Search results for: spatial metrics

Authors: N. David, H. O. Gao

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Air pollution is a serious environmental threat on a global scale and can cause harm to human health, morbidity and premature mortality. Reliable monitoring and control systems are therefore necessary to develop coping skills against the hazards associated with this phenomenon. However, existing environmental monitoring means often do not provide a sufficient response due to practical and technical limitations. Commercial microwave links that form the infrastructure for transmitting data between cell phone towers can be harnessed to map rain at high tempo-spatial resolution. Rainfall causes a decrease in the signal strength received by these wireless communication links allowing it to be used as a built-in sensor network to map the phenomenon. In this study, we point to the potential that lies in this system to indirectly monitor areas where air pollution is reduced. The relationship between pollutant wash-off and rainfall provides an opportunity to acquire important spatial information about air quality using existing cell-phone tower signals. Since the density of microwave communication networks is high relative to any dedicated sensor arrays, it could be possible to rely on this available observation tool for studying precipitation scavenging on air pollutants, for model needs and more.

Keywords: air pollution, commercial microwave links, rainfall, washout

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Raeesa Moolla, Ryan S. Johnson

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Air travel, and the use of airports, has experienced proliferative growth in the past few decades, resulting in the concomitant release of air pollutants. Air pollution needs to be monitored because of the known relationship between exposure to air pollutants and increased adverse effects on human health. This study monitored a group of volatile organic compounds (VOCs); specifically BTEX (viz. benzene, toluene, ethyl-benzene and xylenes), as many are detrimental to human health. Through the use of passive sampling methods, the spatial variability of BTEX within an international airport was investigated, in order to determine ‘hotspots’ where occupational exposure to BTEX may be intensified. The passive sampling campaign revealed BTEX_total concentrations ranged between 12.95–124.04 µg m^-3. Furthermore, BTEX concentrations were dispersed heterogeneously within the airport. Due to the slow wind speeds recorded (1.13 m.s^-1); the hotspots were located close to their main BTEX sources. The main hotspot was located over the main apron of the airport. Employees working in this area may be chronically exposed to these emissions, which could be potentially detrimental to their health.

Keywords: air pollution, air quality, hotspot monitoring, volatile organic compounds

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Authors: M. A. Wanzala, L. A. Ogallo, F. J. Opijah, J. N. Mutemi

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The usefulness and limitations in climate information are due to uncertainty inherent in the climate system. For any given region to have sustainable development it is important to apply climate information into its socio-economic strategic plans. The overall objective of the study was to assess the performance of the Coupled Model Inter-comparison Project (CMIP5) over the Lake Victoria Basin. The datasets used included the observed point station data, gridded rainfall data from Climate Research Unit (CRU) and hindcast data from eight CMIP5. The methodology included trend analysis, spatial analysis, correlation analysis, Principal Component Analysis (PCA) regression analysis, and categorical statistical skill score. Analysis of the trends in the observed rainfall records indicated an increase in rainfall variability both in space and time for all the seasons. The spatial patterns of the individual models output from the models of MPI, MIROC, EC-EARTH and CNRM were closest to the observed rainfall patterns.

Keywords: categorical statistics, coupled model inter-comparison project, principal component analysis, statistical downscaling

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Authors: AnjalI A. Prasad

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Nowadays, social media played an important role in spreading misinformation or fake news. This study analyzes the fake news related to the COVID-19 pandemic spread in social media. This paper aims at evaluating and comparing different approaches that are used to mitigate this issue, including popular deep learning approaches, such as CNN, RNN, LSTM, and BERT algorithm for classification. To evaluate models’ performance, we used accuracy, precision, recall, and F1-score as the evaluation metrics. And finally, compare which algorithm shows better result among the four algorithms.

Keywords: BERT, CNN, LSTM, RNN

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Authors: Seo-Hee Kim, Kee-Won Kim, Seung-Hoon Kim

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The most important elements of a novel are the characters, events and background. The background represents the time, place and situation that character appears, and conveys event and atmosphere more realistically. If readers have the proper knowledge about background of novels, it may be helpful for understanding the atmosphere of a novel and choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels because spatio-temporal background especially performs an important role in historical novels among the genre of Korean novels. To the best of our knowledge, we could not find previous study that was aimed at Korean novels. In this paper, we build a Korean historical national dictionary. Our dictionary has historical places and temple names of kings over many generations as well as currently existing spatial words or temporal words in Korean history. We also present a method for recognizing spatio-temporal background based on patterns of phrasal words in Korean sentences. Our rules utilize postposition for spatial background recognition and temple names for temporal background recognition. The knowledge of the recognized background can help readers to understand the flow of events and atmosphere, and can use to visualize the elements of novels.

Keywords: data mining, Korean historical novels, Korean linguistic feature, spatio-temporal background

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Authors: Liu Danping

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Walking space has very important historical and cultural value in ancient and even modern urban development. As far as the footpath itself is concerned, it reflects the spatial organization mode and traditional architectural construction characteristics of mountain cities. In terms of the spatial nature of streets, traditional streets contain the history of urban development and the most primitive urban life. The slow walking speed allows people to carefully perceive the space and scenery along the way. The real city life in the streets often makes people feel the cultural connotation and unique charm of the city. According to the regional characteristics of pedestrian traffic in the main urban area of Chongqing, the charm of chongqing is discussed. Based on the study of chongqing characteristic walking space elements, this paper summarizes the characteristics of Chongqing urban walking traffic, analyzes the existing problems of mountain city walking traffic, and takes Yuzhong Peninsula as an example to analyze the charm promotion strategy of urban walking traffic.

Keywords: mountain city, walking space, urban charm, urban renewal, regional culture

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Authors: Sankaran Rajendran

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

Keywords: Alkhod Dam, ASTER siltation, Landsat, remote sensing, Oman

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Authors: Catharina Dwi Astuti Depari, Gregorius Agung Setyonugroho

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In concern for human safety, living in disaster-prone areas is twofold: it is profoundly cataclysmic yet perceptibly contributive. This paradox could be identified in Kalitengah Lor Sub-village community who inhabit Mount Merapi’s most hazardous area, putting them to the highest exposure to eruptions’ cataclysmic impacts. After the devastating incident in 2010, through the Action Plan for Rehabilitation and Reconstruction, the National Government with immediate aid from humanitarian agencies initiated a relocation program by establishing nearly 2,613 temporary shelters throughout the mountain’s region. The problem arose as some of the most affected communities including those in Kalitengah Lor Sub-village, persistently refused to relocate. The obnoxious experience of those living in temporary shelters resulted from the program’s failure to support a long-term living was assumed to instigate the rejection. From the psychological standpoint, this phenomenon reflects the emotional bond between the affected communities with their former dwellings. Regarding this, the paper aims to reveal the factors influencing the emotional attachment of Kalitengah Lor community to their former dwellings including the dwellings’ spatial design transformation prior and post the eruption in 2010. The research adopted Likert five scale-questionnaire comprising a wide range of responses from strongly agree to strongly disagree. The responses were then statistically measured, leading to consensus that provides bases for further interpretations toward the local’s characteristics. Using purposive unit sampling technique, 50 respondents from 217 local households were randomly selected. Questions in the questionnaire were developed with concerns on the aspects of place attachment concept: affection, cognitive, behavior, and perception. Combined with quantitative method, the research adopted diachronic method which was aimed to analyze the spatial design transformation of each dwelling in relation to the inhabitant’s daily activities and personal preferences. The research found that access to natural resources like sand mining, agricultural farms and wood forests, social relationship and physical proximity from house to personal asset like cattle shed, are the dominant factors encouraging the locals to emotionally attached to their former dwellings. Consequently, each dwelling’s spatial design is suffered from changes in which the current house is typically larger in dimension and the bathroom is replaced by public toilet located outside the house’s backyard. Relatively unchanged, the cattle shed is still located in front of the house, the continuous visual relationship, particularly between the living and family room, is maintained, as well as the main orientation of the house towards the local street.

Keywords: diachronic method, former dwellings, local’s characteristics, place attachment, spatial design transformation

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Authors: M. K. Benhaoua, A. K. Singh, A. E. H. Benyamina

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In this paper, we propose heuristic for dynamic communications mapping that considers the placement of communications in order to optimize the overall performance. The mapping technique uses a newly proposed Algorithm to place communications between the tasks. The placement we propose of the communications leads to a better optimization of several performance metrics (time and energy consumption). Experimental results show that the proposed mapping approach provides significant performance improvements when compared to those using static routing.

Keywords: Multi-Processor Systems-on-Chip (MPSoCs), Network-on-Chip (NoC), heterogeneous architectures, dynamic mapping heuristics

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Authors: Ajay Kumar

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Using data from census of India, sample registration system and national family health survey (NFHS-3), this paper traces spatial pattern, trends and the factors which have played their role differently in fertility transition in Uttar Pradesh and Tamil Nadu. For the purpose spatial variation analysis, trend line and binary logistic regression analysis has been carried out. There exist considerable regional disparities in terms of fertility decline in northern and southern states. The pace of fertility decline has been faster in southern and coastal regions, and at a slow pace in backward northern state. In Tamil Nadu fertility declined substantially among the women of lower and higher age groups in comparison to Uttar Pradesh characterized by low literacy, low female age at marriage, poor health infrastructure and low status of women. The Study shows that Fertility rates have been higher among the most vulnerable and deprived sections of the society like Illiterate women, women belong to scheduled caste, scheduled tribe and women residing in rural areas.

Keywords: age specific fertility rate, fertility transition, replacement level, total fertility rate

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Authors: Iacopo Testi, Diego Pajarito, Nicoletta Roberto, Carmen Greco

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Today, a consistent segment of the world’s population lives in urban areas, and this proportion will vastly increase in the next decades. Therefore, understanding the key trends in urbanization, likely to unfold over the coming years, is crucial to the implementation of sustainable urban strategies. In parallel, the daily amount of digital data produced will be expanding at an exponential rate during the following years. The analysis of various types of data sets and its derived applications have incredible potential across different crucial sectors such as healthcare, housing, transportation, energy, and education. Nevertheless, in city development, architects and urban planners appear to rely mostly on traditional and analogical techniques of data collection. This paper investigates the prospective of the data science field, appearing to be a formidable resource to assist city managers in identifying strategies to enhance the social, economic, and environmental sustainability of our urban areas. The collection of different new layers of information would definitely enhance planners' capabilities to comprehend more in-depth urban phenomena such as gentrification, land use definition, mobility, or critical infrastructural issues. Specifically, the research results correlate economic, commercial, demographic, and housing data with the purpose of defining the youth economic discomfort index. The statistical composite index provides insights regarding the economic disadvantage of citizens aged between 18 years and 29 years, and results clearly display that central urban zones and more disadvantaged than peripheral ones. The experimental set up selected the city of Rome as the testing ground of the whole investigation. The methodology aims at applying statistical and spatial analysis to construct a composite index supporting informed data-driven decisions for urban planning.

Keywords: data science, spatial analysis, composite index, Rome, urban planning, youth economic discomfort index

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Authors: Pedro Martinez-Santos, Víctor Gómez-Escalonilla, Silvia Díaz-Alcaide, Esperanza Montero, Miguel Martín-Loeches

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Groundwater monitoring networks are critical in evaluating the vulnerability of groundwater resources to depletion and contamination, both in space and time. Groundwater monitoring networks typically grow over decades, often in organic fashion, with relatively little overall planning. The groundwater monitoring networks in the Madrid area, Spain, were reviewed for the purpose of identifying gaps and opportunities for improvement. Spatial analysis reveals the presence of various monitoring networks belonging to different institutions, with several hundred observation wells in an area of approximately 4000 km2. This represents several thousand individual data entries, some going back to the early 1970s. Major issues included overlap between the networks, unknown screen depth/vertical distribution for many observation boreholes, uneven time series, uneven monitored species, and potentially suboptimal locations. Results also reveal there is sufficient information to carry out a spatial and temporal analysis of groundwater vulnerability based on machine learning applications. These can contribute to improve the overall planning of monitoring networks’ expansion into the future.

Keywords: groundwater monitoring, observation networks, machine learning, madrid

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Authors: Devansh Desai, Rahul Nigam

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Crop water stress (W) at a given growth stage starts to set in as moisture availability (M) to roots falls below 75% of maximum. It has been found that ratio of crop evapotranspiration (ET) and reference evapotranspiration (ET0) is an indicator of moisture adequacy and is strongly correlated with ‘M’ and ‘W’. The spatial variability of ET0 is generally less over an agricultural farm of 1-5 ha than ET, which depends on both surface and atmospheric conditions, while the former depends only on atmospheric conditions. Solutions from surface energy balance (SEB) and thermal infrared (TIR) remote sensing are now known to estimate latent heat flux of ET. In the present study, ET and moisture adequacy index (MAI) (=ET/ET0) have been estimated over two contrasting western India agricultural farms having rice-wheat system in semi-arid climate and arid grassland system, limited by moisture availability. High-resolution multi-band TIR sensing observations at 65m from ECOSTRESS (ECOsystemSpaceborne Thermal Radiometer Experiment on Space Station) instrument on-board International Space Station (ISS) were used in an analytical SEB model, STIC (Surface Temperature Initiated Closure) to estimate ET and MAI. The ancillary variables used in the ET modeling and MAI estimation were land surface albedo, NDVI from close-by LANDSAT data at 30m spatial resolution, ET0 product at 4km spatial resolution from INSAT 3D, meteorological forcing variables from short-range weather forecast on air temperature and relative humidity from NWP model. Farm-scale ET estimates at 65m spatial resolution were found to show low RMSE of 16.6% to 17.5% with R2 >0.8 from 18 datasets as compared to reported errors (25 – 30%) from coarser-scale ET at 1 to 8 km spatial resolution when compared to in situ measurements from eddy covariance systems. The MAI was found to show lower (<0.25) and higher (>0.5) magnitudes in the contrasting agricultural farms. The study showed the potential need of high-resolution high-repeat spaceborne multi-band TIR payloads alongwith optical payload in estimating farm-scale ET and MAI for estimating consumptive water use and water stress. A set of future high-resolution multi-band TIR sensors are planned on-board Indo-French TRISHNA, ESA’s LSTM, NASA’s SBG space-borne missions to address sustainable irrigation water management at farm-scale to improve crop water productivity. These will provide precise and fundamental variables of surface energy balance such as LST (Land Surface Temperature), surface emissivity, albedo and NDVI. A synchronization among these missions is needed in terms of observations, algorithms, product definitions, calibration-validation experiments and downstream applications to maximize the potential benefits.

Keywords: thermal remote sensing, land surface temperature, crop water stress, evapotranspiration

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Authors: Nawaf Alotaibi, Andy Evans, Alison Heppenstall, Nick Malleson

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Throughout the last two decades, motor vehicle theft (MVT) has accounted for the largest proportion of property crime incidents in Saudi Arabia (SA). However, to date, few studies have investigated SA’s MVT problem. Those that have are primarily focused on the characteristics of car thieves, and most have overlooked any spatial-temporal distribution of MVT incidents and the characteristics of victims. This paper represents the first step in understanding this problem by reviewing the existing MVT studies contextualised within the theoretical frameworks developed in environmental criminology theories – originating in the West – and exploring to what extent they are relevant to the SA context. To achieve this, the paper has identified a range of key features in SA that are different from typical Western contexts, that could limit the appropriateness and capability of applying existing environmental criminology theories. Furthermore, despite these Western studies reviewed so far having introduced a number of explanatory variables for MVT rates, a range of significant elements are apparently absent in the current literature and this requires further analysis. For example, almost no attempts have been made to quantify the associations between the locations of vehicle theft, recovery of stolen vehicles, joyriding and traffic volume.

Keywords: environmental criminology theories, motor vehicle theft, Saudi Arabia, spatial analysis

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Authors: Masoud Sheidaei, Fahimeh Koohdar

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Date palms are economically important tree plants with high nutrition and medicinal values. More than 400 date palm cultivars are cultivated in many regions of Iran, but no report is available on landscape genetics and species distribution modeling of these trees from the country. Therefore, the present study provides a detailed insight into the genetic diversity and structure of date palm populations in Iran and investigates the effects of geographical and climatic variables on the structuring of genetic diversity in them. We used different computational methods in the study like, spatial principal components analysis (sPCA), redundancy analysis (RDA), latent factor mixed model (LFMM), and Maxent and Dismo models of species distribution modeling. We used a combination of different molecular markers for this study. The results showed that both global and local spatial features play an important role in the genetic structuring of date palms, and the genetic regions associated with local adaptation and climatic variables were identified. The effects of climatic change on the distribution of these taxa and the genetic regions adaptive to these changes will be discussed.

Keywords: adaptive genetic regions, genetic diversity, isolation by distance, populations divergence

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Authors: V. S. Binu, Amitha Puranik, Sintomon Mathew, Sebin Thomas

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Globally, women are more vulnerable to various forms of crimes than males. The crimes that are directed specifically towards women are classified as crime against women. Crime against women in India is observed to increase year after year and according to the National Crime Records Bureau (NCRB) report, in 2014 there was an increase of 9.2% cases of crime against women compared to the previous year. The violence in a population depends on socio-demographic factors, unemployment, poverty, number of police officials etc. There are very few studies that explored to identify hotspots of various types of crime against women in India. Hotspots are geographical regions where the number of observed cases is more than the expected number for that region. It is important to identify the hotspots of crime against women in India in order to control and prevent violence against women in that region. The goal of this study is to identify the hotspots of crime against women in India using spatial data analysis techniques. For the present study, we used the district level data of various types of crime against women in India in the year 2011 published by NCRB and the 2011 Census population in each of these districts. The study used spatial scan statistic to identify the hotspots using SaTScan software.

Keywords: crime, hotspots, India, Satscan, Women

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Authors: Tamal Roy, Anuradha Bhat

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Cognitive abilities aid fishes in foraging, avoiding predators & locating mates. Factors like predation pressure & habitat complexity govern learning & memory in fishes. This study aims to compare spatial learning & memory across four natural populations of zebrafish. Zebrafish, a small cyprinid inhabits a diverse range of freshwater habitats & this makes it amenable to studies investigating role of native environment in spatial cognitive abilities. Four populations were collected across India from waterbodies with contrasting ecological conditions. Habitat complexity of the water-bodies was evaluated as a combination of channel substrate diversity and diversity of vegetation. Experiments were conducted on populations under controlled laboratory conditions. A square shaped spatial testing arena (maze) was constructed for testing the performance of adult zebrafish. The square tank consisted of an inner square shaped layer with the edges connected to the diagonal ends of the tank-walls by connections thereby forming four separate chambers. Each of the four chambers had a main door in the centre. Each chamber had three sections separated by two windows. A removable coloured window-pane (red, yellow, green or blue) identified each main door. A food reward associated with an artificial plant was always placed inside the left-hand section of the red-door chamber. The position of food-reward and plant within the red-door chamber was fixed. A test fish would have to explore the maze by taking turns and locate the food inside the right-side section of the red-door chamber. Fishes were sorted from each population stock and kept individually in separate containers for identification. At a time, a test fish was released into the arena and allowed 20 minutes to explore in order to find the food-reward. In this way, individual fishes were trained through the maze to locate the food reward for eight consecutive days. The position of red door, with the plant and the reward, was shuffled every day. Following training, an intermission of four days was given during which the fishes were not subjected to trials. Post-intermission, the fishes were re-tested on the 13th day following the same protocol for their ability to remember the learnt task. Exploratory tendencies and latency of individuals to explore on 1st day of training, performance time across trials, and number of mistakes made each day were recorded. Additionally, mechanism used by individuals to solve the maze each day was analyzed across populations. Fishes could be expected to use algorithm (sequence of turns) or associative cues in locating the food reward. Individuals of populations did not differ significantly in latencies and tendencies to explore. No relationship was found between exploration and learning across populations. High habitat-complexity populations had higher rates of learning & stronger memory while low habitat-complexity populations had lower rates of learning and much reduced abilities to remember. High habitat-complexity populations used associative cues more than algorithm for learning and remembering while low habitat-complexity populations used both equally. The study, therefore, helped understand the role of natural ecology in explaining variations in spatial learning abilities across populations.

Keywords: algorithm, associative cue, habitat complexity, population, spatial learning

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Authors: Lakshay Kharbanda, Aabhas Chauhan

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In this paper, an application of Normalized Compression Distance (NCD) to detect notable scene alterations occurring in videos is presented. Several research groups have been developing methods to perform image classification using NCD, a computable approximation to Normalized Information Distance (NID) by studying the degree of similarity in images. The timeframes where significant aberrations between the frames of a video have occurred have been identified by obtaining a threshold NCD value, using two compressors: LZMA and BZIP2 and defining scene alterations using Pixel Difference Percentage metrics.

Keywords: image compression, Kolmogorov complexity, normalized compression distance, root mean square error

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Authors: Lee-Ann Foster, Wynand Malherbe, Martin Ferriera, Johan Van Vuren

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Aquatic macroinvertebrates are rarely used in wetland assessments due to their variability. However, in terms of biodiversity, these invertebrates form an important component of wetlands. The objective of this study was to compare the spatial and temporal variation of macroinvertebrate assemblages within endorheic depressions in Mpumalanga and North West Provinces of South Africa. Sampling was conducted over a period of two seasons during 2012 and 2013 at all sampling points to account for a wet and dry season. The identification of macroinvertebrate community samples resulted in 24 taxa for both provinces. Results showed similarities in the structure of communities in perennial endorheic depressions in both provinces with the exception of one or two species. Macroinvertebrates sampled in Mpumalanga depressions (locally called pans) were similar to those reported in previous studies completed in the area and most of the macroinvertebrates sampled in Mpumalanga and the North West are known to be commonly found in temporary habitats. The knowledge acquired can now be utilised to enhance the available literature on these systems. Long-term studies have to be implemented to better understand the ecological functioning of the pans in the North West Province.

Keywords: aquatic, macroinvertebrate assemblages, pans, spatial variation

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Authors: Ishan Kumar Garg

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Urban Fringes have been witnessing unforeseeable, haphazard, and ineffective spatial planning systems for many decades. It invades peripheral villages in the zest of the land as an abundant resource. The process, popularly known as "Urban Sprawl", is commonly seen in many fast-growing cities, especially in developing countries like India. The research for this paper reveals significant neglect in rural development policies, which are not recognized as crucial in current town and country planning regulations. This promotes urban-centric development in the fringe areas that are subjected to real-estate speculation. Therefore, being surrounded by arbitrary urban functions, these villages compromise with necessary strategies to retain the rural cultural identities, traditional ways of living, and villages’ interconnections while remaining deprived of urban amenities such as adequate water supply, education, sanitation, etc. Such socio-spatial separation makes us wonder about their right to development. The possibilities of a sustainable and socially inclusive city expansion are also explored through direct consumer–manufacturer media to bring positive socio-financial transformation. The paper aims to identify a rational playground for both the rural and urban population, which creates possibilities for economic and knowledge transactions beyond their local boundaries. This is achieved by empowering the intact community of villages with economic sufficiency and developing skills to pass on to future generations. In the above context, revolving around unregulated urban sprawl, the northeast region of Bareilly city in the Indian state of Uttar Pradesh is also discussed, i.e., currently under the influence of such development pressures. As we see, exclusive developments like residential, hospitality, industries, etc., over the unplanned landscapes are emerging with the development aligned to only urban means, not the rural. The paper ultimately re-envisions urban-rural associations through appropriate design combinations with economic growth. It integrates broken linkages by revising methodologies and encourages local entrepreneurship that taps the possibility of a gradual social transformation. Concurrently, the addition of required urban amenities leads to rural life strengthening and fulfilling aspirations. Since the proposed thesis carries through an inclusive fringe development, the study caters to cities of similar scales and situations that bolster such coexistence.

Keywords: smart growth framework, empowering rural economy, socio spatial separation, urban fringe development, urban sprawl consequences

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Authors: Bikramjit Goswami, Manoranjan Kalita

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Active microwave remote sensing is useful in remote sensing applications in cloud-covered regions in the world. Because of high spatial resolution, the spatial variations of land cover can be monitored in greater detail using synthetic aperture radar (SAR). Inundation is studied using the SAR images obtained from Sentinel-1A in both VH and VV polarizations in the present experimental study. The temporal variation of the SAR scattering coefficient values for the area gives a good indication of flood and its boundary. The study area is the district of Morigaon in the state of Assam in India. The period of flood monitoring study is the monsoon season of the year 2017, during which high flood occurred in the state of Assam. The variation of microwave scattering value shows a distinctive indication of flood from the non-flooded period. Frequent monitoring of flood in a large area (10 km x 10 km) using passive microwave sensing and pin-pointing the actual flooded portions (5 m x 5 m) within the flooded area using active microwave sensing, can be a highly useful combination, as revealed by the present experimental results.

Keywords: active remote sensing, flood monitoring, microwave remote sensing, synthetic aperture radar

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Authors: Christakis Chatzichristou, Elias Kranos

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Architectural awards, especially if they are given by the state, recognize excellence in the field and, at the same time, strongly contribute to the making of the architectural culture of a place. The present research looks at the houses that have been awarded through such a system in Cyprus in order to discuss the values promoted, directly or not, by such a setup which is quite similar to other prestigious award systems such as the Mies van de Rohe Prize in Europe. In fact, many of the projects signed out through the state award system end up being selected to represent the country for the European awards. The residential architecture encouraged by such systems is quite interesting in that the most public of institutions influence how the most private unit of society is architecturally accommodated. The methodology uses both qualitative as well as quantitative research tools in order to analyze: the official state call for entries to the competition; the final report of the evaluation committee; the spatial characteristics of the houses through the Space Syntax methodology; the statements of the architects regarding their intentions and the final outcome; the feelings of the owners and users of the houses regarding the design process as well as the degree of satisfaction regarding the final product. The above-mentioned analyses allow for a more thorough discussion regarding not only the values promoted explicitly by the system through the brief that describes what the evaluation committee is looking for but also the values that are actually being promoted indirectly through the results of the actual evaluation itself. The findings suggest that: the strong emphasis in brief on bioclimatic design and issues of sustainability weakens significantly, if at all present, in the actual selection process; continuous improvement seems to be fuzzily used as a concept; most of the houses tend to have a similar spatial genotype; most of the houses have similar aesthetic qualities; discrepancies between the proposed lifestyle through the design and the actual use of the spaces do not seem to be acknowledged in the evaluation as an issue; the temporal factor seems to be ignored as the projects are required to be ‘finished projects’ as though the users and their needs do not change through time. The research suggests that, rather than preserving a critical attitude regarding the role of the architect in society, the state award system tends, like any other non-reflective social organism, to simply promote its own unexamined values as well as prejudices. This is perhaps more evident in the shared aesthetic character of the awarded houses and less so in the hidden spatial genotype to which they belong. If the design of houses is indeed a great opportunity for architecture to contribute in a more deliberate manner to the evolution of society, then what the present study shows is that this opportunity seems to be largely missed. The findings may serve better less as a verdict and more as a chance for introspection and discussion.

Keywords: award systems, houses, spatial genotype, aesthetic qualities

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Authors: Bencherif Kada

Abstract:

In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, diversity, shrublands

Procedia PDF Downloads 101

Authors: Saad M. Algharib

Abstract:

The major concern of planners when placing fire stations is finding their optimal locations such that the fire companies can reach fire locations within reasonable response time or distance. Planners are also concerned with the numbers of fire stations that are needed to cover all service areas and the fires, as demands, with standard response time or distance. One of the tools for such analysis is location-allocation models. Location-allocation models enable planners to determine the optimal locations of facilities in an area in order to serve regional demands in the most efficient way. The purpose of this study is to examine the geographic distribution of the existing fire stations in Kuwait City. This study utilized location-allocation models within the Geographic Information System (GIS) environment and a number of statistical functions to assess the current locations of fire stations in Kuwait City. Further, this study investigated how well all service areas are covered and how many and where additional fire stations are needed. Four different location-allocation models were compared to find which models cover more demands than the others, given the same number of fire stations. This study tests many ways to combine variables instead of using one variable at a time when applying these models in order to create a new measurement that influences the optimal locations for locating fire stations. This study also tests how location-allocation models are sensitive to different levels of spatial dependency. The results indicate that there are some districts in Kuwait City that are not covered by the existing fire stations. These uncovered districts are clustered together. This study also identifies where to locate the new fire stations. This study provides users of these models a new variable that can assist them to select the best locations for fire stations. The results include information about how the location-allocation models behave in response to different levels of spatial dependency of demands. The results show that these models perform better with clustered demands. From the additional analysis carried out in this study, it can be concluded that these models applied differently at different spatial patterns.

Keywords: geographic information science, GIS, location-allocation models, geography

Procedia PDF Downloads 158

Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu

Abstract:

In order to effectively detect aerial targets over long distances, an optimal matching design method of space-based optical payload is proposed. Firstly, main factors affecting optical detectability of small targets under complex environment are analyzed based on the full link of a detection system, including band center, band width and spatial resolution. Then a performance characterization model representing the relationship between image signal-to-noise ratio (SCR) and the above influencing factors is established to describe a detection system. Finally, an optimal matching design example is demonstrated for a typical aerial target by simulating and analyzing its SCR under different scene clutter coupling with multi-scale characteristics, and the optimized detection band and spatial resolution are presented. The method can provide theoretical basis and scientific guidance for space-based detection system design, payload specification demonstration and information processing algorithm optimization.

Keywords: space-based detection, aerial targets, optical system design, detectability characterization

Procedia PDF Downloads 154

Authors: Ma. Rosario Concepcion O. Ang, Luis Caezar Ian K. Panganiban, Charmyne B. Mamador, Oliver Dan G. De Luna, Michael D. Bausas, Joselito P. Cruz

Abstract:

PhilSHORE is a multi-site, multi-device and multi-criteria decision support tool designed to support the development of tidal current energy in the Philippines. Its platform is based on Geographic Information Systems (GIS) which allows for the collection, storage, processing, analyses and display of geospatial data. Combining GIS tools with open source web development applications, PhilSHORE becomes a webGIS-based marine spatial planning tool. To date, PhilSHORE displays output maps and graphs of power and energy density, site suitability and site-device analysis. It enables stakeholders and the public easy access to the results of tidal current energy resource assessments and site suitability analyses. Results of the initial development shows PhilSHORE is a promising decision support tool for ORE project developments.

Keywords: gis, site suitability analysis, tidal current energy resource assessment, webgis

Procedia PDF Downloads 508

Authors: Bencherif Kada

Abstract:

In forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects, and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction and area of an object, etc.) and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants and bare soils. Texture attributes seem to provide no useful information while spatial attributes of shape, compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, biodiversity, shrublands

Procedia PDF Downloads 11

Authors: Ebru Cubukcu, Gozde Eksioglu Cetintahra, Burcin Hepguzel Hatip, Mert Cubukcu

Abstract:

Obesity and overweight cause serious health problems. Public and private organizations aim to encourage walking in various ways in order to cope with the problem of obesity and overweight. This study aims to understand how the spatial characteristics of urban street pattern, connectivity and complexity influence young people’s choice to walk or not. 185 public university students in Izmir, the third largest city in Turkey, participated in the study. Each participant had worn an accelerometer and a global positioning (GPS) device for a week. The accelerometer device records data on the intensity of the participant’s activity at a specified time interval, and the GPS device on the activities’ locations. Combining the two datasets, activity maps are derived. These maps are then used to differentiate the participants’ walk trips and motor vehicle trips. Given that, the frequency of walk and motor vehicle trips are calculated at the street segment level, and the street segments are then categorized into two as ‘preferred by pedestrians’ and ‘preferred by motor vehicles’. Graph Theory-based accessibility indices are calculated to quantify the spatial characteristics of the streets in the sample. Six different indices are used: (I) edge density, (II) edge sinuosity, (III) eta index, (IV) node density, (V) order of a node, and (VI) beta index. T-tests show that the index values for the ‘preferred by pedestrians’ and ‘preferred by motor vehicles’ are significantly different. The findings indicate that the spatial characteristics of the street network have a measurable effect on young people’s choice to walk or not. Policy implications are discussed. This study is funded by the Scientific and Technological Research Council of Turkey, Project No: 116K358.

Keywords: graph theory, walkability, accessibility, street network

Procedia PDF Downloads 206

Authors: Lauren C. Porter, Andrew Curtis, Eric Jefferis, Susanne Mitchell

Abstract:

A wealth of research has been generated examining the variation in crime across neighborhoods. However, there is also a striking degree of crime concentration within neighborhoods. A number of studies show that a small percentage of street segments, intersections, or addresses account for a large portion of crime. Not surprisingly, a focus on these crime hot spots can be an effective strategy for reducing community level crime and related ills, such as health problems. However, research is also limited in an important respect. Studies tend to use official data to identify hot spots, such as 911 calls or calls for service. While the use of call data may be more representative of the actual level and distribution of crime than some other official measures (e.g. arrest data), call data still suffer from the 'dark figure of crime.' That is, there is most certainly a degree of error between crimes that occur versus crimes that are reported to the police. In this study, we present an alternative method of identifying crime hot spots, that does not rely on official data. In doing so, we highlight the potential utility of neighborhood-insiders to identify and understand crime dynamics within geographic spaces. Specifically, we use spatial video and geo-narratives to record the crime insights of 36 police, ex-offenders, and residents of a high crime neighborhood in northeast Ohio. Spatial mentions of crime are mapped to identify participant-identified hot spots, and these are juxtaposed with calls for service (CFS) data. While there are bound to be differences between these two sources of data, we find that one location, in particular, a corner store, emerges as a hot spot for all three groups of participants. Yet it does not emerge when we examine CFS data. A closer examination of the space around this corner store and a qualitative analysis of narrative data reveal important clues as to why this store may indeed be a hot spot, but not generate disproportionate calls to the police. In short, our results suggest that researchers who rely solely on official data to study crime hot spots may risk missing some of the most dangerous places.

Keywords: crime, narrative, video, neighborhood

Procedia PDF Downloads 221