Search results for: satellite interferometry (InSAR)

Authors: Reza Zakerinejad

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Gully erosion is a serious problem that threading the sustainability of agricultural area and rangeland and water in a large part of Iran. This type of water erosion is the main source of sedimentation in many catchment areas in the north of Iran. Since in many national assessment approaches just qualitative models were applied the aim of this study is to predict the spatial distribution of gully erosion processes by means of detail terrain analysis and GIS -based logistic regression in the loess deposition in a case study in the Golestan Province. This study the DEM with 25 meter result ion from ASTER data has been used. The Landsat ETM data have been used to mapping of land use. The TreeNet model as a stochastic modeling was applied to prediction the susceptible area for gully erosion. In this model ROC we have set 20 % of data as learning and 20 % as learning data. Therefore, applying the GIS and satellite image analysis techniques has been used to derive the input information for these stochastic models. The result of this study showed a high accurate map of potential for gully erosion.

Keywords: TreeNet model, terrain analysis, Golestan Province, Iran

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Authors: Rabia Shabbir, Sheikh Saeed Ahmad, Amna Butt

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Rapid land use changes have taken place in Islamabad, the capital city of Pakistan, over the past decades due to accelerated urbanization and industrialization. In this study, land use changes in the metropolitan area of Islamabad was observed by the combined use of GIS and satellite remote sensing for a time period of 15 years. High-resolution Google Earth images were downloaded from 2000-2015, and object-based classification method was used for accurate classification using eCognition software. The information regarding urban settlements, industrial area, barren land, agricultural area, vegetation, water, and transportation infrastructure was extracted. The results showed that the city experienced a spatial expansion, rapid urban growth, land use change and expanding transportation infrastructure. The study concluded the integration of GIS and remote sensing as an effective approach for analyzing the spatial pattern of urban growth and land use change.

Keywords: land use change, urban growth, Islamabad, object-based classification, Google Earth, remote sensing, GIS

Procedia PDF Downloads 148

Authors: Man Li, Wanting Zhou, Lei Li

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Communication stability is the primary concern of communication satellites. Communication satellites are easily affected by particle radiation to generate single event effects (SEE), which leads to soft errors (SE) of the combinational logic circuit. The existing research on soft error rates (SER) of the combined logic circuit is mostly based on the assumption that the logic gates being bombarded have the same pulse width. However, in the actual radiation environment, the pulse widths of the logic gates being bombarded are different due to different linear energy transfers (LET). In order to improve the accuracy of SER evaluation model, this paper proposes a soft error rate evaluation method based on LET. In this paper, the authors analyze the influence of LET on the pulse width of combinational logic and establish the pulse width model based on the LET. Based on this model, the error rate of test circuit ISCAS'85 is calculated. The effectiveness of the model is proved by comparing it with previous experiments.

Keywords: communication satellite, pulse width, soft error rates, LET

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Authors: Mahyar Mehrafarin, Reza Mehrafarin

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The Sistan region in eastern Iran is a significant archaeological area in Iran and the Middle East, encompassing 10,000 square kilometers. Previous archeological field surveys have identified 1662 ancient sites dating from prehistoric periods to the Islamic period. Research Aim: This article aims to explore the utilization of modern technologies and computers in archaeological field surveys in Sistan, Iran, and the benefits derived from their implementation. Methodology: The research employs a descriptive-analytical approach combined with field methods. New technologies and software, such as GPS, drones, magnetometers, equipped cameras, satellite images, and software programs like GIS, Map source, and Excel, were utilized to collect information and analyze data. Findings: The use of modern technologies and computers in archaeological field surveys proved to be essential. Traditional archaeological activities, such as excavation and field surveys, are time-consuming and costly. Employing modern technologies helps in preserving ancient sites, accurately recording archaeological data, reducing errors and mistakes, and facilitating correct and accurate analysis. Creating a comprehensive and accessible database, generating statistics, and producing graphic designs and diagrams are additional advantages derived from the use of efficient technologies in archaeology. Theoretical Importance: The integration of computers and modern technologies in archaeology contributes to interdisciplinary collaborations and facilitates the involvement of specialists from various fields, such as geography, history, art history, anthropology, laboratory sciences, and computer engineering. The utilization of computers in archaeology spanned across diverse areas, including database creation, statistical analysis, graphics implementation, laboratory and engineering applications, and even artificial intelligence, which remains an unexplored area in Iranian archaeology. Data Collection and Analysis Procedures: Information was collected using modern technologies and software, capturing geographic coordinates, aerial images, archeogeophysical data, and satellite images. This data was then inputted into various software programs for analysis, including GIS, Map source, and Excel. The research employed both descriptive and analytical methods to present findings effectively. Question Addressed: The primary question addressed in this research is how the use of modern technologies and computers in archeological field surveys in Sistan, Iran, can enhance archaeological data collection, preservation, analysis, and accessibility. Conclusion: The utilization of modern technologies and computers in archaeological field surveys in Sistan, Iran, has proven to be necessary and beneficial. These technologies aid in preserving ancient sites, accurately recording archaeological data, reducing errors, and facilitating comprehensive analysis. The creation of accessible databases, statistics generation, graphic designs, and interdisciplinary collaborations are further advantages observed. It is recommended to explore the potential of artificial intelligence in Iranian archaeology as an unexplored area. The research has implications for cultural heritage organizations, archaeology students, and universities involved in archaeological field surveys in Sistan and Baluchistan province. Additionally, it contributes to enhancing the understanding and preservation of Iran's archaeological heritage.

Keywords: archaeological surveys, computer use, iran, modern technologies, sistan

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Authors: Yuri V. Kim

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This article presents a new approach to the Functional Testing of Space Systems (SS). It can be considered as a generic test and used for a wide class of SS that from the point of view of System Dynamics and Control may be described by the ordinary differential equations. Suggested methodology is based on using semi-natural experiment- laboratory stand that doesn’t require complicated, precise and expensive technological control-verification equipment. However, it allows for testing system as a whole totally assembled unit during Assembling, Integration and Testing (AIT) activities, involving system hardware (HW) and software (SW). The test physically activates system input (sensors) and output (actuators) and requires recording their outputs in real time. The data is then inserted in laboratory PC where it is post-experiment processed by Matlab/Simulink Identification Toolbox. It allows for estimating system dynamics in form of estimation of system differential equations by the experimental way and comparing them with expected mathematical model prematurely verified by mathematical simulation during the design process.

Keywords: system dynamics, space system ground tests and space qualification, system dynamics identification, satellite attitude control, assembling, integration and testing

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Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

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Authors: Ahmed S. Afifi, Ahmed Magdy

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Satellite monitoring is an essential tool to study, understand, and map large-scale environmental changes that affect humans, climate, and biodiversity. The Sentinel-1 Synthetic Aperture Radar (SAR) instrument provides a high collection of data in all-weather, short revisit time, and high spatial resolution that can be used effectively in flood management. Floods occur when an overflow of water submerges dry land that requires to be distinguished from flooded areas. In this study, we use global flood mapper (GFM), a new google earth engine application that allows users to quickly map floods using Sentinel-1 SAR. The GFM enables the users to adjust manually the flood map parameters, e.g., the threshold for Z-value for VV and VH bands and the elevation and slope mask threshold. The composite R:G:B image results by coupling the bands of Sentinel-1 (VH:VV:VH) reduces false classification to a large extent compared to using one separate band (e.g., VH polarization band). The flood mapping algorithm in the GFM and the Otsu thresholding are compared with Sentinel-2 optical data. And the results show that the GFM algorithm can overcome the misclassification of a flooded area in An Giang, Vietnam.

Keywords: SAR backscattering, Sentinel-1, flood mapping, disaster

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Authors: Wang Zhaoming, Shao Shegang, Chen Xiaorong, Qi Yanan, Tian Lei, Wang Jian

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This study conducts a comparative analysis of the spectral curves of asphalt pavements at various aging stages to improve road information extraction from high-resolution remote sensing imagery. By examining the distinguishing capabilities and spectral characteristics, the research aims to establish a pavement information extraction methodology based on China's high-resolution satellite images. The process begins by analyzing the spectral features of asphalt pavements to construct a spectral assessment model suitable for evaluating pavement health. This model is then tested at a national highway traffic testing site in China, validating its effectiveness in distinguishing different pavement aging levels. The study's findings demonstrate that the proposed model can accurately assess road health, offering a valuable tool for road maintenance planning and infrastructure management.

Keywords: spectral analysis, asphalt pavement aging, high-resolution remote sensing, pavement health assessment

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Authors: Y. Lacroix, J.-F. Malbranque

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We present a chronological evolution for naval telecommunication networks. We distinguish periods: with or without multiplexers, with switch systems, with federative systems, with medium switching, and with medium switching with wireless networks. This highlights the introduction of new layers and technology in the architecture. These architectures are presented using layer models of transmission, in a unified way, which enables us to integrate pre-existing models. A ship of a naval fleet has internal communications (i.e. applications' networks of the edge) and external communications (i.e. the use of the means of transmission between edges). We propose architectures, deduced from the layer model, which are the point of convergence between the networks on board and the HF, UHF radio, and satellite resources. This modelling allows to consider end-to-end naval communications, and in a more global way, that is from the user on board towards the user on shore, including transmission and networks on the shore side. The new architectures need take care of quality of services for end-to-end communications, the more remote control develops a lot and will do so in the future. Naval telecommunications will be more and more complex and will use more and more advanced technologies, it will thus be necessary to establish clear global communication schemes to grant consistency of the architectures. Our latest model has been implemented in a military naval situation, and serves as the basic architecture for the RIFAN2 network.

Keywords: equilibrium beach profile, eastern tombolo of Giens, potential function, erosion

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Authors: Fatemeh Sadat Sharifi

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In the present study, the capabilities of WAVEWATCH-III and MIKE21-SW for predicting the characteristics of wind waves in Hormuz Strait are evaluated. The GFS wind data (Global Forecast System) were derived. The bathymetry of gride with 2 arc-minute resolution, also were extracted from the ETOPO1. WAVEWATCH-III findings illustrate more valid prediction of wave features comparing to the MIKE-21 SW in deep water. Apparently, in shallow area, the MIKE-21 provides more uniformities with altimetry measurements. This may be due to the merits of the unstructured grid which are used in MIKE-21, leading to better representations of the coastal area. The findings on the direction of waves generated by wind in the modeling area indicate that in some regions, despite the increase in wind speed, significant wave height stays nearly unchanged. This is fundamental because of swift changes in wind track over the Strait of Hormuz. After discussing wind-induced waves in the region, the impact of instability of the surface layer on wave growth has been considered. For this purpose, the average monthly mean air temperature has been used. The results in cold months, when the surface layer is unstable, indicates an acceptable increase in the accuracy of prediction of the indicator wave height.

Keywords: numerical modeling, WAVEWATCH-III, Strait of Hormuz, MIKE21-SW

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Authors: Zulkiflee Abd Latif, Sitinor Atikah Nordin, Alawi Sulaiman

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Different tree species possess different and various benefits. Arenga Pinnata tree species own several potential uses that is valuable for the economy and the country. Mapping vegetation using remote sensing technique involves various process, techniques and consideration. Using satellite imagery, this method enables the access of inaccessible area and with the availability of near infra-red band; it is useful in vegetation analysis, especially in identifying tree species. Pixel-based and object-based classification technique is used as a method in this study. Pixel-based classification technique used in this study divided into unsupervised and supervised classification. Object based classification technique becomes more popular another alternative method in classification process. Using spectral, texture, color and other information, to classify the target make object-based classification is a promising technique for classification. Classification of Arenga Pinnata trees is overlaid with elevation, slope and aspect, soil and river data and several other data to give information regarding the tree character and living environment. This paper will present the utilization of remote sensing technique in order to map Arenga Pinnata tree species

Keywords: Arenga Pinnata, pixel-based classification, object-based classification, remote sensing

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Authors: Mohamad Muqtada Ali Khan, Nor Ashikin Shaari, Donny Adriansyah bin Nazaruddin, Hafzan Eva Bt Mansoor

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Floods play a key role in landform evolution of an area. This process is likely to alter the topography of the earth’s surface. The present study area, Kota Bharu is very prone to floods extends from upstream of Kelantan River near Kemubu to the downstream area near Kuala Besar. These flood events which occur every year in the study area exhibit a strong bearing on river morphological set-up. In the present study, three satellite imageries of different time periods have been used to manifest the post-flood landform changes. The pre-processing of the images such as subset, geometric corrections and atmospheric corrections were carried-out using ENVI 4.5 followed by the analysis processes. Twenty sets of cross sections were plotted using software Erdas 9.2, ERDAS and ArcGis 10 for the all three images. The results show a significant change in the length of the cross section which suggest that the geomorphological processes play a key role in carving and shaping the river banks during the floods.

Keywords: flood induced, geomorphic imprints, Kelantan river, Malaysia

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Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

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A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

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Authors: Anish Bhargava

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By 2050, there will be more plastic than fish in our oceans. 51 trillion micro-plastics pollute our waters and contaminate the food on our plates, increasing the risk of tumours and diseases such as cancer. Our product is a solution to the ever-growing problem of plastic pollution. We call it the SmartBin. The SmartBin is a cylindrical device which will float just below the surface of the water, able to move with the aid of 4 water thrusters situated on the sides. As it floats, our SmartBin will suck water into itself and pump it out through the bottom. All waste is collected into a reusable filter including microplastics measuring down to 1.5mm. A speaker emitting sound at a frequency of 9 hertz ensures marine life stays away from the SmartBin. Featured along with our product is a smartphone app which will enable the user to designate an area for the SmartBin to cover on a satellite image. The SmartBin will then return to its start position near the shore, configured through the app. As global pressure to tackle water pollution continues to increase, environmental spending increases too. As our product provides an effective solution to this issue, we can seize the opportunity and scale our company. Our product is unparalleled. It can move at a high speed, covering a wide area rather than being restricted to one position. We target not only oceans and sea-shores, but also rivers, lakes, reservoirs and canals, as they are much easier to access and control.

Keywords: water, plastic, pollution, solution, hydroclean, smartbin, cleanup

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Authors: Siyu Bu, Jie Wang, Yajing Jiang

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Nowadays, villages still occupying 94.7% of the national territorial area (almost nine million square kilometers) of China. Some of them are meeting urbanization and grow as satellite; however, others are witnessing more and more citizens swarming into with nostalgia, seek enjoyment from the beautiful green countryside. In villages, new types of house come and we see billions of old houses lay unused, or even be dying at every second, which cause a lot of 'bad palaces', decadent and dangerous. In this context, there are lots of tries for gearing villages in China. This article deconstructs the traditional village house to excavate its’ landscape potential for future. By research in CunWei Village, Nanping City, Fujian Province, China, a method of reconstruction of old houses comes out: the wreckage will be a strong landscape, showing the great beauty of nature. It will be a better use of the old material as well as the space pattern. It was supposed to gain a juxtaposition of traditional village life and modern social life by offering possibilities of multiple event, replacing the bad space to attractive one by strengthen the old structures without destroy traditional patterns. Furthermore , this method acts as an exploring for building redefinition of village landscape that fit Chinese villages, using local nature resource and traditional construction logic.

Keywords: juxtaposition, replace, village, ruins

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Authors: Othman Maklouf, Abdunnaser Tresh

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GPS and inertial navigation system (INS) have complementary qualities that make them ideal use for sensor fusion. The limitations of GPS include occasional high noise content, outages when satellite signals are blocked, interference and low bandwidth. The strengths of GPS include its long-term stability and its capacity to function as a stand-alone navigation system. In contrast, INS is not subject to interference or outages, have high bandwidth and good short-term noise characteristics, but have long-term drift errors and require external information for initialization. A combined system of GPS and INS subsystems can exhibit the robustness, higher bandwidth and better noise characteristics of the inertial system with the long-term stability of GPS. The most common estimation algorithm used in integrated INS/GPS is the Kalman Filter (KF). KF is able to take advantages of these characteristics to provide a common integrated navigation implementation with performance superior to that of either subsystem (GPS or INS). This paper presents a simplified KF algorithm for land vehicle navigation application. In this integration scheme, the GPS derived positions and velocities are used as the update measurements for the INS derived PVA. The KF error state vector in this case includes the navigation parameters as well as the accelerometer and gyroscope error states.

Keywords: GPS, INS, Kalman filter, inertial navigation system

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Authors: Andi Syahputra, R. H. Jatmiko, D. R. Hizbaron

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Land surface temperature (LST) in an area is influenced by conditions of vegetation density, building density, and the number of inhabitants who live in the area. Medan City is one of the largest cities in Indonesia, with a high rate of change from vegetation to developed land. This study aims to identify the relationship between the percentage of building density and land surface temperature in Medan City. Pixel image analysis method is carried out to obtain the value of building density in pixel images of Landsat 8 images with the help of WorldView-2 satellite imagery. The results showed the highest land surface temperature in 2018 of 35, 4°C was found in Medan Perjuangan District, and the lowest was 22.5°C in Medan Belawan District. Building density samples with a density level of 889.17 m were also found in Medan Perjuangan District, while the lowest building density sample was found in Medan Timur District. Linear regression analysis of the effect of building density with land surface temperature obtained a correlation (R) was 0.64, and a coefficient of determination (R²) was 0.411 and modeling of building density based on the LST has a correlation (R), and a coefficient of determination (R²) was 0.72 with The RMSE obtained 0.853.

Keywords: land surface temperature, Landsat, imagery, building density, vegetation, density

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Authors: Sidi Mohamed Mesli, Mohamed Habchi, Mohamed Kotbi, Rafik Benallal, Abdelali Derouiche

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Fluoride glasses with a nominal composition of BaMnMF7 (M = FeV assuming isomorphous replacement) have been structurally modelled through the simultaneous simulation of their neutron diffraction patterns by a reverse Monte Carlo (RMC) model and by a Rietveld for disordered materials (RDM) method. Model is consistent with an expected network of interconnected [MF6] polyhedra. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term in acceptance criteria. This method is called the Hybrid Reverse Monte Carlo (HRMC) method. The idea of this paper is to apply the (HRMC) method to the title glasses, in order to make a study of the phenomenon nature of order and disorder by displaying and discussing the partial pair distribution functions (PDFs) g(r). We suggest that this method can be used to describe average correlations between components of fluoride glass or similar system.

Keywords: fluoride glasses, RMC simulation, neutron scattering, hybrid RMC simulation, Lennard-Jones potential, partial pair distribution functions

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Authors: R. R. Galiev, I. I. Lykov, A. E. Shitikov, I. A. Bilenko

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Dual-comb interferometry is based on the mixing of two optical frequency combs with slightly different lines spacing which results in the mapping of the optical spectrum into the radio-frequency domain for future digitizing and numerical processing. The dual-comb approach enables diverse applications, including metrology, fast high-precision spectroscopy, and distance range. Ordinary frequency-modulated continuous-wave (FMCW) laser-based Light Identification Detection and Ranging systems (LIDARs) suffer from two main disadvantages: slow and unreliable mechanical, spatial scan and a rather wide linewidth of conventional lasers, which limits speed measurement resolution. Dual-comb distance measurements with Allan deviations down to 12 nanometers at averaging times of 13 microseconds, along with ultrafast ranging at acquisition rates of 100 megahertz, allowing for an in-flight sampling of gun projectiles moving at 150 meters per second, was previously demonstrated. Nevertheless, pump lasers with EDFA amplifiers made the device bulky and expensive. An alternative approach is a direct coupling of the laser to a reference microring cavity. Backscattering can tune the laser to the eigenfrequency of the cavity via the so-called self-injection locked (SIL) effect. Moreover, the nonlinearity of the cavity allows a solitonic frequency comb generation in the very same cavity. In this work, we developed a fully integrated, power-efficient, electrically driven dual-micro comb source based on the semiconductor lasers SIL to high-quality integrated Si3N4 microresonators. We managed to obtain robust 1400-1700 nm combs generation with a 150 GHz or 1 THz lines spacing and measure less than a 1 kHz Lorentzian withs of stable, MHz spaced beat notes in a GHz band using two separated chips, each pumped by its own, self-injection locked laser. A deep investigation of the SIL dynamic allows us to find out the turn-key operation regime even for affordable Fabry-Perot multifrequency lasers used as a pump. It is important that such lasers are usually more powerful than DFB ones, which were also tested in our experiments. In order to test the advantages of the proposed techniques, we experimentally measured a minimum detectable speed of a reflective object. It has been shown that the narrow line of the laser locked to the microresonator provides markedly better velocity accuracy, showing velocity resolution down to 16 nm/s, while the no-SIL diode laser only allowed 160 nm/s with good accuracy. The results obtained are in agreement with the estimations and open up ways to develop LIDARs based on compact and cheap lasers. Our implementation uses affordable components, including semiconductor laser diodes and commercially available silicon nitride photonic circuits with microresonators.

Keywords: dual-comb spectroscopy, LIDAR, optical microresonator, self-injection locking

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Authors: Shimaa Holail, Tamer Saleh, Xiongwu Xiao

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Building change detection (BCD) from satellite imagery is an essential topic in urbanization monitoring, agricultural land management, and updating geospatial databases. Recently, methods for detecting changes based on deep learning have made significant progress and impressive results. However, it has the problem of being insensitive to changes in buildings with complex spectral differences, and the features being extracted are not discriminatory enough, resulting in incomplete buildings and irregular boundaries. To overcome these problems, we propose a dual Siamese network based on the Unet model with the addition of a deep supervision strategy (DS) in this paper. This network consists of a backbone (encoder) based on ImageNet pre-training, a fusion block, and feature pyramid networks (FPN) to enhance the step-by-step information of the changing regions and obtain a more accurate BCD map. To train the proposed method, we created a new dataset (EGY-BCD) of high-resolution and multi-temporal aerial images captured over New Cairo in Egypt to detect building changes for this purpose. The experimental results showed that the proposed method is effective and performs well with the EGY-BCD dataset regarding the overall accuracy, F1-score, and mIoU, which were 91.6 %, 80.1 %, and 73.5 %, respectively.

Keywords: building change detection, deep supervision, semantic segmentation, EGY-BCD dataset

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Authors: Omar Hamdy, Schichen Zhao, Hussein Abd El-Atty, Ayman Ragab, Muhammad Salem

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One of the most risky areas in Aswan is Abouelreesh, which is suffering from flood disasters, as heavy deluge inundates urban areas causing considerable damage to buildings and infrastructure. Moreover, the main problem was the urban sprawl towards this risky area. This paper aims to identify the urban areas located in the risk areas prone to flash floods. Analyzing this phenomenon needs a lot of data to ensure satisfactory results; however, in this case the official data and field data were limited, and therefore, free sources of satellite data were used. This paper used ArcGIS tools to obtain the storm water drains network by analyzing DEM files. Additionally, historical imagery in Google Earth was studied to determine the age of each building. The last step was to overlay the urban area layer and the storm water drains layer to identify the vulnerable areas. The results of this study would be helpful to urban planners and government officials to make the disasters risk estimation and develop primary plans to recover the risky area, especially urban areas located in torrents.

Keywords: risk area, DEM, storm water drains, GIS

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Authors: Lianzhong Zhang, Chao Huang

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Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

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Authors: Jan-Peter Mund, Christian Kind

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In view of the ongoing climate change and global warming, fires along railways in Germany are occurring more frequently, with sometimes massive consequences for railway operations and affected railroad infrastructure. In the absence of systematic studies within the infrastructure network of German Rail, little is known about the causes of such embankment fires. Since a further increase in these hazards is to be expected in the near future, there is a need for a sound knowledge of triggers and drivers for embankment fires as well as methodical knowledge of prediction tools. Two predictable future trends speak for the increasing relevance of the topic: through the intensification of the use of rail for passenger and freight transport (e.g..: doubling of annual passenger numbers by 2030, compared to 2019), there will be more rail traffic and also more maintenance and construction work on the railways. This research project approach uses satellite data to identify historical embankment fires along rail network infrastructure. The team links data from these fires with infrastructure and weather data and trains a machine-learning model with the aim of predicting fire hazards on sections of the track. Companies reflect on the results and use them on a pilot basis in precautionary measures.

Keywords: embankment fires, railway maintenance, machine learning, remote sensing, VIIRS data

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Authors: Rachita Lal

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Urban sprawl is a significant contributor to land use change in developing countries, where urbanization rates are high. The most important driver of environmental changes is also considered to be the shift in land use and land cover. Our local and regional land managers must carefully analyze urbanization and its effects on cities to make the best choices. This study uses satellite imagery to examine how urbanization affects the local ecosystem through geographic expansion. The following research focuses on the effects of city growth on the local environment, land use, and Land cover. The primary focus of this research is to study, To understand the role of urbanization on city expansion. To study the impact of spatial growth of urban areas on the Land cover. In this paper, the GIS tool will be used to analyze. For this purpose, four digital images are used for the years 2000, 2005, 2011, and 2019. The use of the approach in the Bhubaneswar Urban Core, one of the fastest developing and planned cities in India, has proved that it is highly beneficial and successful for monitoring urban sprawl. It offers a helpful tool for quantitative assessment, which is crucial for determining the spatial dynamics, variations, and changes of urban sprawl patterns in quickly increasing regions.

Keywords: LULC, urbanization, environment impact assessment, spatial growth

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Authors: Yulia Chalri, E. T. P. Lussiana, Sarifuddin Madenda, Bambang Trisakti, Yuhilza Hanum

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Water is a natural resource needed by humans and other living creatures. The territorial water of Indonesia is 81% of the country area, consisting of inland waters and the sea. The research object is inland waters in the form of lakes and reservoirs, since 90% of inland waters are in them, therefore the water quality should be monitored. One of water quality parameters is Total Suspended Solid (TSS). Most of the earlier research did direct measurement by taking the water sample to get TSS values. This method takes a long time and needs special tools, resulting in significant cost. Remote sensing technology has solved a lot of problems, such as the mapping of watershed and sedimentation, monitoring disaster area, mapping coastline change, and weather analysis. The aim of this research is to estimate TSS of Rawa Pening lake in Central Java by using the Lansat 8 image. The result shows that the proposed method successfully estimates the Rawa Pening’s TSS. In situ TSS shows normal water quality range, and so does estimation result of segmentation method.

Keywords: total suspended solid (TSS), remote sensing, image segmentation, RGB value

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Davaanyam Surenjav, Chinzolboo Dandarbaatar, Ganbold Batkhuyag

Abstract:

Primate city induced rapid urbanization has been become one of the main challenges in sustainable development in Mongolia like other developing countries since transition to market economy in 1990. According due to statistical yearbook, population number of Ulaanbaatar city has increased from 0.5 million to 1.5 million for last 30 years and contains now almost half (47%) of total Mongolian population. Rural-Ulaanbaatar and local Cities-Ulaanbaatar city migration leads to social issues like uncontrolled urbanization, income inequality, poverty, overwork of public service, economic over cost for redevelopment and limitation of transport and environmental degradation including air, noise, water and soil pollution. Most thresholds of all of the sustainable urban development main and sub-indicators over exceeded from safety level to unsafety level in Ulaanbaatar. So, there is an urgent need to remove migration pull factors including some administrative and high education functions from Ulaanbaatar city to its satellite cities or secondary cities. Moreover, urban smart transport system and green and renewable energy technologies should be introduced to urban development master plan of Ulaanbaatar city.

Keywords: challenge for sustainable urban development, migration factors, primate city , urban safety thresholds

Procedia PDF Downloads 130

Authors: Chunhong Zhao

Abstract:

Remotely sensed land surface temperature (LST) is vital to understand the land-atmosphere energy balance, hydrological cycle, and thus is widely used to describe the urban heat island (UHI) phenomenon. However, due to technical constraints, satellite thermal sensors are unable to provide LST measurement with both high spatial and high temporal resolution. Despite different downscaling techniques and algorithms to generate high spatiotemporal resolution LST. Four major metropolitan areas in Texas, USA: Dallas-Fort Worth, Houston, San Antonio, and Austin all demonstrate UHI effects. Different cities are expected to have varying SUHI effect during the urban development trajectory. With the help of the Landsat, ASTER, and MODIS archives, this study focuses on the spatial patterns of UHIs and the seasonal and annual variation of these metropolitan areas. With Gaussian model, and Local Indicators of Spatial Autocorrelations (LISA), as well as data fusion methods, this study identifies the hotspots and the trajectory of the UHI phenomenon of the four cities. By making comparison analysis, the result can help to alleviate the advent effect of UHI and formulate rational urban planning in the long run.

Keywords: spatiotemporal analysis, land surface temperature, urban heat island evaluation, metropolitan areas of Texas, USA

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

Abstract:

Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression.

Keywords: image compression, radon transform, linear predictive coding (LPC), run lengthcoding (RLC), meteosat second generation (MSG)

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Authors: Rida Kanwal, Wang Yuhui, Song Weiguo

Abstract:

Wildfires are one of the most prominent threats to ecosystems, human health, and economic activities, with wind acting as a critical driving factor. This study combines machine learning (ML) and remote sensing (RS) to assess the effects of wind on wildfires in Chongqing Province from August 16-23, 2022. Landsat 8 satellite images were used to estimate the difference normalized burn ratio (dNBR), representing prefire and postfire vegetation conditions. Wind data was analyzed through geographic information system (GIS) mapping. Correlation analysis between wind speed and fire radiative power (FRP) revealed a significant relationship. An autoregressive integrated moving average (ARIMA) model was developed for wind forecasting, and linear regression was applied to determine the effect of wind speed on FRP. The results identified high wind speed as a key factor contributing to the surge in FRP. Wind-rose plots showed winds blowing to the northwest (NW), aligning with the wildfire spread. This model was further validated with data from other provinces across China. This study integrated ML, RS, and GIS to analyze wildfire behavior, providing effective strategies for prediction and management.

Keywords: wildfires, machine learning, remote sensing, wind speed, GIS, wildfire behavior

Procedia PDF Downloads 18