Fatemeh Tabib MahmoudiShahid Rajaee University | SRTTU · Department of Geomatics Engineering
Fatemeh Tabib Mahmoudi
PhD
About
32
Publications
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141
Citations
Citations since 2017
Introduction
Fatemeh Tabib Mahmoudi currently works at the Department of Geomatics Engineering, Faculty of Civil, Shahid Rajaee University. Fatemeh does research in Advanced pattern recognition algorithms, Artificial Intelligence and Data Mining.
Publications
Publications (32)
Urban vegetation recognition based on remote sensing data is highly affected by the complexities of urban areas due to the existence of various kinds of objects and their relations. Spectral similarities between tree canopies and types of grass lands, spatial adjacency between houses and tall trees, shadow and occluded areas make some difficulties...
More complexities in urban areas due to the existence of buildings with roofs made of various materials, roads and parking lots, diverse plant species and vehicles along with developed very high spatial resolution (VHR) remote sensing imageries lead to increase the difficulties of urban objects recognition. Defining human cognition semantic categor...
The yield of the wheat crop is affected by the climate and soil parameters such as moisture and nutrients, plant pests and diseases. The main objective of this research is the feature level fusion of multiple effective criteria on the wheat yields using linear and machine learning regression models. The effects of vegetation condition, moisture, nu...
Increasing human desire for urbanization and, as a result, urban growth and development has caused the replacement of natural objects such as vegetation and mountains with building structures and roads. This exacerbates the phenomenon of urban heat islands (UHI), one of the main threats to the quality of human life. In this research, a post-classif...
Background and Objective: Land is rapidly changing at the local, regional, national, and global scales, with a significant impact on the environment. Some changes occur due to natural causes, while other changes due to human projects such as urban growth.
Material and Methodology: This article provides an overview on the categorization of different...
Introduction: Vehicle detection and counting is an important issue for many applications such as remote monitoring, vehicle tracking for security purposes, traffic management, rescue tasks, parking capacity analysis and metropolitan planning. Vehicle monitoring is also an important part of traffic information, crash control, vehicle flow statistics...
Background and objectives: As the occurrence of water stress in plants and agricultural crops is affected by the drought, global warming, population growth and the urban heat islands, the lack of traffic and human activities in natural environment during the Covid-19 virus pandemic can be considered as a factor reducing plants’ water stress. As wat...
Natural disasters such as earthquakes and floods together with the urban sprawl conducted by increasing the population make multi-temporal changes in building areas. Destruction, buildings’ renovation, and constructing new buildings are the main changes of the urban areas that should be detected to update three-dimensional city models. The results...
Introduction: Multi temporal changes in built up areas are mainly caused by natural disasters (such as floods and earthquakes) or urban sprawl. Detecting these changes which consist of construction, destruction and renovation of buildings can play an important role in updating three dimensional city models. Multi-temporal remote sensing data are on...
Introduction: Information about vegetation cover and their health has always been interesting to ecologists due to its importance in terms of habitat, energy production and other important characteristics of plants on the earth planet. Nowadays, developments in remote sensing technologies caused more remotely sensed data accessible to researchers....
Background and Objectives: Pan-sharpening algorithms integrate the spectral capabilities of the multispectral imagery with the spatial details of the panchromatic one to obtain a product with confident spectral and spatial resolutions. Due to the large diversities in the utilized pan-sharpening algorithms, occurring spatial and spectral deviations...
Automatic vehicle recognition has an important role for many applications such as supervision, traffic management and rescue tasks. The ability of online supervision on the distribution of vehicles in urban environments prevents traffic, which in turn reduces air pollution and noise. However, this is extremely challenging due to the small size of v...
Road recognition and extraction based on remotely sensed data is efficient and applicable in much urban management studies. In this research, the capabilities of SPOT and SAR images are investigated for road recognition. Spectral and textural similarities between roads and other urban objects such as building’s roofs many cause some difficulties in...
Multi temporal changes in built up areas are mainly caused by natural disasters (such as floods and earthquakes) or urban sprawl. Detecting these changes which consist of construction, destruction and renovation of buildings can play an important role in updating three dimensional city models and making the right decisions for urban management. Gen...
In this paper, the potential of per-pixel Support Vector Machine (SVM) classification method is investigated for monitoring the changes in the wetland areas. The proposed change detection method composed of three main steps. In the first step, pre-processing is performed on the images for geometric and radiometric corrections and improving the spat...
Each of the urban land cover types has unique thermal pattern. Therefore, thermal remote sensing can be used over urban areas for indicating temperature differences and comparing the relationships between urban surface temperatures and land cover types. On the other hand, synthetic-aperture radar (SAR) sensors are playing an increasingly important...
با توجه به تنوع عوارض شهری و حساسیت هریک نسبت به محدوده طیفی مشخص در طیف الکترومغناطیس، سنجنده های مختلف تصویربرداری رفتارهای متفاوتی را در رابطه با برخی از عوارض ثبت می¬کنند. همچنین اعوجاجات رنگی و پاسخ غیرطبیعی سنجنده به محدوده طیفی مشخص، بهعنوان یکی از مهمترین چالش¬های تشخیص صحیح عوارض در دورکاوی، مطرح است. ادغام دادهها بهمنظور بهره¬گیری از...
![Figure 7.6 Pseudocode of the PSO algorithm [21]](profile/Fatemeh-Tabib-Mahmoudi/publication/322244717/figure/fig4/AS:687327865229312@1540883141027/Pseudocode-of-the-PSO-algorithm-21_Q320.jpg)
Object Based Image Analysis (OBIA) approaches are often superior to the pixel based classifications at Very High Resolution (VHR) remotely sensed images. Due to the similar spectral signatures of land cover classes especially in urban areas, spatial information must be exploited to produce improved classification maps at finer resolutions. Segmentat...
Spectral similarities, spatial adjacencies and complex relationships between various
object types lead to the recognition difficulties and ambiguities in complex urban areas.
Using a knowledge base containing contextual information together with higher level
modifications in object based analysis may improve recognition results in such a
situation....
![Fig. 2. Illustration of the angle-based rule [28].](profile/Peter-Reinartz/publication/266259788/figure/fig2/AS:295799616491546@1447535532772/Illustration-of-the-angle-based-rule-28_Q320.jpg)
Spectral similarities and spatial adjacencies between various kinds of objects, shadow and occluded areas behind high rise objects as well as the complex relationships between various object types lead to the difficulties and ambiguities in object recognition in urban areas. Using a knowledge base containing the contextual information together with...
In this paper, using spatial and spectral characteristics of
the WorldView-2 satellite imagery, capabilities of multi-agent
systems are used for solving multiple object recognition difficulties
in complex urban areas. The methodology has two
main steps: object based image analysis (OBIA) and multiagent
object recognition. In the first step, segment...
Spectral similarity and spatial adjacency between various kinds of objects, shadow and occluded areas behind high rise objects as well as complex relationships between various object types leads to object recognition difficulties and ambiguities in urban areas. Using new multi-angular satellite imagery, higher levels of analysis and developing a kn...
Spectral similarity and spatial adjacency between various kinds of objects, shadow and occluded areas behind high rise objects as well as complex relationships lead to object recognition difficulties and ambiguities in complex urban areas. Using new multi-angular satellite imagery, higher levels of analysis and developing a context aware system may...
In this paper, the capabilities of multi-agent systems are used in order to solve object recognition difficulties in complex urban areas based on the characteristics of WorldView-2 satellite imagery and digital surface model (DSM). The proposed methodology has three main steps: pre-processing of dataset, object based image analysis and multi-agent...
Despite rich and fine spectral information of hyperspectral imagery, curse of dimensionality and Hughes phenomenon affect the land use/cover classification accuracy of such images. In this situation, optimal feature/band selection based on optimization procedures has high potential to improve the accuracy of hyperspectral image pattern recognition...
Lidar has proved to be a promising data source for various mapping and D modelling of buildings in urban areas. Therefore, many researchers have been trying to study and develop automatic building recognition algorithms based on Lidar data. But, according to the adjacency of buildings and other objects in urban areas, especially trees, the performa...
Light detection and ranging (lidar) as a modern and powerful remote sensing technology has proven to be a
promising data source for modelling of various three-dimensional (3D) objects such as buildings and trees in urban areas.
Nevertheless, because of the adjacency of buildings and other objects, especially trees, the results obtained from most
tr...
Light detection and ranging (lidar) as a modern and powerful remote sensing technology has proven to be a promising data source for modelling of various three-dimensional (3D) objects such as buildings and trees in urban areas. Nevertheless, because of the adjacency of buildings and other objects, especially trees, the results obtained from most tr...
Three dimensional object recognition and extraction from Lidar and other airborne or space borne data have been an area of major interest in photogrammetry for quite a long time. Therefore, many researchers have been trying to study and develop automatic or semi-automatic approaches for object extraction based on sensory data in urban areas. Lidar...
Lidar has proved to be a promising data source for various mapping and 3D modeling of buildings in urban areas. Therefore, many researchers have been trying to study and develop automatic building recognition algorithms based on Lidar data. But, according to the complicated relationships between buildings and other objects in urban areas, especiall...
Projects
Project (1)
each of the urban land cover types has unique thermal pattern. Therefore, thermal remote sensing can be used over urban areas for indicating temperature differences and comparing the relationships between urban surface temperatures and land cover types. On the other hand, Synthetic Aperture Radar (SAR) sensors are playing an increasingly important role in land cover classification due to their ability to operate day and night through cloud cover, and capturing the structure and dielectric properties of the earth surface materials. In this postdoctoral research, a fusion of SAR image textures and thermal bands of Landsat8 data is performed in order to modify the accuracy of urban land cover classification.
