Search results for: LEO satellite constellations

Authors: Revalin Herdianto

Abstract:

Recent climate changes increase uncertainties in vegetation conditions such as health and biomass globally and locally. The detection is, however, difficult due to the spatial and temporal scale of vegetation coverage. Due to unique vegetation response to its environmental conditions such as water availability, the interplay between vegetation dynamics and hydrologic conditions leave a signature in their feedback relationship. Vegetation indices (VI) depict vegetation biomass and photosynthetic capacity that indicate vegetation dynamics as a response to variables including hydrologic conditions and microclimate factors such as rainfall characteristics and land surface temperature (LST). It is hypothesized that the signature may be depicted by VI in its relationship with other variables. To study this signature, several catchments in Asia, Australia, and Indonesia were analysed to assess the variations in hydrologic characteristics with vegetation types. Methods used in this study includes geographic identification and pixel marking for studied catchments, analysing time series of VI and LST of the marked pixels, smoothing technique using Savitzky-Golay filter, which is effective for large area and extensive data. Time series of VI, LST, and rainfall from satellite and ground stations coupled with digital elevation models were analysed and presented. This study found that the hydrologic response of vegetation to rainfall variations may be shown in one hydrologic year, in which a drought event can be detected a year later as a suppressed growth. However, an annual rainfall of above average do not promote growth above average as shown by VI. This technique is found to be a robust and tractable approach for assessing catchment dynamics in changing climates.

Keywords: vegetation indices, land surface temperature, vegetation dynamics, catchment

Procedia PDF Downloads 262

Authors: Sumaira Hafeez, Saira Akram

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Albeit the populace in metropolitan regions on the planet develops each year, the urban communities battling to adapt to the expanded metropolitan movement grow at different rates. Land Surface Temperature and other atmospheric parameters of the area of not really settled using Landsat pictures more than 10 years isolated. The LULC types were moreover arranged using managed gathering techniques. Quick urbanization is changing the current examples of Land Use Land Cover (LULC) all around the world, which is thusly expanding the Land Surface Temperature (LST) other atmospheric parameters in numerous districts. Present review was centered around assessing the current and recreating the future LULC and Land Surface Temperature patterns in the elevated climate of lower Himalayan district of Pakistan. Past examples of LULC and Land Surface Temperature were distinguished through the multi-unearthly Landsat satellite pictures during the 1995–2019 information period. The future forecasts were made for the year 2030 to work out LULC and LST changes separately, utilizing their previous examples. The review presumes that the reliably extending encroachment of the city's as of late advanced provincial regions over the totally open have went with an overall warming of the district's typical. Meteorological parameters over the earlier ten years and that permitting the land to lie void for a significant long time resulting to clearing the country fields for future metropolitan improvement is a preparation that has lamentable natural effects.

Keywords: surface urban heat island, land surface temperature, urban climate change, spatial analysis of meterological and atmospheric science

Procedia PDF Downloads 101

Authors: Juliana Lukša, Bazilė Ravoitytė, Elena Servienė, Saulius Serva

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Totiviridae L-A virus is a persistent Saccharomyces cerevisiae dsRNA virus. It encodes the major structural capsid protein Gag and Gag-Pol fusion protein, responsible for virus replication and encapsulation. These features also enable the copying of satellite dsRNAs (called M dsRNAs) encoding a secreted toxin and immunity to it (known as killer toxin). Viral capsid pore presumably functions in nucleotide uptake and viral mRNA release. During cell division, sporogenesis, and cell fusion, the virions remain intracellular and are transferred to daughter cells. By employing high throughput RNA sequencing data analysis, we describe the influence of solely L-A virus on the expression of genes in three different S. cerevisiae hosts. We provide a new perception into Totiviridae L-A virus-related transcriptional regulation, encompassing multiple bioinformatics analyses. Transcriptional responses to L-A infection were similar to those induced upon stress or availability of nutrients. It also delves into the connection between the cell metabolism and L-A virus-conferred demands to the host transcriptome by uncovering host proteins that may be associated with intact virions. To better understand the virus-host interaction, we applied differential proteomic analysis of virus particle-enriched fractions of yeast strains that harboreither complete killer system (L-A-lus and M-2 virus), M-2 depleted orvirus-free. Our analysis resulted in the identification of host proteins, associated with structural proteins of the virus (Gag and Gag-Pol). This research was funded by the European Social Fund under the No.09.3.3-LMT-K-712-19-0157“Development of Competences of Scientists, other Researchers, and Students through Practical Research Activities” measure.

Keywords: totiviridae, killer virus, proteomics, transcriptomics

Procedia PDF Downloads 112

Authors: Mahesh K. Jat, Ankan Jana, Mahender Choudhary

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Rapid population and economic growth resulted in changes in large-scale land use land cover (LULC) changes. Changes in the biophysical properties of the Earth's surface and its impact on climate are of primary concern nowadays. Different approaches, ranging from location-based relationships or modelling earth surface - atmospheric interaction through modelling techniques like surface energy balance (SEB) are used in the recent past to examine the relationship between changes in Earth surface land cover and climatic characteristics like temperature and precipitation. A remote sensing-based model i.e., Surface Energy Balance Algorithm for Land (SEBAL), has been used to estimate the surface heat fluxes over Mahi Bajaj Sagar catchment (India) from 2001 to 2020. Landsat ETM and OLI satellite data are used to model the SEB of the area. Changes in observed precipitation and temperature, obtained from India Meteorological Department (IMD) have been correlated with changes in surface heat fluxes to understand the relative contributions of LULC change in changing these climatic variables. Results indicate a noticeable impact of LULC changes on climatic variables, which are aligned with respective changes in SEB components. Results suggest that precipitation increases at a rate of 20 mm/year. The maximum and minimum temperature decreases and increases at 0.007 ℃ /year and 0.02 ℃ /year, respectively. The average temperature increases at 0.009 ℃ /year. Changes in latent heat flux and sensible heat flux positively correlate with precipitation and temperature, respectively. Variation in surface heat fluxes influences the climate parameters and is an adequate reason for climate change. So, SEB modelling is helpful to understand the LULC change and its impact on climate.

Keywords: LULC, sensible heat flux, latent heat flux, SEBAL, landsat, precipitation, temperature

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Authors: Joy Ghosh, Debasmita Biswas

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The road network of any area is the most important indicator of regional planning. For proper utilization of urban road networks, the structural parameters such as connectivity and accessibility should be analyzed and evaluated. This paper aims to explain the application of GIS on urban road network connectivity and accessibility analysis with a case study of Chandannagar City. This paper has been made to analyze the road network connectivity through various connectivity measurements like the total number of nodes and links, Cyclomatic Number, Alpha Index, Beta Index, Gamma index, Eta index, Pi index, Theta Index, and Aggregated Transport Score, Road Density based on existing road network in Chandannagar city in India. Accessibility is measured through the shortest Path Matrix, associate Number, and Shimbel Index. Various urban services, such as schools, banks, Hospitals, petrol pumps, ATMs, police stations, theatres, parks, etc., are considered for the accessibility analysis for each ward. This paper also highlights the relationship between urban land use/ land cover (LULC) and urban road network and population density using various spatial and statistical measurements. The datasets were collected through a field survey of 33 wards of the Chandannagar Municipal Corporation area, and the secondary data were collected through an open street map and satellite image of LANDSAT8 OLI & TIRS from USGS. Chandannagar was actually once a French colony, and at that time, various sort of planning was applied, but now Chandannagar city continues to grow haphazardly because that city is facing some problems; the knowledge gained from this paper helps to create a more efficient and accessible road network. Therefore, it would be suggested that some wards need to improve their connectivity and accessibility for the future growth and development of Chandannagar.

Keywords: accessibility, connectivity, transport, road network

Procedia PDF Downloads 34

Authors: Ronald Collins, Jonathon Coleman, Joel Dasari, George Holt, Carl Metelko, Matthew Murdoch, Alexander Morgan, Yan-Jie Schnellbach, Robert Mills, Gareth Edwards, Alexander Roberts

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At the Wylfa Magnox Power Plant between 2014–2016, the VIDARR prototype anti-neutrino detector was deployed. It is comprised of extruded plastic scintillating bars measuring 4 cm × 1 cm × 152 cm and utilised wavelength shifting fibres (WLS) and multi-pixel photon counters (MPPCs) to detect and quantify radiation. During deployment, it took cosmic muon data in accidental coincidence with the anti-neutrino measurements with the power plant site buildings obscuring the muon sky. Cosmic muons have a significantly higher probability of being attenuated and/or absorbed by denser objects, and so one-sided cosmic muon tomography was utilised to image the reactor site buildings. In order to achieve clear building outlines, a control data set was taken at the University of Liverpool from 2016 – 2018, which had minimal occlusion of the cosmic muon flux by dense objects. By taking the ratio of these two data sets and using GEANT4 simulations, it is possible to perform a one-sided cosmic muon tomography analysis. This analysis can be used to discern specific buildings, building heights, and features at the Wylfa reactor site, including the reactor core/reactor core shielding using ∼ 3 hours worth of cosmic-ray detector live time. This result demonstrates the feasibility of using cosmic muon analysis to determine a segmented detector’s location with respect to surrounding buildings, assisted by aerial photography or satellite imagery.

Keywords: anti-neutrino, GEANT4, muon, tomography, occlusion

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Authors: Arya Farjand

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The Nihewan Basin is a critical region in order to understand the Plio-Pleistocene paleoenvironment and its fauna in Northern China. The rich fossiliferous, fluvial-lacustrine sediments around the Nihewan Village hosted the specimens known as the Classic Nihewan Fauna. The primary excavations in the early 1920-30s produced more than 2000 specimens housed in Tianjin and Paris Museum. Nevertheless, the exact locality of excavations, fossil beds, and the reliable ages remained ambiguous until recent paleomagnetic studies and extensive work in conjunction sites. In this study, for the first time, we successfully relocated some of the original excavation sites. We reexamined more than 1500 specimens held in Tianjin Museum and cited their locality numbers and properties. During the field-season of 2017-2019, we visited the Xiashagou Valley. By reading the descriptions of the original site, utilization of satellite pictures, and comparing them with the current geomorphology of the area, we ensured the exact location of 26 of these sites and 17 fossil layers. Furthermore, by applying the latest technologies, such as GPS, Compass, digital barometers, laser measurer, and Abney level, we ensured the accuracy of the measurement. We surveyed 133-meter thickness of the deposits. Ultimately by applying the available Paleomagnetic data for this section, we estimated the ages of different horizons. The combination of our new data and previously published researches present a unique age control for the Classic Nihewan Fauna. These findings prove the hypothesis in which the Classic Nihewan Fauna belongs to different horizons, ranging from before Reunion up to after Olduvai earth geomagnetic field excursion (2.2-1.7 Mya).

Keywords: classic Nihewan basin fauna, Olduvai excursion, Pleistocene, stratigraphy

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Authors: Ima Rahmawati, Nur Hafizul Kalam

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Development of industrial and economic sectors in various countries very rapidly caused raising the greenhouse gas (GHG) emissions. Greenhouse gases are dominated by carbon dioxide (CO2) and methane (CH4) in the atmosphere that make the surface temperature of the earth always increase. The increasing gases caused by incomplete combustion of fossil fuels such as petroleum and coals and also high rate of deforestation. Yogyakarta Special Province which every year always become tourist destination, has a great potency in increasing of greenhouse gas emissions mainly from the incomplete combustion. One of effort to reduce the concentration of gases in the atmosphere is keeping and empowering the existing forests in the Province of Yogyakarta, especially forest in Kulonprogro is to be maintained the greenness so that it can absorb and store carbon maximally. Remote sensing technology can be used to determine the ability of forests to absorb carbon and it is connected to the density of vegetation. The purpose of this study is to determine the density of the biomass of forest vegetation and determine the ability of forests to store carbon through Photo-interpretation and Geographic Information System approach. Remote sensing imagery that used in this study is LANDSAT 8 OLI year 2015 recording. LANDSAT 8 OLI imagery has 30 meters spatial resolution for multispectral bands and it can give general overview the condition of the carbon stored from every density of existing vegetation. The method is the transformation of vegetation index combined with allometric calculation of field data then doing regression analysis. The results are model maps of density and capability level of forest vegetation in Kulonprogro, Yogyakarta in storing carbon.

Keywords: remote sensing, carbon, kulonprogo, forest vegetation, vegetation index

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

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Rapid urbanization significantly change land use, urban nature, land surface vegetation cover, and heat distribution, leading to the formation of urban heat island (UHI) effect and affecting the healthy growth of cities and the comfort of human living style. Past information and present changes in Land Surface Temperature (LST) and urban landscapes could be useful to geographers, environmentalists, and urban planners in an attempt to shape the urban development process and mitigate the effects of urban heat islands (UHI). This study aims at using Satellite Remote Sensing (SRS) and GIS techniques to develop an approach for assessing the urban nature and UHI effects in Lahore, Pakistan. The study employed the Radiative Transfer Method (RTM) in estimating LST to assess the SUHI effect during the interval of 20 years (2000-2020). The assessment was performed by the available Landsat 7/ETM+ and Landsat 8/OIL_TIRs data for the years 2000, 2010, and 2020 respectively. Pearson’s correlation and normalized mutual information were applied to investigate the relationship between green space characteristics and LST. The result of this work revealed that the influence of urban heat island is not always at the city centers but sometimes in the outskirt where a lot of development activities were going on towards the direction of expansion of Lahore, Pakistan. The present study explores the usage of image processing and spatial analysis in the drive towards achieving urban greening of Lahore and a sustainable urban environment in terms of urban planning, policy, and decision making and promoting the healthy and sustainable urban environment of the city.

Keywords: urban nature, urban heat islands, urban green space, land use, Lahore

Procedia PDF Downloads 88

Authors: Mahesh Kumar Jat, Manisha Choudhary

Abstract:

Rapid population and economic growth resulted in changes in large-scale land use land cover (LULC) changes. Changes in the biophysical properties of the Earth's surface and its impact on climate are of primary concern nowadays. Different approaches, ranging from location-based relationships or modelling earth surface - atmospheric interaction through modelling techniques like surface energy balance (SEB) have been used in the recent past to examine the relationship between changes in Earth surface land cover and climatic characteristics like temperature and precipitation. A remote sensing-based model i.e., Surface Energy Balance Algorithm for Land (SEBAL), has been used to estimate the surface heat fluxes over Mahi Bajaj Sagar catchment (India) from 2001 to 2020. Landsat ETM and OLI satellite data are used to model the SEB of the area. Changes in observed precipitation and temperature, obtained from India Meteorological Department (IMD) have been correlated with changes in surface heat fluxes to understand the relative contributions of LULC change in changing these climatic variables. Results indicate a noticeable impact of LULC changes on climatic variables, which are aligned with respective changes in SEB components. Results suggest that precipitation increases at a rate of 20 mm/year. The maximum and minimum temperature decreases and increases at 0.007 ℃ /year and 0.02 ℃ /year, respectively. The average temperature increases at 0.009 ℃ /year. Changes in latent heat flux and sensible heat flux positively correlate with precipitation and temperature, respectively. Variation in surface heat fluxes influences the climate parameters and is an adequate reason for climate change. So, SEB modelling is helpful to understand the LULC change and its impact on climate.

Keywords: remote sensing, GIS, object based, classification

Procedia PDF Downloads 95

Authors: Magdy Roman, Mostafa Shoeib, Mostafa Rostom

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Global vision, whether provided by overhead fixed cameras, on-board aerial vehicle cameras, or satellite images can always provide detailed information on the environment around mobile robots. In this paper, an intelligent vision-based method of path planning and obstacle avoidance for mobile robots is presented. The method integrates visual perception with a new proposed field-based path-planning method to overcome common path-planning problems such as local minima, unreachable destination and unnecessary lengthy paths around obstacles. The method proposes an exponential angle deviation field around each obstacle that affects the orientation of a close robot. As the robot directs toward, the goal point obstacles are classified into right and left groups, and a deviation angle is exponentially added or subtracted to the orientation of the robot. Exponential field parameters are chosen based on Lyapunov stability criterion to guarantee robot convergence to the destination. The proposed method uses obstacles' shape and location, extracted from global vision system, through a collision prediction mechanism to decide whether to activate or deactivate obstacles field. In addition, a search mechanism is developed in case of robot or goal point is trapped among obstacles to find suitable exit or entrance. The proposed algorithm is validated both in simulation and through experiments. The algorithm shows effectiveness in obstacles' avoidance and destination convergence, overcoming common path planning problems found in classical methods.

Keywords: path planning, collision avoidance, convergence, computer vision, mobile robots

Procedia PDF Downloads 161

Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

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Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

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Authors: Lican Guzmán, José Manuel Lattus, Mariana Cervetto, Mauricio Calderón

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Today the estimation of effects produced by climate change in high Andean wetland environments is confronted by big challenges. This study provides a way to an analysis by remote sensing how some Ambiental aspects have evolved on the Maricunga salt flat in the last 30 years, divided into the summer and winter seasons, and if global warming is conditioning these changes. The first step to achieve this goal was the recompilation of geological, hydrological, and morphometric antecedents to ensure an adequate contextualization of its environmental parameters. After this, software processing and analysis of Landsat 5,7 and 8 satellite imagery was required to get the vegetation, water, surface temperature, and soil moisture indexes (NDVI, NDWI, LST, and SMI) in order to see how their spatial-temporal conditions have evolved in the area of study during recent decades. Results show a tendency of regular increase in surface temperature and disponibility of water during both seasons but with slight drought periods during summer. Soil moisture factor behaves as a constant during the dry season and with a tendency to increase during wintertime. Vegetation analysis shows an areal and quality increase of its surface sustained through time that is consistent with the increase of water supply and temperature in the basin mentioned before. Roughly, the effects of climate change can be described as positive for the Maricunga salt flat; however, the lack of exact correlation in dates of the imagery available to remote sensing analysis could be a factor for misleading in the interpretation of results.

Keywords: global warming, geology, SIG, Atacama Desert, Salar de Maricunga, environmental geology, NDVI, SMI, LST, NDWI, Landsat

Procedia PDF Downloads 57

Authors: Gurbanova Lamiya

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The Republic of Azerbaijan is considered a region with limited water resources, as up to 70% of surface water is formed outside the country's borders, and most of its territory is an arid (dry) climate zone. It is located at the lower limit of transboundary flows, which is the weakest source of natural water resources in the South Caucasus. It is essential to correctly assess the quality of natural, collector-drainage and groundwater of the area and their suitability for irrigation in order to properly carry out land reclamation measures, provide the normal water-salt regime, and prevent repeated salinization. Through the 141-km-long main Mil-Mugan collector, groundwater, household waste, and floodwaters generated during floods and landslides are poured into the Caspian Sea. The hydrochemical composition of the samples taken from the Sabir irrigation canal passing through the center of the Kura-Araz plain, the Main Mil-Mugan Collector, and the groundwater of the region, which we chose as our research object, were studied and the obtained results were compared by periods. A model is proposed that allows for a complete visualization of the primary materials collected for the study area. The practical use of the established digital model provides all possibilities. The practical use of the established digital model provides all possibilities. An extensive database was created with the ArcGis 10.8 package, using publicly available LandSat satellite images as primary data in addition to ground surveys to build the model. The principles of the construction of the geographic information system of modern GIS technology were developed, the boundary and initial condition of the research area were evaluated, and forecasts and recommendations were given.

Keywords: irrigation channel, groundwater, collector, meliorative measures

Procedia PDF Downloads 47

Authors: Amin Naboureh, Ainong Li, Jinhu Bian, Guangbin Lei, Hamid Ebrahimy

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Large-scale land cover mapping has become a new challenge in land change and remote sensing field because of involving a big volume of data. Moreover, selecting the right classification method, especially when there are different types of landscapes in the study area is quite difficult. This paper is an attempt to compare the performance of different machine learning (ML) algorithms for generating a land cover map of the China-Central Asia–West Asia Corridor that is considered as one of the main parts of the Belt and Road Initiative project (BRI). The cloud-based Google Earth Engine (GEE) platform was used for generating a land cover map for the study area from Landsat-8 images (2017) by applying three frequently used ML algorithms including random forest (RF), support vector machine (SVM), and artificial neural network (ANN). The selected ML algorithms (RF, SVM, and ANN) were trained and tested using reference data obtained from MODIS yearly land cover product and very high-resolution satellite images. The finding of the study illustrated that among three frequently used ML algorithms, RF with 91% overall accuracy had the best result in producing a land cover map for the China-Central Asia–West Asia Corridor whereas ANN showed the worst result with 85% overall accuracy. The great performance of the GEE in applying different ML algorithms and handling huge volume of remotely sensed data in the present study showed that it could also help the researchers to generate reliable long-term land cover change maps. The finding of this research has great importance for decision-makers and BRI’s authorities in strategic land use planning.

Keywords: land cover, google earth engine, machine learning, remote sensing

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Authors: Fatemeh Parhizkar, Mojtaba Yamani, Abdolla Behboodi, Masoomeh Hashemi

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The mangrove forests are natural and valuable gifts that exist in some parts of the world, including Iran. Regarding the threats faced by these forests and the declining area of them all over the world, as well as in Iran, it is very necessary to manage and monitor them. The current study aimed to investigate the changes in mangrove forests and the relationship between these changes and the marine hydrodynamics and coastal morphology in the area between qeshm island and the west coast of the Hormozgan province (i.e. the coastline between Mehran river and Bandar-e Pol port) in the 49-year period. After preprocessing and classifying satellite images using the SVM, MLC, and ANN classifiers and evaluating the accuracy of the maps, the SVM approach with the highest accuracy (the Kappa coefficient of 0.97 and overall accuracy of 98) was selected for preparing the classification map of all images. The results indicate that from 1972 to 1987, the area of these forests have had experienced a declining trend, and in the next years, their expansion was initiated. These forests include the mangrove forests of Khurkhuran wetland, Muriz Deraz Estuary, Haft Baram Estuary, the mangrove forest in the south of the Laft Port, and the mangrove forests between the Tabl Pier, Maleki Village, and Gevarzin Village. The marine hydrodynamic and geomorphological characteristics of the region, such as average intertidal zone, sediment data, the freshwater inlet of Mehran river, wave stability and calmness, topography and slope, as well as mangrove conservation projects make the further expansion of mangrove forests in this area possible. By providing significant and up-to-date information on the development and decline of mangrove forests in different parts of the coast, this study can significantly contribute to taking measures for the conservation and restoration of mangrove forests.

Keywords: mangrove forests, marine hydrodynamics, coastal morphology, west of strait of Hormuz, Iran

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Authors: Maryam Jaberi, Siavosh Shayan, Mojtaba Yamani

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Habble-Rud River basin (HR), up to 100 km length, one of the largest watersheds which drain into deserts to the north of Central Iran (Dasht-e Kavir). This stream is oblique with the NE-SW trending, flow in the southern range of central Alborz Mountains and the northern border of Central Iran. The end of the ~17 km suddenly change direction and with the southern trending to have a morphology which meanders passes through the Alborz Mountain ridge and flows into the Garmsar plain where it forms one of the largest alluvial fans in Iran, i.e. the vast Garmsar alluvial fan with an area of 476 km2. This study was carried out through morphometric analyses, longitudinal river profiles, and study of geomorpholic evidence such as fluvial terraces, gypsum-salt domes, seismic data, and satellite images. This study aimed to investigate the changes in the pattern of rivers in the southern part of the HR river basin. The southern part of HR river basin located at the southern foothills of the Central Alborz is characterized the thrust faults (Sorkheh-Kalut and Garmsar faults), folds,diapirs and arid climate. The activity of more than 10 salt domes that belong to the Oligocene-Miocene period has considerably influenced the pattern of streams in this region. Dissolution of these domes has not only reduced the quality of water and soil resources, but also has led to the formation of badlands and gullies.Our results indicated that the pattern of rivers in the southern part of HR river basin was influenced by discharge of the HR river in Quaternary, geological structure, subsidence of Central Iran and vertical uplift of Alborz mountain. These agents caused the formation meanders in the southern part of the HR River and evaluation of the seasonal rivers like Shoor-Darre and Garmabsar.

Keywords: geomorphologic evaluation, rivers pattern, Habble-Rud River basin, seasonal rivers

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Authors: M. N. Kadir, M. M. H. Oliver, T. Naher

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The study assesses the areal extent of riverine flood in the flood-prone area of Faridpur District of Bangladesh using hydrological model and Geographic Information System (GIS). In the context of preparing the inundation map, flood frequency analysis was carried out to assess flooding for different flood magnitudes. Flood inundation maps were prepared based on DEM, and discharge at the river using Delft-3D model. LANDSAT satellite images have been used to develop a land cover map in the study area. The land cover map was used for mapping of cropland area. By incorporating the inundation maps on the land cover map, agricultural damage was assessed. Present monetary values of crop damage were collected through field survey from actual flood of the study area. Two different inundation maps were produced from the model for the year 2000 and 2016. In the year 2000, the floods began in the month of July, whereas in the case of the year 2016 is started in August. Under both cases, most of the areas were found to have been flooded in the month of September followed by flood recession. In order to prepare the land cover maps, four categories of LCs were considered viz., cropland, water body, trees, and rivers. Among the 755791 acres area of Faridpur District, the croplands were categorized to be 334,589 acres, followed by water bodies (279900 acres), trees (101930 acres) and rivers 39372 (acres). Damage assessment data revealed that 40% of the total cropland area had been affected by the flood in the year 2000, whereas only 19% area was affected by the 2016 flood. The study concluded that September is the critical month for cropland protection since the highest flood is expected at this time of the year in Faridpur. The northwestern and the southwestern part of the district was categorized as most vulnerable to flooding.

Keywords: agricultural damage, Delft-3d, flood management, land cover map

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Authors: Arragaw Alemayehu, Woldeamlak Bewket

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The aim of this study was to understand the influence of current climate variability on crop production in the central highlands of Ethiopia. We used monthly rainfall and temperature data from 132 points each representing a pixel of 10×10 km. The data are reconstructions based on station records and meteorological satellite observations. Production data of the five major crops in the area were collected from the Central Statistical Agency for the period 2004-2013 and for the main cropping season, locally known as Meher. The production data are at the Enumeration Area (EA ) level and hence the best available dataset on crop production. The results show statistically significant decreasing trends in March–May (Belg) rainfall in the area. However, June – September (Kiremt) rainfall showed increasing trends in Efratana Gidim and Menz Gera Meder which the latter is statistically significant. Annual rainfall also showed positive trends in the area except Basona Werana where significant negative trends were observed. On the other hand, maximum and minimum temperatures showed warming trends in the study area. Correlation results have shown that crop production and area of cultivation have positive correlation with rainfall, and negative with temperature. When the trends in crop production are investigated, most crops showed negative trends and below average production was observed. Regression results have shown that rainfall was the most important determinant of crop production in the area. It is concluded that current climate variability has a significant influence on crop production in the area and any unfavorable change in the local climate in the future will have serious implications for household level food security. Efforts to adapt to the ongoing climate change should begin from tackling the current climate variability and take a climate risk management approach.

Keywords: central highlands, climate variability, crop production, Ethiopia, regression, trend

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Authors: Angel Liduvino Vara-Vela, Dirceu Luis Herdies, Debora Souza Alvim, Eder Paulo Vendrasco, Silvio Nilo Figueroa, Jayant Pendharkar, Julio Pablo Reyes Fernandez

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Biomass-burning episodes are quite common in the central Amazon rainforest and represent a dominant source of aerosols during the dry season, between August and October. The increase in the occurrence of fires in 2019 in the world’s largest biomes has captured the attention of the international community. In particular, a rare and extreme smoke-related event occurred in the afternoon of Monday, August 19, 2019, in the most populous city in the Western Hemisphere, the São Paulo Metropolitan Area (SPMA), located in southeastern Brazil. The sky over the SPMA suddenly blackened, with the day turning into night, as reported by several news media around the world. In order to clarify whether or not the smoke that plunged the SPMA into sudden darkness was related to wildfires in the Amazon rainforest region, a set of 48-hour simulations over South America were performed using the Weather Research and Forecasting with Chemistry (WRF-Chem) model at 20 km horizontal resolution, on a daily basis, during the period from August 16 to August 19, 2019. The model results were satisfactorily compared against satellite-based data products and in situ measurements collected from air quality monitoring sites. Although a very strong smoke transport coming from the Amazon rainforest was observed in the middle of the afternoon on August 19, its impact on air quality over the SPMA took place in upper levels far above the surface, where, conversely, low air pollutant concentrations were observed.

Keywords: Amazon rainforest, biomass burning aerosols, São Paulo metropolitan area, WRF-Chem model

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Authors: Binod C. Agrawal

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In modern history, industrial and media merchandising in South Asia from East Asia, Europe, United States and other countries of the West is over 200 years old. Hence, continued external technology and media exposure is not a new experience in multi-lingual and multi religious South Asia which evolved cultural means to withstand structural change. In the post-World War II phase, media exposure especially of telecommunication, film, Internet, radio, print media and television have increased manifold. South Asia did not lose any time in acquiring and adopting digital media accelerated by chip revolution, computer and satellite communication. The penetration of digital media and utilization are exceptionally high though the spread has an unequal intensity, use and effects. The author argues that industrial and media products are “cultural products” apart from being “technological products”; hence their influences are most felt in the cultural domain which may lead to blunting of unique cultural specifics in the multi-cultural, multi-lingual and multi religious South Asia. Social scientists, political leaders and parents have voiced concern of “Cultural domination”, “Digital media colonization” and “Westernization”. Increased digital media access has also opened up doors of pornography and other harmful information that have sparked fresh debates and discussions about serious negative, harmful, and undesirable social effects especially among youth. Within ‘techno-social’ perspective, based on recent research studies, the paper aims to describe and analyse possible socio-economic change due to digital media penetration. Further, analysis supports the view that the ancient multi-lingual and multi-religious cultures of South Asia due to inner cultural strength may sustain without setting in a process of irreversible structural changes in South Asia.

Keywords: cultural sustainability, digital media effects, digital media impact in South Asia, social change in South Asia

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Authors: Krima M. Rohela, Raja Sabarinath Sundaralingam

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Humans have been launching rockets since the beginning of the space age in the late 1950s. We have come a long way since then, and the success rate for the launch of rockets has increased considerably. With every successful launch, there is a large amount of junk or debris which is released into the upper layers of the atmosphere. Space debris has been a huge concern for a very long time now. This includes the rocket shells released from the launch and the parts of defunct satellites. Some of this junk will come to fall towards the Earth and burn in the atmosphere. But most of the junk goes into orbit around the Earth, and they remain in orbits for at least 100 years. This can cause a lot of problems to other functioning satellites and may affect the future manned missions to space. The main concern of the space-debris is the increase in space activities, which leads to risks of collisions if not taken care of soon. These collisions may result in what is known as Kessler Syndrome. This debris can be removed by a space-based laser targeting system. Hence, the matter is investigated and discussed. The first step in this involves launching a satellite with a high-power laser device into space, above the debris belt. Then the target material is ablated with a focussed laser beam. This step of the process is highly dependent on the attitude and orientation of the debris with respect to the Earth and the device. The laser beam will cause a jet of vapour and plasma to be expelled from the material. Hence, the force is applied in the opposite direction, and in accordance with Newton’s third law of motion, this will cause the material to move towards the Earth and get pulled down due to gravity, where it will get disintegrated in the upper layers of the atmosphere. The larger pieces of the debris can be directed towards the oceans. This method of removal of the orbital debris will enable safer passage for future human-crewed missions into space.

Keywords: altitude, Kessler syndrome, laser ablation, Newton’s third law of motion, satellites, Space debris

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Authors: Maulita Sari Hani, Abraham B. Sianipar, Jamaluddin Jompa, Natsir Nessa, Alan T. White

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Manta ray is an icon for tourism in Raja Ampat. The tourist volume has been increased for the past ten years which up to approximately 23,000 tourists in 2017. Since 2013, Conservation International Indonesia deployed satellite and acoustic tags on manta ray in Dampier strait to track the species and identify the aggregation areas. These findings encourage the government and the local community to boost conservation through the management of marine protected areas for tourism purposes. Community in Dampier strait including the village of Arborek, Kurkapa, Kapisawar, and Sawingray involved in variety of small scale tourism business including homestay, dive shop, tour operator, and crafts. Working groups of related local businesses were established to support the local community and to ensure the sustainability of the economic viability and environmental sustainability. In order to analyze the economic benefits of manta ray tourism, this study was conducted to identify the number of local business in Dampier Strait and the economic impacts in terms of local finance security, social, humanity, individual, and physical assets. The results of this study identify 30 homestays, 2 dive shops, 10 tour operators, 30 women involved in crafts, and about 50 villagers worked for dive resorts. In addition to community assets, we confirmed the welfare of community has been improved in terms of food security, households, education for children, savings, and health insurance.

Keywords: marine wildlife tourism, elasmobranch, conservation, ecotourism, co-management, economic viability, environmental sustainability

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Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell

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Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.

Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis

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Authors: Hyelim Park, Juan Martin Zorrilla

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Climate change influences very widely and in various ways ocean ecosystem functioning. The consequences of climate change on marine ecosystems are an increase in temperature and irregular behavior of some solute concentrations. These changes would affect fisheries catches in several ways. Our aim is to assess the quantitative contribution change of fishery catches along the time and express them through four environment variables: Sea Surface Temperature (SST4) and the concentrations of Chlorophyll (CHL), Particulate Inorganic Carbon (PIC) and Particulate Organic Carbon (POC) at two spatial scales: Global and the nineteen FAO Major Fishing Areas divisions. Data collection was based on the FAO FishStatJ 2014 database as well as MODIS Aqua satellite observations from 2002 to 2012. Some data had to be corrected and interpolated using some existing methods. As the results, a multivariable regression model for average Global fisheries captures contained temporal mean of SST4, standard deviation of SST4, standard deviation of CHL and standard deviation of PIC. Global vector auto-regressive (VAR) model showed that SST4 was a statistical cause of global fishery capture. To accommodate varying conditions in fishery condition and influence of climate change variables, a model was constructed for each FAO major fishing area. From the management perspective it should be recognized some limitations of the FAO marine areas division that opens to possibility to the discussion of the subdivision of the areas into smaller units. Furthermore, it should be treated that the contribution changes of fishery species and the possible environment factor for specific species at various scale levels.

Keywords: fisheries-catch, FAO FishStatJ, MODIS Aqua, sea surface temperature (SST), chlorophyll, particulate inorganic carbon (PIC), particulate organic carbon (POC), VAR, granger causality

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Zongyao Sha

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Green vegetation plays a vital role in energy flows and matter cycles in terrestrial ecosystems, and vegetation phenology may not only be influenced by but also impose active feedback on climate changes. The phenological events of vegetation, such as the start of the season (SOS), end of the season (EOS), and length of the season (LOS), can respond to climate changes and affect gross primary productivity (GPP). Here we coupled satellite remote sensing imagery with FLUXNET observations to systematically map the shift of SOS, EOS, and LOS in global vegetated areas and explored their response to climate fluctuations and feedback on GPP during the last two decades. Results indicated that SOS advanced significantly, at an average rate of 0.19 days/year at a global scale, particularly in the northern hemisphere above the middle latitude (≥30°N) and that EOS was slightly delayed during the past two decades, resulting in prolonged LOS in 72.5% of the vegetated area. The climate factors, including seasonal temperature and precipitation, are attributed to the shifts in vegetation phenology but with a high spatial and temporal difference. The study revealed interactions between vegetation phenology and climate changes. Both temperature and precipitation affect vegetation phenology. Higher temperature as a direct consequence of global warming advanced vegetation green-up date. On the other hand, 75.9% and 20.2% of the vegetated area showed a positive correlation and significant positive correlation between annual GPP and length of vegetation growing season (LOS), likely indicating an enhancing effect on vegetation productivity and thus increased carbon uptake from the shifted vegetation phenology. Our study highlights a comprehensive view of the vegetation phenology changes of the global terrestrial ecosystems during the last two decades. The interactions between the shifted vegetation phenology and climate changes may provide useful information for better understanding the future trajectory of global climate changes. The feedback on GPP from the shifted vegetation phenology may serve as an adaptation mechanism for terrestrial ecosystems to mitigate global warming through improved carbon uptake from the atmosphere.

Keywords: vegetation phenology, growing season, NPP, correlation analysis

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Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

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In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

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Authors: Sara Tokhi Arab, Tariq Salari, Ryozo Noguchi, Tofael Ahamed

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Land suitability analysis is essential for table grape cultivation in order to increase its production and productivity under the dry condition of Afghanistan. In this context, the main aim of this paper was to determine the suitable locations for vineyards based on satellite remote sensing and GIS (geographical information system) in Kabul Province of Afghanistan. The Landsat8 OLI (operational land imager) and thermal infrared sensor (TIRS) and shuttle radar topography mission digital elevation model (SRTM DEM) images were processed to obtain the normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI), land surface temperature (LST), and topographic criteria (elevation, aspect, and slope). Moreover, Jaxa rainfall (mm per hour), soil properties information are also used for the physical suitability of vineyards. Besides, socio-economic criteria were collected through field surveys from Kabul Province in order to develop the socio-economic suitability map. Finally, the suitable classes were determined using weighted overly based on a reclassification of each criterion based on AHP (Analytical Hierarchy Process) weights. The results indicated that only 11.1% of areas were highly suitable, 24.8% were moderately suitable, 35.7% were marginally suitable and 28.4% were not physically suitable for grapes production. However, 15.7% were highly suitable, 17.6% were moderately suitable, 28.4% were marginally suitable and 38.3% were not socio-economically suitable for table grapes production in Kabul Province. This research could help decision-makers, growers, and other stakeholders with conducting precise land assessments by identifying the main limiting factors for the production of table grapes management and able to increase land productivity more precisely.

Keywords: vineyards, land physical suitability, socio-economic suitability, AHP

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Authors: Islam Abou El-Magd, Elham Ali, Moahmed Zakzouk, Nesreen Khairy, Naglaa Zanaty

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Maine environment and coastal zone are wealthy with natural resources that contribute to the local economy of Egypt. The Gulf of Suez and Red Sea area accommodates diverse human activities that contribute to the local economy, including oil exploration and production, touristic activities, export and import harbors, etc, however, it is always under the threat of pollution due to human interaction and activities. This research aimed at integrating in-situ measurements and remotely sensed data with hydrodynamic model to map and simulate the oil pollution. High-resolution satellite sensors including Sentinel 2 and Plantlab were functioned to trace the oil pollution. Spectral band ratio of band 4 (infrared) over band 3 (red) underpinned the mapping of the point source pollution from the oil industrial estates. This ratio is supporting the absorption windows detected in the hyperspectral profiles. ASD in-situ hyperspectral device was used to measure experimentally the oil pollution in the marine environment. The experiment used to measure water behavior in three cases a) clear water without oil, b) water covered with raw oil, and c) water after a while from throwing the raw oil. The spectral curve is clearly identified absorption windows for oil pollution, particularly at 600-700nm. MIKE 21 model was applied to simulate the dispersion of the oil contamination and create scenarios for crises management. The model requires precise data preparation of the bathymetry, tides, waves, atmospheric parameters, which partially obtained from online modeled data and other from historical in-situ stations. The simulation enabled to project the movement of the oil spill and could create a warning system for mitigation. Details of the research results will be described in the paper.

Keywords: oil pollution, remote sensing, modelling, Red Sea, Egypt

Procedia PDF Downloads 323