Search results for: non-contact sensing

Authors: A. Kabir, D. Boulainine, I. Bouanane, N. Benslim, B. Boudjema, C. Sedrati

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SnO₂ is an n-type semiconductor with a direct gap of about 3.6 eV. It is largely used in several domains such as nanocrystalline photovoltaic cells. Due to its interesting physic-chemical properties, this material was elaborated in thin film forms using different deposition techniques. It was found that SnO₂ properties were directly affected by the deposition method parameters. In this work, the RGTO method (Rheotaxial Growth and Thermal Oxidation) was used to deposit elaborate SnO₂ thin films. This technique consists on thermal oxidation of the Sn films deposited onto a substrate heated to a temperature close to Sn melting point (232°C). Such process allows the preparation of high porosity tin oxide films which are very suitable for the gas sensing. The films structural, morphological and optical properties pre and post thermal oxidation were studied using X-ray diffraction (XRD), scanning electron microscopy (SEM), UV-Visible spectroscopy and Fourier transform infrared spectroscopy (FTIR) respectively. XRD patterns showed a polycrystalline structure of the cassiterite phase of SnO₂. The grain growth was found affected by the oxidation temperature. This grain size evolution was confronted to existing grain growth models in order to understand the growth mechanism. From SEM images, the as deposited Sn film was formed of difference diameter spherical agglomerations. As a function of the oxidation temperature, these spherical agglomerations shape changed due to the introduction of oxygen ions. The deformed spheres started to interconnect by forming bridges between them. The volume porosity, determined from the UV-Visible reflexion spectra, Changes as a function of the oxidation temperature. The variation of the crystalline fraction, determined from FTIR spectra, correlated with the variation of both the grain size and the volume porosity.

Keywords: tin oxide, RGTO, grain growth, volume porosity, crystalline fraction

Procedia PDF Downloads 258

Authors: Muhammad Zainuddin Arriafdi, Hamudah Hakimah Abdullah, Mohd Helmi Sani, Wan Azlina Ahmad, Muhd Nazrul Hisham Zainal Alam

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The biotechnology process development demands numerous experimental works. In laboratory environment, this is typically carried out using a shake flask platform. This paper presents the design and fabrication of a miniature bioreactor system as an alternative research tool for bioprocessing. The working volume of the reactor is 100 ml, and it is made of plastic. The main features of the reactor included stirring control, temperature control via the electrical heater, aeration strategy through a miniature air compressor, and online optical cell density (OD) sensing. All sensors and actuators integrated into the reactor was controlled using an Arduino microcontroller platform. In order to demonstrate the functionality of such miniature bioreactor concept, series of batch Saccharomyces cerevisiae fermentation experiments were performed under various glucose concentrations. Results attained from the fermentation experiments were utilized to solve the Monod equation constants, namely the saturation constant, Ks, and cells maximum growth rate, μmax as to further highlight the usefulness of the device. The mixing capacity of the reactor was also evaluated. It was found that the results attained from the miniature bioreactor prototype were comparable to results achieved using a shake flask. The unique features of the device as compared to shake flask platform is that the reactor mixing condition is much more comparable to a lab-scale bioreactor setup. The prototype is also integrated with an online OD sensor, and as such, no sampling was needed to monitor the progress of the reaction performed. Operating cost and medium consumption are also low and thus, making it much more economical to be utilized for biotechnology process development compared to lab-scale bioreactors.

Keywords: biotechnology, miniature bioreactor, research tools, Saccharomyces cerevisiae

Procedia PDF Downloads 117

Authors: Jiwon Lee, Yeong-Ju Go, Jong-Soo Choi

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Drones were first developed for military use and were used in World War 1. But recently drones have been used in a variety of fields. Several companies actively utilize drone technology to strengthen their services, and in agriculture, drones are used for crop monitoring and sowing. Other people use drones for hobby activities such as photography. However, as the range of use of drones expands rapidly, problems caused by drones such as improperly flying, privacy and terrorism are also increasing. As the need for monitoring and tracking of drones increases, researches are progressing accordingly. The drone detection system estimates the position of the drone using the physical phenomena that occur when the drones fly. The drone detection system measures being developed utilize many approaches, such as radar, infrared camera, and acoustic detection systems. Among the various drone detection system, the acoustic detection system is advantageous in that the microphone array system is small, inexpensive, and easy to operate than other systems. In this paper, the acoustic signal is acquired by using minimum microphone when drone is flying, and direction of drone is estimated. When estimating the Direction of Arrival(DOA), there is a method of calculating the DOA based on the Time Difference of Arrival(TDOA) and a method of calculating the DOA based on the beamforming. The TDOA technique requires less number of microphones than the beamforming technique, but is weak in noisy environments and can only estimate the DOA of a single source. The beamforming technique requires more microphones than the TDOA technique. However, it is strong against the noisy environment and it is possible to simultaneously estimate the DOA of several drones. When estimating the DOA using acoustic signals emitted from the drone, it is impossible to measure the position of the drone, and only the direction can be estimated. To overcome this problem, in this work we show how to estimate the position of drones by arranging multiple microphone arrays. The microphone array used in the experiments was four tetrahedral microphones. We simulated the performance of each DOA algorithm and demonstrated the simulation results through experiments.

Keywords: acoustic sensing, direction of arrival, drone detection, microphone array

Procedia PDF Downloads 160

Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

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A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

Procedia PDF Downloads 130

Authors: Muhittin Karaman, Murat Budakoglu

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In this study, derivation of lake bathymetry was evaluated using the high resolution Worldview-2 multispectral images in the very shallow hypersaline Lake Acıgöl which does not have a stable water table due to the wet-dry season changes and industrial usage. Every year, a great part of the lake water budget has been consumed for the industrial salt production in the evaporation ponds, which are generally located on the south and north shores of Lake Acıgöl. Therefore, determination of the water level changes from a perspective of remote sensing-based lake water by bathymetry studies has a great importance in the sustainability-control of the lake. While the water table interval is around 1 meter between dry and wet season, dissolved ion concentration, salinity and turbidity also show clear differences during these two distinct seasonal periods. At the same time, with the satellite data acquisition (June 9, 2013), a field study was conducted to collect the salinity values, Secchi disk depths and turbidity levels. Max depth, Secchi disk depth and salinity were determined as 1,7 m, 0,9 m and 43,11 ppt, respectively. Eight-band Worldview-2 image was corrected for atmospheric effects by ATCOR technique. For each sampling point in the image, mean reflectance values in 1*1, 3*3, 5*5, 7*7, 9*9, 11*11, 13*13, 15*15, 17*17, 19*19, 21*21, 51*51 pixel reflectance neighborhoods were calculated separately. A unique image has been derivated for each matrix resolution. Spectral values and depth relation were evaluated for these distinct resolution images. Correlation coefficients were determined for the 1x1 matrix: 0,98, 0,96, 0,95 and 0,90 for the 724 nm, 831 nm, 908 nm and 659 nm, respectively. While 15x5 matrix characteristics with 0,98, 0,97 and 0,97 correlation values for the 724 nm, 908 nm and 831 nm, respectively; 51x51 matrix shows 0,98, 0,97 and 0,96 correlation values for the 724 nm, 831 nm and 659 nm, respectively. Comparison of all matrix resolutions indicates that RedEdge band (724 nm) of the Worldview-2 satellite image has the best correlation with the saline shallow lake of Acıgöl in-situ depth.

Keywords: bathymetry, Worldview-2 satellite image, ATCOR technique, Lake Acıgöl, Denizli, Turkey

Procedia PDF Downloads 447

Authors: Mohsen Adabi, Mahdi Adabi, Reza Saber

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The recent advancements in nanomaterials have provided a platform to develop efficient transduction matrices for sensors. Modified electrodes allow to electrochemists to enhance the property of electrode surface and provide desired properties such as improved sensing capabilities, higher electron transfer rate and prevention of undesirable reactions competing kinetically with desired electrode process. Nanostructured electrodes including arrays of carbon nanotubes have demonstrated great potential for the development of electrochemical sensors and biosensors. The aim of this work is to evaluate the concentration of multi-walled carbon nanotubes (MWCNTs) on the conductivity of gold electrode. For this work, raw MWCNTs was functionalized and shortened. Raw and shorten MWCNTs were characterized using transfer electron microscopy (TEM). Next, 0.5, 2 and 3.5 mg of Shortened and functionalized MWCNTs were dispersed in 2 mL Dimethyl formamide (DMF) and cysteamine modified gold electrodes were incubated in the different concentrations of MWCNTs for 8 hours. Then, the immobilization of MWCNTs on cysteamine modified gold electrode was characterized by scanning electron microscopy (SEM) and the effect of MWCNT concentrations on electron transfer of modified electrodes was investigated by cyclic voltammetry (CV). The results demonstrated that CV response of ferricyanide redox at modified gold electrodes increased as concentration of MWCNTs enhanced from 0.5 to 2 mg in 2 mL DMF. This increase can be attributed to the number of MWCNTs which enhance on the surface of cysteamine modified gold electrode as the MWCNTs concentration increased whereas CV response of ferricyanide redox at modified gold electrodes did not changed significantly as the MWCNTs concentration increased from 2 to 3.5 mg in 2 mL DMF. The reason may be that amine groups of cysteamine modified gold electrodes are limited to a given number which can interact with the given number of carboxylic groups of MWCNTs and CV response of ferricyanide redox at modified gold do not enhance after amine groups of cysteamine are saturated with carboxylic groups of MWCNTs.

Keywords: carbon nanotube, cysteamine, electrochemical sensor, gold electrode

Procedia PDF Downloads 467

Authors: Shringika Soni, Utkarsh Jain, Nidhi Chauhan

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Aptamers are recently discovered ~80-100 bp long artificial oligonucleotides that not only demonstrated their applications in therapeutics; it is tremendously used in diagnostic and sensing application to detect different biomarkers and drugs. Synthesizing aptamers for proteins or genomic template is comparatively feasible in laboratory, but drugs or other chemical target based aptamers require major specification and proper optimization and validation. One has to optimize all selection, amplification, and characterization steps of the end product, which is extremely time-consuming. Therefore, we performed asymmetric PCR (polymerase chain reaction) for random oligonucleotides pool synthesis, and further use them in Systematic evolution of ligands by exponential enrichment (SELEX) for anti-psychotic drugs based aptamers synthesis. Anti-psychotic drugs are major tranquilizers to control psychosis for proper cognitive functions. Though their low medical use, their misuse may lead to severe medical condition as addiction and can promote crime in social and economical impact. In this work, we have approached the in-vitro SELEX method for ssDNA synthesis for anti-psychotic drugs (in this case ‘target’) based aptamer synthesis. The study was performed in three stages, where first stage included synthesis of random oligonucleotides pool via asymmetric PCR where end product was analyzed with electrophoresis and purified for further stages. The purified oligonucleotide pool was incubated in SELEX buffer, and further partition was performed in the next stage to obtain target specific aptamers. The isolated oligonucleotides are characterized and quantified after each round of partition, and significant results were obtained. After the repetitive partition and amplification steps of target-specific oligonucleotides, final stage included sequencing of end product. We can confirm the specific sequence for anti-psychoactive drugs, which will be further used in diagnostic application in clinical and forensic set-up.

Keywords: anti-psychotic drugs, aptamer, biosensor, ssDNA, SELEX

Procedia PDF Downloads 134

Authors: Saleh Nabiyev

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Renewable energy is becoming increasingly important in today's world due to its significant impact on the green economy, ecology, environment, and climate change. Renewable energy sources, such as solar and wind, are clean and sustainable, making them an ideal solution to reduce carbon emissions and mitigate the effects of climate change. The Karabakh region is located in the South Caucasus and covers an area of approximately 11,500 km². The region has a mountainous terrain, which can affect the availability of wind and solar resources. The Karabakh region has significant wind power potential, particularly in its mountainous areas where wind speeds are typically higher. According to a study conducted by the European Commission Joint Research Centre, the average wind speed in the Karabakh region is between 4 and 6 meters per second (m/s) at a height of 50 meters above ground level (AGL). However, wind speeds can be higher in some areas, reaching up to 10 m/s in some mountainous areas. The region also has significant solar power potential, with an average of 2,000 to 2,200 hours of sunshine per year. The region's high altitude and clear skies make it particularly suitable for the development of solar power projects. In this research, the application of satellite images, solar radiation, wind speed and direction, as well as various other materials to determine suitable areas for alternative energy sources, is investigated. The methodology for selecting suitable locations for solar and wind energy consists of four main parts: identification of factors, evaluation of factors, data preparation, and application of suitability analysis. At the end of the research, the territory of the Kalbajar and Lachin districts is suitable for wind energy. The southern plain part of Karabakh is highly evaluated in terms of solar energy potential, especially Jabrayil district. Generally, outcomes taken from this research are essential data for increasing of rational using natural resources, as well as combating climate change.

Keywords: GIS, remote sensing, suitability analysis, solar energy, wind energy

Procedia PDF Downloads 31

Authors: Yu-Cheng Chen, Tzu-Ping Lin, Feng-Yi Lin, Chih-Yu Chen

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Due to the urban heat island effect caused by highly development of city, the heat stress increased in recent year rapidly. Resulting in a sharp raise of the energy used in urban area. The heat stress during summer time exacerbated the usage of air conditioning and electric equipment, which caused more energy consumption and anthropogenic heat. Therefore, an accurate and simple method to measure energy used in urban area can be helpful for the architectures and urban planners to develop better energy efficiency goals. This research applies the combination of airborne LiDAR data and thermal imager to provide an innovate method to estimate energy consumption. Owing to the high resolution of remote sensing data, the accurate current volume and total floor area and the surface temperature of building derived from LiDAR and thermal imager can be herein obtained to predict energy used. In the estimate process, the LiDAR data will be divided into four type of land cover which including building, road, vegetation, and other obstacles. In this study, the points belong to building were selected to overlay with the land use information; therefore, the energy consumption can be estimated precisely with the real value of total floor area and energy use index for different use of building. After validating with the real energy used data from the government, the result shows the higher building in high development area like commercial district will present in higher energy consumption, caused by the large quantity of total floor area and more anthropogenic heat. Furthermore, because of the surface temperature can be warm up by electric equipment used, this study also applies the thermal image of building to find the hot spots of energy used and make the estimation method more complete.

Keywords: urban heat island, urban planning, LiDAR, thermal imager, energy consumption

Procedia PDF Downloads 239

Authors: Pebri Nurhayati, Rozanah Ahlam Fadiyah

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In the development of the city often use rural areas that can not be separated from the change in land use that lead to the degradation of urban green space in the city fringe. In the long run, the degradation of green open space this can impact on the decline of ecological, psychological and public health. Therefore, this research aims to (1) determine the relationship between the parameters of the degradation rate of urban development with green space, (2) develop a spatial model of the impact of urban development on the degradation of green open space with remote sensing techniques and Geographical Information Systems in an integrated manner. This research is a descriptive research with data collection techniques of observation and secondary data . In the data analysis, to interpret the direction of urban development and degradation of green open space is required in 2005-2010 ASTER image with NDVI. Of interpretation will generate two maps, namely maps and map development built land degradation green open space. Secondary data related to the rate of population growth, the level of accessibility, and the main activities of each city map is processed into a population growth rate, the level of accessibility maps, and map the main activities of the town. Each map is used as a parameter to map the degradation of green space and analyzed by non-parametric statistical analysis using Crosstab thus obtained value of C (coefficient contingency). C values were then compared with the Cmaximum to determine the relationship. From this research will be obtained in the form of modeling spatial map of the City Development Impact Degradation Green Space in Urban Fringe eastern city of Yogyakarta 2005-2010. In addition, this research also generate statistical analysis of the test results of each parameter to the degradation of green open space in the Urban Fringe eastern city of Yogyakarta 2005-2010.

Keywords: spatial analysis, urban development, degradation of green space, urban fringe

Procedia PDF Downloads 313

Authors: Abdullah Alenezi, Mane Alsudrawi, Rafat Misak

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Kuwait is faced with a potentially wide and harmful range of both natural and anthropogenic hazardous events such as dust storms, floods, fires, nuclear accidents, earthquakes, oil spills, tsunamis and other disasters. For Kuwait can be highly vulnerable to these complex environmental risks, an up-to-date and in-depth understanding of their typology, genesis, and impact on the Kuwaiti society is needed. Adequate anticipation and management of environmental crises further require a comprehensive system of decision support to the benefit of decision makers to further bridge the gap between (technical) risk understanding and public action. For that purpose, the Kuwait Institute for Scientific Research (KISR), intends to establish a decision support center for management of the environmental crisis in Kuwait. The center will support policy makers, stakeholders and national committees with technical information that helps them efficiently and effectively assess, monitor to manage environmental disasters using decision support tools. These tools will build on state of the art quantification and visualization techniques, such as remote sensing information, Geographical Information Systems (GIS), simulation and prediction models, early warning systems, etc. The center is conceived as a central facility which will be designed, operated and managed by KISR in coordination with national authorities and decision makers of the country. Our vision is that by 2035 the center will be recognized as a leading national source of scientific advice on national risk management in Kuwait and build unity of effort among Kuwaiti’s institutions, government agencies, public and private organizations through provision and sharing of information. The project team now focuses on capacity building through upgrading some KISR facilities manpower development, build strong collaboration with international alliance.

Keywords: decision support, environment, hazard, Kuwait

Procedia PDF Downloads 313

Authors: Muhammad Nasar-u-Minallah, Dagmar Haase, Salman Qureshi

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In a rapidly growing developing country cities are becoming more urbanized leading to modifications in urban climate. Rapid urbanization, especially unplanned urban land expansion, together with climate change has a profound impact on the urban settlement and urban thermal environment. Cities, particularly Pakistan are facing remarkably environmental issues and uneven development, and thus it is important to strengthen the investigation of urban environmental pressure brought by land-use changes and urbanization. The present study investigated the long term modification of the urban environment by urbanization utilizing Spatio-temporal dynamics of land-use change, urban population data, urban heat islands, monthly maximum, and minimum temperature of thirty years, multi remote sensing imageries, and spectral indices such as Normalized Difference Built-up Index and Normalized Difference Vegetation Index. The results indicate rapid growth in an urban built-up area and a reduction in vegetation cover in the last three decades (1990-2020). A positive correlation between urban heat islands and Normalized Difference Built-up Index, whereas a negative correlation between urban heat islands and the Normalized Difference Vegetation Index clearly shows how urbanization is affecting the local environment. The increase in air and land surface temperature temperatures is dangerous to human comfort. Practical approaches, such as increasing the urban green spaces and proper planning of the cities, have been suggested to help prevent further modification of the urban thermal environment by urbanization. The findings of this work are thus important for multi-sectorial use in the cities of Pakistan. By taking into consideration these results, the urban planners, decision-makers, and local government can make different policies to mitigate the urban land use impacts on the urban thermal environment in Pakistan.

Keywords: land use, urban environment, local climate, Lahore

Procedia PDF Downloads 111

Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 222

Authors: Khalifa Abdunaser, Salem Eljawashi

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Study area is threatened by numerous petroleum activities. The most important risk is associated with dramatic dangers of misuse and oil and gas pollutions, such as significant volumes of produced water, which refers to waste water generated during the production of oil and natural gas and disposed on the surface surrounded oil and gas fields. This work concerns the impact of oil exploration and production activities on the physical and environment fate of the area, focusing on the investigation and observation of crude oil migration as toxic fluid. Its penetration in groundwater resulted from the produced water impacted by oilfield operations disposed to the earth surface in Al Wahat area. Describing the areal distribution of the dominant groundwater quality constituents has been conducted to identify the major hydro-geochemical processes that affect the quality of water and to evaluate the relations between rock types and groundwater flow to the quality and geochemistry of water in Post-Eocene aquifer. The chemical and physical characteristics of produced water, where it is produced, and its potential impacts on the environment and on oil and gas operations have been discussed. Field work survey was conducted to identify and locate a large number of monitoring wells previously drilled throughout the study area. Groundwater samples were systematically collected in order to detect the fate of spills resulting from the various activities at the oil fields in the study area. Spatial distribution maps of the water quality parameters were built using Kriging methods of interpolation in ArcMap software. Thematic maps were generated using GIS and remote sensing techniques, which were applied to include all these data layers as an active database for the area for the purpose of identifying hot spots and prioritizing locations based on their environmental conditions as well as for monitoring plans.

Keywords: Sirt Basin, produced water, Al Wahat area, Ground water

Procedia PDF Downloads 142

Authors: Raheleh Farzanmanesh, Christopher J. Weston

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Mangroves are forest ecosystems located in the inter-tidal regions of tropical and subtropical coastlines that provide many valuable economic and ecological benefits for millions of people, such as preventing coastal erosion, providing breeding, and feeding grounds, improving water quality, and supporting the well-being of local communities. In addition, mangroves capture and store high amounts of carbon in biomass and soils that play an important role in combating climate change. The decline in mangrove area has prompted government and private sector interest in mangrove conservation and restoration projects to achieve multiple Sustainable Development Goals, from reducing poverty to improving life on land. Mangrove aboveground biomass plays an essential role in the global carbon cycle, climate change mitigation and adaptation by reducing CO2 emissions. However, little information is available about the effectiveness of mangrove sustainable management on mangrove change area and aboveground biomass (AGB). Here, we proposed a method for mapping, modeling, and assessing mangrove area and AGB in two Global Environment Facility (GEF) blue forests projects based on Sentinel-2 Level 1C imagery during their conservation lifetime. The SVR regression model was used to estimate AGB in Tahiry Honko project in Madagascar and the Abu Dhabi Blue Carbon Demonstration Project (Abu Dhabi Emirates. The results showed that mangrove forests and AGB declined in the Tahiry Honko project, while in the Abu Dhabi project increased after the conservation initiative was established. The results provide important information on the impact of mangrove conservation activities and contribute to the development of remote sensing applications for mapping and assessing mangrove forests in blue carbon initiatives.

Keywords: blue carbon, mangrove forest, REDD+, aboveground biomass, Sentinel-2

Procedia PDF Downloads 73

Authors: Anuja Singh, Avik K. Pati, Ashok K. Mishra

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Organic fluorophores with π-conjugated scaffolds are important because of their interesting optoelectronic properties. In recent years, our lab has been engaged in understanding the photophysics of small diacetylene bridged fluorophores and found the diynes as a promising class of π-conjugated fluorophores. Building on this understanding, recently we have focused on the photophysics of a less explored class of cross-conjugated Y-shaped enediynes (one double and two triple bonds). Here we present the photophysical properties of such enediynes which show interesting photophysical properties that include dual emissions from locally excited (LE) and intramolecular charge transfer (ICT) states and ring size dependent aggregate fluorescence in non-aqueous media. The dyes also show prominent aggregate fluorescence in mixed-aqueous solvents and solid powder form. We further show that the solid state fluorescence can be reversibly switched multiple of cycles by external stimuli, highlighting their potential applications in solid states. The enediynes with push-pull electronic substituents/moieties exhibit high contrast fluorescence color switching upon continuous photon illumination. The intriguing photophysical outcomes of the enediynyl fluorophores are judiciously exploited to generate single-component white light emission in binary solvent mixtures and sense polar aprotic vapor in polymer film matrices. The photophysical behavior of the dyes is further successfully utilized to monitor the microenvironment changes of biologically relevant anisotropic media such as bile salts. In summary, the newly introduced cross-conjugated enediynes enrich the toolbox of organic fluorophores and vouch to display versatile applications.

Keywords: aggregation in solution and solid state, enediynes, physical photochemistry and photophysics, vapor sensing and white light emission

Procedia PDF Downloads 480

Authors: Oyatayo Kehinde Taofik, Ndabula Christopher

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Drainage basins are a central theme in the green economy. The rising challenges in flooding, erosion or sediment transport and sedimentation threaten the green economy. This has led to increasing emphasis on quantitative analysis of drainage basin parameters for better understanding, estimation and prediction of fluvial responses and, thus associated hazards or disasters. This can be achieved through direct measurement, characterization, parameterization, or modeling. This study applied the Remote Sensing and Geographic Information System approach of parameterization and characterization of the morphometric variables of Katsina – Ala basin using a 30 m resolution Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM). This was complemented with topographic and hydrological maps of Katsina-Ala on a scale of 1:50,000. Linear, areal and relief parameters were characterized. The result of the study shows that Ala and Udene sub-watersheds are 4th and 5th order basins, respectively. The stream network shows a dendritic pattern, indicating homogeneity in texture and a lack of structural control in the study area. Ala and Udene sub-watersheds have the following values for elongation ratio, circularity ratio, form factor and relief ratio: 0.48 / 0.39 / 0.35/ 9.97 and 0.40 / 0.35 / 0.32 / 6.0. They also have the following values for drainage texture and ruggedness index of 0.86 / 0.011 and 1.57 / 0.016. The study concludes that the two sub-watersheds are elongated, suggesting that they are susceptible to erosion and, thus higher sediment load in the river channels, which will dispose the watersheds to higher flood peaks. The study also concludes that the sub-watersheds have a very coarse texture, with good permeability of subsurface materials and infiltration capacity, which significantly recharge the groundwater. The study recommends that efforts should be put in place by the Local and State Governments to reduce the size of paved surfaces in these sub-watersheds by implementing a robust agroforestry program at the grass root level.

Keywords: erosion, flood, mitigation, morphometry, watershed

Procedia PDF Downloads 87

Authors: Zafar Beg, Kumar Gaurav

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The lost Saraswati is described as a large perennial river which was 'lost' in the desert towards the end of the Indus-Saraswati civilisation. It has been proposed earlier that the lost Saraswati flowed in the Sutlej-Yamuna interfluve, parallel to the present day Indus River. It is believed that one of the earliest known ancient civilizations, the 'Indus-Saraswati civilization' prospered along the course of the Saraswati River. The demise of the Indus civilization is considered to be due to desiccation of the river. Today in the Sutlej-Yamuna interfluve, we observe an ephemeral river, known as Ghaggar. It is believed that along with the Ghaggar River, two other Himalayan Rivers Sutlej and Yamuna were tributaries of the lost Saraswati and made a significant contribution to its discharge. Presence of a large number of archaeological sites and the occurrence of thick fluvial sand bodies in the subsurface in the Sutlej-Yamuna interfluve has been used to suggest that the Saraswati River was a large perennial river. Further, the wider course of about 4-7 km recognized from satellite imagery of Ghaggar-Hakra belt in between Suratgarh and Anupgarh strengthens this hypothesis. Here we develop a methodology to estimate the paleo discharge and paleo width of the lost Saraswati River. In doing so, we rely on the hypothesis which suggests that the ancient Saraswati River used to carry the combined flow or some part of the Yamuna, Sutlej and Ghaggar catchments. We first established a regime relationship between the drainage area-channel width and catchment area-discharge of 29 different rivers presently flowing on the Himalayan Foreland from Indus in the west to the Brahmaputra in the East. We found the width and discharge of all the Himalayan rivers scale in a similar way when they are plotted against their corresponding catchment area. Using these regime curves, we calculate the width and discharge of paleochannels originating from the Sutlej, Yamuna and Ghaggar rivers by measuring their corresponding catchment area from satellite images. Finally, we add the discharge and width obtained from each of the individual catchments to estimate the paleo width and paleo discharge respectively of the Saraswati River. Our regime curves provide a first-order estimate of the paleo discharge of the lost Saraswati.

Keywords: Indus civilization, palaeochannel, regime curve, Saraswati River

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Authors: Gholba Niranjan Dilip, Anil Kumar

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Conduct of accurate reliable mapping of oil palm plantations and census of individual palm trees is a huge challenge. This study addresses this challenge and developed an optimized solution implemented deep learning techniques on remote sensing data. The oil palm is a very important tropical crop. To improve its productivity and land management, it is imperative to have accurate census over large areas. Since, manual census is costly and prone to approximations, a methodology for automated census using panchromatic images from Cartosat-2, SkySat and World View-3 satellites is demonstrated. It is selected two different study sites in Indonesia. The customized set of training data and ground-truth data are created for this study from Cartosat-2 images. The pre-trained model of Single Shot MultiBox Detector (SSD) Lite MobileNet V2 Convolutional Neural Network (CNN) from the TensorFlow Object Detection API is subjected to transfer learning on this customized dataset. The SSD model is able to generate the bounding boxes for each oil palm and also do the counting of palms with good accuracy on the panchromatic images. The detection yielded an F-Score of 83.16 % on seven different images. The detections are buffered and dissolved to generate polygons demarcating the boundaries of the oil palm plantations. This provided the area under the plantations and also gave maps of their location, thereby completing the automated census, with a fairly high accuracy (≈100%). The trained CNN was found competent enough to detect oil palm crowns from images obtained from multiple satellite sensors and of varying temporal vintage. It helped to estimate the increase in oil palm plantations from 2014 to 2021 in the study area. The study proved that high-resolution panchromatic satellite image can successfully be used to undertake census of oil palm plantations using CNNs.

Keywords: object detection, oil palm tree census, panchromatic images, single shot multibox detector

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Authors: Ranjit Kumar Sahu, Ramakar Jha

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Urban Water Management is the practice of managing freshwater, waste water, and storm water as components of a basin-wide management plan. It builds on existing water supply and sanitation considerations within an urban settlement by incorporating urban water management within the scope of the entire river basin. The pervasive problems generated by urban development have prompted, in the present work, to study the spatial extent of urbanization in Golden Triangle of Odisha connecting the cities Bhubaneswar (20.2700° N, 85.8400° E), Puri (19.8106° N, 85.8314° E) and Konark (19.9000° N, 86.1200° E)., and patterns of periodic changes in urban development (systematic/random) in order to develop future plans for (i) urbanization promotion areas, and (ii) urbanization control areas. Remote Sensing, using USGS (U.S. Geological Survey) Landsat8 maps, supervised classification of the Urban Sprawl has been done for during 1980 - 2014, specifically after 2000. This Work presents the following: (i) Time series analysis of Hydrological data (ground water and rainfall), (ii) Application of SWMM (Storm Water Management Model) and other soft computing techniques for Urban Water Management, and (iii) Uncertainty analysis of model parameters (Urban Sprawl and correlation analysis). The outcome of the study shows drastic growth results in urbanization and depletion of ground water levels in the area that has been discussed briefly. Other relative outcomes like declining trend of rainfall and rise of sand mining in local vicinity has been also discussed. Research on this kind of work will (i) improve water supply and consumption efficiency (ii) Upgrade drinking water quality and waste water treatment (iii) Increase economic efficiency of services to sustain operations and investments for water, waste water, and storm water management, and (iv) engage communities to reflect their needs and knowledge for water management.

Keywords: Storm Water Management Model (SWMM), uncertainty analysis, urban sprawl, land use change

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Authors: Samuel O. Akande

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The human-induced climate change is likely to have severe consequences on forest ecosystems in Nigeria. Recent discussions and emphasis on issues concerning the environment justify the need for this research which examined deforestation monitoring in Oban Forest, Nigeria using Remote Sensing techniques. The Landsat images from TM (1986), ETM+ (2001) and OLI (2015) sensors were obtained from Landsat online archive and processed using Erdas Imagine 2014 and ArcGIS 10.3 to obtain the land use/land cover and Normalized Differential Vegetative Index (NDVI) values. Ground control points of deforested areas were collected for validation. It was observed that the forest cover decreased in area by about 689.14 km² between 1986 and 2015. The NDVI was used to determine the vegetation health of the forest and its implications on agricultural sustainability. The result showed that the total percentage of the healthy forest cover has reduced to about 45.9% from 1986 to 2015. The results obtained from analysed questionnaires shown that there was a positive correlation between the causes and effects of deforestation in the study area. The coefficient of determination value was calculated as R² ≥ 0.7, to ascertain the level of anthropogenic activities, such as fuelwood harvesting, intensive farming, and logging, urbanization, and engineering construction activities, responsible for deforestation in the study area. Similarly, temperature and rainfall data were obtained from Nigerian Meteorological Agency (NIMET) for the period of 1986 to 2015 in the study area. It was observed that there was a significant increase in temperature while rainfall decreased over the study area. Responses from the administered questionnaires also showed that futile destruction of forest ecosystem in Oban forest could be reduced to its barest minimum if fuelwood harvesting is disallowed. Thus, the projected impacts of climate change on Nigeria’s forest ecosystems and environmental stability is better imagined than experienced.

Keywords: deforestation, ecosystems, normalized differential vegetative index, sustainability

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Authors: Christian Fercher, Jiaul Islam, Simon R. Corrie

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Fluorescence-based immunodiagnostics are an emerging field in biosensor development and exhibit several advantages over traditional detection methods. While various affinity biosensors have been developed to generate a fluorescence signal upon sensing varying concentrations of analytes, reagentless, reversible, and continuous monitoring of complex biological samples remains challenging. Here, we aimed to genetically engineer biosensors based on single-chain antibody fragments (scFv) that are site-specifically labeled with environmentally sensitive fluorescent unnatural amino acids (UAA). A rational design approach resulted in quantifiable analyte-dependent changes in peak fluorescence emission wavelength and enabled antigen detection in vitro. Incorporation of a polarity indicator within the topological neighborhood of the antigen-binding interface generated a titratable wavelength blueshift with nanomolar detection limits. In order to ensure continuous analyte monitoring, scFv candidates with fast binding and dissociation kinetics were selected from a genetic library employing a high-throughput phage display and affinity screening approach. Initial rankings were further refined towards rapid dissociation kinetics using bio-layer interferometry (BLI) and surface plasmon resonance (SPR). The most promising candidates were expressed, purified to homogeneity, and tested for their potential to detect biomarkers in a continuous microfluidic-based assay. Variations of dissociation kinetics within an order of magnitude were achieved without compromising the specificity of the antibody fragments. This approach is generally applicable to numerous antibody/antigen combinations and currently awaits integration in a wide range of assay platforms for one-step protein quantification.

Keywords: antibody engineering, biosensor, phage display, unnatural amino acids

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Authors: Kevin A. Droguett, Edwin G. Pérez, Denis Fuentealba, Margarita E. Aliaga, Angélica M. Fierro

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Supramolecular chemistry is a field of growing interest. Moreover, studying the formation of host-guest complexes between macrocycles and dyes is highly attractive due to their potential applications. Examples of the above are drug delivery, catalytic process, and sensing, among others. There are different dyes of interest in the literature; one example is the quinolinone derivatives. Those molecules have good optical properties and chemical and thermal stability, making them suitable for developing fluorescent probes. Secondly, several macrocycles can be seen in the literature. One example is the cucurbiturils. This water-soluble macromolecule family has a hydrophobic cavity and two identical carbonyl portals. Additionally, the thermodynamic analysis of those supramolecular systems could help understand the affinity between the host and guest, their interaction, and the main stabilization energy of the complex. In this work, two 7-(diethylamino) quinoline-2 (1H)-one derivative (QD1-2) and their interaction with cucurbit[7]uril (CB[7]) were studied from an experimental and in-silico point of view. For the experimental section, the complexes showed a 1:1 stoichiometry by HRMS-ESI and isothermal titration calorimetry (ITC). The inclusion of the derivatives on the macrocycle lends to an upward shift in the fluorescence intensity, and the pKa value of QD1-2 exhibits almost no variation after the formation of the complex. The thermodynamics of the inclusion complexes was investigated using ITC; the results demonstrate a non-classical hydrophobic effect with a minimum contribution from the entropy term and a constant binding on the order of 106 for both ligands. Additionally, dynamic molecular studies were carried out during 300 ns in an explicit solvent at NTP conditions. Our finding shows that the complex remains stable during the simulation (RMSD ~1 Å), and hydrogen bonds contribute to the stabilization of the systems. Finally, thermodynamic parameters from MMPBSA calculations were obtained to generate new computational insights to compare with experimental results.

Keywords: host-guest complexes, molecular dynamics, quinolin-2(1H)-one derivatives dyes, thermodynamics

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Authors: Binh T. T. Nguyen, Zhenyu Li, Eric Yap, Yi Zhang, Ai-Qun Liu

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Silicon-photonic-sensor system is an emerging class of analytical technologies that use evanescent field wave to sensitively measure the slight difference in the surrounding environment. The wavelength shift induced by local refractive index change is used as an indicator in the system. These devices can be served as sensors for a wide variety of chemical or biomolecular detection in clinical and environmental fields. In our study, a system including a silicon-based micro-ring resonator, microfluidic channel, and optical processing is designed, fabricated for biomolecule detection. The system is demonstrated to detect Clostridium botulinum type A neurotoxin (BoNT) in different water sources. BoNT is one of the most toxic substances known and relatively easily obtained from a cultured bacteria source. The toxin is extremely lethal with LD50 of about 0.1µg/70kg intravenously, 1µg/ 70 kg by inhalation, and 70µg/kg orally. These factors make botulinum neurotoxins primary candidates as bioterrorism or biothreat agents. It is required to have a sensing system which can detect BoNT in a short time, high sensitive and automatic. For BoNT detection, silicon-based micro-ring resonator is modified with a linker for the immobilization of the anti-botulinum capture antibody. The enzymatic reaction is employed to increase the signal hence gains sensitivity. As a result, a detection limit to 30 pg/mL is achieved by our silicon-photonic sensor within a short period of 80 min. The sensor also shows high specificity versus the other type of botulinum. In the future, by designing the multifunctional waveguide array with fully automatic control system, it is simple to simultaneously detect multi-biomaterials at a low concentration within a short period. The system has a great potential to apply for online, real-time and high sensitivity for the label-free bimolecular rapid detection.

Keywords: biotoxin, photonic, ring resonator, sensor

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Authors: Velimir Monty Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Mohammad Arif, Soumen Chatterjee, Krishnendu Gupta

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The peri-urban interface is an area of transition where the urban and rural areas meet and interact. So the peri-urban areas, which is characterized by strong urban influence, easy access to markets, services and other inputs, are ready supplies of labour but distant from the land paucity and pollution related to urban growth. Hence, the present study is primarily aimed at quantifying the spatio-temporal pattern of land use/land cover change during the last three decades (i.e., 1987 to 2016) in the peri-urban area of Burdwan city. In the recent past, the morphology of the study region has rapid change due to high growth of population and establishment of industries. The change has predominantly taken place along the State and National Highway 2 (NH-2) and around the Burdwan Municipality for meeting both residential and commercial purposes. To ascertain the degree of change in land use and land cover, over the specified time, satellite imageries and topographical sheets are employed. The data is processed through appropriate software packages to arrive at a deduction that most of the land use changes have occurred by obliterating agricultural land & water bodies and substituting them by built area and industrial spaces. Geospatial analysis of study area showed that this area has experienced a steep increase (30%) of built-up areas and excessive decrease (15%) in croplands between 1987 and 2016. Increase in built-up areas is attributed to the increase of out-migration during this period from the core city. This study also examined social, economic and institutional factors that lead to this rapid land use change in peri-urban areas of the Burdwan city by carrying out a field survey of 250 households in peri-urban areas. The research concludes with an urgency for regulating land subdivisions in peri-urban areas to prevent haphazard land use development. It is expected that the findings of the study would go a long way in facilitating better policy making.

Keywords: growth, land use land cover, morphology, peri-urban, policy making

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Authors: Loubna Khalile, Hicham Lahlaoi, Hassan Rhinane, A. Kaoukaya, S. Fal

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Green spaces is an essential element, they contribute to improving the quality of lives of the towns around them. They are a place of relaxation, walk and rest a playground for sport and youths. According to United Nations Organization Forests cover 31% of the land. In Morocco in 2013 that cover 12.65 % of the total land area, still, a small proportion compared to the natural needs of forests as a green lung of our planet. The Benslimane Forest is a large green area It belongs to Chaouia-Ouardigha Region and Greater Casablanca Region, it is located geographically between Casablanca is considered the economic and business Capital of Morocco and Rabat the national political capital, with an area of 12261.80 Hectares. The essential problem usually encountered in suburban forests, is visitation and tourism pressure it is anthropogenic actions, as well as other ecological and environmental factors. In recent decades, Morocco has experienced a drought year that has influenced the forest with increasing human pressure and every day it suffers heavy losses, as well as over-exploitation. The Moroccan forest ecosystems are weak with intense ecological variation, domanial and imposed usage rights granted to the population; forests are experiencing a significant deterioration due to forgetfulness and immoderate use of forest resources which can influence the destruction of animal habitats, vegetation, water cycle and climate. The purpose of this study is to make a model of the degree of degradation of the forest and know the causes for prevention by using remote sensing and geographic information systems by introducing climate and ancillary data. Analytic hierarchy process was used to find out the degree of influence and the weight of each parameter, in this case, it is found that anthropogenic activities have a fairly significant impact has thus influenced the climate.

Keywords: analytic hierarchy process, degradation, forest, geographic information system

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Authors: M. P. Tripathi, Priti Tiwari

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Soil and Water Assessment Tool (SWAT) is a distributed parameter continuous time model and was tested on daily and fortnightly basis for a small agricultural watershed (Dhangaon) of Chhattisgarh state in India. The SWAT model recently interfaced with ArcGIS and called as ArcSWAT. The watershed and sub-watershed boundaries, drainage networks, slope and texture maps were generated in the environment of ArcGIS of ArcSWAT. Supervised classification method was used for land use/cover classification from satellite imageries of the years 2009 and 2012. Manning's roughness coefficient 'n' for overland flow and channel flow and Fraction of Field Capacity (FFC) were calibrated for monsoon season of the years 2009 and 2010. The model was validated on a daily basis for the years 2011 and 2012 by using the observed daily rainfall and temperature data. Calibration and validation results revealed that the model was predicting the daily surface runoff and sediment yield satisfactorily. Sensitivity analysis showed that the annual sediment yield was inversely proportional to the overland and channel 'n' values whereas; annual runoff and sediment yields were directly proportional to the FFC. The model was also tested (calibrated and validated) for the fortnightly runoff and sediment yield for the year 2009-10 and 2011-12, respectively. Simulated values of fortnightly runoff and sediment yield for the calibration and validation years compared well with their observed counterparts. The calibration and validation results revealed that the ArcSWAT model could be used for identification of critical sub-watershed and for developing management scenarios for the Dhangaon watershed. Further, the model should be tested for simulating the surface runoff and sediment yield using generated rainfall and temperature before applying it for developing the management scenario for the critical or priority sub-watersheds.

Keywords: watershed, hydrologic and water quality, ArcSWAT model, remote sensing, GIS, runoff and sediment yield

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Authors: Umberto Di Staso, Marco Soave, Alessio Giori, Federico Prandi, Raffaele De Amicis

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The increasing availability of information about earth surface elevation (Digital Elevation Models DEM) generated from different sources (remote sensing, Aerial Images, Lidar) poses the question about how to integrate and make available to the most than possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the quality of data management plays a fundamental role. Due to the high acquisition costs and the huge amount of generated data, highresolution terrain surveys tend to be small or medium sized and available on limited portion of earth. Here comes the need to merge large-scale height maps that typically are made available for free at worldwide level, with very specific high resolute datasets. One the other hand, the third dimension increases the user experience and the data representation quality, unlocking new possibilities in data analysis for civil protection, real estate, urban planning, environment monitoring, etc. The open-source 3D virtual globes, which are trending topics in Geovisual Analytics, aim at improving the visualization of geographical data provided by standard web services or with proprietary formats. Typically, 3D Virtual globes like do not offer an open-source tool that allows the generation of a terrain elevation data structure starting from heterogeneous-resolution terrain datasets. This paper describes a technological solution aimed to set up a so-called “Terrain Builder”. This tool is able to merge heterogeneous-resolution datasets, and to provide a multi-resolution worldwide terrain services fully compatible with CesiumJS and therefore accessible via web using traditional browser without any additional plug-in.

Keywords: Terrain Builder, WebGL, Virtual Globe, CesiumJS, Tiled Map Service, TMS, Height-Map, Regular Grid, Geovisual Analytics, DTM

Procedia PDF Downloads 426