaced and non-stationary time series exhibiting components with variable amplitude and frequency over time. There are a few methods such as cross wavelet transform and wavelet coherence that can analyze two time series...
Poster
Full-text available
We propose a new method of analyzing a time series as well a method to compute the coherency between two (or more) time series. These methods, namely, the least-squares wavelet analysis (LSWA) and the least-squares cross wavelet analysis (LSCWA), respectively, can analyze any time series that exhibit non-stationarity, while they may be unequally sp...
Article
Full-text available
Spatial transformation of irregularly sampled data series to regularly sampled data series is a challenging problem in many areas such as seismology. The discrete Fourier analysis is limited to regularly sampled data series. On the other hand, the least-squares spectral analysis (LSSA) can analyze irregularly sampled data series. Although the LSSA...
Article
Full-text available
Craigen introduced and studied signed group Hadamard matrices extensively and eventually provided an asymptotic existence result for Hadamard matrices. Following his lead, Ghaderpour introduced signed group orthogonal designs and showed an asymptotic existence result for orthogonal designs and consequently Hadamard matrices. In this paper, we const...
Article
Full-text available
The least-squares spectral analysis, an alternative to the classical Fourier transform, is a method of analyzing unequally spaced and non-stationary time series in their first and second statistical moments. However, when a time series has components with low or high amplitude and frequency variability over time, it is not appropriate to use either...
Conference Paper
Full-text available
Spatial transformation of irregularly sampled data to regularly sampled data is a challenging problem in many areas such as seismology. The least-squares spectral analysis (LSSA) is an alternative to the classical Fourier analysis that can analyze irregularly sampled data (data series). Although the LSSA takes into account the correlation among the...
Conference Paper
Atmospheric pressure variations introduce significant systematic effects on gravity observations that can reach up to 10 percent of tidal signal. In this study, a time-frequency dependent admittance is determined based on the least squares wavelet and cross least squares wavelet analyses. Five superconducting gravimeters distributed in northern and...
Article
Map projections have been widely used in many areas such as geography, oceanography, meteorology, geology, geodesy, photogrammetry and global positioning systems. Understanding different types of map projections is very crucial in these areas. This paper presents a tutorial review of various types of current map projections such as equal-area, conf...
Article
Full-text available
Orthogonal designs and weighing matrices have many applications in areas such as coding theory, cryptography, wireless networking, and communication. In this paper, we first show that if positive integer k cannot be written as the sum of three integer squares, then there does not exist any skew-symmetric weighing matrix of order 4 n and weight...
Article
Full-text available
Hadamard matrices, orthogonal designs and amicable orthogonal designs have a number of applications in coding theory, cryptography, wireless network communication and so on. Product designs were introduced by Robinson in order to construct orthogonal designs especially full orthogonal designs (no zero entries) with maximum number of variables for s...
Research
Full-text available
In this report, we describe how we developed a Graphical User Interface (GUI) in MATLAB for Global Navigation Satellite System (GNSS) Planning.
Conference Paper
Full-text available
In many applications, time series may not be sampled at equally spaced intervals or they may contain data gaps. Measurements have variances, so the time series may also be unequally weighted. Time series may also contain systematic noise, such as trends and/or datum shifts (offsets). In certain geodynamic applications, seismic noise may contaminate...
Article
Full-text available
Craigen introduced and studied signed group Hadamard matrices extensively. Following his lead, studied and provided a better estimate for the asymptotic existence of signed group Hadamard matrices and consequently improved the asymptotic existence of Hadamard matrices. In this paper, we introduce and study signed group orthogonal designs. The main...
Article
Full-text available
In this paper, we introduce some known map projections from a model of the Earth to a flat sheet of paper or map and derive the plotting equations for these projections. The first fundamental form and the Gaussian fundamental quantities are defined and applied to obtain the plotting equations and distortions in length, shape and size for some of th...
Article
Full-text available
Given any ℓ-tuple (s 1 ,s 2 ,⋯,s ℓ ) of positive integers, there is an integer N=N(s 1 ,s 2 ,⋯,s ℓ ) such that an orthogonal design of order 2 n (s 1 +s 2 +⋯+s ℓ ) and type (2 n s 1 ,2 n s 2 ,⋯,2 n s ℓ ) exists, for each n≥N. This complements a result of P. Eades et al. [“An algorithm for orthogonal designs”, Congr. Numerantium 15, 279-292 (1975)]...
Thesis
Full-text available
An orthogonal design of order n and type (s_1, ... , s_m), denoted OD(n; s_1, ... , s_m), is a square matrix X of order n with entries from {0; +/- x_1, ... , +/- x_m}, where the x_j 's are commuting variables, that satisfies XX^t = (\sum_{j=1}^m s_j (x_j)^2) I_n, where X^t denotes the transpose of X, and I_n is the identity matrix of order n. An...
Article
Full-text available
We show that if G is any nilpotent, finite group, and the commutator subgroup of G is cyclic, then every connected Cayley graph on G has a hamiltonian cycle.
Article
Full-text available
Suppose G is a finite group of order 30p, where p is prime. We show that if S is any generating set of G, then there is a hamiltonian cycle in the corresponding Cayley graph Cay(G;S).
Article
Full-text available
Suppose G is a finite group, such that |G| = 27p, where p is prime. We show that if S is any generating set of G, then there is a hamiltonian cycle in the corresponding Cayley graph Cay(G;S).

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Projects

Projects (7)
Project
Artificial Intelligence (AI) can significantly help to protect our environment and conserve resources by monitoring vegetation, deforestation and water surface, predicting extreme weather conditions, CO2 removal, and developing greener transportation networks. It is estimated that using AI for environmental applications could significantly help our environment and economy by the mid-century. We are working on AI techniques to aid in solving environmental challenges, improving economy and energy consumption. We are headed toward a clean energy transition, and our goal is to efficiently use sources of energy that are clean and powerful. Wind, water, solar, and nuclear energy are some of the main clean energy sources to generate electricity, replacing fossil fuels that emit harmful byproducts.
Project
To come up with an innovative method for combining Sentinel-1 SAR and Landsat-8 data in other to monitor water surface dynamics of lakes located in high latitude regions.
Project
The main goal is to analyse non-stationary time series using wavelet transfrom