Search results for: land use classification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4105

Search results for: land use classification

3805 A Simulation of Land Market through Agent-Based Modeling

Authors: Zilin Zhang

Abstract:

Agent-based simulation has become a popular method of exploring the behavior of all kinds of urban systems. The city clearly is viewed as such a system. Many urban evolution processes, such as the development or the transaction of a piece of land, can be modeled with a set of rules. Such modeling approaches can be used to gain insight into urban-development and land market transactions in the real world. Our work contributes to such type of research by modeling the transactions of lands in a city and its surrounding suburbs. By replicating the demand and supply needs in the land market, we are able to demonstrate the different transaction patterns in three types of residential areas - downtown, city-suburban, and further suburban areas. In addition, we are also able to compare the vital roles of different activation conditions play in generating the various transaction patterns of the land market at the macro level. We use this simulation to loosely test our hypotheses about the nature of activation regimes by the replication of the Zi traders’ model. In the end, we hope our analytical results can be useful for city planners and policymakers to develop rational city plans and policies for shaping sustainable urban development.

Keywords: simulation, agent-based modeling, housing market, city

Procedia PDF Downloads 62
3804 Access and Outcome of Khas Land in Bangladesh: An Insight into Its Distribution Process and Influence on Landless Farmers

Authors: M. Foysul Alam

Abstract:

Land diluvion is a common phenomenon in Bangladesh. According to Bangladesh land administration manual, land gained by diluvion and alluvion are considered as Khas (state) lands. Distributing khas lands to the poorest landless people was suggested as a way of improving the livelihood by mobilizing their economic activity and improving their social status in Bangladesh. The impact of this initiative, which started in 1980 as a state policy, is perhaps one of the least experimentally documented ones in the country. The primary aim of this study was to investigate the economic and social status of some landless farmers focusing on determining whether the distribution of khas lands provide part of the explanation for possible improvement of their livelihood during this period of almost four decades. If not, the secondary objective of this study was to identify the issues and challenges of this policy, whether in strategic planning or implementation efforts. Both subjectively observable and objectively measurable data were collected from 150 households from 30 villages of 6 districts worse suffering from landlessness. A well-organized questionnaire, including 10 open ended question, were used to collect specific data and experiences of the landless farmers. Special attention was given to those who left peasantry becoming involved in other economic activities. The study found that Khas lands have very nominal or even zero influence on landless farmers due to 1. Lack of Khas land inventory 2. Lack of availability of information to the farmers 3. Complexity in application procedure for demanding Khas land and 4. Political nexus of local influential farmers makes it nearly impossible for those farmers who actually deserve it. It also found that most of the lucky farmers who eventually got a piece of Khas land had links with the local elites of their community. The research concludes that it is too early to decide how good the Khas land is for the marginalized landless farmers in Bangladesh, with actually a few numbers of them given the possession of one. This document provides crucial recommendations for overcoming the prevailing challenges.

Keywords: Khas land, land distribution, marginalized farmers, rural livelihood

Procedia PDF Downloads 99
3803 International Tourists’ Travel Motivation by Push-Pull Factors and Decision Making for Selecting Thailand as Destination Choice

Authors: Siripen Yiamjanya, Kevin Wongleedee

Abstract:

This research paper aims to identify travel motivation by push and pull factors that affected decision making of international tourists in selecting Thailand as their destination choice. A total of 200 international tourists who traveled to Thailand during January and February, 2014 were used as the sample in this study. A questionnaire was employed as a tool in collecting the data, conducted in Bangkok. The list consisted of 30 attributes representing both psychological factors as “push- based factors” and destination factors as “pull-based factors”. Mean and standard deviation were used in order to find the top ten travel motives that were important determinants in the respondents’ decision making process to select Thailand as their destination choice. The finding revealed the top ten travel motivations influencing international tourists to select Thailand as their destination choice included [i] getting experience in foreign land; [ii] Thai food; [iii] learning new culture; [iv] relaxing in foreign land; [v] wanting to learn new things; [vi] being interested in Thai culture, and traditional markets; [vii] escaping from same daily life; [viii] enjoying activities; [ix] adventure; and [x] good weather. Classification of push- based and pull- based motives suggested that getting experience in foreign land was the most important push motive for international tourists to travel, while Thai food portrayed its highest significance as pull motive. Discussion and suggestions were also made for tourism industry of Thailand.

Keywords: decision making, destination choice, international tourist, pull factor, push factor, Thailand, travel motivation

Procedia PDF Downloads 370
3802 Automatic Classification Using Dynamic Fuzzy C Means Algorithm and Mathematical Morphology: Application in 3D MRI Image

Authors: Abdelkhalek Bakkari

Abstract:

Image segmentation is a critical step in image processing and pattern recognition. In this paper, we proposed a new robust automatic image classification based on a dynamic fuzzy c-means algorithm and mathematical morphology. The proposed segmentation algorithm (DFCM_MM) has been applied to MR perfusion images. The obtained results show the validity and robustness of the proposed approach.

Keywords: segmentation, classification, dynamic, fuzzy c-means, MR image

Procedia PDF Downloads 448
3801 Classification of Construction Projects

Authors: M. Safa, A. Sabet, S. MacGillivray, M. Davidson, K. Kaczmarczyk, C. T. Haas, G. E. Gibson, D. Rayside

Abstract:

To address construction project requirements and specifications, scholars and practitioners need to establish a taxonomy according to a scheme that best fits their need. While existing characterization methods are continuously being improved, new ones are devised to cover project properties which have not been previously addressed. One such method, the Project Definition Rating Index (PDRI), has received limited consideration strictly as a classification scheme. Developed by the Construction Industry Institute (CII) in 1996, the PDRI has been refined over the last two decades as a method for evaluating a project's scope definition completeness during front-end planning (FEP). The main contribution of this study is a review of practical project classification methods, and a discussion of how PDRI can be used to classify projects based on their readiness in the FEP phase. The proposed model has been applied to 59 construction projects in Ontario, and the results are discussed.

Keywords: project classification, project definition rating index (PDRI), risk, project goals alignment

Procedia PDF Downloads 654
3800 Minimizing Vehicular Traffic via Integrated Land Use Development: A Heuristic Optimization Approach

Authors: Babu Veeregowda, Rongfang Liu

Abstract:

The current traffic impact assessment methodology and environmental quality review process for approval of land development project are conventional, stagnant, and one-dimensional. The environmental review policy and procedure lacks in providing the direction to regulate or seek alternative land uses and sizes that exploits the existing or surrounding elements of built environment (‘4 D’s’ of development – Density, Diversity, Design, and Distance to Transit) or smart growth principles which influence the travel behavior and have a significant effect in reducing vehicular traffic. Additionally, environmental review policy does not give directions on how to incorporate urban planning into the development in ways such as incorporating non-motorized roadway elements such as sidewalks, bus shelters, and access to community facilities. This research developed a methodology to optimize the mix of land uses and sizes using the heuristic optimization process to minimize the auto dependency development and to meet the interests of key stakeholders. A case study of Willets Point Mixed Use Development in Queens, New York, was used to assess the benefits of the methodology. The approved Willets Point Mixed Use project was based on maximum envelop of size and land use type allowed by current conventional urban renewal plans. This paper will also evaluate the parking accumulation for various land uses to explore the potential for shared parking to further optimize the mix of land uses and sizes. This research is very timely and useful to many stakeholders interested in understanding the benefits of integrated land uses and its development.

Keywords: traffic impact, mixed use, optimization, trip generation

Procedia PDF Downloads 189
3799 New Approach to Construct Phylogenetic Tree

Authors: Ouafae Baida, Najma Hamzaoui, Maha Akbib, Abdelfettah Sedqui, Abdelouahid Lyhyaoui

Abstract:

Numerous scientific works present various methods to analyze the data for several domains, specially the comparison of classifications. In our recent work, we presented a new approach to help the user choose the best classification method from the results obtained by every method, by basing itself on the distances between the trees of classification. The result of our approach was in the form of a dendrogram contains methods as a succession of connections. This approach is much needed in phylogeny analysis. This discipline is intended to analyze the sequences of biological macro molecules for information on the evolutionary history of living beings, including their relationship. The product of phylogeny analysis is a phylogenetic tree. In this paper, we recommend the use of a new method of construction the phylogenetic tree based on comparison of different classifications obtained by different molecular genes.

Keywords: hierarchical classification, classification methods, structure of tree, genes, phylogenetic analysis

Procedia PDF Downloads 478
3798 Rapid Soil Classification Using Computer Vision with Electrical Resistivity and Soil Strength

Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, P. L. Goh, Grace H. B. Foo, M. L. Leong

Abstract:

This paper presents the evaluation of various soil testing methods such as the four-probe soil electrical resistivity method and cone penetration test (CPT) that can complement a newly developed novel rapid soil classification scheme using computer vision, to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from the local construction industry are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labor-intensive. Thus, a rapid classification method is needed at the SGs. Four-probe soil electrical resistivity and CPT were evaluated for their feasibility as suitable additions to the computer vision system to further develop this innovative non-destructive and instantaneous classification method. The computer vision technique comprises soil image acquisition using an industrial-grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the following three items were targeted to be added onto the computer vision scheme: the apparent electrical resistivity of soil (ρ) measured using a set of four probes arranged in Wenner’s array, the soil strength measured using a modified mini cone penetrometer, and w measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay,” and a mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay” and are feasible as complementing methods to the computer vision system.

Keywords: computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

Procedia PDF Downloads 214
3797 The Ecological Footprint of Tourism in Jalapão/TO/Brazil

Authors: Mary L. G. S. Senna, Afonso R. Aquino

Abstract:

The development of tourism causes negative impacts on the environment. It is in this context, through the Ecological Footprint (EF) method that this study aimed to characterize the impacts of ecotourism on the community of Mateiros, Jalapão, Brazil. The EF, which consisted in its original a method to construct a land use matrix, considering some major categories of human consumption such as food, housing, transportation, consumer goods and services, and six other categories from the main land use which are divided into the topics: land use, degraded environment, gardens, fertile land, pasture and forests protected by the government. The main objective of this index is to calculate the land area required for the production and maintenance of goods and services consumed by a community. The field research was conducted throughout the year of 2014 until July 2015. After the calculations of each category, these components were added according to the presented method in order to determine the annual EF of the tourism sector in Mateiros. The results show that the EF resulting from tourism in Mateiros is 2,194.22 hectares of land required for tourism activities in the region. The EF of tourism was considered high, nevertheless, if it is added the total of hectares needed annually for tourism activities, the result found would be 2,194.22 hectares needed to absorb the CO2 emissions generated in the region directly from the tourism sector.

Keywords: sustainable tourism, tourism ecological footprint, Jalapão/TO/Brazil

Procedia PDF Downloads 303
3796 Brainwave Classification for Brain Balancing Index (BBI) via 3D EEG Model Using k-NN Technique

Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

Abstract:

In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

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3795 Bioremediation of PAHs-Contaminated Soil Using Land Treatment Processes

Authors: Somaye Eskandary

Abstract:

Polycyclic aromatic hydrocarbons (PAHs) are present in crude oil and its derivatives contaminate soil and also increase carcinogen and mutagen contamination, which is a concern for researchers. Land farming is one of the methods that remove pollutants from the soil by native microorganisms. It seems that this technology is cost-effective, environmentally friendly and causes less debris problem to be disposed. This study aimed to refine the polycyclic aromatic hydrocarbons from oil-contaminated soil using the land farming method. In addition to examine the concentration of polycyclic aromatic hydrocarbons by GC-FID, some characteristics such as soil microbial respiration and dehydrogenase, peroxidase, urease, acid and alkaline phosphatase enzyme concentration were also measured. The results showed that after land farming process the concentrations of some polycyclic aromatic hydrocarbons dropped to 50 percent. The results showed that the enzyme concentration is reduced by reducing the concentration of hydrocarbons and microbial respiration. These results emphasize the process of land farming for removal of polycyclic aromatic hydrocarbons from soil by indigenous microorganisms.

Keywords: soil contamination, gas chromatography, native microorganisms, soil enzymes, microbial respiration, carcinogen

Procedia PDF Downloads 359
3794 Women Right to Land Entitlement for Gender Equality: Critical Review

Authors: A. Yousuf, M. Iqbal, A. Mir, S. Aziz

Abstract:

This study deals with the women’s right to land for gender equality. Economic Transformation Initiative, Gilgit-Baltistan (ETI-GB), an ambitious program supported by International Fund for Agricultural Development United Nation (IFAD, UN), aims to strengthen land reforms process in disputed area of Gilgit-Baltistan (GB) Pakistan, that is taking place first time in the history. This project is a brick to build the foundation of land reforms and land policies in GB. The ETI-GB provides substantive support to government of GB in developing policy measures and initiatives to promote women’s right to have and to own land is kind of unconventional step in a very traditional society. It would be interesting to have discussion and document the people’s response regarding this project. The study has used mixed method for data collection. For qualitative data, content analysis is used to have a thorough understanding of different types of land reforms across the globe particularly in South Asia. Theoretical understanding of the literature is essential which provides the basis why land reforms are important and how far it plays an important role when it comes to eliminating inequality. Focused group discussion was carried out for verification and triangulation of data. For quantitative, survey was conducted to take responses from the people of the region and analyzed. The program is implemented in Ghizer district of GB. 2340 households were identified as beneficiaries of newly developed land. Among them, 2285 were men households, and 55 were women households. There is a significant difference between men and women households. In spite of great difference, it is a great achievement of the donor that in history of GB, first time women are going to be entitled to land ownership. GB is a patriarchal society, many social factors like cultural, religious play role for gender inequality. In developing countries, such as Pakistan, the awareness of land property rights has not been given proper attention to gender equality development frameworks. It is argued that land property rights of women have not been taken into mainstream policymaking in the development of nation building process. Consequently, this has generated deprivation of women’s property rights, low income level, lack of education and poor health. This paper emphasises that there should have proper land property right of women in Gilgit-Baltistan Pakistan, provided that the gender empowerment could be increased in terms of women’s property rights.

Keywords: gender equality, women right to land ownership, property rights, women empowerment

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3793 Impact of Private Oil Palm Expansion on Indonesia Tropical Forest Deforestation Rate: Case Study in the Province of Riau

Authors: Arzyana Sunkar, Yanto Santosa, Intan Purnamasari, Yohanna Dalimunthe

Abstract:

A variety of negative allegations have criticized the Indonesian oil palm plantations as being environmentally unfriendly. One of the important allegations thus must be verified is that expansion of Indonesian oil palm plantation has increased the deforestation rate of primary tropical forest. In relation to this, a research was conducted to study the origin or history of the status and land use of 8 private oil palm plantations (with a total of 46,372.38 ha) located in Riau Province. Several methods were employed: (1) conducting analysis of overlay maps between oil palm plantation studied with the 1986 Forest Map Governance Agreement (TGHK) and the 1994 and 2014 Riau Provincial Spatial Plans(RTRWP); (2) studying the Cultivation Right on Land (HGU) documents including the Forestry Ministerial Decree on the release of forest area and (3) interpretation of lands at imagery of bands 542, covering 3 years before and after the oil palm industries operated. In addition, field cross-checked, and interviews were conducted with National Land Agency, Plantation and Forestry Office and community figures. The results indicated that as much as 1.95% of the oil palm plantations under study were converted from production forest, 30.34% from limited production forest and 67.70% from area for other usage /conversion production forest. One year prior to the establishment of the plantations, the land cover types comprised of rubber plantations (49.96%), secondary forest (35.99%), bare land (10.17%), shrubs (3.03%) and mixed dryland farming-shrubs (0.84%), whereas the land use types comprised of 35.99% forest concession areas, 14.04% migrants dryland farms, and 49.96% Cultivation Right on Land of other companies. These results indicated that most of the private oil palm plantations under study, resulted from the conversion of production forests and the previous land use were not primary forest but rubber plantations and secondary forests.

Keywords: land cover types, land use history, primary forest, private oil palm plantations

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3792 The Relationship between Land Use Factors and Feeling of Happiness at the Neighbourhood Level

Authors: M. Moeinaddini, Z. Asadi-Shekari, Z. Sultan, M. Zaly Shah

Abstract:

Happiness can be related to everything that can provide a feeling of satisfaction or pleasure. This study tries to consider the relationship between land use factors and feeling of happiness at the neighbourhood level. Land use variables (beautiful and attractive neighbourhood design, availability and quality of shopping centres, sufficient recreational spaces and facilities, and sufficient daily service centres) are used as independent variables and the happiness score is used as the dependent variable in this study. In addition to the land use variables, socio-economic factors (gender, race, marital status, employment status, education, and income) are also considered as independent variables. This study uses the Oxford happiness questionnaire to estimate happiness score of more than 300 people living in six neighbourhoods. The neighbourhoods are selected randomly from Skudai neighbourhoods in Johor, Malaysia. The land use data were obtained by adding related questions to the Oxford happiness questionnaire. The strength of the relationship in this study is found using generalised linear modelling (GLM). The findings of this research indicate that increase in happiness feeling is correlated with an increasing income, more beautiful and attractive neighbourhood design, sufficient shopping centres, recreational spaces, and daily service centres. The results show that all land use factors in this study have significant relationship with happiness but only income, among socio-economic factors, can affect happiness significantly. Therefore, land use factors can affect happiness in Skudai more than socio-economic factors.

Keywords: neighbourhood land use, neighbourhood design, happiness, socio-economic factors, generalised linear modelling

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3791 Investigating the Effect of Urban Expansion on the Urban Heat Island and Land Use Land Cover Changes: The Case Study of Lahore, Pakistan

Authors: Shah Fahad

Abstract:

Managing the Urban Heat Island (UHI) effects is a pressing concern for achieving sustainable urban development and ensuring thermal comfort in major cities of developing nations, such as Lahore, Pakistan. The current UHI effect is mostly triggered by climate change and rapid urbanization. This study explored UHI over the Lahore district and its adjoining urban and rural-urban fringe areas. Landsat satellite data was utilized to investigate spatiotemporal patterns of Land Use and Land Cover changes (LULC), Land Surface Temperature (LST), UHI, Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and Urban Thermal Field Variance Index (UTFVI). The built-up area increased very fast, with a coverage of 22.99% in 2000, 36.06% in 2010, and 47.17% in 2020, while vegetation covered 53.21 % in 2000 and 46.16 % in 2020. It also revealed a significant increase in the mean LST, from 33°C in 2000 to 34.8°C in 2020. The results indicated a significantly positive correlation between LST and NDBI, a weak correlation was also observed between LST and NDVI. The study used scatterplots to show the correlation between NDBI and NDVI with LST, results revealed that the NDBI and LST had an R² value of 0.6831 in 2000 and 0.06541 in 2022, while NDVI and LST had an R² value of 0.0235 in 1998 and 0.0295 in 2022. Proper environmental planning is vital in specific locations to enhance quality of life, protect the ecosystem, and mitigate climate change impacts.

Keywords: land use land cover, spatio-temporal analysis, remote sensing, land surface temperature, urban heat island, lahore pakistan

Procedia PDF Downloads 50
3790 Land Equivalent Ration of Chickpea - Barley as Affected by Mixed Cropping System and Vermicompost in Water Stress Condition

Authors: Masoud Rafiee

Abstract:

Study of the effect of vermin compost on yield, and Land equivalent ration (LER) of chickpea-barley mixed cropping under normal dry land condition can be useful in order to increase qualitative and quantitative performance. In this case, two factors include fertilizer (vermicompost biological fertilizer, ammonium phosphate chemical fertilizer, vermicompost + %75 chemical fertilizer) and chickpea + barley mixed cropping (sole chickpea, %75 chickpea: %25 barley, %50 chickpea: %50 barley, %25 chickpea: %75 barley, and sole barley) in RCBD in three replications in two experiments include normal and dry land conditions were studied. Result showed that total LER base on dry matter was affected by environment and mixed cropping interaction and was more than 1 in all mixed cropping treatments. In different mixed cropping rates, wet forage yield decreased by decreasing chickpea ratio as well as increasing barley ratio. Total LER mean in base on forage dry matter in mixed-, chemical-, and vermicompost fertilizer treatments were 1.12, 1.05 and 1.10 in normal condition and 1.15, 1.08 and 1.14 in dry land condition, respectively, represented the important of biological fertilizer in mixed cropping systems.

Keywords: land equivalent ration, biological fertilizer, mixed cropping systems, water stress

Procedia PDF Downloads 279
3789 Identifying the Phases of Indian Agriculture Towards Desertification: An Introspect of Karnataka State, India

Authors: Arun Das

Abstract:

Indian agriculture is acclaimed from the dates of Indus civilization (2500 BC). Since this time until the day, there were tremendous expansion in terms of space and technology has taken place. Abrupt growth in technology took place past one and half century. Consequent to this development, the land which was brought under agriculture in the initial stages of introducing agriculture for the first time, that land is not possessing the same physical condition. Either it has lost the productive capacity or modified into semi agriculture land. On the grounds of its capacity and interwoven characteristics seven phases of agriculture scenario has been identified. Most of the land is on the march of desertification. Identifying the stages and the phase of the agriculture scenario is most relevant from the point of view of food security at regional, national and at global level. Secondly decisive measure can put back the degenerating environmental condition into arrest. GIS and Remote sensing applications have been used to identify the phases of agriculture.

Keywords: agriculture phases, desertification, deforestation, foods security, transmigration

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3788 Optimization of Waqf Land through Sukuk Al-Intifa’ to Build MSMEs in Indonesia

Authors: Khadijah Hasim, Achmad Fauzan Firdaus, Choirunnisa

Abstract:

Waqf land which previously was idle assets can be built on top of a building that is a means for people to conduct business. Nadzir (waqf managers) lease of waqf lands it manages, the agreed rental fee, which is payable in the form of the building, not in cash. After standing building, the developer will lease to interested companies. Given the magnitude of the beginning funds needed, The company later issuing sukuk al-intifa on the trading floor. With this sukuk issuance, the company has sufficient capital to begin operations and pay obligations of the rental fee to the developer each year. Building that had stood trade area will be established (Micro, Small, Middle Entreprises) MSMEs. It is expected that through the sukuk al-intifa, can help to make waqf land previously unproductive due to lack of capital to be very beneficial and help awaken the people of Indonesian MSMEs

Keywords: Sukuk Al-Intifa, MSMEs, waqf land, underlying asset

Procedia PDF Downloads 448
3787 The Inter-Play Between Traditional Religion and Christianity in Eggon Landn Eggon Land

Authors: Akolo Ajige

Abstract:

Before the advent of Christianity in Eggon land, the Eggon people were adherents of Traditional Religion. The religion is traditional because it was the religion that they grew up in it. A religion that was practiced by their fore fathers, and it was handed over to them. Traditional Religion created in the Eggon people the spirit of communalism, brotherhood and the value for humanity. The advent of Christianity in the 19th Century in Eggon land, some of the adherents of Traditional Religion changed their religion affiliation to Christianity and let gone, of the Traditional Religion. There was a need for the adherents of these two religions (i.e. Christianity and ATR) to leave in peace with one another. Even though there means of worship varies; it was obvious that Christianity and Africa Traditional Religion leaved in harmony with one another. The obvious spread of Christianity in Eggon land can attest to the fact that Traditional Religion welcomed Christianity and gave it room to operate without any issue. The inter-play of Christianity and Traditional Religion of Eggon people is seen during the Ashimu festival where Christians come to watch, why during Christmas celebration, the Traditional Religious adherents also visit the Christians to celebrate with them. It is obvious that there an Inter-Play between Christianity and Traditional Religion in Eggon land. The peace enjoy by the people attest to the fact of religious harmony. A historical research method was adopted for this research work.

Keywords: inter-play, traditional religion, christianity, eggon

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3786 A Framework for Vacant City-Owned Land to Be Utilised for Urban Agriculture: The Case of Cape Town, South Africa

Authors: P. S. Van Staden, M. M. Campbell

Abstract:

Vacant City of Cape Town-owned land lying un-utilized and -productive could be developed for land uses such as urban agriculture that may improve the livelihoods of low income families. The new City of Cape Town zoning scheme includes an Urban Agriculture zoning for the first time. Unstructured qualitative interviews among town planners revealed their optimism about this inclusion as it will provide low-income residents with opportunities to generate an income. An existing farming community at Philippi, located within the municipal boundary of the city, was approached and empirical data obtained through questionnaires provided proof that urban agriculture could be viable in a coastal metropolitan city such as Cape Town even if farmers only produce for their own households. The lease method proposed for urban agriculture is a usufruct agreement conferring the right to another party, other than the legal owner, to enjoy the use and advantages of the property.

Keywords: land uses, urban agriculture, agriculture, food engineering

Procedia PDF Downloads 275
3785 Development of Fake News Model Using Machine Learning through Natural Language Processing

Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

Abstract:

Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

Procedia PDF Downloads 135
3784 Remote Sensing Approach to Predict the Impacts of Land Use/Land Cover Change on Urban Thermal Comfort Using Machine Learning Algorithms

Authors: Ahmad E. Aldousaria, Abdulla Al Kafy

Abstract:

Urbanization is an incessant process that involves the transformation of land use/land cover (LULC), resulting in a reduction of cool land covers and thermal comfort zones (TCZs). This study explores the directional shrinkage of TCZs in Kuwait using Landsat satellite data from 1991 – 2021 to predict the future LULC and TCZ distribution for 2026 and 2031 using cellular automata (CA) and artificial neural network (ANN) algorithms. Analysis revealed a rapid urban expansion (40 %) in SE, NE, and NW directions and TCZ shrinkage in N – NW and SW directions with 25 % of the very uncomfortable area. The predicted result showed an urban area increase from 44 % in 2021 to 47 % and 52 % in 2026 and 2031, respectively, where uncomfortable zones were found to be concentrated around urban areas and bare lands in N – NE and N – NW directions. This study proposes an effective and sustainable framework to control TCZ shrinkage, including zero soil policies, planned landscape design, manmade water bodies, and rooftop gardens. This study will help urban planners and policymakers to make Kuwait an eco–friendly, functional, and sustainable country.

Keywords: land cover change, thermal environment, green cover loss, machine learning, remote sensing

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3783 Socio-Economic and Environmental Impact of Urban Sprawl: A Case Study Adigrat City, Tigray, Ethiopia

Authors: Fikre Belay Tekulu

Abstract:

This thesis presents the socio-economic and environmental impacts of urban sprawl in the case of Adigrat city, Tigray Region, Ethiopia. The main objective of this research is to assess major causes, trends and socio-economic and environmental impacts of the urban sprawl of Adigrat city. The study employed both quantitative and qualitative methods as questionnaires, interviews and observation used for data collection. Simple random sampling has been used to select the participants. The land use and land cover change for agricultural land and forest and grassland resource analysis is done with the aid of GIS. Urban sprawl is mainly caused by the rapid population growth, increase in the living and property cost in the core of the city, land demand and land speculation and the growth of transport and an increase in income of people and demand of more living space. The study indicates 15726.24 hectares (515.49 per cent) of new land added to the city jurisdiction from its adjacent Gantafeshum Wereda between 1986 and 2018. The population of Adigrat city increased by 9.045 per cent per year, while the city expanded 16.01 per cent per annum and the LCR was 0.0233 hectares per person between 1986 and 2018.Built-up area increased by 35.27 per cent per annum, while agricultural land, forests and grassland cover decreased by 1.68 per cent and 1.26 per cent per annum respectively in the last thirty three years. This rapid growth of urban sprawl brought social-economic and environmental change in the city that has been observed by the city residents. Therefore, the city administration should need strong, integrated, effective and efficient work, with its neighbor rural area and also done timely preparation, implementation, supervision, and evaluation of the structural plan of the city to bring out sustainable development of the city.

Keywords: cause, , trends, urban sprawl, land use land cover, GIS

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3782 Classifying and Predicting Efficiencies Using Interval DEA Grid Setting

Authors: Yiannis G. Smirlis

Abstract:

The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.

Keywords: data envelopment analysis, interval DEA, efficiency classification, efficiency prediction

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3781 The Right to State Lands: A Case Study of a Squatter Community in Egypt

Authors: Salwa Salman

Abstract:

On February 2016, Egypt’s President Abdel Fattah Al-Sisi ordered the former Prime Minister, Ibrahim Mehleb, to establish a committee responsible for retrieving looted state lands or providing squatters with land titles according to their individual cases. The specificity of desert lands emerges from its unique position in both Islamic law and Egypt’s Civil Code. In Egypt, desert lands can be transferred to private ownership through peaceful occupation and cultivation. This study explores the (re-) conceptualization of land rights, state territoriality, and sovereignty as a part of an emerging narrative on informal land tenure. Through the lens of an informal settlement, the study employs methodological insights from studies in the anthropology of development and their interpretation of Foucauldian discourse analysis to examine official representations on squatting over state lands and put them in conversation with individual narratives on land ownership and dispossession. It also employs Bruno Latour’s actor-network theory to explore the development of social networks through primary land contracts and informal local resource management.

Keywords: State lands, squatter community, Islamic law, Egypt’s Civil Code

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3780 A Supervised Learning Data Mining Approach for Object Recognition and Classification in High Resolution Satellite Data

Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

Abstract:

Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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3779 Probabilistic Crash Prediction and Prevention of Vehicle Crash

Authors: Lavanya Annadi, Fahimeh Jafari

Abstract:

Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

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3778 Exploring the Role of Data Mining in Crime Classification: A Systematic Literature Review

Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

Abstract:

This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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3777 Feature Weighting Comparison Based on Clustering Centers in the Detection of Diabetic Retinopathy

Authors: Kemal Polat

Abstract:

In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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3776 The Effects of Land Use Types to Determine the Status of Sustainable River

Authors: Michael Louis Sunaris, Robby Yussac Tallar

Abstract:

The concept of sustainable river is evolving in Indonesia today. Many rivers condition in Indonesia have decreased by quality and quantity. The degradation of this condition is caused by rapid land use change as a result of increased population growth and human activity. It brings the degradation of the existing watersheds including some types of land use that an important factor in determining the status of river sustainability. Therefore, an evaluation method is required to determine the sustainability status of waterbody within watershed. The purpose of this study is to analyze various types of land use in determining the status of river sustainability. This study takes the watersheds of Citarum Upstream as a study area. The results of the analysis prove the index of sustainability status of the river that changes from good to bad or average in the rivers in the study area. The rapid and uncontrolled changes of land use especially in the upper watersheds area are the main causes that happened over time. It was indicated that the cumulative runoff coefficients were increased significantly. These situations indicated that the damage of watersheds has an impact on the water surplus or deficit problem yearly. Therefore, the rivers in Indonesia should be protected and conserved. The sustainability index of the rivers is an index to indicate the condition of watersheds by defining status of rivers in order to achieve sustainable water resource management.

Keywords: land use change, runoff coefficient, a simple index, sustainable river

Procedia PDF Downloads 128