Search results for: Urban remote sensing

Authors: Limin Zhao, Xingfa Gu, C. Tao Yu

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one of the significant factors for improving the accuracy of Land Surface Temperature (LST) retrieval is the correct understanding of the directional anisotropy for thermal radiance. In this paper, the multiple scattering effect between heterogeneous non-isothermal surfaces is described rigorously according to the concept of configuration factor, based on which a directional thermal radiance model is built, and the directional radiant character for urban canopy is analyzed. The model is applied to a simple urban canopy with row structure to simulate the change of Directional Brightness Temperature (DBT). The results show that the DBT is aggrandized because of the multiple scattering effects, whereas the change range of DBT is smoothed. The temperature difference, spatial distribution, emissivity of the components can all lead to the change of DBT. The “hot spot" phenomenon occurs when the proportion of high temperature component in the vision field came to a head. On the other hand, the “cool spot" phenomena occur when low temperature proportion came to the head. The “spot" effect disappears only when the proportion of every component keeps invariability. The model built in this paper can be used for the study of directional effect on emissivity, the LST retrieval over urban areas and the adjacency effect of thermal remote sensing pixels.

Keywords: Directional thermal radiance, multiple scattering, configuration factor, urban canopy, hot spot effect

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Authors: D. Gouwanda, S. M. N. A. Senanayake

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This paper presents a real time force sensing instrument that is designed for human gait analysis purposes. It is capable of recording and monitoring ground reaction forces exerted by human foot during various activities such as walking, running and jumping in real time. In overall, force sensing mat mainly consists of three elements: the force sensing mat, signal conditioning circuit and data acquisition device. Force sensing mat is the mat that contains an array of force sensing elements. To control and process the incoming signal from the force sensing mat, Force-Logger and Force-Reloader are developed using National Instrument Labview. This paper describes the architecture of the force sensing mat, signal conditioning circuit and the real time streaming of the incoming data from the force sensing mat. Additionally, a preliminary experiment dataset is presented in this paper.

Keywords: Force platform, force sensing resistor, human gait analysis.

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Authors: Mahesh Pal

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In recent years, a number of works proposing the combination of multiple classifiers to produce a single classification have been reported in remote sensing literature. The resulting classifier, referred to as an ensemble classifier, is generally found to be more accurate than any of the individual classifiers making up the ensemble. As accuracy is the primary concern, much of the research in the field of land cover classification is focused on improving classification accuracy. This study compares the performance of four ensemble approaches (boosting, bagging, DECORATE and random subspace) with a univariate decision tree as base classifier. Two training datasets, one without ant noise and other with 20 percent noise was used to judge the performance of different ensemble approaches. Results with noise free data set suggest an improvement of about 4% in classification accuracy with all ensemble approaches in comparison to the results provided by univariate decision tree classifier. Highest classification accuracy of 87.43% was achieved by boosted decision tree. A comparison of results with noisy data set suggests that bagging, DECORATE and random subspace approaches works well with this data whereas the performance of boosted decision tree degrades and a classification accuracy of 79.7% is achieved which is even lower than that is achieved (i.e. 80.02%) by using unboosted decision tree classifier.

Keywords: Ensemble learning, decision tree, remote sensingclassification.

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Authors: Miloš Marjanović, Jaroslav Burian, Ja kub Miřijovský, Jan Harbula

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This paper regards the phenomena of intensive suburbanization and urbanization in Olomouc city and in Olomouc region in general for the period of 1986–2009. A Remote Sensing approach that involves tracking of changes in Land Cover units is proposed to quantify the urbanization state and trends in temporal and spatial aspects. It actually consisted of two approaches, Experiment 1 and Experiment 2 which implied two different image classification solutions in order to provide Land Cover maps for each 1986–2009 time split available in the Landsat image set. Experiment 1 dealt with the unsupervised classification, while Experiment 2 involved semi- supervised classification, using a combination of object-based and pixel-based classifiers. The resulting Land Cover maps were subsequently quantified for the proportion of urban area unit and its trend through time, and also for the urban area unit stability, yielding the relation of spatial and temporal development of the urban area unit. Some outcomes seem promising but there is indisputably room for improvements of source data and also processing and filtering.

Keywords: Change detection, image classification, land cover, Landsat images, Olomouc city, urbanization.

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Authors: K. Tunde Olagunju, C. Scott Allen, F.D. (Freek) van der Meer

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Identification of hydrocarbon oil in remote sensing images is often the first step in monitoring oil during spill events. Most remote sensing methods adopt techniques for hydrocarbon identification to achieve detection in order to model an appropriate cleanup program. Identification on optical sensors does not only allow for detection but also for characterization and quantification. Until recently, in optical remote sensing, quantification and characterization were only potentially possible using high-resolution laboratory and airborne imaging spectrometers (hyperspectral data). Unlike multispectral, hyperspectral data are not freely available, as this data category is mainly obtained via airborne survey at present. In this research, two operational high-resolution multispectral satellites (WorldView-3 and Sentinel-2) are theoretically assessed for their suitability for hydrocarbon characterization, using the Hydrocarbon Spectra Slope model (HYSS). This method utilized the two most persistent hydrocarbon diagnostic/absorption features at 1.73 µm and 2.30 µm for hydrocarbon mapping on multispectral data. In this research, spectra measurement of seven different hydrocarbon oils (crude and refined oil) taken on 10 different substrates with the use of laboratory ASD Fieldspec were convolved to Sentinel-2 and WorldView-3 resolution, using their full width half maximum (FWHM) parameter. The resulting hydrocarbon slope values obtained from the studied samples enable clear qualitative discrimination of most hydrocarbons, despite the presence of different background substrates, particularly on WorldView-3. Due to close conformity of central wavelengths and narrow bandwidths to key hydrocarbon bands used in HYSS, the statistical significance for qualitative analysis on WorldView-3 sensors for all studied hydrocarbon oil returned with 95% confidence level (P-value ˂ 0.01), except for Diesel. Using multifactor analysis of variance (MANOVA), the discriminating power of HYSS is statistically significant for most hydrocarbon-substrate combinations on Sentinel-2 and WorldView-3 FWHM, revealing the potential of these two operational multispectral sensors as rapid response tools for hydrocarbon mapping. One notable exception is highly transmissive hydrocarbons on Sentinel-2 data due to the non-conformity of spectral bands with key hydrocarbon absorptions and the relatively coarse bandwidth (> 100 nm).

Keywords: hydrocarbon, oil spill, remote sensing, hyperspectral, multispectral, hydrocarbon – substrate combination, Sentinel-2, WorldView-3

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Authors: F. Meskine, N. Taleb, M. Chikr El-Mezouar, K. Kpalma, A. Almhdie

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Image registration is the process of establishing point by point correspondence between images obtained from a same scene. This process is very useful in remote sensing, medicine, cartography, computer vision, etc. Then, the task of registration is to place the data into a common reference frame by estimating the transformations between the data sets. In this work, we develop a rigid point registration method based on the application of genetic algorithms and Hausdorff distance. First, we extract the feature points from both images based on the algorithm of global and local curvature corner. After refining the feature points, we use Hausdorff distance as similarity measure between the two data sets and for optimizing the search space we use genetic algorithms to achieve high computation speed for its inertial parallel. The results show the efficiency of this method for registration of satellite images.

Keywords: Feature extraction, Genetic algorithms, Hausdorff distance, Image registration, Point registration.

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Authors: K. Kajsanthia, J. Wittayakun, S. Prayoonpokarach

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An optical chemical sensing film based on immobilizing of 1,1′- diethyl 2,2′-cyanine (pseudocyanine iodide) in nafion film was developed for the determination of Fe(III). The sensing film was homogeneous, transparent, and mechanically stable. Decrease of the absorbance measured at 518 nm was observed when the sensing film was immersed in a solution of Fe(III). The optimum response of the sensing film to Fe(III) was obtained in a solution with pH 4.0. Linear calibration curve over an Fe(III) concentration range of 1-30 ppm with a limit of detection of 0.71 ppm was obtained. Cd(II) is the major interference. The sensing film exhibited good stability for 2 months and high reproducibility. The proposed method was applied for the determination of Fe(III) in water samples with satisfactory results.

Keywords: iron(III), _nafion, optical sensing film, pseudocyanine iodide

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Authors: Delphine Mukaneza, Lin Qiao, Wang Pengxin, Li Yan, Chen Yingyi

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Human activities on land use make the land-cover gradually change or transit. In this study, we examined the use of Landsat TM data to detect the land use change of Kigali between 1987 and 2009 using remote sensing techniques and analysis of data using ENVI and ArcGIS, a GIS software. Six different categories of land use were distinguished: bare soil, built up land, wetland, water, vegetation, and others. With remote sensing techniques, we analyzed land use data in 1987, 1999 and 2009, changed areas were found and a dynamic situation of land use in Kigali city was found during the 22 years studied. According to relevant Landsat data, the research focused on land use change in accordance with the role of remote sensing in the process of urbanization. The result of the work has shown the rapid increase of built up land between 1987 and 1999 and a big decrease of vegetation caused by the rebuild of the city after the 1994 genocide, while in the period of 1999 to 2009 there was a reduction in built up land and vegetation, after the authority of Kigali city established, a Master Plan where all constructions which were not in the range of the master Plan were destroyed. Rwanda's capital, Kigali City, through the expansion of the urban area, it is increasing the internal employment rate and attracts business investors and the service sector to improve their economy, which will increase the population growth and provide a better life. The overall planning of the city of Kigali considers the environment, land use, infrastructure, cultural and socio-economic factors, the economic development and population forecast, urban development, and constraints specification. To achieve the above purpose, the Government has set for the overall planning of city Kigali, different stages of the detailed description of the design, strategy and action plan that would guide Kigali planners and members of the public in the future to have more detailed regional plans and practical measures. Thus, land use change is significantly the performance of Kigali active human area, which plays an important role for the country to take certain decisions. Another area to take into account is the natural situation of Kigali city. Agriculture in the region does not occupy a dominant position, and with the population growth and socio-economic development, the construction area will gradually rise and speed up the process of urbanization. Thus, as a developing country, Rwanda's population continues to grow and there is low rate of utilization of land, where urbanization remains low. As mentioned earlier, the 1994 genocide massacres, population growth and urbanization processes, have been the factors driving the dramatic changes in land use. The focus on further research would be on analysis of Rwanda’s natural resources, social and economic factors that could be, the driving force of land use change.

Keywords: Land use change, urbanization, Kigali City, Landsat.

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Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

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Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: Cooperative networks, normalized capacity, sensing time.

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Authors: A. H. W. Goh, Y. S. Yong, C. H. Chan, S. J. Then, L. P. Chu, S. W. Chau, H. W. Hon

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This paper proposes an alternative control mechanism for an interactive Pan/Tilt/Zoom (PTZ) camera control system. Instead of using a mouse or a joystick, the proposed mechanism utilizes a Nintendo Wii remote and infrared (IR) sensor bar. The Wii remote has buttons that allows the user to control the movement of a PTZ camera through Bluetooth connectivity. In addition, the Wii remote has a built-in motion sensor that allows the user to give control signals to the PTZ camera through pitch and roll movement. A stationary IR sensor bar, placed at some distance away opposite the Wii remote, enables the detection of yaw movement. In addition, the Wii remote-s built-in IR camera has the ability to detect its spatial position, and thus generates a control signal when the user moves the Wii remote. Some experiments are carried out and their performances are compared with an industry-standard PTZ joystick.

Keywords: Bluetooth, Infrared, Pan/Tilt/Zoom, PTZ Camera, Visual Surveillance, Wii Remote

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Authors: Hidetoshi Nonaka, Masahito Kurihara

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In this paper, an authentication system using keystroke dynamics is presented. We introduced pressure sensing for the improvement of the accuracy of measurement and durability against intrusion using key-logger, and so on, however additional instrument is needed. As the result, it has been found that the pressure sensing is also effective for estimation of real moment of keystroke.

Keywords: Biometric authentication, Keystroke dynamics, Pressure sensing, Time-frequency analysis.

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Authors: Darwin Gouwanda, S. M. N. Arosha Senanayake, M. M. Danushka Ranjana Marasinghe, Mervin Chandrapal, Jeya Mithra Kumar, Tung Mun Hon, Yulius

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This paper presents a real time force sensing instrument that is designed for human gait analysis purposes. This instrument mainly consists of three main elements: the force sensing mat, signal conditioning and switching circuit and data acquisition device. In order to control and to process the incoming signals from the force sensing mat, Force-Logger and Force-Reloader program are developed using Labview 8.0. This paper describes the architecture of the force sensing mat, signal conditioning and switching circuit and the real time streaming of the incoming data from the force sensing mat.

Keywords: Force platform, Force sensing resistor, human gait analysis

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Authors: Abegunde Linda, Adedeji Oluwatola

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It has become an increasing evident that large development influences the climate. There are concerns that rising temperature over developed areas could have negative impact and increase living discomfort within city boundaries. Temperature trends in Ibadan city have received little attention, yet the area has experienced heavy urban expansion between 1972 and 2014. This research aims at examining the impact of landuse change on surface temperature knowing that the built-up environment absorb and store solar energy, resulting into the Urban Heat Island (UHI) effect. The Landsat imagery was used to examine the landuse change for a period of 42 years (1972-2014). Land Surface Temperature (LST) was obtained by converting the thermal band to a surface temperature map and zonal statistic analyses was used to examine the relationship between landuse and temperature emission. The results showed that the settlement area increased to a large extent while the area covered by vegetation reduced during the study period. The spatial and temporal trends of surface temperature are related to the gradual change in urban landuse/landcover and the settlement area has the highest emission. This research provides useful insight into the temporal behavior of the Ibadan city.

Keywords: Landuse, LST, Remote sensing, UHI.

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Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

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Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words, classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar.

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Authors: Weishou Shen, Dong Liu, Di Ji, Haoyun Shen, Naifeng Lin

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Based on the field investigation and long term remote sensing data, the dynamics of the alpine wetland in the river basin and their response to climate change were studied. Results showed the alpine wetlands accounted for 3.73% of total basin in 2010. Lake and river appeared an increasing trend in the past 30 years, with an increase of 34.36 % and 24.57%. However, swamp exhibited a tendency of decreasing with 233.74 km2. Annual average temperature, maximum temperature, minimum temperature and precipitation in the river basin all exhibited an increasing trend, whereas relative humidity exhibited a decreasing trend. Ice and snow melting are main reasons of lake and river area enhancement and swamp area descend. There existed 91.78%-97.86% of reduced swamp converted into lakes on the basis of remote sensing image interpretation. China-s government policy of implementing development in the river basin is the major driving force of artificial wetland growth.

Keywords: alpine wetland dynamics, climate change, Yarlung Zangbo River basin

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Authors: Sankaran Rajendran

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Remote sensing plays a vital role in mapping of resources and monitoring of environments of the earth. In the present research study, mapping and monitoring of clay siltations occurred in the Alkhod Dam of Muscat, Sultanate of Oman are carried out using low-cost multispectral Landsat and ASTER data. The dam is constructed across the Wadi Samail catchment for ground water recharge. The occurrence and spatial distribution of siltations in the dam are studied with five years of interval from the year 1987 of construction to 2014. The deposits are mainly due to the clay, sand and silt occurrences derived from the weathering rocks of ophiolite sequences occurred in the Wadi Samail catchment. The occurrences of clays are confirmed by minerals identification using ASTER VNIR-SWIR spectral bands and Spectral Angle Mapper supervised image processing method. The presence of clays and their spatial distribution are verified in the field. The study recommends the technique and the low-cost satellite data to similar region of the world.

Keywords: Alkhod Dam, ASTER Siltation, Landsat, Remote Sensing, Oman.

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Authors: Hoda Zolfagharnejad, Behnam Kamkar, Omid Abdi

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Crop coefficient (Kc) is an important factor contributing to estimation of evapotranspiration, and is also used to determine the irrigation schedule. This study investigated and determined the monthly Kc of winter wheat (Triticum aestivum L.) using five vegetation indices (VIs): Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI), Soil Adjusted Vegetation Index (SAVI), Infrared Percentage Vegetation Index (IPVI), and Ratio Vegetation Index (RVI) of four basins in Golestan province, Iran. 14 Landsat-8 images according to crop growth stage were used to estimate monthly Kc of wheat. VIs were calculated based on infrared and near infrared bands of Landsat 8 images using Geographical Information System (GIS) software. The best VIs were chosen after establishing a regression relationship among these VIs with FAO Kc and Kc that was modified for the study area by the previous research based on R² and Root Mean Square Error (RMSE). The result showed that local modified SAVI with R²= 0.767 and RMSE= 0.174 was the best index to produce monthly wheat Kc maps.

Keywords: Crop coefficient, remote sensing, vegetation indices, wheat.

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Authors: Afzeri, A.G.E Sujtipto, R. Muhida, M. Konneh, Darmawan

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Increasing the demand for effectively use of the production facility requires the tools for sharing the manufacturing facility through remote operation of the machining process. This research introduces the methodology of machining technology for direct remote operation of networked milling machine. The integrated tools with virtual simulation, remote desktop protocol and Setup Free Attachment for remote operation of milling process are proposed. Accessing and monitoring of machining operation is performed by remote desktop interface and 3D virtual simulations. Capability of remote operation is supported by an auto setup attachment with a reconfigurable pin type setup free technology installed on the table of CNC milling machine to perform unattended machining process. The system is designed using a computer server and connected to a PC based controlled CNC machine for real time monitoring. A client will access the server through internet communication and virtually simulate the machine activity. The result has been presented that combination between real time virtual simulation and remote desktop tool is enabling to operate all machine tool functions and as well as workpiece setup..

Keywords: Remote Desktop, PC Based CNC, Remote Machining.

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Authors: A. Junpen, S. Garivait, S. Bonnet, A. Pongpullponsak

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The forest fires in Thailand are annual occurrence which is the cause of air pollutions. This study intended to estimate the emission from forest fire during 2005-2009 using MODerateresolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites, experimental data, and statistical data. The forest fire emission is estimated using equation established by Seiler and Crutzen in 1982. The spatial and temporal variation of forest fire emission is analyzed and displayed in the form of grid density map. From the satellite data analysis suggested between 2005 and 2009, the number of fire hotspots occurred 86,877 fire hotspots with a significant highest (more than 80% of fire hotspots) in the deciduous forest. The peak period of the forest fire is in January to May. The estimation on the emissions from forest fires during 2005 to 2009 indicated that the amount of CO, CO2, CH4, and N2O was about 3,133,845 tons, 47,610.337 tons, 204,905 tons, and 6,027 tons, respectively, or about 6,171,264 tons of CO2eq. They also emitted 256,132 tons of PM10. The year 2007 was found to be the year when the emissions were the largest. Annually, March is the period that has the maximum amount of forest fire emissions. The areas with high density of forest fire emission were the forests situated in the northern, the western, and the upper northeastern parts of the country.

Keywords: Emissions, Forest fire, Remote sensing information.

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Authors: Tallataf Rasheed, Adnan Rashdi, Ahmad Naeem Akhtar

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The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.

Keywords: Cognitive radio, spectrum sensing, energy detector, reliability factors, fuzzy logic.

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Authors: Keunhong Chae, Youngpo Lee, Seokho Yoon

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In cognitive radio (CR) systems, the primary user (PU) signal would randomly depart or arrive during the sensing period of a CR user, which is referred to as the high traffic environment. In this paper, we propose a novel spectrum sensing scheme based on the cyclostationarity of PU signals in high traffic environments. Specifically, we obtain a test statistic by applying an estimate of spectral autocoherence function of the PU signal to the generalized- likelihood ratio. From numerical results, it is confirmed that the proposed scheme provides a better spectrum sensing performance compared with the conventional spectrum sensing scheme based on the energy of the PU signals in high traffic environments.

Keywords: Spectrum sensing, cyclostationarity, high traffic environments.

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Authors: Bernard Kumi-Boateng, Issaka Yakubu

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Forest fire, which is, an uncontrolled fire occurring in nature has become a major concern for the Forestry Commission of Ghana (FCG). The forest fires in Ghana usually result in massive destruction and take a long time for the firefighting crews to gain control over the situation. In order to assess the effect of forest fire at local scale, it is important to consider the role fire plays in vegetation composition, biodiversity, soil erosion, and the hydrological cycle. The occurrence, frequency and behaviour of forest fires vary over time and space, primarily as a result of the complicated influences of changes in land use, vegetation composition, fire suppression efforts, and other indigenous factors. One of the forest zones in Ghana with a high level of vegetation stress is the Goaso forest area. The area has experienced changes in its traditional land use such as hunting, charcoal production, inefficient logging practices and rural abandonment patterns. These factors which were identified as major causes of forest fire, have recently modified the incidence of fire in the Goaso area. In spite of the incidence of forest fires in the Goaso forest area, most of the forest services do not provide a cartographic representation of the burned areas. This has resulted in significant amount of information being required by the firefighting unit of the FCG to understand fire risk factors and its spatial effects. This study uses Remote Sensing and Geographic Information System techniques to develop a fire risk hazard model using the Goaso Forest Area (GFA) as a case study. From the results of the study, natural forest, agricultural lands and plantation cover types were identified as the major fuel contributing loads. However, water bodies, roads and settlements were identified as minor fuel contributing loads. Based on the major and minor fuel contributing loads, a forest fire risk hazard model with a reasonable accuracy has been developed for the GFA to assist decision making.

Keywords: Forest risk, GIS, remote sensing, Goaso.

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Authors: M. Ranjeeth, S. Anuradha

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Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. In this paper we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m fading channels with the simulation results using energy detection based spectrum sensing. The numerical results are plotted as Pf Vs Pd for different SNR values, fading parameters. It is observed that Nakagami fading channel performance is better than other fading channels by using energy detection in spectrum sensing. A MATLAB simulation test bench has been implemented to know the performance of energy detection in different fading channel environment.

Keywords: Spectrum sensing, Energy detection, fading channels, Probability of detection, probability of false alarm.

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Authors: Rhoda M. Darkwah, Patrick B. Cobbinah

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Urban greenery remains the bastion of urban landscape and a key to sustainable development due to its integral connections to the general health and wellbeing of urban residents. However, in an era of rapid urbanisation, recent studies indicate that urban greenery, especially ecologically sensitive areas, in many African cities is becoming increasingly depleted. Given the scale and rate of natural and anthropogenic change, effective management of urban greenery as the ultimate goal of restoring depleting urban landscapes is urgent. This review advocates for an urban resilience model to managing urban greenery.

Keywords: Green spaces, resilience, urbanisation, urban greenery.

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Authors: F. F. Howard, C. B. Boye, I. Yakubu, J. S. Y. Kuma

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One of the ways that could be used for the production of land use and land cover maps by a procedure known as image classification is the use of the remote sensing technique. Numerous elements ought to be taken into consideration, including the availability of highly satisfactory Landsat imagery, secondary data and a precise classification process. The goal of this study was to classify and map the land use and land cover of the study area using remote sensing and Geospatial Information System (GIS) analysis. The classification was done using Landsat 8 satellite images acquired in December 2020 covering the study area. The Landsat image was downloaded from the USGS. The Landsat image with 30 m resolution was geo-referenced to the WGS_84 datum and Universal Transverse Mercator (UTM) Zone 30N coordinate projection system. A radiometric correction was applied to the image to reduce the noise in the image. This study consists of two sections: the Land Use/Land Cover (LULC) and Accuracy Assessments using the confusion and contingency matrix and the Kappa coefficient. The LULC classifications were vegetation (agriculture) (67.87%), water bodies (0.01%), mining areas (5.24%), forest (26.02%), and settlement (0.88%). The overall accuracy of 97.87% and the kappa coefficient (K) of 97.3% were obtained for the confusion matrix. While an overall accuracy of 95.7% and a Kappa coefficient of 0.947 were obtained for the contingency matrix, the kappa coefficients were rated as substantial; hence, the classified image is fit for further research.

Keywords: Confusion Matrix, contingency matrix, kappa coefficient, land used/ land cover, accuracy assessment.

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Authors: Sanaeinejad, S. H.; A. Astaraei, . P. Mirhoseini.Mousavi, M. Ghaemi,

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One of the main environmental problems which affect extensive areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Neyshaboor area, North East of Iran was selected as a field study of this research. Landsat satellite images for this area were used in order to prepare suitable learning samples for processing and classifying the images. 300 locations were selected randomly in the area to collect soil samples and finally 273 locations were reselected for further laboratory works and image processing analysis. Electrical conductivity of all samples was measured. Six reflective bands of ETM+ satellite images taken from the study area in 2002 were used for soil salinity classification. The classification was carried out using common algorithms based on the best composition bands. The results showed that the reflective bands 7, 3, 4 and 1 are the best band composition for preparing the color composite images. We also found out, that hybrid classification is a suitable method for identifying and delineation of different salinity classes in the area.

Keywords: Soil salinity, Remote sensing, Image processing, ETM+, Nyshaboor

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Authors: Toyomi Fujita

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This paper presents a sensing system for 3D sensing and mapping by a tracked mobile robot with an arm-type sensor movable unit and a laser range finder (LRF). The arm-type sensor movable unit is mounted on the robot and the LRF is installed at the end of the unit. This system enables the sensor to change position and orientation so that it avoids occlusions according to terrain by this mechanism. This sensing system is also able to change the height of the LRF by keeping its orientation flat for efficient sensing. In this kind of mapping, it may be difficult for moving robot to apply mapping algorithms such as the iterative closest point (ICP) because sets of the 2D data at each sensor height may be distant in a common surface. In order for this kind of mapping, the authors therefore applied interpolation to generate plausible model data for ICP. The results of several experiments provided validity of these kinds of sensing and mapping in this sensing system.

Keywords: Laser Range Finder, Arm-Type Sensor Movable Unit, Tracked Mobile Robot, 3D Mapping.

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Authors: M. C. Proença

Abstract:

The tools described in this paper enable the location of burned areas where took place the annihilation of natural habitats and establishes a baseline for major changes in forest ecosystems during recovery. Moreover, the result allows the follow up of the surface fuel loading, allowing the evaluation and guidance of restoration measures to remote areas by phased time planning. This case study implements the evaluation of burned areas that suffered successive wildfires in Portugal mainland during the summer of 2017, killing more than 60 people. The goal is to show that this evaluation can be done with remote sense data free of charges in a simple laptop, with open-source software, describing the not-so-simple methodology step by step, to make it accessible for local workers in the areas attained, where the availability of information is essential for the immediate planning of mitigation measures, such as restoring road access, allocate funds for the recovery of human dwellings and assess further needs for restoration of the ecological system. Wildfires also devastate forest ecosystems having a direct impact on vegetation cover and killing or driving away the animal population, besides loss of all crops in rural areas that are essential as local resources. The economic interests are also attained, as the pinewood burned becomes useless for the noblest applications, so its value decreases, and resin extraction ends for several years.

Keywords: Image processing, remote sensing, wildfires, burned areas, SENTINEL-2.

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Authors: Hansung Wan, Hyungkwan Cho, Kiho Sung, Hongkyu Kim

Abstract:

The amount of urban artificial heat which affects the urban temperature rise in urban meteorology was investigated in order to clarify the relationships between urbanization and urban meteorology in this study. The results of calculation to identify how urban temperate was increased through the establishment of a model for measuring the amount of urban artificial heat and theoretical testing revealed that the amount of urban artificial heat increased urban temperature by plus or minus 0.23 ˚ C in 2007 compared with 1996, statistical methods (correlation and regression analysis) to clarify the relationships between urbanization and urban weather were as follows. New design techniques and urban growth management are necessary from urban growth management point of view suggested from this research at city design phase to decrease urban temperature rise and urban torrential rain which can produce urban disaster in terms of urban meteorology by urbanization.

Keywords: The amount of urban artificial heat, Urban growth management, Urbanization, Urban meteorology

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Authors: Gulam Mohiuddin, Jan-Peter Mund

Abstract:

This study assessed the correlation between Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) in Phnom Penh City (Cambodia) from 2016 to 2020. Understanding the LST and NDVI can be helpful to understand the Urban Heat Island (UHI) scenario, and it can contribute to planning urban greening and combating the effects of UHI. The study used Landsat-8 images as the data for analysis. They have 100 m spatial resolution (per pixel) in the thermal band. The current study used an approach for the statistical analysis that considers every pixel from the study area instead of taking few sample points or analyzing descriptive statistics. Also, this study is examining the correlation between NDVI and LST with a spatially explicit approach. The study found a strong negative correlation between NDVI and LST (coefficient range -0.56 to -0.59), and this relationship is linear. This study showed a way to avoid the probable error from the sample-based approach in examining two spatial variables. The method is reproducible for a similar type of analysis on the correlation between spatial phenomena. The findings of this study will be used further to understand the causation behind LST change in that area triangulating LST, NDVI and land-use changes.

Keywords: Land Surface Temperature, NDVI, Normalized Difference Vegetation Index, remote sensing, methodological development.

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