Search results for: navigation satellite

Authors: Mohamed Abdelkareem

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Remote sensing data contributed on predicting the prospective areas of water resources. Integration of microwave and multispectral data along with climatic, hydrologic, and geological data has been used here. In this article, Sentinel-2, Landsat-8 Operational Land Imager (OLI), Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), and Advanced Land Observing Satellite (ALOS) Phased Array Type L‐band Synthetic Aperture Radar (PALSAR) data were utilized to identify the geological, hydrologic and structural features of Wadi Asyuti which represents a defunct tributary of the Nile basin, in the eastern Sahara. The image transformation of Sentinel-2 and Landsat-8 data allowed characterizing the different varieties of rock units. Integration of microwave remotely-sensed data and GIS techniques provided information on physical characteristics of catchments and rainfall zones that are of a crucial role for mapping groundwater prospective zones. A fused Landsat-8 OLI and ALOS/PALSAR data improved the structural elements that difficult to reveal using optical data. Lineament extraction and interpretation indicated that the area is clearly shaped by the NE-SW graben that is cut by NW-SE trend. Such structures allowed the accumulation of thick sediments in the downstream area. Processing of recent OLI data acquired on March 15, 2014, verified the flood potential maps and offered the opportunity to extract the extent of the flooding zone of the recent flash flood event (March 9, 2014), as well as revealed infiltration characteristics. Several layers including geology, slope, topography, drainage density, lineament density, soil characteristics, rainfall, and morphometric characteristics were combined after assigning a weight for each using a GIS-based knowledge-driven approach. The results revealed that the predicted groundwater potential zones (GPZs) can be arranged into six distinctive groups, depending on their probability for groundwater, namely very low, low, moderate, high very, high, and excellent. Field and well data validated the delineated zones.

Keywords: GIS, remote sensing, groundwater, Egypt

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Authors: Nateepat Srivarom, Weng Jingnong, Serm Chinnarat

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Precise Point Positioning (PPP) technique is use to improve accuracy by using precise satellite orbit and clock correction data, but this technique is complicated methods and high costs. Currently, there are several online processing service providers which offer simplified calculation. In the first part of this research, we compare the efficiency and precision of four software. There are three popular online processing service providers: Australian Online GPS Processing Service (AUSPOS), CSRS-Precise Point Positioning and CenterPoint RTX post processing by Trimble and 1 offline software, RTKLIB, which collected data from 10 the International GNSS Service (IGS) stations for 10 days. The results indicated that AUSPOS has the least distance root mean square (DRMS) value of 0.0029 which is good enough to be calculated for monitoring the movement of tectonic plates. The second, we use AUSPOS to process the data of geodetic network of Thailand. In December 26, 2004, the earthquake occurred a 9.3 MW at the north of Sumatra that highly affected all nearby countries, including Thailand. Earthquake effects have led to errors of the coordinate system of Thailand. The Royal Thai Survey Department (RTSD) is primarily responsible for monitoring of the crustal movement of the country. The difference of the geodetic network movement is not the same network and relatively large. This result is needed for survey to continue to improve GPS coordinates system in every year. Therefore, in this research we chose the AUSPOS to calculate the magnitude and direction of movement, to improve coordinates adjustment of the geodetic network consisting of 19 pins in Thailand during October 2013 to November 2017. Finally, results are displayed on the simulation map by using the ArcMap program with the Inverse Distance Weighting (IDW) method. The pin with the maximum movement is pin no. 3239 (Tak) in the northern part of Thailand. This pin moved in the south-western direction to 11.04 cm. Meanwhile, the directional movement of the other pins in the south gradually changed from south-west to south-east, i.e., in the direction noticed before the earthquake. The magnitude of the movement is in the range of 4 - 7 cm, implying small impact of the earthquake. However, the GPS network should be continuously surveyed in order to secure accuracy of the geodetic network of Thailand.

Keywords: precise point positioning, online processing service, geodetic network, inverse distance weighting

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Authors: Jhoga Parth, T. Nasar, K. V. Anand

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An idealized definition of shoreline is that it is the zone of coincidence of three spheres such as atmosphere, lithosphere, and hydrosphere. Despite its apparent simplicity, this definition in practice a challenge to apply. In reality, the shoreline location deviates continually through time, because of various dynamic factors such as wave characteristics, currents, coastal orientation and the bathymetry, which makes the shoreline volatile. This necessitates us to monitor the shoreline in a temporal basis. If shoreline’s nature is understood at particular coastal stretch, it need not be the same trend at the other location, though belonging to the same sea front. Shoreline change is hence a local phenomenon and has to be studied with great intensity considering as many factors involved as possible. Erosion and accretion of sediment are such natures of a shoreline, which needs to be quantified by comparing with its predeceasing variations and understood before implementing any coastal projects. In recent years, advent of Global Positioning System (GPS) and Geographic Information System (GIS) acts as an emerging tool to quantify the intra and inter annual sediment rate getting accreted or deposited compared to other conventional methods in regards with time was taken and man power. Remote sensing data, on the other hand, paves way to acquire historical sets of data where field data is unavailable with a higher resolution. Short term and long term period shoreline change can be accurately tracked and monitored using a software residing in GIS - Digital Shoreline Analysis System (DSAS) developed by United States Geological Survey (USGS). In the present study, using DSAS, End Point Rate (EPR) is calculated analyze the intra-annual changes, and Linear Rate Regression (LRR) is adopted to study inter annual changes of shoreline. The shoreline changes are quantified for the scenario during the construction of breakwater in Ponnani river inlet along Kerala coast, India. Ponnani is a major fishing and landing center located 10°47’12.81”N and 75°54’38.62”E in Malappuram district of Kerala, India. The rate of erosion and accretion is explored using satellite and field data. The full paper contains the rate of change of shoreline, and its analysis would provide us understanding the behavior of the inlet at the study area during the construction of the training walls.

Keywords: DSAS, end point rate, field measurements, geo-informatics, shoreline variation

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Authors: Moaawia Abdulgader Gdara

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En Naga sub - basin considered the most southern of the concessions in the Sirte Basin operated by HOO. En Naga Sub-basin has likely been point-sourced of CO₂ accumulations during the last 7 million years from local satellite intrusives associated with the Haruj Al Aswad igneous complex. CO₂ occurs in the En Naga Sub-basin as a result of the igneous activity of the Al Harouge Al Aswad complex. Igneous extrusives have been pierced in the subsurface and are exposed to the surface. The lower cretaceous Bahi Sandstone facies are recognized in the En Naga Sub-basin. In the Lower Cretaceous Bahi Sandstones, the presence of trapped carbon dioxide is proven within the En Naga Sub-basin. This makes it unique in providing an abundance of CO₂ gas reservoirs with almost pure magmatic CO₂, which can be easily sampled. Huge amounts of CO₂ exist in the Lower Cretaceous Bahi Sandstones in the En Naga sub-basin, where the economic value of CO₂ is related to its use for enhanced oil recovery (EOR). Based on the production tests for the drilled wells that make Lower Cretaceous Bahi sandstones the principal reservoir rocks for CO₂ where large volumes of CO₂ gas have been discovered in the Bahi Formation on and near Concession 72 (En Naga sub-basin). The Bahi sandstones are generally described as a good reservoir rock. Intergranular porosities and permeabilities are highly variable and can exceed 25% and 100 MD. In the (En Naga sub-basin), three main developed structures (Barrut I, En Naga A, and En Naga O) are thought to be prospective for the lower Cretaceous Bahi sandstone reservoir. These structures represent a good example of the deep over-pressure potential in (the En Naga sub-basin). The very high pressures assumed to be associated with local igneous intrusives may account for the abnormally high Bahi (and Lidam) reservoir pressures. The best gas tests from these facies are at F1-72 on the (Barrut I structure) from part of a 458 feet+ section having an estimated high value of CO₂ as 98% overpressured. Bahi CO₂ prospectivity is thought to be excellent in the central to western areas where At U1-72 (En Naga O structure). A significant CO₂ gas kick occurred at 11,971 feet and quickly led to blowout conditions due to uncontrollable leaks in the surface equipment, which reflects better reservoir quality sandstones associated with Paleostructural highs. Condensate and gas prospectivity increases to the east as the CO₂ prospectivity decreases with distance away from the Al Haruj Al Aswad igneous complex. To date, it has not been possible to accurately determine the volume of these strategically valuable reserves, although there are positive indications that they are very large.

Keywords: En Naga Sub Basin, Al Harouge Al Aswad, CO₂ generation and migration in the Bahi sandstone reservoir, lower cretaceous Bahi sandstone

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Authors: Adan Valdez, Shawn Gallaher, James Morison, Jordan Aragon

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Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport and modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116 km3/year. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff. The total climatological freshwater content is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity driven pycnocline as opposed to the temperature driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and remotely sensed dynamic ocean topography (DOT). In-situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time consuming. NASA’s Advanced Topographic Laser Altimeter System (ATLAS) derived dynamic ocean topography (DOT), and Air Expendable CTD (AXCTD) derived Freshwater Content are used to develop a linear regression model. In-situ data for the regression model is collected across the 150° West meridian, which typically defines the centerline of the Beaufort Gyre. Two freshwater content models are determined by integrating the freshwater volume between the surface and an isopycnal corresponding to reference salinities of 28.7 and 34.8. These salinities correspond to those of the winter pycnocline and total climatological freshwater content, respectively. Using each model, we determine the strength of the linear relationship between freshwater content and satellite derived DOT. The result of this modeling study could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non in-situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: ICESat-2, dynamic ocean topography, freshwater content, beaufort gyre

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Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

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In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

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Authors: Jigg Pelayo, Ricardo Villar, Einstine Opiso

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The rampant and unintended spread of urban areas resulted in increasing artificial component features in the land cover types of the countryside and bringing forth the urban heat island (UHI). This paved the way to wide range of negative influences on the human health and environment which commonly relates to air pollution, drought, higher energy demand, and water shortage. Land cover type also plays a relevant role in the process of understanding the interaction between ground surfaces with the local temperature. At the moment, the depiction of the land surface temperature (LST) at city/municipality scale particularly in certain areas of Misamis Oriental, Philippines is inadequate as support to efficient mitigations and adaptations of the surface urban heat island (SUHI). Thus, this study purposely attempts to provide application on the Landsat 8 satellite data and low density Light Detection and Ranging (LiDAR) products in mapping out quality automated LST model and crop-level land cover classification in a local scale, through theoretical and algorithm based approach utilizing the principle of data analysis subjected to multi-dimensional image object model. The paper also aims to explore the relationship between the derived LST and land cover classification. The results of the presented model showed the ability of comprehensive data analysis and GIS functionalities with the integration of object-based image analysis (OBIA) approach on automating complex maps production processes with considerable efficiency and high accuracy. The findings may potentially lead to expanded investigation of temporal dynamics of land surface UHI. It is worthwhile to note that the environmental significance of these interactions through combined application of remote sensing, geographic information tools, mathematical morphology and data analysis can provide microclimate perception, awareness and improved decision-making for land use planning and characterization at local and neighborhood scale. As a result, it can aid in facilitating problem identification, support mitigations and adaptations more efficiently.

Keywords: LiDAR, OBIA, remote sensing, local scale

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Authors: Akinwumi Omotayo, Badu-B Apraku, Joseph Olobasola, Petra Abdul Saghir, Yinka Sobowale

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In southwestern Nigeria, climate change has led to loss of at least two months of rainfall. Consequently, only one cycle of maize can now be grown because of the shorter duration of rainy season as against two cycles in the past. The Early and Extra-early maturing varieties of maize were originally developed for the semi-arid and arid zones of West and Central Africa where there are seasonal challenges of water threatening optimum performance of the traditional maize grown, which are commonly late in maturity (115 to 120 days). The early varieties of maize mature in 90 to 95 days; while the Extra-Early maize varieties reach physiological maturity in less than 90 days. It was broadly hypothesized that the extra early varieties of maize could mitigate the effects of climate change in southwestern Nigeria with higher levels of rainfall by reinstating the original two cycles of rain-fed maize crop. Trials were therefore carried out in southwestern Nigeria on the possibility of adapting the extra early maize to mitigate the effects of climate change. The trial was the Mother/Baby design. The mother trial involves the evaluation of extra-early varieties following ideal recommendations and closely supervised centrally at the University research farm and the Agricultural Development Programmes (ADPs). This requires farmers to observe and evaluate the technology and the management regime meant to precede the second stage of evaluation at several satellite farmers field managed by selected farmers. The Baby Trial is expected to provide a realistic assessment of the technology by farmers in their own environment. A stratified selection of thirty farmers for the Baby Trial ensured appropriate representation across the different categories of the farming population by age and gender. Data from the trials indicate that extra early maize can be grown in two cycles rain fed in south west Nigeria and a third and fourth cycle could be obtained with irrigation. However the long duration varieties outyielded the extra early maize in both the mother and baby trials. When harvested green, the extra early maize served as source of food between March and May when there was scarcity of food. This represents a major advantage. The study recommends that further work needs to be done to improve the yield of extra early maize to encourage farmers to adopt.

Keywords: adaptation, climate change, extra early, maize varieties, mitigation

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Authors: Yarra Sulina, Nunna Tagore Sai Priya, Ankhi Banerjee

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With the rapid growth in tourist arrivals, there has been a huge demand for the growth of infrastructure in the destinations. With the increasing preference of tourists to stay near attractions, there has been a considerable change in the land use around tourist sites. However, with the inclusion of certain regulations and guidelines provided by the authorities based on the nature of tourism activity and geographical constraints, the pattern of growth of built form is different for various tourist sites. Therefore, this study explores the patterns of growth of built-up for a decade from 2009 to 2019 through two-dimensional and three-dimensional analysis. Land use maps are created through supervised classification of satellite images obtained from LANDSAT 4-5 and LANDSAT 8 for 2009 and 2019, respectively. The overall expansion of the built-up area in the region is analyzed in relation to the distance from the city's geographical center and the tourism-related growth regions are identified which are influenced by the proximity of tourist attractions. The primary tourist sites of various destinations with different geographical characteristics and tourism activities, that have undergone a significant increase in built-up area and are occupied with tourism-related infrastructure are selected for further study. Proximity analysis of the tourism-related growth sites is carried out to delineate the influence zone of the tourist site in a destination. Further, a temporal analysis of volumetric growth of built form is carried out to understand the morphology of the tourist precincts over time. The Digital Surface Model (DSM) and Digital Terrain Model (DTM) are used to extract the building footprints along with building height. Factors such as building height, and building density are evaluated to understand the patterns of three-dimensional growth of the built area in the region. The study also explores the underlying reasons for such changes in built form around various tourist sites and predicts the impact of such growth patterns in the region. The building height and building density around tourist site creates a huge impact on the appeal of the destination. The surroundings that are incompatible with the theme of the tourist site have a negative impact on the attractiveness of the destination that leads to negative feedback by the tourists, which is not a sustainable form of development. Therefore, proper spatial measures are necessary in terms of area and volume of the built environment for a healthy and sustainable environment around the tourist sites in the destination.

Keywords: sustainable tourism, growth patterns, land-use changes, 3-dimensional analysis of built-up area

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Authors: B. S. Chaudhary

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The severity and frequencies of different disasters on the globe is increasing in recent years. India is also facing the disasters in the form of drought, cyclone, earthquake, landslides, and floods. One of the major causes of disasters in northern India is flood. There are great losses and extensive damage to the agricultural crops, property, human, and animal life. This is causing environmental imbalances at places. The annual global figures for losses due to floods run into over 2 billion dollar. India is a vast country with wide variations in climate and topography. Due to widespread and heavy rainfall during the monsoon months, floods of varying magnitude occur all over the country during June to September. The magnitude depends upon the intensity of rainfall, its duration and also the ground conditions at the time of rainfall. Haryana, one of the agriculturally dominated northern states is also suffering from a number of disasters such as floods, desertification, soil erosion, land degradation etc. Earthquakes are also frequently occurring but of small magnitude so are not causing much concern and damage. Most of the damage in Haryana is due to floods. Floods in Haryana have occurred in 1978, 1988, 1993, 1995, 1998, and 2010 to mention a few. The present paper deals with the Remote Sensing and GIS applications in preparing flood risk maps in parts of Haryana State India. The satellite data of various years have been used for mapping of flood affected areas. The Flooded areas have been interpreted both visually and digitally and two classes-flooded and receded water/ wet areas have been identified for each year. These have been analyzed in GIS environment to prepare the risk maps. This shows the areas of high, moderate and low risk depending on the frequency of flood witness. The floods leave a trail of suffering in the form of unhygienic conditions due to improper sanitation, water logging, filth littered in the area, degradation of materials and unsafe drinking water making the people prone to many type diseases in short and long run. Attempts have also been made to enumerate the causes of floods. The suggestions are given for mitigating the fury of floods and proper management issues related to evacuation and safe places nearby.

Keywords: flood mapping, GIS, Haryana, India, remote sensing, space technology

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Authors: T. B. Karu Jayasundara

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The Earth’s gravity is not uniform. The satellite imageries of the Earth’s surface from NASA reveal a number of different gravity anomaly regions all over the globe. When the moon rotates around the earth, its gravity has a major physical influence on a number of regions on the earth. This physical change can be seen by the tides. The tides make sea levels high and low in coastal regions. During high tide, the gravitational force of the Moon pulls the Earth’s gravity so that the total gravitational intensity of Earth is reduced; it is further reduced in the low gravity regions of Earth. This reduction in gravity helps keep the suspended particles such as dust in the atmosphere, sand grains in the sea water for longer. Dramatic differences can be seen from the floating dust in the low gravity regions when compared with other regions. The above phenomena can be demonstrated from experiments. The experiments have to be done in high and low gravity regions of the earth during high and low tide, which will assist in comparing the final results. One of the experiments that can be done is by using a water filled cylinder about 80 cm tall, a few particles, which have the same density and same diameter (about 1 mm) and a stop watch. The selected particles were dropped from the surface of the water in the cylinder and the time taken for the particles to reach the bottom of the cylinder was measured using the stop watch. The times of high and low tide charts can be obtained from the regional government authorities. This concept is demonstrated by the particle drop times taken at high and low tides. The result of the experiment shows that the particle settlement time is less in low tide and high in high tide. The experiment for dust particles in air can be collected on filters, which are cellulose ester membranes and using a vacuum pump. The dust on filters can be used to make slides according to the NOHSC method. Counting the dust particles on the slides can be done using a phase contrast microscope. The results show that the concentration of dust is high at high tide and low in low tide. As a result of the high tides, a high concentration of heavy minerals deposit on placer deposits and dust particles retain in the atmosphere for longer in low gravity regions. These conditions are remarkably exhibited in the lowest low gravity region of the earth, mainly in the regions of India, Sri Lanka and in the middle part of the Indian Ocean. The biggest heavy mineral placer deposits are found in coastal regions of India and Sri Lanka and heavy dust particles are found in the atmosphere of India, particularly in the Delhi region.

Keywords: gravity, minerals, tides, moon, costal, atmosphere

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Authors: Charlotte Dreger, Erik Bollaert

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This paper presents two environmentally-friendly coastal structures realized on the Lake of Neuchâtel. Both structures reflect current environmental issues of concern on the lake and have been strongly affected by extreme meteorological conditions between their period of design and their actual operational period. The Lake of Neuchatel is one of the biggest Swiss lakes and measures around 38 km in length and 8.2 km in width, for a maximum water depth of 152 m. Its particular topographical alignment, situated in between the Swiss Plateau and the Jura mountains, combines strong winds and large fetch values, resulting in significant wave heights during storm events at both north-east and south-west lake extremities. In addition, due to flooding concerns, historically, lake levels have been lowered by several meters during the Jura correction works in the 19th and 20th century. Hence, during storm events, continuous erosion of the vulnerable molasse shorelines and sand banks generate frequent and abundant littoral transport from the center of the lake to its extremities. This phenomenon does not only cause disturbances of the ecosystem, but also generates numerous problems at natural or man-made infrastructures located along the shorelines, such as reed plants, harbor entrances, canals, etc. A first example is provided at the southwestern extremity, near the city of Yverdon, where an ensemble of 11 small islands, the Iles des Vernes, have been artificially created in view of enhancing biological conditions and food availability for bird species during their migration process, replacing at the same time two larger islands that were affected by lack of morphodynamics and general vegetalization of their surfaces. The article will present the concept and dimensioning of these islands based on 2D numerical modelling, as well as the realization and follow-up campaigns. In particular, the influence of several major storm events that occurred immediately after the works will be pointed out. Second, a sediment retention dike is discussed at the northeastern extremity, at the entrance of the Canal de la Broye into the lake. This canal is heavily used for navigation and suffers from frequent and significant sedimentation at its outlet. The new coastal structure has been designed to minimize sediment deposits around the exutory of the canal into the lake, by retaining the littoral transport during storm events. The article will describe the basic assumptions used to design the dike, as well as the construction works and follow-up campaigns. Especially the huge influence of changing meteorological conditions on the littoral transport of the Lake of Neuchatel since project design ten years ago will be pointed out. Not only the intensity and frequency of storm events are increasing, but also the main wind directions alter, affecting in this way the efficiency of the coastal structure in retaining the sediments.

Keywords: meteorological evolution, sediment transport, lake of Neuchatel, numerical modelling, environmental measures

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Authors: Yurike, Yonariza, Rudi Febriamansyah, Syafruddin Karimi

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Forest is a natural resource that has an important function as a supporting element of human life. Forest degradation enormous impact on global warming is a reality we have experienced together, that disruption of ecosystems, extreme weather conditions, disruption of water management system watersheds and the threat of natural disasters as floods, landslides and droughts, even disruption food security. Dharmasraya is a district in the province of West Sumatra, which has an area of 92.150 ha of forest, which is largely a former production forest concessions (Forest Management Rights) which is supposed to be a secondary forest. This study answers about the impact of land use in the former concession area Dharmasraya on the environment. The methodology used is the household survey, key informants, and satellite data / GIS. From the results of the study, the former concession area in Dharmasraya experienced a reduction of forest cover over time significantly. Forest concessions should be secondary forests in Dharmasraya, now turned conversion to oil palm plantations. Population pressures and growing economic pressures, resulting in more intensive harvesting. As a result of these forest disturbances caused changes in forest functions. These changes put more emphasis towards economic function by ignoring social functions or ecological function. Society prefers to maximize their benefits today and pay less attention to the protection of natural resources. This causes global warming is increasing and this is not only felt by people around Dharmasraya but also the world. Land clearing by the community through a process in slash and burn. This fire was observed by NOAA satellites and recorded by the Forest Service of West Sumatra. This demonstrates the ability of trees felled trees to absorb carbon dioxide (CO2) to be lost, even with forest fires accounted for carbon dioxide emitted into the air, and this has an impact on global warming. In addition to the change of control of land into oil palm plantations water service has been poor, people began to trouble the water and oil palm plantations are located in the watershed caused the river dried up. Through the findings of this study is expected to contribute ideas to the policy makers to pay more attention to the former concession forest management as the prevention or reduction of global warming.

Keywords: climate change, community, concession forests, environment

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Authors: Abdul Mutolib, Yonariza Mahdi, Hanung Ismono

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The existence of forests is essential to human lives on earth, but its existence is threatened by forest deforestations and degradations. Forest deforestations and degradations in Indonesia is not only caused by the illegal activity by the company or the like, even today many cases in Indonesia forest damage caused by human activities, one of which cut down forests for agriculture and plantations. In West Sumatra, community forest management are the result supported the enactment of customary land tenure, including ownership of land within the forest. Indigenous forest management have a positive benefit, which gives the community an opportunity to get livelihood and income, but if forest management practices by indigenous peoples is not done wisely, then there is the destruction of forests and cause adverse effects on the environment. Based on intensive field works in Dhamasraya District employing some data collection techniques such as key informant interviews, household surveys, secondary data analysis, and satellite image interpretation. This paper answers the following questions; how the impact of forest management by local communities on forest conditions (foccus in Forest Production and Limited Production Forest) and knowledge of the local community on the benefits of forests. The site is a Nagari Bonjol, Dharmasraya District, because most of the forest in Dharmasraya located and owned by Nagari Bonjol community. The result shows that there is damage to forests in Dharmasraya because of forest management activities by local communities. Damage to the forest area of 33,500 ha in Dharmasraya because forests are converted into oil palm and rubber plantations with monocultures. As a result of the destruction of forests, water resources are also diminishing, and the community has experienced a drought in the dry season due to forest cut down and replaced by oil palm plantations. Knowledge of the local community on the benefits of low forest, the people considered that the forest does not have better benefits and cut down and converted into oil palm or rubber plantations. Local people do not understand the benefits of ecological and environmental services that forests. From the phenomena in Dharmasraya on land ownership, need to educate the local community about the importance of protecting the forest, and need a strategy to integrate forests management to keep the ecological functions that resemble the woods and counts the economic benefits for the welfare of local communities. One alternative that can be taken is to use forest management models agroforestry smallholders in accordance with the characteristics of the local community who still consider the economic, social and environmental.

Keywords: community, customary land, farmer plantations, and forests

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Authors: Britt Erni, Aldara Vazquez Fernandez, Roland Maurer

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Visuospatial perspective taking (VSPT) is a process that allows to integrate spatial information from different points of view, and to transform the mental images we have of the environment to properly orient our movements and anticipate the location of landmarks during navigation. VSPT is also related to egocentric perspective transformations (imagined rotations or translations of one's point of view) and to infer the visuospatial experiences of another person (e.g. if and how another person sees objects). This process is deeply related to a wide-ranging capacity called the theory of mind (ToM), an essential cognitive function that allows us to regulate our social behaviour by attributing mental representations to individuals in order to make behavioural predictions. VSPT is often considered in the literature as the starting point of the development of the theory of mind. VSPT and ToM include several levels of knowledge that have to be assessed by specific tasks. Unfortunately, the lack of tasks assessing these functions in clinical neuropsychology leads to underestimate, in brain-damaged patients, deficits of these functions which are essential, in everyday life, to regulate our social behaviour (ToM) and to navigate in known and unknown environments (VSPT). Therefore, this study aims to create and standardize a VSPT task in order to explore the cognitive requirements of VSPT and ToM, and to specify their relationship in healthy adults and thereafter in brain-damaged patients. Two versions of a computerized VSPT task were administered to healthy participants (M = 28.18, SD = 4.8 years). In both versions the environment was a 3D representation of 10 different geometric shapes placed on a circular base. Two sets of eight pictures were generated from this: of the environment with an avatar somewhere on its periphery (locations) and of what the avatar sees from that place (views). Two types of questions were asked: a) identify the location from the view, and b) identify the view from the location. Twenty participants completed version 1 of the task and 20 completed the second version, where the views were offset by ±15° (i.e., clockwise or counterclockwise) and participants were asked to choose the closest location or the closest view. The preliminary findings revealed that version 1 is significantly easier than version 2 for accuracy (with ceiling scores for version 1). In version 2, participants responded significantly slower when they had to infer the avatar's view from the latter's location, probably because they spent more time visually exploring the different views (responses). Furthermore, men significantly performed better than women in version 1 but not in version 2. Most importantly, a sensitive task (version 2) has been created for which the participants do not seem to easily and automatically compute what someone is looking at yet which does not involve more heavily other cognitive functions. This study is further completed by including analysis on non-clinical participants with low and high degrees of schizotypy, different socio-educational status, and with a range of older adults to examine age-related and other differences in VSPT processing.

Keywords: mental transformation, spatial cognition, theory of mind, visuospatial perspective taking

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Authors: Judith Margaret Tymon

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As cities struggle to incorporate informal settlements into the fabric of urban areas, the focus has often been on the provision of housing. This study explores the underlying structure of street networks, with the goal of understanding the morphogenesis of informal settlements through the lens of the access network. As the stages of development progress from infill to consolidation and eventually, to a planned in-situ settlement, the access networks retain the form of the core segments; however, a majority of street patterns are adapted to a grid design to support infrastructure in the final upgraded phase. A case study is presented to examine the street network in the informal settlement of Gobabis Namibia as it progresses from its initial stages to a planned, in-situ, and permanently upgraded development. The Informal Development Stages framework of foundation, infill, and consolidation, as developed by Dr. Jota Samper, is utilized to examine the evolution of street networks. Data is gathered from historical Google Earth satellite images for the time period between 2003 and 2022. The results demonstrate that during the foundation through infill stages, incremental changes follow similar patterns, with pathways extended, lengthened, and densified as housing is created and the settlement grows. In the final stage of consolidation, the resulting street layout is transformed to support the installation of infrastructure; however, some elements of the original street patterns remain. The core pathways remain intact to accommodate the installation of infrastructure and the creation of housing plots, defining the shape of the settlement and providing the basis of the urban form. The adaptations, growth, and consolidation of the street network are critical to the eventual formation of the spatial layout of the settlement. This study will include a comparative analysis of findings with those of recent research performed by Kamalipour, Dovey, and others regarding incremental urbanism within informal settlements. Further comparisons will also include studies of street networks of well-established urban centers that have shown links between the morphogenesis of access networks and the eventual spatial layout of the city. The findings of the study can be used to guide and inform strategies for in-situ upgrading and can contribute to the sustainable development of informal settlements.

Keywords: Gobabis Namibia, incremental urbanism, informal development stages, informal settlements, street networks

Procedia PDF Downloads 65

Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

Procedia PDF Downloads 134

Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

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Authors: Sunghun Jung, Wonkook Kim

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Due to the difficulty of the utilization of satellite and an aircraft, conventional ocean color remote sensing has a disadvantage in that it is difficult to obtain images of desired places at desired times. These disadvantages make it difficult to capture the anomalies such as the occurrence of the red tide which requires immediate observation. It is also difficult to understand the phenomena such as the resuspension-precipitation process of suspended solids and the spread of low-salinity water originating in the coastal areas. For the remote sensing reflectance of seawater, above-water radiometers (AWR) have been used either by carrying portable AWRs on a ship or installing those at fixed observation points on the Ieodo ocean research station, Socheongcho base, and etc. In particular, however, it requires the high cost to measure the remote reflectance in various seawater environments at various times and it is even not possible to measure it at the desired frequency in the desired sea area at the desired time. Also, in case of the stationary observation, it is advantageous that observation data is continuously obtained, but there is the disadvantage that data of various sea areas cannot be obtained. It is possible to instantly capture various marine phenomena occurring on the coast using the unmanned aerial system (UAS) including vertical takeoff and landing (VTOL) type unmanned aerial vehicles (UAV) since it could move and hover at the one location and acquire data of the desired form at a high resolution. To remotely estimate seawater constituents, it is necessary to install an ultra-spectral sensor. Also, to calculate reflected light from the surface of the sea in consideration of the sun’s incident light, a total of three sensors need to be installed on the UAV. The remote sensing reflectance of seawater is the most basic optical property for remotely estimating color components in seawater and we could remotely estimate the chlorophyll concentration, the suspended solids concentration, and the dissolved organic amount. Estimating seawater physics from the remote sensing reflectance requires the algorithm development using the accumulation data of seawater reflectivity under various seawater and atmospheric conditions. The UAS with three AWRs is developed for the remote reflection sensing on the surface of the sea. Throughout the paper, we explain the details of each UAS component, system operation scenarios, and simulation and experiment results. The UAS consists of a UAV, a solar tracker, a transmitter, a ground control station (GCS), three AWRs, and two gimbals.

Keywords: above-water radiometers (AWR), ground control station (GCS), unmanned aerial system (UAS), unmanned aerial vehicle (UAV)

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Authors: Abdelkhalek Bouchikhi, Elyes Benmokhtar, Sebastien Saletzki

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The aeronautical field is experiencing issues with RF spectrum congestion due to the constant increase in the number of flights, aircrafts and telecom systems on board. In addition, these systems are bulky in size, weight and energy consumption. The cognitive radio helps particularly solving the spectrum congestion issue by its capacity to detect idle frequency channels then, allowing an opportunistic exploitation of the RF spectrum. The present work aims to propose a new use case for aeronautical spectrum sharing and to study the performances of three different detection techniques: energy detector, matched filter and cyclostationary detector within the aeronautical use case. The spectrum in the proposed cognitive radio is allocated dynamically where each cognitive radio follows a cognitive cycle. The spectrum sensing is a crucial step. The goal of the sensing is gathering data about the surrounding environment. Cognitive radio can use different sensors: antennas, cameras, accelerometer, thermometer, etc. In IEEE 802.22 standard, for example, a primary user (PU) has always the priority to communicate. When a frequency channel witch used by the primary user is idle, the secondary user (SU) is allowed to transmit in this channel. The Distance Measuring Equipment (DME) is composed of a UHF transmitter/receiver (interrogator) in the aircraft and a UHF receiver/transmitter on the ground. While the future cognitive radio will be used jointly to alleviate the spectrum congestion issue in the aeronautical field. LDACS, for example, is a good candidate; it provides two isolated data-links: ground-to-air and air-to-ground data-links. The first contribution of the present work is a strategy allowing sharing the L-band. The adopted spectrum sharing strategy is as follow: the DME will play the role of PU which is the licensed user and the LDACS1 systems will be the SUs. The SUs could use the L-band channels opportunely as long as they do not causing harmful interference signals which affect the QoS of the DME system. Although the spectrum sensing is a key step, it helps detecting holes by determining whether the primary signal is present or not in a given frequency channel. A missing detection on primary user presence creates interference between PU and SU and will affect seriously the QoS of the legacy radio. In this study, first brief definitions, concepts and the state of the art of cognitive radio will be presented. Then, a study of three communication channel detection algorithms in a cognitive radio context is carried out. The study is made from the point of view of functions, material requirements and signal detection capability in the aeronautical field. Then, we presented a modeling of the detection problem by three different methods (energy, adapted filter, and cyclostationary) as well as an algorithmic description of these detectors is done. Then, we study and compare the performance of the algorithms. Simulations were carried out using MATLAB software. We analyzed the results based on ROCs curves for SNR between -10dB and 20dB. The three detectors have been tested with a synthetics and real world signals.

Keywords: aeronautic, communication, navigation, surveillance systems, cognitive radio, spectrum sensing, software defined radio

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Authors: M. L. Gaol, I. W. Mudita

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Indonesia is well known as a country covered by lush tropical rain forests, but in fact, the northeastern part of the country, within the areas geologically known as Lesser Sunda, the dominant vegetation is tropical savanna. Lesser Sunda is a chain of islands located closer to Australia than to islands in the other parts of the country. Among those of islands in the chain which is closes to Australia, and thereby most strongly affected by the hot and dry Australian climate, is the island of Timor, the western part of which belongs to Indonesia and the eastern part is a sovereign state East Timor. Regardless of being the most dominant vegetation cover, tropical savanna in West Timor, especially its understory, is rarely investigated. This research was therefore carried out to investigate the structure, composition and diversity of the understory of this tropical savanna as the basis for looking at the possibility of introducing other spesieis for various purposes. For this research, 14 terrestrial communities representing major types of the existing savannas in West Timor was selected with aid of the most recently available satellite imagery. At each community, one stand of the size of 50 m x 50 m most likely representing the community was as the site of observation for the type of savanna under investigation. At each of the 14 communities, 20 plots of 1 m x 1 m in size was placed at random to identify understory species and to count the total number of individuals and to estimate the cover of each species. Based on such counts and estimation, the important value of each species was later calculated. The results of this research indicated that the understory of savanna in West Timor consisted of 73 understory species. Of this number of species, 18 species are grasses and 55 are non-grasses. Although lower than non-grass species, grass species indeed dominated the savanna as indicated by their number of individuals (65.33 vs 34.67%), species cover (57.80 vs 42.20%), and important value (123.15 vs 76.85). Of the 14 communities, the lowest density of grass was 13.50/m2 and the highest was 417.50/m2. Of 18 grass species found, all were commonly found as agricultural weeds, whereas of 55 non-grass, 10 species were commonly found as agricultural weeds, environmental weeds, or invasive species. In terms of better managing the savanna in the region, these findings provided the basis for planning a more integrated approach in managing such agricultural and environmental weeds as well as invasive species by considering the structure, composition, and species diversity of the understory species existing in each site. These findings also provided the basis for better understanding the flora of the region as a whole and for developing a flora database of West Timor in future.

Keywords: tropical savanna, understory species, integrated management, weedy and invasive species

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Authors: Jaime E. Salazar Lagos

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Chongqing is located in southwest China and is becoming one of the most significant cities in the world. Its urban territories and metropolitan-related areas have one of the largest urban populations in China and are partitioned and shaped by two of the biggest and longest rivers on Earth, the Yangtze and Jialing Rivers, making Chongqing a megalopolis intersected by rivers. Historically, Chongqing City enjoyed fundamental connections with its rivers; however, current urban development of Chongqing City has lost effective integration of the riverbanks within the urban space and structural dynamics of the city. Therefore, there exists a critical lack of physical and urban space conjoined with the rivers, which diminishes the economic, tourist, and environmental development of Chongqing. Using multi-scale satellite-map site verification the study confirmed the hypothesis and urban-waterside disconnect. Collected data demonstrated that the Chongqing urban zone, an area of 5292 square-kilometers and a water front of 203.4 kilometers, has only 23.49 kilometers of extension (just 11.5%) with high-quality physical and spatial urban-waterside connection. Compared with other metropolises around the world, this figure represents a significant lack of spatial development along the rivers, an issue that has not been successfully addressed in the last 10 years of urban development. On a macro scale, the study categorized the different kinds of relationships between the city and its riverbanks. This data was then utilized in the creation of an urban-waterfront relationship map that can be a tool for future city planning decisions and real estate development. On a micro scale, we discovered there are three primary elements that are causing the urban-waterside disconnect: extensive highways along the most dense areas and city center, large private real estate developments that do not provide adequate riverside access, and large industrial complexes that almost completely lack riverside utilization. Finally, as part of the suggested strategies, the study concludes that the most efficient and practical way to improve this situation is to follow the historic master-planning of Chongqing and create connective nodes in critical urban locations along the river, a strategy that has been used for centuries to handle the same urban-waterside relationship. Reviewing and implementing this strategy will allow the city to better connect with the rivers, reducing the various impacts of disconnect and urban transformation.

Keywords: Chongqing City, megalopolis, nodes, riverbanks disconnection, urban

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Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

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The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

Procedia PDF Downloads 132

Authors: Siphesihle Hlongwane

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Background: Globally, alcohol consumption, smoking, and the use of illicit drugs kill more than 11.8 million people each year. In sub-Saharan Africa, substance abuse is responsible for more than 6.4% of all deaths recorded and about 4.7% of all Disability Adjusted Life Years (DALYs), with numbers still expected to grow if no drastic measures are taken to curb and address drug use. In a setting where substance use is rife, understanding contextual factors that influence an individual’s perceived eligibility to seek rehabilitation is paramount. Using the candidacy framework, we unpack how situational factors influence an individual’s perceived eligibility for healthcare uptake in adolescents and youth with substance use disorder (SUD). Methods: The candidacy framework is concerned with how people consider their eligibility for accessing a health service. The study collected and analyzed primary qualitative data to answer the research question. Data were collected between January and July 2022 on participants aged between 18 and 35 for drug users and 18 to 60 for family members. Participants include 20 previous and current drug users and 20 family members that experience the effects of addiction. A pre-drafted semi-structured interview guide was administered to a conveniently sampled population supplemented with a referral sampling method. Data were thematically analyzed using the NVivo 12pro software to manage the data. Findings: Our findings show that people with substance use disorders are aware of their drug use habits and acknowledge their candidacy for health services. Candidacy for health services is also acknowledged by those around them, such as family members and peers, and as such, information on the navigation of health services for drug users is shared by those who have attended health services, those affected by drug use, and this includes health service research by family members to identify accessible health services. While participants reported willingness to quit drug use if assistance is provided, the permeability of health care services is hindered by both individual determinations to quit drug use from long-time use and the availability of health services for drug users, such as rehabilitation centers. Our findings also show that drug users are conscious and can articulate their ailments; however, the hunt for the next dose of drugs and long waiting cues for health service acquisition overshadows their claim to health services. Participants reported a mixture of treatments prescribed, with some more gruesome than others prescribed, thus serving as both a facilitator and barrier for health service uptake. Despite some unorthodox forms of treatments prescribed in health care, the majority of those who enter treatment complete the process of treatment, although some are met with setbacks and sometimes relapse after treatment has finished. Conclusion: Drug users are able to ascertain their candidacy for health services; however, individual and environmental characteristics relating to drug use hinder the use of health services. Drug use interventions need to entice health service uptake as a way to improve candidacy for health use.

Keywords: substance use disorder, rehabilitation, drug use, relapse, South Africa, candidacy framework

Procedia PDF Downloads 98

Authors: Gustavo Cruz-Bello

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Progreso is a coastal community in Yucatan, Mexico, highly exposed to floods produced by severe storms and tropical cyclones. A participatory cartography approach was conducted to help to reduce floods disasters and assess social vulnerability within the community. The first step was to engage local authorities in risk management to facilitate the process. Two workshop were conducted, in the first, a poster size printed high spatial resolution satellite image of the town was used to gather information from the participants: eight women and seven men, among them construction workers, students, government employees and fishermen, their ages ranged between 23 and 58 years old. For the first task, participants were asked to locate emblematic places and place them in the image to familiarize with it. Then, they were asked to locate areas that get flooded, the buildings that they use as refuges, and to list actions that they usually take to reduce vulnerability, as well as to collectively come up with others that might reduce disasters. The spatial information generated at the workshops was digitized and integrated into a GIS environment. A printed version of the map was reviewed by local risk management experts, who validated feasibility of proposed actions. For the second workshop, we retrieved the information back to the community for feedback. Additionally a survey was applied in one household per block in the community to obtain socioeconomic, prevention and adaptation data. The information generated from the workshops was contrasted, through T and Chi Squared tests, with the survey data in order to probe the hypothesis that poorer or less educated people, are less prepared to face floods (more vulnerable) and live near or among higher presence of floods. Results showed that a great majority of people in the community are aware of the hazard and are prepared to face it. However, there was not a consistent relationship between regularly flooded areas with people’s average years of education, house services, or house modifications against heavy rains to be prepared to hazards. We could say that the participatory cartography intervention made participants aware of their vulnerability and made them collectively reflect about actions that can reduce disasters produced by floods. They also considered that the final map could be used as a communication and negotiation instrument with NGO and government authorities. It was not found that poorer and less educated people are located in areas with higher presence of floods.

Keywords: climate change, floods, Mexico, participatory mapping, social vulnerability

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Authors: Jia-Chao Wang

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A model of the universe without invoking space expansion is proposed to explain the observed redshift-distance relation and the cosmic microwave background radiation (CMB). The main hypothesized feature of the model is that photons traveling in space interact with the CMB photon gas. This interaction causes the photons to gradually lose energy through dissipation and, therefore, experience redshift. The interaction also causes some of the photons to be scattered off their track toward an observer and, therefore, results in beam intensity attenuation. As observed, the CMB exists everywhere in space and its photon density is relatively high (about 410 per cm³). The small average energy of the CMB photons (about 6.3×10⁻⁴ eV) can reduce the energies of traveling photons gradually and will not alter their momenta drastically as in, for example, Compton scattering, to totally blur the images of distant objects. An object moving through a thermalized photon gas, such as the CMB, experiences a drag. The cause is that the object sees a blue shifted photon gas along the direction of motion and a redshifted one in the opposite direction. An example of this effect can be the observed CMB dipole: The earth travels at about 368 km/s (600 km/s) relative to the CMB. In the all-sky map from the COBE satellite, radiation in the Earth's direction of motion appears 0.35 mK hotter than the average temperature, 2.725 K, while radiation on the opposite side of the sky is 0.35 mK colder. The pressure of a thermalized photon gas is given by Pγ = Eγ/3 = αT⁴/3, where Eγ is the energy density of the photon gas and α is the Stefan-Boltzmann constant. The observed CMB dipole, therefore, implies a pressure difference between the two sides of the earth and results in a CMB drag on the earth. By plugging in suitable estimates of quantities involved, such as the cross section of the earth and the temperatures on the two sides, this drag can be estimated to be tiny. But for a photon traveling at the speed of light, 300,000 km/s, the drag can be significant. In the present model, for the dissipation part, it is assumed that a photon traveling from a distant object toward an observer has an effective interaction cross section pushing against the pressure of the CMB photon gas. For the attenuation part, the coefficient of the typical attenuation equation is used as a parameter. The values of these two parameters are determined by fitting the 748 µ vs. z data points compiled from 643 supernova and 105 γ-ray burst observations with z values up to 8.1. The fit is as good as that obtained from the lambda cold dark matter (ΛCDM) model using online cosmological calculators and Planck 2015 results. The model can be used to interpret Hubble's constant, Olbers' paradox, the origin and blackbody nature of the CMB radiation, the broadening of supernova light curves, and the size of the observable universe.

Keywords: CMB as the lowest energy state, model of the universe, origin of CMB in a static universe, photon-CMB photon gas interaction

Procedia PDF Downloads 134

Authors: Selvaprakash Ramalingam, Rabi N. Sahoo, Dharmendra Saraswat, A. Kumar, Rajeev Ranjan, Joydeep Mukerjee, Viswanathan Chinnasamy, K. K. Chaturvedi, Sanjeev Kumar

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Rice is one of the most important staple food crops in the world. Among the various diseases that affect rice crops, rice blast is particularly significant, causing crop yield and economic losses. While the plant has defense mechanisms in place, such as chemical indicators (proteins, salicylic acid, jasmonic acid, ethylene, and azelaic acid) and resistance genes in certain varieties that can protect against diseases, susceptible varieties remain vulnerable to these fungal diseases. Early prediction of rice blast (RB) disease is crucial, but conventional techniques for early prediction are time-consuming and labor-intensive. Hyperspectral remote sensing techniques hold the potential to predict RB disease at its asymptomatic stage. In this study, we aimed to demonstrate the prediction of RB disease at the asymptomatic stage using non-imaging hyperspectral ASD spectroradiometer under controlled laboratory conditions. We applied statistical spectral discrimination theory to identify unknown spectra of M. Oryzae, the fungus responsible for rice blast disease. The infrared (IR) region was found to be significantly affected by RB disease. These changes may result in alterations in the absorption, reflection, or emission of infrared radiation by the affected plant tissues. Our research revealed that the protein spectrum in the IR region is impacted by RB disease. In our study, we identified strong correlations in the region (Amide group - I) around X 1064 nm and Y 1300 nm with the Lambda / Lambda derived spectra methods for protein detection. During the stages when the disease is developing, typically from day 3 to day 5, the plant's defense mechanisms are not as effective. This is especially true for the PB-1 variety of rice, which is highly susceptible to rice blast disease. Consequently, the proteins in the plant are adversely affected during this critical time. The spectral contour plot reveals the highly correlated spectral regions 1064 nm and Y 1300 nm associated with RB disease infection. Based on these spectral sensitivities, we developed new spectral disease indices for predicting different stages of disease emergence. The goal of this research is to lay the foundation for future UAV and satellite-based studies aimed at long-term monitoring of RB disease.

Keywords: rice blast, asymptomatic stage, spectral sensitivity, IR

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Authors: Ahmed Elaksher

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Over the last few years, significant progresses have been made and new approaches have been proposed for efficient collection of 3D spatial data from Unmanned aerial vehicles (UAVs) with reduced costs compared to imagery from satellite or manned aircraft. In these systems, a low-cost GPS unit provides the position, velocity of the vehicle, a low-quality inertial measurement unit (IMU) determines its orientation, and off-the-shelf cameras capture the images. Structure from Motion (SfM) and photogrammetry are the main tools for 3D surface reconstruction from images collected by these systems. Unlike traditional techniques, SfM allows the computation of calibration parameters using point correspondences across images without performing a rigorous laboratory or field calibration process and it is more flexible in that it does not require consistent image overlap or same rotation angles between successive photos. These benefits make SfM ideal for UAVs aerial mapping. In this paper, a direct comparison between SfM Digital Elevation Models (DEM) and those generated through traditional photogrammetric techniques was performed. Data was collected by a 3DR IRIS+ Quadcopter with a Canon PowerShot S100 digital camera. Twenty ground control points were randomly distributed on the ground and surveyed with a total station in a local coordinate system. Images were collected from an altitude of 30 meters with a ground resolution of nine mm/pixel. Data was processed with PhotoScan, VisualSFM, Imagine Photogrammetry, and a photogrammetric algorithm developed by the author. The algorithm starts with performing a laboratory camera calibration then the acquired imagery undergoes an orientation procedure to determine the cameras’ positions and orientations. After the orientation is attained, correlation based image matching is conducted to automatically generate three-dimensional surface models followed by a refining step using sub-pixel image information for high matching accuracy. Tests with different number and configurations of the control points were conducted. Camera calibration parameters estimated from commercial software and those obtained with laboratory procedures were comparable. Exposure station positions were within less than few centimeters and insignificant differences, within less than three seconds, among orientation angles were found. DEM differencing was performed between generated DEMs and few centimeters vertical shifts were found.

Keywords: UAV, photogrammetry, SfM, DEM

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Authors: Atefeh Omidkhah Kharashtomi, Rasoul Hedayat Nejad, Saeed Bakhtiyari

Abstract:

Circulation paths and indoor connection network of the building play an important role both in the daily operation of the building and during evacuation in emergency situations. The degree of legibility of the paths for navigation inside the building has a deep connection with the perceptive and cognitive system of human, and the way the surrounding environment is being perceived. Human perception of the space is based on the sensory systems in a three-dimensional environment, and non-linearly, so it is necessary to avoid reducing its representations in architectural design as a two-dimensional and linear issue. Today, the advances in the field of virtual reality (VR) technology have led to various applications, and architecture and building science can benefit greatly from these capabilities. Especially in cases where the design solution requires a detailed and complete understanding of the human perception of the environment and the behavioral response, special attention to VR technologies could be a priority. Way-finding in the indoor circulation network is a proper example for such application. Success in way-finding could be achieved if human perception of the route and the behavioral reaction have been considered in advance and reflected in the architectural design. This paper discusses the VR technology applications for the way-finding improvements in indoor engineering of the building. In a systematic review, with a database consisting of numerous studies, firstly, four categories for VR applications for circulation way-finding have been identified: 1) data collection of key parameters, 2) comparison of the effect of each parameter in virtual environment versus real world (in order to improve the design), 3) comparing experiment results in the application of different VR devices/ methods with each other or with the results of building simulation, and 4) training and planning. Since the costs of technical equipment and knowledge required to use VR tools lead to the limitation of its use for all design projects, priority buildings for the use of VR during design are introduced based on case-studies analysis. The results indicate that VR technology provides opportunities for designers to solve complex buildings design challenges in an effective and efficient manner. Then environmental parameters and the architecture of the circulation routes (indicators such as route configuration, topology, signs, structural and non-structural components, etc.) and the characteristics of each (metrics such as dimensions, proportions, color, transparency, texture, etc.) are classified for the VR way-finding experiments. Then, according to human behavior and reaction in the movement-related issues, the necessity of scenario-based and experiment design for using VR technology to improve the design and receive feedback from the test participants has been described. The parameters related to the scenario design are presented in a flowchart in the form of test design, data determination and interpretation, recording results, analysis, errors, validation and reporting. Also, the experiment environment design is discussed for equipment selection according to the scenario, parameters under study as well as creating the sense of illusion in the terms of place illusion, plausibility and illusion of body ownership.

Keywords: virtual reality (VR), way-finding, indoor, circulation, design

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

Abstract:

Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

Procedia PDF Downloads 133