Search results for: Argos satellite telemetry

Authors: Timma Reddy, Srikonda Ramesh

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India has been traditionally vulnerable to natural disasters such as Floods, droughts, cyclones, earthquakes and landslides. It has become a recurrent phenomenon as observed in last five decades. The survey indicates that about 60% of the landmass is prone to earthquakes of various intensities; over 40 million hectares is prone to floods; about 8% of the total area is prone to cyclones and 68% of the area is susceptible to drought. Climate change is likely to be perceived through experience of extreme weather events. There is growing societal concern about climate change, given the potential impacts of associated natural hazards such as cyclones, flooding, earthquakes, landslides etc, hence it is essential and crucial to strengthening our settlements to respond to such calamities. So, the research paper focus is to analyze the effective planning strategy/mechanism to integrate disaster mitigation measures in coastal regions in general and Capital Region of Andhra Pradesh in particular. The basic hypothesis is to govern the appropriate special planning considerations would facilitate to have organized way of protective life and properties from natural disasters. And further to integrate the infrastructure planning with conscious direction would provide an effective mitigations measures. It has been planned and analyzed to Vijayawada city with conscious land use planning with reference to space syntax trajectory in accordance to required social infrastructure such as health facilities, institution areas and recreational and other open spaces. It has been identified that the geographically ideal location with reference to the population densities based on GIS tools the properness strategies can be effectively integrated to protect the life and to save the properties by means of reducing the damage/impact of natural disasters in general earth quake/cyclones or floods in particularly.

Keywords: modular, trajectories, social infrastructure, evidence based syntax, drills and equipments, GIS, geographical micro zoning, high resolution satellite image

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Authors: Israel Ropo Orimoloye, Johanes A. Belle, Olusola Adeyemi, Olusola O. Ololade

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With more than 100,000 orbits during the past 20 years, Terra has significantly improved our knowledge of the Earth's climate and its implications on societies and ecosystems of human activity and natural disasters, including drought events. With Terra instrument's performance and the free distribution of its products, this study utilised Terra MOD13Q1 satellite data to assess drought disaster events and its spatiotemporal patterns over the Free State Province of South Africa between 2001 and 2019 for summer, autumn, winter, and spring seasons. The study also used high-resolution downscaled climate change projections under three representative concentration pathways (RCP). Three future periods comprising the short (the 2030s), medium (2040s), and long term (2050s) compared to the current period are analysed to understand the potential magnitude of projected climate change-related drought. The study revealed that the year 2001 and 2016 witnessed extreme drought conditions where the drought index is between 0 and 20% across the entire province during summer, while the year 2003, 2004, 2007, and 2015 observed severe drought conditions across the region with variation from one part to the another. The result shows that from -24.5 to -25.5 latitude, the area witnessed a decrease in precipitation (80 to 120mm) across the time slice and an increase in the latitude -26° to -28° S for summer seasons, which is more prominent in the year 2041 to 2050. This study emphasizes the strong spatio-environmental impacts within the province and highlights the associated factors that characterise high drought stress risk, especially on the environment and ecosystems. This study contributes to a disaster risk framework to identify areas for specific research and adaptation activities on drought disaster risk and for environmental planning in the study area, which is characterised by both rural and urban contexts, to address climate change-related drought impacts.

Keywords: remote sensing, drought disaster, climate scenario, assessment

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Authors: Poonam Sharma, Ankur Srivastav

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Cities are complex and dynamic systems that constitute a significant challenge to urban planning. The increasing size of the built-up area owing to growing population pressure and economic growth have lead to massive Landuse/Landcover change resulted in the loss of natural habitat and thus reducing the green covers in urban areas. Urban environmental quality is influenced by several aspects, including its geographical configuration, the scale, and nature of human activities occurring and environmental impacts generated. Cities have transformed into complex and dynamic systems that constitute a significant challenge to urban planning. Cities and their sustainability are often discussed together as the cities stand confronted with numerous environmental concerns as the world becoming increasingly urbanized, and the cities are situated in the mesh of global networks in multiple senses. A rapid transformed urban setting plays a crucial role to change the green area of natural habitats. To examine the pattern of urban growth and to measure the Landuse/Landcover change in Gurgoan in Haryana, India through the integration of Geospatial technique is attempted in the research paper. Satellite images are used to measure the spatiotemporal changes that have occurred in the land use and land cover resulting into a new cityscape. It has been observed from the analysis that drastically evident changes in land use has occurred with the massive rise in built up areas and the decrease in green cover and therefore causing the sustainability of the city an important area of concern. The massive increase in built-up area has influenced the localised temperatures and heat concentration. To enhance the decision-making process in urban planning, a detailed and real world depiction of these urban spaces is the need of the hour. Monitoring indicators of key processes in land use and economic development are essential for evaluating policy measures.

Keywords: cityscape, geospatial techniques, green cover index, urban environmental quality, urban planning

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Authors: Humphrey Agevi, Harrison Tsingalia, Richard Onwonga, Shem Kuyah

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Most of the world ecosystems have been affected by the effects of climate change. Efforts have been made to mitigate against climate change effects. While most studies have been done in forest ecosystems and pure plant plantations, trees on farms including agroforestry have only received attention recently. Agroforestry systems and tree cover on agricultural lands make an important contribution to climate change mitigation but are not systematically accounted for in the global carbon budgets. This study sought to: (i) determine tree diversity in different agroforestry practices; (ii) determine tree biomass in different agroforestry practices. Study area was determined according to the Land degradation surveillance framework (LSDF). Two study sites were established. At each of the site, a 5km x 10km block was established on a map using Google maps and satellite images. Way points were then uploaded in a GPS helped locate the blocks on the ground. In each of the blocks, Nine (8) sentinel clusters measuring 1km x 1km were randomized. Randomization was done in a common spreadsheet program and later be downloaded to a Global Positioning System (GPS) so that during surveys the researchers were able to navigate to the sampling points. In each of the sentinel cluster, two farm boundaries were randomly identified for convenience and to avoid bias. This led to 16 farms in Kakamega South and 16 farms in Kakamega North totalling to 32 farms in Kakamega Site. Species diversity was determined using Shannon wiener index. Tree biomass was determined using allometric equation. Two agroforestry practices were found; homegarden and hedgerow. Species diversity ranged from 0.25-2.7 with a mean of 1.8 ± 0.10. Species diversity in homegarden ranged from 1-2.7 with a mean of 1.98± 0.14. Hedgerow species diversity ranged from 0.25-2.52 with a mean of 1.74± 0.11. Total Aboveground Biomass (AGB) determined was 13.96±0.37 Mgha-1. Homegarden with the highest abundance of trees had higher above ground biomass (AGB) compared to hedgerow agroforestry. This study is timely as carbon budgets in the agroforestry can be incorporated in the global carbon budgets and improve the accuracy of national reporting of greenhouse gases.

Keywords: agroforestry, allometric equations, biomass, climate change

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Authors: A. Berraf-Tebbal, Z. Bouznad, , A.J.L. Phillips

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Phaeomoniella is a fungus genus in the mitosporic ascomycota which includes Phaeomoniella chlamydospora specie associated with two declining diseases on grapevine (Vitis vinifera) namely Petri disease and esca. Recent studies have shown that several Phaeomoniella species also cause disease on many other woody crops, such as forest trees and woody ornamentals. Two new species, Phaeomoniella zymoides and Phaeomoniella pinifoliorum H.B. Lee, J.Y. Park, R.C. Summerbell et H.S. Jung, were isolated from the needle surface of Pinus densiflora Sieb. et Zucc. in Korea. The identification of species in Phaeomoniella genus can be a difficult task if based solely on morphological and cultural characters. In this respect, the application of molecular methods, particularly PCR-based techniques, may provide an important contribution. MSP-PCR (microsatellite primed-PCR) fingerprinting has proven useful in the molecular typing of fungal strains. The high discriminatory potential of this method is particularly useful when dealing with closely related or cryptic species. In the present study, the application of PCR fingerprinting was performed using the micro satellite primer M13 for the purpose of species identification and strain typing of 84 Phaeomoniella -like isolates collected from grapevines with typical symptoms of dieback. The bands produced by MSP-PCR profiles divided the strains into 3 clusters and 5 singletons with a reproducibility level of 80%. Representative isolates from each group and, when possible, isolates from Eutypa dieback and esca symptoms were selected for sequencing of the ITS region. The ITS sequences for the 16 isolates selected from the MSP-PCR profiles were combined and aligned with sequences of 18 isolates retrieved from GenBank, representing a selection of all known Phaeomoniella species. DNA sequences were compared with those available in GenBank using Neighbor-joining (NJ) and Maximum-parsimony (MP) analyses. The phylogenetic trees of the ITS region revealed that the Phaeomoniella isolates clustered with Phaeomoniella chlamydospora reference sequences with a bootstrap support of 100 %. The complexity of the pathosystems vine-trunk diseases shows clearly the need to identify unambiguously the fungal component in order to allow a better understanding of the etiology of these diseases and justify the establishment of control strategies against these fungal agents.

Keywords: Genotyping, MSP-PCR, ITS, phylogeny, trunk diseases

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Authors: Khojesta Kawish, Tetsuya Ando, Sayed Abdul Basir Samimi

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Bagh-e Dasht area is situated in the northern part of Herat, an old city in western Afghanistan located on the Silk Road which has received a strong influence from Persian culture. Initially, the Bagh-e Dasht area was developed for gardens and palaces near Joy-e Injil canal during the Timurid Empire in the 15^th century. It is assumed Bagh-e Dasht became a settlement in the 16^th century during the Safavid Empire. The oldest area is the southern part around the canal bank which is characterized by Dalans, sun-dried brick arcades above which houses are often constructed. Traditional houses in this area are built with domical vault roofs constructed with sun-dried bricks. Bagh-e Dasht is one of the best-preserved settlements of traditional houses in Herat. This study examines the transformation of the Bagh-e Dasht area with a focus on Dalans, where traditional houses with domical vault roofs have been well-preserved until today. The aim of the study is to examine the extent of physical changes to the area as well as changes to houses and the community. This research paper contains original results which have previously not been published in architectural history. The roof types of houses in the area are investigated through examining high resolution satellite images. The boundary of each building and space is determined by both a field survey and aerial photographs of the study area. A comprehensive field survey was then conducted to examine each space and building in the area. In addition, a questionnaire was distributed to the residents of the Dalan houses and interviews were conducted with the Wakil (Chief) of the area, a local historian, residents and traditional builders. The study finds that the oldest part of Bagh-e Dasht area, the south, contains both Dalans and domical vault roof houses. The next oldest part, which is the north, only has domical vault roof houses. The rest of the area only has houses with modernized flat roofs. This observation provides an insight into the process of historical development in the Bagh-e Dasht area.

Keywords: Afghanistan, Bagh-e Dasht, Dalan, domical vault, Herat, over path house, traditional house

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Authors: Yasir E. Mohieldeen

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Qatar is one of the most water scarce countries in the World. In 2014, the average per capita rainfall was less than 29 m3/y/ca, while the global average is 6,000 m3/y/ca. However, the per capita water consumption in Qatar is among the highest in the World: more than 500 liters per person per day, whereas the global average is 160 liters per person per day. Since the early 2000s, Qatar has been relying heavily on desalinated water from the Arabian Gulf as the main source of fresh water. In 2009, about 99.9% of the total potable water produced was desalinated. Reliance on desalinated water makes Qatar very vulnerable to water related natural disasters, such as the red-tide phenomenon. Qatar’s strategic water reserve lasts for only 7 days. In case of red-tide outbreak, the country would not be able to desalinate water for days, let alone the months that this disaster would bring about (as it clogs the desalination equipment). The 2008-09 red-tide outbreak, for instance, lasted for more than eight months and forced the closure of desalination plants in the region for weeks. This study aims at identifying favorite conditions for red-tide outbreaks, using satellite data along with in-situ measurements. This identification would allow the prediction of these outbreaks and their hotspots. Prediction and monitoring of outbreaks are crucial to water security in the country, as different measures could be put in place in advance to prevent an outbreak and mitigate its impact if it happened. Red-tide outbreaks are detected using different algorithms for chlorophyll concentration in the Gulf waters. Vegetation indices, such as Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were used along with Surface Algae Bloom Index (SABI) to detect known outbreaks. MODIS (or Moderate Resolution Imaging Spectroradiometer) bands are used to calculate these indices. A red-tide outbreaks atlas in the Arabian Gulf is being produced. Prediction of red-tide outbreaks ahead of their occurrences would give critical information on possible water-shortage in the country. Detecting known outbreaks in the past few decades and related parameters (e.g. water salinity, water surface temperature, nutrition, sandstorms, … etc) enables the identification of favorite conditions of red-tide outbreak that are key to the prediction of these outbreaks.

Keywords: Arabian Gulf, MODIS, red-tide detection, strategic water reserve, water desalination

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Authors: Ashok Tejankar, Rohan K. Pathrikar

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Maharashtra is covered by heterogeneous flows of Deccan basaltic terrains of upper cretaceous to lower Eocene age. It consist mainly different types of basalt flow, having heterogeneous Geohydrological characters. The study area Aurangabad dist. lies in the central part of Maharashtra. The study area is typically covered by Deccan traps formation mainly basalt type of igneous volcanic rock. The area is located in the survey of India toposheet No. 47M and laying between 19° to 20° north latitudes and 74° to 76° east longitudes. Groundwater is the primary source for fresh water in the study area. There has been a growing demand for fresh water in domestic & agriculture sectors. Due to over exploitation and rainfall failure has been created an irrecoverable stress on groundwater in study area. In an effort to maintain the water table condition in balance, artificial recharge is being implemented. The selection of site for artificial recharge is a very important task in recharge basalt. The present study aims at sitting artificial recharge structure at village Pachod in basaltic terrain of the Godavari-Purna river basin in Aurangabad district of Maharashtra, India. where the average annual rainfall is 650mm. In this investigation, integrated remote sensing and GIS techniques were used and various parameters like lithology, structure, etc. aspect of drainage basins, landforms and other parameters were extracted from visual interpretation of IRS P6 Satellite data and Survey of India (SIO) topographical sheets, aided by field checks by carrying well inventory survey. The depth of weathered material, water table conditions, and rainfall data were been considered. All the thematic information layers were digitized and analyzed in Arc-GIS environment and the composite maps produced show suitable site, depth of bed rock flows for successful artificial recharge in village Pachod to increase groundwater potential of low laying area.

Keywords: hard rock, artificial recharge, remote sensing, GIS

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Authors: M. Achemo, O. Saito

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Jefoure land use system is one of the traditional landscape human settlement patterns, and it is a cultural design and peculiar art of the people of Gurage in Ethiopia via which houses and trees flank roads left and right. Assessment of the multiple benefits of the traditional road that benefit society and development could enhance the understanding of the land use planners and decision makers to pay attention while planning and managing the land use system. Recent trend shows that the Jefoure land use is on the threshold of change as a result of flourishing road networks, overgrazing, and agricultural expansion. This study aimed to evaluate the multiple ecosystem services provided by the Jefoure land use system after characterization of the socio-ecological landscape. Information was compiled from existing data sources such as ordnance survey maps, aerial photographs, recent high resolution satellite imageries, designated questionnaires and interviews, and local authority contacts. The result generated scientific data on the characteristics, ecosystem services provision, and drivers of changes. The cultural landscape has novel characteristics and providing multiple ecosystem services to the community for long period of time. It is serving as road for humans, livestock and vehicles, habitat for plant species, regulating local temperature, climate, runoff and infiltration, and place for meeting, conducting religious and spiritual activities, holding social events such as marriage and mourning, playing station for children and court for football and other traditional games. As a result of its aesthetic quality and scenic beauty, it is considered as recreational place for improving mental and physical health. The study draws relevant land use planning and management solution in the improvement of socio-ecological resilience in the Jefoure land use system. The study suggests the landscape needs to be registrar as heritage site for recognizing the wisdom of the community and enhancing the conservation mechanisms.

Keywords: cultural landscape, ecosystem services, Gurage, Jefoure

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Authors: Periklis Brakatsoulas

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Recent empirical research shows a growing interest in investment decision-making under market anomalies that contradict the rational paradigm. Momentum is undoubtedly one of the most robust anomalies in the empirical asset pricing research and remains surprisingly lucrative ever since first documented. Although predominantly phenomena identified across equities, momentum premia are now evident across various asset classes. Yet few many attempts are made so far to provide traders a diversified portfolio of strategies across different assets and markets. Moreover, literature focuses on patterns from past returns rather than mechanisms to signal future price directions prior to momentum runs. The aim of this paper is to develop a diversified portfolio approach to price distortion signals using daily position data on stocks, credit derivatives, and bonds. An algorithm allocates assets periodically, and new investment tactics take over upon price momentum signals and across different ranking groups. We focus on momentum life cycles, trend reversals, and price acceleration signals. The main effort here concentrates on the density, time span and maturity of momentum phenomena to identify consistent patterns over time and measure the predictive power of buy-sell signals generated by these anomalies. To tackle this, we propose a two-stage modelling process. First, we generate forecasts on core macroeconomic drivers. Secondly, satellite models generate market risk forecasts using the core driver projections generated at the first stage as input. Moreover, using a combination of the ARFIMA and FIGARCH models, we examine the dependence of consecutive observations across time and portfolio assets since long memory behavior in volatilities of one market appears to trigger persistent volatility patterns across other markets. We believe that this is the first work that employs evidence of volatility transmissions among derivatives, equities, and bonds to identify momentum life cycle patterns.

Keywords: forecasting, long memory, momentum, returns

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Authors: Saeed Farhadypour, Majid Azadi, Habibolla Sayyari, Mahmood Mosavi, Shahram Irani, Aliakbar Bidokhti, Omid Alizadeh Choobari, Ziba Hamidi

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In the recent decades, frequencies of dust events have increased significantly in west and south west of Iran. First, a survey on the dust events during the period (1990-2013) is investigated using historical dust data collected at 6 weather stations scattered over west and south-west of Iran. After statistical analysis of the observational data, one of the most severe dust storm event that occurred in the region from 3rd to 6th July 2009, is selected and analyzed. WRF-Chem model is used to simulate the amount of PM10 and how to transport it to the areas. The initial and lateral boundary conditions for model obtained from GFS data with 0.5°×0.5° spatial resolution. In the simulation, two aerosol schemas (GOCART and MADE/SORGAM) with 3 options (chem_opt=106,300 and 303) were evaluated. Results of the statistical analysis of the historical data showed that south west of Iran has high frequency of dust events, so that Bushehr station has the highest frequency between stations and Urmia station has the lowest frequency. Also in the period of 1990 to 2013, the years 2009 and 1998 with the amounts of 3221 and 100 respectively had the highest and lowest dust events and according to the monthly variation, June and July had the highest frequency of dust events and December had the lowest frequency. Besides, model results showed that the MADE / SORGAM scheme has predicted values and trends of PM10 better than the other schemes and has showed the better performance in comparison with the observations. Finally, distribution of PM10 and the wind surface maps obtained from numerical modeling showed that the formation of dust plums formed in Iraq and Syria and also transportation of them to the West and Southwest of Iran. In addition, comparing the MODIS satellite image acquired on 4th July 2009 with model output at the same time showed the good ability of WRF-Chem in simulating spatial distribution of dust.

Keywords: dust storm, MADE/SORGAM scheme, PM10, WRF-Chem

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Authors: Saad Algharib, Jay Lee

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Urbanization is a complex phenomenon that occurs during the city’s development from one form to another. In other words, it is the process when the activities in the land use/land cover change from rural to urban. Since the oil exploration, Kuwait City has been growing rapidly due to its urbanization and population growth by both natural growth and inward immigration. The main objective of this study is to detect changes in urban land use/land cover and to examine the changing spatial patterns of urban growth in and around Kuwait City between 1989 and 2001. In addition, this study also evaluates the spatial patterns of the changes detected and how they can be related to the spatial configuration of the city. Recently, the use of remote sensing and geographic information systems became very useful and important tools in urban studies because of the integration of them can allow and provide the analysts and planners to detect, monitor and analyze the urban growth in a region effectively. Moreover, both planners and users can predict the trends of the growth in urban areas in the future with remotely sensed and GIS data because they can be effectively updated with required precision levels. In order to identify the new urban areas between 1989 and 2001, the study uses satellite images of the study area and remote sensing technology for classifying these images. Unsupervised classification method was applied to classify images to land use and land cover data layers. After finishing the unsupervised classification method, GIS overlay function was applied to the classified images for detecting the locations and patterns of the new urban areas that developed during the study period. GIS was also utilized to evaluate the distribution of the spatial patterns. For example, Moran’s index was applied for all data inputs to examine the urban growth distribution. Furthermore, this study assesses if the spatial patterns and process of these changes take place in a random fashion or with certain identifiable trends. During the study period, the result of this study indicates that the urban growth has occurred and expanded 10% from 32.4% in 1989 to 42.4% in 2001. Also, the results revealed that the largest increase of the urban area occurred between the major highways after the forth ring road from the center of Kuwait City. Moreover, the spatial distribution of urban growth occurred in cluster manners.

Keywords: geographic information systems, remote sensing, urbanization, urban growth

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Magdy Torab

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Ancient Egyptians built their temples purposefully close to the River Nile to use it for transporting construction stones from far away quarries to building sites in river-boats. Most temples, therefore, have river-harbors associated with their geometric designs. The paleoriver channel remapped by using this idea, besides other geomorphological and geoarchaeological indicators/evidence located between Aswan and Luxor cities. In this sense, this paper defines the characteristics of this ancient course and its associated landforms using paleochannel morphology, paleomeandering, and ancient river dynamics during historic and prehistoric times. Both geomorphological and geoarchaeological approaches used to reconstruct the paleomorphology of the river course. It helps to investigate the ancient river morphology by using the following techniques: comparison and interpretation of multi dates satellite images and historical maps between 1943 and 2004. The results illustrated on maps using GIS (ARC GIS V.10 software) and the field data collected from the western bank of The Nile River at Luxor area and Karnak, Edfu, Esna and Kom Ombo temples. Created both current and paleogeomorphological maps depending upon the results of geoarchaeological surveying and soil analysis and dating, for surface and subsurface soil sampling by handle auger, laser diffraction analysis for 7 soil samples collected from some mounds and Malkata channel in the western bank of The Nile River near Luxor. Paleo-current directions were determined by using standard Brunton compass to use it as an indicator is evidence for the direction of flow of The Nile River during deposition of some accumulated mounds on the western part of the floodplain near Luxor city. C-14 dating was used for two samples collected from these mounds as well as geographical information system (GIS) technique for mapping. The geomorphological and geoarchaeological evidence shows that the Nile River course in Luxor area was around 4.5 km wide and contained many islands and sandbars which separated inside the river channel, now appearing as scattered mounds inside the floodplain. Upper Egypt has migrated during the historic times to the east up to five kilometers and become far away from the ancient temples, quarries, and harbors. It has also become as well as become more meandering and narrower than before.

Keywords: Nile River, ancient harbours, Luxor, paleogeomorphology, geoarchaeology

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Authors: Yun Chen, Qihang Liu, Catherine Ticehurst, Chandrama Sarker, Fazlul Karim, Dave Penton, Ashmita Sengupta

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The application of ICESAT-2 altimetry data in river hydrology critically depends on the accuracy of the mean water surface elevation (WSE) at a virtual station (VS) where satellite observations intersect with water. The ICESAT-2 track generates multiple VSs as it crosses the different water bodies. The difficulties are particularly pronounced in large river basins where there are many tributaries and meanders often adjacent to each other. One challenge is to split photon segments along a beam to accurately partition them to extract only the true representative water height for individual elements. As far as we can establish, there is no automated procedure to make this distinction. Earlier studies have relied on human intervention or river masks. Both approaches are unsatisfactory solutions where the number of intersections is large, and river width/extent changes over time. We describe here an automated approach called “auto-segmentation”. The accuracy of our method was assessed by comparison with river water level observations at 10 different stations on 37 different dates along the Lower Murray River, Australia. The congruence is very high and without detectable bias. In addition, we compared different outlier removal methods on the mean WSE calculation at VSs post the auto-segmentation process. All four outlier removal methods perform almost equally well with the same R2 value (0.998) and only subtle variations in RMSE (0.181–0.189m) and MAE (0.130–0.142m). Overall, the auto-segmentation method developed here is an effective and efficient approach to deriving accurate mean WSE at river VSs. It provides a much better way of facilitating the application of ICESAT-2 ATL13 altimetry to rivers compared to previously reported studies. Therefore, the findings of our study will make a significant contribution towards the retrieval of hydraulic parameters, such as water surface slope along the river, water depth at cross sections, and river channel bathymetry for calculating flow velocity and discharge from remotely sensed imagery at large spatial scales.

Keywords: lidar sensor, virtual station, cross section, mean water surface elevation, beam/track segmentation

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Authors: Sara Tokhi Arab, Rozo Noguchi, Tofeal Ahamed

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Drought is a natural disaster that occurs in a region due to a lack of precipitation and high temperatures over a continuous period or in a single season as a consequence of climate change. Precipitation deficits and prolonged high temperatures mostly affect the agricultural sector, water resources, socioeconomics, and the environment. Consequently, it causes agricultural product loss, food shortage, famines, migration, and natural resources degradation in a region. Agriculture is the first sector affected by drought. Therefore, it is important to develop an agricultural drought risk and loss assessment to mitigate the drought impact in the agriculture sector. In this context, the main purpose of this study was to assess yield loss using composite drought indices in the drought-affected vineyards. In this study, the CDI was developed for the years 2016 to 2020 by comprising five indices: the vegetation condition index (VCI), temperature condition index (TCI), deviation of NDVI from the long-term mean (NDVI DEV), normalized difference moisture index (NDMI) and precipitation condition index (PCI). Moreover, the quantitative principal component analysis (PCA) approach was used to assign a weight for each input parameter, and then the weights of all the indices were combined into one composite drought index. Finally, Bayesian regularized artificial neural networks (BRANNs) were used to evaluate the yield variation in each affected vineyard. The composite drought index result indicated the moderate to severe droughts were observed across the Kabul Province during 2016 and 2018. Moreover, the results showed that there was no vineyard in extreme drought conditions. Therefore, we only considered the severe and moderated condition. According to the BRANNs results R=0.87 and R=0.94 in severe drought conditions for the years of 2016 and 2018 and the R= 0.85 and R=0.91 in moderate drought conditions for the years of 2016 and 2018, respectively. In the Kabul Province within the two years drought periods, there was a significate deficit in the vineyards. According to the findings, 2018 had the highest rate of loss almost -7 ton/ha. However, in 2016 the loss rates were about – 1.2 ton/ha. This research will support stakeholders to identify drought affect vineyards and support farmers during severe drought.

Keywords: grapes, composite drought index, yield loss, satellite remote sensing

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

Procedia PDF Downloads 92

Authors: Bruna P. De Souza, Ricardo C. De Almeida

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In some cities in the State of Parana – Brazil and in other countries atmospheric bromeliads (Tillandsia spp - Bromeliaceae) are considered weeds in trees, electric power lines, satellite dishes and other artificial supports. In this study, a numerical model was developed to simulate the seed dispersal of the Tillandsia recurvata species by wind with the objective of evaluating seeds displacement in the city of Ponta Grossa – PR, Brazil, since it is considered that the region is already infested. The model simulates the dispersal of each individual seed integrating parameters from the atmospheric boundary layer (ABL) and the local wind, simulated by the Weather Research Forecasting (WRF) mesoscale atmospheric model for the 2012 to 2015 period. The dispersal model also incorporates the approximate number of bromeliads and source height data collected from most infested electric power lines. The seeds terminal velocity, which is an important input data but was not available in the literature, was measured by an experiment with fifty-one seeds of Tillandsia recurvata. Wind is the main dispersal agent acting on plumed seeds whereas atmospheric turbulence is a determinant factor to transport the seeds to distances beyond 200 meters as well as to introduce random variability in the seed dispersal process. Such variability was added to the model through the application of an Inverse Fast Fourier Transform to wind velocity components energy spectra based on boundary-layer meteorology theory and estimated from micrometeorological parameters produced by the WRF model. Seasonal and annual wind means were obtained from the surface wind data simulated by WRF for Ponta Grossa. The mean wind direction is assumed to be the most probable direction of bromeliad seed trajectory. Moreover, the atmospheric turbulence effect and dispersal distances were analyzed in order to identify likely regions of infestation around Ponta Grossa urban area. It is important to mention that this model could be applied to any species and local as long as seed’s biological data and meteorological data for the region of interest are available.

Keywords: atmospheric turbulence, bromeliad, numerical model, seed dispersal, terminal velocity, wind

Procedia PDF Downloads 141

Authors: Abdelrahman Elsehsah

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Land Use and Land Cover (LULC) dynamics in Riyadh over a decade were comprehensively analyzed using the Google Earth Engine (GEE) platform. By harnessing the Landsat 8 Image collection and night-time light image collection from May to August for the years 2013 and 2023, we were able to generate insightful datasets capturing the changing landscape of the region. Our approach involved a Random Forest (RF) classification model that consistently displayed commendable precision scores above 92% for both years. A notable discovery from the study was the pronounced urban expansion, particularly around Riyadh city. Within a mere ten-year span, urbanization surged noticeably, affecting the broader ecological environment of the region. Interestingly, the northeastern part of Riyadh emerged as a focal point of this growth, signaling rapid urban growth of urban sprawl and development. A comparison between the two years indicates a 21.51% increase in built-up areas, revealing the transformative pace of urban sprawl. Contrastingly, vegetation cover patterns presented a more nuanced picture. While our initial hypothesis predicted a decline in vegetation, the actual findings depicted both vegetation reduction in certain pockets and new growth in others, resulting in an overall 25.89% increase. This intricate pattern might be attributed to shifting agricultural practices, afforestation efforts, or even satellite image timings not aligning with seasonal vegetation growth. The bare soil, predominant in the desert landscape of Riyadh, saw a marginal reduction of 0.37% over the decade, challenging our initial expectations. Urban and agricultural advancements in Saudi Arabia appear to have slightly reduced the expanse of barren terrains. This study, underpinned by a rigorous methodological framework, reveals the multifaceted land cover changes in Riyadh in response to urban development and environmental factors. The precise, data-driven insights provided by our analysis serve as invaluable tools for understanding urban growth trajectories, guiding urban planning, policy formulation, and sustainable development endeavors in the region.

Keywords: remote sensing, KSA, ArcGIS, spatio-temporal

Procedia PDF Downloads 36

Authors: Raoudane Bouziyan, Kawser Mohammad Tawhid

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Microstrip antennas are low in profile, light in weight, conformable in structure and are now developed for many applications. The main difficulty of the microstrip antenna is its narrow bandwidth. Several modern applications like satellite communications, remote sensing, and multi-function radar systems will find it useful if there is dual-band antenna operating from a single aperture. Some applications require covering both transmitting and receiving frequency bands which are spaced apart. Providing multiple antennas to handle multiple frequencies and polarizations becomes especially difficult if the available space is limited as with airborne platforms and submarine periscopes. Dual band operation can be realized from a single feed using slot loaded or stacked microstrip antenna or two separately fed antennas sharing a common aperture. The former design, when used in arrays, has certain limitations like complicated beam forming or diplexing network and difficulty to realize good radiation patterns at both the bands. The second technique provides more flexibility with separate feed system as beams in each frequency band can be controlled independently. Another desirable feature of a dual band antenna is easy adjustability of upper and lower frequency bands. This thesis presents investigation of a new dual-band antenna, which is a hybrid of microstrip and waveguide radiating elements. The low band radiator is a Shorted Annular Ring (SAR) microstrip antenna and the high band radiator is an aperture antenna. The hybrid antenna is realized by forming a waveguide radiator in the shorted region of the SAR microstrip antenna. It is shown that the upper to lower frequency ratio can be controlled by the proper choice of various dimensions and dielectric material. Operation in both linear and circular polarization is possible in either band. Moreover, both broadside and conical beams can be generated in either band from this antenna element. Finite Element Method based software, HFSS and Method of Moments based software, FEKO were employed to perform parametric studies of the proposed dual-band antenna. The antenna was not tested physically. Therefore, in most cases, both HFSS and FEKO were employed to corroborate the simulation results.

Keywords: FEKO, HFSS, dual band, shorted annular ring patch

Procedia PDF Downloads 402

Authors: Sri E. Wati, D. Roswidyatmoko, N. Maslahatun, Gunawan, Andhika B. Taji

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Natural resource is the main sources to fulfill human needs. Its utilization must consider not only human prosperity but also sustainability. Balance of natural resources is a tool to manage natural wealth and to control land use change. This tool is needed to organize land use planning as stated on spatial plan in a certain region. Balance of natural resources can be calculated by comparing two-series of natural resource data obtained at different year. In this case, four years data period of land and forest were used (2010 and 2014). Land use data were acquired through satellite image interpretation and field checking. By means of GIS analysis, its result was then assessed with land use plan. It is intended to evaluate whether existing land use is suitable with land use plan. If it is improper, what kind of efforts and policies must be done to overcome the situation. Subosukawonosraten is rapid developed areas in Central Java Province. This region consists of seven regencies/cities which are Sukoharjo Regency, Boyolali Regency, Surakarta City, Karanganyar Regency, Wonogiri Regency, Sragen Regency, and Klaten Regency. This region is regarding to several former areas under Karasidenan Surakarta and their location is adjacent to Surakarta. Balance of forest resources show that width of forest area is not significantly changed. Some land uses within the area are slightly changed. Some rice field areas are converted into settlement (0.03%) whereas water bodies become vacant areas (0.09%). On the other hand, balance of land resources state that there are many land use changes in this region. Width area of rice field decreases 428 hectares and more than 50% of them have been transformed into settlement area and 11.21% is converted into buildings such as factories, hotels, and other infrastructures. It occurs mostly in Sragen, Sukoharjo, and Karanganyar Regency. The results illustrate that land use change in this region is mostly influenced by increasing of population number. Some agricultural lands have been converted into built-up area since demand of settlement, industrial area, and other infrastructures also increases. Unfortunately, recent utilization of more than a half of total area is not appropriate with land use plan declared in spatial planning document. It means, local government shall develop a strict regulation and law enforcement related to any violation in land use management.

Keywords: balance, forest, land, spatial plan

Procedia PDF Downloads 319

Authors: Emily Kislik, Gabriel Mantilla Saltos, Gladys Torres, Mercy Borbor-Córdova

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The Galápagos Marine Reserve (GMR) is an internationally-recognized region of consistent upwelling events, high productivity, and rich biodiversity. Despite its high-nutrient, low-chlorophyll condition, the archipelago has experienced phytoplankton blooms, especially in the western section between Isabela and Fernandina Islands. However, little is known about how climate variability will affect future phytoplankton standing stock in the Galápagos, and no consistent protocols currently exist to quantify phytoplankton biomass, identify species, or monitor for potential harmful algal blooms (HABs) within the archipelago. This analysis investigates physical, chemical, and biological oceanic variables that contribute to algal blooms within the GMR, using 4 km Aqua MODIS satellite imagery and 0.125-degree wind stress data from January 2003 to December 2016. Furthermore, this study analyzes chlorophyll-a concentrations at varying spatial scales— within the greater archipelago, as well as within five smaller bioregions based on species biodiversity in the GMR. Seasonal and interannual trend analyses, correlations, and hotspot identification were performed. Results demonstrate that chlorophyll-a is expressed in two seasons throughout the year in the GMR, most frequently in September and March, with a notable hotspot in the Elizabeth Bay bioregion. Interannual chlorophyll-a trend analyses revealed highest peaks in 2003, 2007, 2013, and 2016, and variables that correlate highly with chlorophyll-a include surface temperature and particulate organic carbon. This study recommends future in situ sampling locations for phytoplankton monitoring, including the Elizabeth Bay bioregion. Conclusions from this study contribute to the knowledge of oceanic drivers that catalyze primary productivity and consequently affect species biodiversity within the GMR. Additionally, this research can inform policy and decision-making strategies for species conservation and management within bioregions of the Galápagos.

Keywords: bioregions, ecological monitoring, phytoplankton, remote sensing

Procedia PDF Downloads 265

Authors: Chahrazed Salhi, Ayoub Zeroual, Yasmina Hamitouche

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Soil water erosion poses a significant threat to the watersheds in Algeria today. The degradation of storage capacity in large dams over the past two decades, primarily due to erosion, necessitates a comprehensive understanding of the factors that contribute to soil erosion. The Isser watershed, located in the Northwestern region of Algeria, faces additional challenges such as recurrent droughts and the presence of delicate marl and clay outcrops, which amplify its susceptibility to water erosion. This study aims to employ advanced techniques such as Geographic Information Systems (GIS) and Remote Sensing (RS), in conjunction with the Canonical Correlation Analysis (CCA) method and Soil Water Assessment Tool (SWAT) model, to predict specific erosion patterns and analyze the key factors influencing erosion in the Isser basin. To accomplish this, an array of data sources including rainfall, climatic, hydrometric, land use, soil, digital elevation, and satellite data were utilized. The application of the SWAT model to the Isser basin yielded an average annual soil loss of approximately 16 t/ha/year. Particularly high erosion rates, exceeding 12 T/ha/year, were observed in the central and southern parts of the basin, encompassing 41% of the total basin area. Through Canonical Correlation Analysis, it was determined that vegetation cover and topography exerted the most substantial influence on erosion. Consequently, the study identified significant and spatially heterogeneous erosion throughout the study area. The impact of land topography on soil loss was found to be directly proportional, while vegetation cover exhibited an inverse proportional relationship. Modeling specific erosion for the Ladrat dam sub-basin estimated a rate of around 39 T/ha/year, thus accounting for the recorded capacity loss of 17.80% compared to the bathymetric survey conducted in 2019. The findings of this research provide valuable decision-support tools for soil conservation managers, empowering them to make informed decisions regarding soil conservation measures.

Keywords: Isser watershed, RS, CCA, SWAT, vegetation cover, topography

Procedia PDF Downloads 71

Authors: K. Ismail, A. Ali, R. C. Hasan, I. Khalil, Z. Bachok, N. M. Said, A. M. Muslim, M. S. Che Din, W. S. Chong

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The marine ecosystem in Malaysia holds invaluable potential in terms of economics, food security, pharmaceuticals components and protection from natural hazards. Although exploration of oil and gas industry and fisheries are active within Malaysian waters, knowledge of the seascape and ecological functioning of benthic habitats is still extremely poor in the marine parks around Malaysia due to the lack of detailed seafloor information. Consequently, it is difficult to manage marine resources effectively, protect ecologically important areas and set legislation to safeguard the marine parks. The limited baseline data hinders scientific linkage to support effective marine spatial management in Malaysia. This became the main driver behind the first seabed mapping effort at the national level. Taman Laut Labuan (TLL) is located to the west coast of Sabah and to the east of South China Sea. The total area of TLL is approximately 158.15 km2, comprises of three islands namely Pulau Kuraman, Rusukan Besar and Rusukan Kecil and is characterised by shallow fringing reef with few submerged shallow reef. The unfamiliar rocky shorelines limit the survey of multibeam echosounder to area with depth more than 10 m. Whereas, singlebeam and side scan sonar systems were used to acquire the data for area with depth less than 10 m. By integrating data from multibeam bathymetry and backscatter with singlebeam bathymetry and side sonar images, we produce a substrate map and coral coverage map for the TLL using i) marine landscape mapping technique and ii) RSOBIA ArcGIS toolbar (developed by T. Le Bas). We take the initiative to explore the ability of aerial drone and satellite image (WorldView-3) to derive the depths and substrate type within the intertidal and subtidal zone where it is not accessible via acoustic mapping. Although the coverage was limited, the outcome showed a promising technique to be incorporated towards establishing a guideline to facilitate a standard practice for efficient marine spatial management in Malaysia.

Keywords: habitat mapping, marine spatial management, South China Sea, National seabed mapping

Procedia PDF Downloads 224

Authors: Shreya Srivastava, Sagnik Dey

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Aerosol direct radiative forcing (ADRF) refers to the alteration of the Earth's energy balance from the scattering and absorption of solar radiation by aerosol particles. India experiences substantial ADRF due to high aerosol loading from various sources. These aerosols' radiative impact depends on their physical characteristics (such as size, shape, and composition) and atmospheric distribution. Quantifying ADRF is crucial for understanding aerosols’ impact on the regional climate and the Earth's radiative budget. In this study, we have taken radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 22 years (2000-2021) over the Indian subcontinent. Except for a few locations, the short-wave DARF exhibits aerosol cooling at the TOA (values ranging from +2.5 W/m2 to -22.5W/m2). Cooling due to aerosols is more pronounced in the absence of clouds. Being an aerosol hotspot, higher negative ADRF is observed over the Indo-Gangetic Plain (IGP). Aerosol Forcing Efficiency (AFE) shows a decreasing seasonal trend in winter (DJF) over the entire study region while an increasing trend over IGP and western south India during the post-monsoon season (SON) in clear-sky conditions. Analysing atmospheric heating and AOD trends, we found that only the aerosol loading is not governing the change in atmospheric heating but also the aerosol composition and/or their vertical profile. We used a Multi-angle Imaging Spectro-Radiometer (MISR) Level-2 Version 23 aerosol products to look into aerosol composition. MISR incorporates 74 aerosol mixtures in its retrieval algorithm based on size, shape, and absorbing properties. This aerosol mixture information was used for analysing long-term changes in aerosol composition and dominating aerosol species corresponding to the aerosol forcing value. Further, ADRF derived from this method is compared with around 35 studies across India, where a plane parallel Radiative transfer model was used, and the model inputs were taken from the OPAC (Optical Properties of Aerosols and Clouds) utilizing only limited aerosol parameter measurements. The result shows a large overestimation of TOA warming by the latter (i.e., Model-based method).

Keywords: aerosol radiative forcing (ARF), aerosol composition, MISR, CERES, SBDART

Procedia PDF Downloads 54

Authors: Govind Kumar

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The concept of ‘e-governance’ that was brought about by the new wave of reforms, namely ‘LPG’ in the early 1990s, has been enabling governments across the globe to digitally transform themselves. Digital transformation is leading the governments with qualitative decisions, optimization in rational use of resources, facilitation of cost-benefit analyses, and elimination of redundancy and corruption with the help of ICT-based applications interface. ICT-based applications/technologies have enormous potential for impacting positive change in the social lives of the global citizenry. Supercomputers test and analyze millions of drug molecules for developing candidate vaccines to combat the global pandemic. Further, e-commerce portals help distribute and supply household items and medicines, while videoconferencing tools provide a visual interface between the clients and hosts. Besides, crop yields are being maximized with the help of drones and machine learning, whereas satellite data, artificial intelligence, and cloud computing help governments with the detection of illegal mining, tackling deforestation, and managing freshwater resources. Such e-applications have the potential to take governance an extra mile by achieving 5 Es (effective, efficient, easy, empower, and equity) of e-governance and six Rs (reduce, reuse, recycle, recover, redesign and remanufacture) of sustainable development. If such digital transformation gains traction within the government framework, it will replace the traditional administration with the digitalization of public administration. On the other hand, it has brought in a new set of challenges, like the digital divide, e-illiteracy, technological divide, etc., and problems like handling e-waste, technological obsolescence, cyber terrorism, e-fraud, hacking, phishing, etc. before the governments. Therefore, it would be essential to bring in a rightful mixture of technological and humanistic interventions for addressing the above issues. This is on account of the reason that technology lacks an emotional quotient, and the administration does not work like technology. Both are self-effacing unless a blend of technology and a humane face are brought in into the administration. The paper will empirically analyze the significance of the technological framework of digital transformation within the government set up for the digitalization of public administration on the basis of the synthesis of two case studies undertaken from two diverse fields of administration and present a future framework of the study.

Keywords: digital transformation, electronic governance, public administration, knowledge framework

Procedia PDF Downloads 99

Authors: Carla Palencia-Aguilar

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In order to attain the 2050’s zero emissions goal, it is necessary to know the carbon dioxide changes over time either from pollution to attenuations in the mining industry versus at green zones to establish real goals and redirect efforts to reduce greenhouse effects. Two methods were used to compute the amount of CO2 tons in specific mining zones in Colombia. The former by means of NPP with MODIS MOD17A3HGF from years 2000 to 2021. The latter by using MODIS MYD021KM bands 33 to 36 with maximum values of 644 data points distributed in 7 sites corresponding to surface mineral mining of: coal, nickel, iron and limestone. The green zones selected were located at the proximities of the studied sites, but further than 1 km to avoid information overlapping. Year 2012 was selected for method 2 to compare the results with data provided by the Colombian government to determine range of values. Some data was compared with 2022 MODIS energy values and converted to kton of CO2 by using the Greenhouse Gas Equivalencies Calculator by EPA. The results showed that Nickel mining was the least pollutant with 81 kton of CO2 e.q on average and maximum of 102 kton of CO2 e.q. per year, with green zones attenuating carbon dioxide in 103 kton of CO2 on average and 125 kton maximum per year in the last 22 years. Following Nickel, there was Coal with average kton of CO2 per year of 152 and maximum of 188, values very similar to the subjacent green zones with average and maximum kton of CO2 of 157 and 190 respectively. Iron had similar results with respect to 3 Limestone sites with average values of 287 kton of CO2 for mining and 310 kton for green zones, and maximum values of 310 kton for iron mining and 356 kton for green zones. One of the limestone sites exceeded the other sites with an average value of 441 kton per year and maximum of 490 kton per year, eventhough it had higher attenuation by green zones than a close Limestore site (3.5 Km apart): 371 kton versus 281 kton on average and maximum 416 kton versus 323 kton, such vegetation contribution is not enough, meaning that manufacturing process should be improved for the most pollutant site. By comparing bands 33 to 36 for years 2012 and 2022 from January to August, it can be seen that on average the kton of CO2 were similar for mining sites and green zones; showing an average yearly balance of carbon dioxide emissions and attenuation. However, efforts on improving manufacturing process are needed to overcome the carbon dioxide effects specially during emissions’ peaks because surrounding vegetation cannot fully attenuate it.

Keywords: carbon dioxide, MODIS, surface mining, vegetation

Procedia PDF Downloads 101

Authors: Lyka Selene Magnayi, Marcos Vinas, Roseanne Ramos

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As the real estate industry continually grows in the Philippines, Geographic Information Systems (GIS) provide advantages in generating spatial databases for efficient delivery of information and services. The real estate sector is not only providing qualitative data about real estate properties but also utilizes various spatial aspects of these properties for different applications such as hazard mapping and assessment. In this study, a three-dimensional (3D) model and a spatial database of real estate properties in Fort Bonifacio, Taguig City are developed using GIS and SketchUp. Spatial datasets include political boundaries, buildings, road network, digital terrain model (DTM) derived from Interferometric Synthetic Aperture Radar (IFSAR) image, Google Earth satellite imageries, and hazard maps. Multiple model layers were created based on property listings by a partner real estate company, including existing and future property buildings. Actual building dimensions, building facade, and building floorplans are incorporated in these 3D models for geovisualization. Hazard model layers are determined through spatial overlays, and different scenarios of hazards are also presented in the models. Animated maps and walkthrough videos were created for company presentation and evaluation. Model evaluation is conducted through client surveys requiring scores in terms of the appropriateness, information content, and design of the 3D models. Survey results show very satisfactory ratings, with the highest average evaluation score equivalent to 9.21 out of 10. The output maps and videos obtained passing rates based on the criteria and standards set by the intended users of the partner real estate company. The methodologies presented in this study were found useful and have remarkable advantages in the real estate industry. This work may be extended to automated mapping and creation of online spatial databases for better storage, access of real property listings and interactive platform using web-based GIS.

Keywords: geovisualization, geographic information systems, GIS, real estate, spatial database, three-dimensional model

Procedia PDF Downloads 158

Authors: Zeynep Pirselimoglu Batman, Elvan Ender Altay, Murat Zencirkiran

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Water and water resources are characteristic areas with their special ecosystems Their natural, cultural and economic value and recreation opportunities are high. Recreational activities differ according to the natural, cultural, socio-economic resource values of the areas. In this sense, water and water edge areas, which are important for their resource values, are also important landscape values for recreational activities. From these landscapes values, creeks and the surrounding areas have become a major source of daily life in the past, as well as a major attraction for people's leisure time. However, their qualities and quantities must be sufficient to enable these areas to be used effectively in a recreational sense and to be able to fulfill their recreational functions. The purpose of the study is to identify the recreational use of the water-based activities and identify effective service areas in dense urbanization zones along the creek and green spaces around them. For this purpose, the study was carried out in the vicinity of Nilufer Creek in Bursa. The study area and its immediate surroundings are in the boundaries of Osmangazi and Nilufer districts. The study was carried out in the green spaces along the creek with an individual interaction of 17.930m. These areas are Hudavendigar Urban Park, Atatürk Urban Forest, Bursa Zoo, Soganlı Botanical Park, Mihrapli Park, Nilufer Valley Park. In the first phase of the study, the efficiency zones of these locations were calculated according to international standards. 3200m of this locations are serving the city population and 800m are serving the district and neighborhood population. These calculations are processed on the digitized map by the AUTOCAD program using the satellite image. The efficiency zone of these green spaces in the city were calculated as 71.04 km². In the second phase of the study, water-based current activities were determined by evaluating the recreational potential of these green spaces, which are located along the Nilufer Creek, where efficiency zones have been identified. It has been determined that water-based activities are used intensively in Hudavendigar Urban Park and interacted with Nilufer Creek. Within the scope of effective zones for the study area, appropriate recreational planning proposals have been developed and water-based activities have been suggested.

Keywords: Bursa, efficiency zone, Nilufer Creek, recreation, water-based activities

Procedia PDF Downloads 161

Authors: Jasmal A. Syamsu, Muhammad Yusuf, Hikmah M. Ali, Mawardi A. Asja, Zulkharnaim

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This study was conducted and aimed in identifying and mapping the pasture as an ecological base of beef cattle. A survey was carried out during a period of April to June 2016, in Suppa, Mattirobulu, the district of Pinrang, South Sulawesi province. The mapping process of grazing area was conducted in several stages; inputting and tracking of data points into Google Earth Pro (version 7.1.4.1529), affirmation and confirmation of tracking line visualized by satellite with a variety of records at the point, a certain point and tracking input data into ArcMap Application (ArcGIS version 10.1), data processing DEM/SRTM (S04E119) with respect to the location of the grazing areas, creation of a contour map (a distance of 5 m) and mapping tilt (slope) of land and land cover map-making. Analysis of land cover, particularly the state of the vegetation was done through the identification procedure NDVI (Normalized Differences Vegetation Index). This procedure was performed by making use of the Landsat-8. The results showed that the topography of the grazing areas of hills and some sloping surfaces and flat with elevation vary from 74 to 145 above sea level (asl), while the requirements for growing superior grass and legume is an altitude of up to 143-159 asl. Slope varied between 0 - > 40% and was dominated by a slope of 0-15%, according to the slope/topography pasture maximum of 15%. The range of NDVI values for pasture image analysis results was between 0.1 and 0.27. Characteristics of vegetation cover of pasture land in the category of vegetation density were low, 70% of the land was the land for cattle grazing, while the remaining approximately 30% was a grove and forest included plant water where the place for shelter of the cattle during the heat and drinking water supply. There are seven types of graminae and 5 types of legume that was dominant in the region. Proportionally, graminae class dominated up 75.6% and legume crops up to 22.1% and the remaining 2.3% was another plant trees that grow in the region. The dominant weed species in the region were Cromolaenaodorata and Lantana camara, besides that there were 6 types of floor plant that did not include as forage fodder.

Keywords: pastoral, ecology, mapping, beef cattle

Procedia PDF Downloads 353