Search results for: land cover classification

Authors: Chevonne Reynolds, Res Altwegg, Andrew Balmford, Claire N. Spottiswoode

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Modern agriculture has revolutionised the planet’s capacity to support humans, yet has simultaneously had a greater negative impact on biodiversity than any other human activity. Balancing the demand for food with the conservation of biodiversity is one of the most pressing issues of our time. Biodiversity-friendly farming (‘land sharing’), or alternatively, separation of conservation and production activities (‘land sparing’), are proposed as two strategies for mediating the trade-off between agriculture and biodiversity. However, there is much debate regarding the efficacy of each strategy, as this trade-off has typically been addressed by short term studies at fine spatial scales. These studies ignore processes that are relevant to biodiversity at larger scales, such as meta-population dynamics and landscape connectivity. Therefore, to better understand species response to agricultural land-use and provide evidence to underpin the planning of better production landscapes, we need to determine the merits of each strategy at larger scales. In South Africa, a remarkable citizen science project - the South African Bird Atlas Project 2 (SABAP2) – collates an extensive dataset describing the occurrence of birds at a 5-min by 5-min grid cell resolution. We use these data, along with fine-resolution data on agricultural land-use, to determine which strategy optimises the agriculture-biodiversity trade-off in a southern African context, and at a spatial scale never considered before. To empirically test this trade-off, we model bird species population density, derived for each 5-min grid cell by Royle-Nicols single-species occupancy modelling, against both the amount and configuration of different types of agricultural production in the same 5-min grid cell. In using both production amount and configuration, we can show not only how species population densities react to changes in yield, but also describe the production landscape patterns most conducive to conservation. Furthermore, the extent of both the SABAP2 and land-cover datasets allows us to test this trade-off across multiple regions to determine if bird populations respond in a consistent way and whether results can be extrapolated to other landscapes. We tested the land sparing/sharing trade-off for 281 bird species across three different biomes in South Africa. Overall, a higher proportion of species are classified as losers, and would benefit from land sparing. However, this proportion of loser-sparers is not consistent and varies across biomes and the different types of agricultural production. This is most likely because of differences in the intensity of agricultural land-use and the interactions between the differing types of natural vegetation and agriculture. Interestingly, we observe a higher number of species that benefit from agriculture than anticipated, suggesting that agriculture is a legitimate resource for certain bird species. Our results support those seen at smaller scales and across vastly different agricultural systems, that land sparing benefits the most species. However, our analysis suggests that land sparing needs to be implemented at spatial scales much larger than previously considered. Species persistence in agricultural landscapes will require the conservation of large tracts of land, and is an important consideration in developing countries, which are undergoing rapid agricultural development.

Keywords: agriculture, birds, land sharing, land sparing

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Authors: Melis Inalpulat, Tugce Civelek, Unal Kizil, Levent Genc

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Livestock production is one of the most important components of rural economy. Due to the urban expansion, rural areas close to expanding cities transform into urban districts during the time. However, the legislations have some restrictions related to livestock farming in such administrative units since they tend to create environmental concerns like odor problems resulted from excessive manure production. Therefore, the existing animal operations should be moved from the settlement areas. This paper was focused on determination of suitable lands for livestock production in Canakkale province of Turkey using remote sensing (RS) data and GIS techniques. To achieve the goal, Formosat 2 and Landsat 8 imageries, Aster DEM, and 1:25000 scaled soil maps, village boundaries, and village livestock inventory records were used. The study was conducted using suitability analysis which evaluates the land in terms of limitations and potentials, and suitability range was categorized as Suitable (S) and Non-Suitable (NS). Limitations included the distances from main and crossroads, water resources and settlements, while potentials were appropriate values for slope, land use capability and land use land cover status. Village-based S land distribution results were presented, and compared with livestock inventories. Results showed that approximately 44230 ha area is inappropriate because of the distance limitations for roads and etc. (NS). Moreover, according to LULC map, 71052 ha area consists of forests, olive and other orchards, and thus, may not be suitable for building such structures (NS). In comparison, it was found that there are a total of 1228 ha S lands within study area. The village-based findings indicated that, in some villages livestock production continues on NS areas. Finally, it was suggested that organized livestock zones may be constructed to serve in more than one village after the detailed analysis complemented considering also political decisions, opinion of the local people, etc.

Keywords: GIS, livestock, LULC, remote sensing, suitable lands

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Authors: Babalola Sunday Oyetayo, Igbinomwanhia Uyi Osamwonyi, Idowu T. O., Herbert Tata

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This paper explores the potential benefits of adopting blockchain technology in Nigeria's land administration systems while also addressing the challenges and implications of its implementation in the country's unique context. Through a comprehensive literature review and analysis of existing research, the paper delves into the key attributes of blockchain that can revolutionize land administration practices, with a particular focus on simplifying land registration procedures, expediting land title issuance, and enhancing data transparency and security. The decentralized and immutable nature of blockchain offers unique advantages, instilling trust and confidence in land transactions, which are especially crucial in Nigeria's land governance landscape. However, integrating blockchain in Nigeria's land administration ecosystem presents specific challenges, necessitating a critical evaluation of technical, socio-economic, and infrastructural barriers. These challenges encompass data privacy concerns, scalability, interoperability with outdated systems, and gaining acceptance from various stakeholders. By synthesizing these insights, the paper proposes strategies tailored to Nigeria's context to optimize the benefits of blockchain adoption while addressing the identified challenges. The research findings contribute significantly to the ongoing discourse on blockchain technology in Nigeria's land governance, offering evidence-based recommendations to policymakers, land administrators, and stakeholders. Ultimately, the paper aims to promote the effective utilization of blockchain, fostering efficiency, transparency, and trust in Nigeria's land administration systems to drive sustainable development and societal progress.

Keywords: block-chain, technology, stakeholders, land registration

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Authors: Yvonne Christelle M. de Guzman, Charity Faye T. Cabie

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This study analyzed the contents of ten issues of Cosmopolitan Magazine from 2011 to 2015. The researcher found out the hegemony among Filipino women as dictated by Cosmopolitan magazine through the use of Semiotic Analysis, Laura Mulvey’s Male Gaze and Gramsci’s concept of hegemony. The researcher also looked at the themes of cover stories, words used to describe women, meanings behind the color of magazine’s front cover, clothing, physique and pose such as gesture and facial expression used by the cover girl. However, the entire content of the magazine was not taken into account.

Keywords: dominant ideology, male gaze, semiotics, women

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Authors: Niringiye Fred

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Banyabunagana has always had access to land resources for grazing animals, sand mining, and farmland across the border in the Democratic Republic of Congo during the pre-colonial and colonial times, usually on an informal arrangement facilitated by kinship ties and rent transactions for these resources. However, in recent periods, the government of the Democratic Republic of the Congo (DRC) has been pursuing a policy of constructing barriers such as walls and fences so that Banyabunagana communities do not access the land on the DRC side of the border. This is happening in the background of increased and intensified demand for land use on the side of the Ugandan community. This paper will attempt to discuss the reasons behind the construction of walls, fences, and other barriers which deny access to land for Banyabunagana communities in Bunagana Parish, Muramba Sub-county- Kisoro district, Uganda. The research will attempt to answer the following main questions, among others, whether there are the factors that explain the construction of walls and fences which could limit or deny access to the informal use of land and other resources and whether policy options to ensure continued access to land and other resources for local communities.

Keywords: border, walls, fences, land resource access

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Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

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Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

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Authors: Adrian Rifqi, Febe Napitupulu, Erdi Hermawan, Edwin Putra, Yang Leprilian

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This article focuses on the implementation of the production improvement process of the Indonesian land certificate product that printed in Perum Peruri as the state-owned enterprises. Based on the data obtained, there are several complaints from customers of the 2019 land certificate production. The complaints become a negative value to loyal customers of Perum Peruri. Almost all the complaints are referring to ‘defective printouts and the difference between products in packaging and packaging labels both in terms of type and quantity’. To overcome this problem, we intend to make an improvement to the production process that focuses on complaints ‘there is a difference between products in packaging with packaging labels’. Improvements in the land certificate production process are relying on the technology of the scales and QR code on the packaging label. In addition, using the QR code on the packaging label will facilitate the process of tracking product data. With this method, we hope to reduce the error rate between products in packaging with the packaging label both in terms of quantity, type, and product number on the land certificate and error rate of sending land certificates, which will be sent to many places to 0%. With this solution, we also hope to get precise data and real-time reports on the production of land certificates in the near future, so track and trace implementation can be done as the solution of the land certificate production.

Keywords: land certificates, QR code, track and trace, packaging

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Authors: E. Vazquez-Santacruz, M. Gamboa-Zuniga

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In this paper, we show a methodology for bodies classification in lying state using HOG descriptors and pressures sensors positioned in a matrix form (14 x 32 sensors) on the surface where bodies lie down. it will be done in real time. Our system is embedded in a care robot that can assist the elderly patient and medical staff around to get a better quality of life in and out of hospitals. Due to current technology a limited number of sensors is used, wich results in low-resolution data array, that will be used as image of 14 x 32 pixels. Our work considers the problem of human posture classification with few information (sensors), applying digital process to expand the original data of the sensors and so get more significant data for the classification, however, this is done with low-cost algorithms to ensure the real-time execution.

Keywords: real-time classification, sensors, robots, health care, elderly patients, artificial intelligence

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Authors: W. A. M. Abdel Kawy, Kh. M. Darwish

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Adequate land use selection is an essential step towards achieving sustainable development. The main object of this study is to develop a new scale for land suitability system, which can be compatible with the local conditions. Furthermore, it aims to adapt the conventional land suitability systems to match the actual environmental status in term of soil types, climate and other conditions to evaluate land suitability for newly reclaimed areas. The new system suggests calculation of land suitability considering 20 factors affecting crop selection grouping into five categories; crop-agronomic, land management, development, environmental conditions and socio – economic status. Each factor is summed by each other to calculate the total points. The highest rating for each factor indicates the highest preference for the evaluated crop. The highest rated crops for each group are those with the highest points for the actual suitability. This study was conducted to assess the application efficiency of the new land suitability scale in recently reclaimed sites in Egypt. Moreover, 35 representative soil profiles were examined, and soil samples were subjected to some physical and chemical analysis. Actual and potential suitabilities were calculated by using the new land suitability scale. Finally, the obtained results confirmed the applicability of a new land suitability system to recommend the most promising crop rotation that can be applied in the study areas. The outputs of this research revealed that the integration of different aspects for modeling and adapting a proposed model provides an effective and flexible technique, which contribute to improve land suitability assessment for several crops to be more accurate and reliable.

Keywords: analytic hierarchy process, land suitability, multi-criteria analysis, new reclaimed areas, soil parameters

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Authors: Cecilia Sosa, Fernanda Figueroa, Leonardo Calzada

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Biosphere reserves (BR) are considered as the main strategy for biodiversity and ecosystems conservation. Mexican BR are mainly inhabited by rural communities who strongly depend on forests and their resources. Even though the dual objective of conservation and development has been sought in BR, land cover change is a common process in these areas, while most rural communities are highly marginalized, partly as a result of restrictions imposed by conservation to the access and use of resources. Achieving ecosystems conservation and social development face serious challenges. Factors such as financial support for development projects (public/private), environmental conditions, infrastructure and regional economic conditions might influence both land use change and wellbeing. Examining the temporal trends of conservation and development in BR is central for the evaluation of outcomes for these conservation strategies. In this study, we analyzed changes in primary vegetation cover (as a proxy for conservation) and the index of marginalization (as a proxy for development) in Mexican BR (2000-2015); we also explore the influence of various factors affecting these trends, such as conservation-development projects financial support (public or private), geographical distribution in ecoregions (as a proxy for shared environmental conditions) and in economic zones (as a proxy for regional economic conditions). We developed a spatial analysis at the municipal scale (2,458 municipalities nationwide) in ArcGIS, to obtain road densities, geographical distribution in ecoregions and economic zones, the financial support received, and the percent of municipality area under protection by protected areas and, particularly, by BR. Those municipalities with less than 25% of area under protection were regarded as part of the protected area. We obtained marginalization indexes for all municipalities and, using MODIS in Google Earth Engine, the number of pixels covered by primary vegetation. We used a linear mixed model in RStudio for the analysis. We found a positive correlation between the marginalization index and the percent of primary vegetation cover per year (r=0.49-0.5); i.e., municipalities with higher marginalization also show higher percent of primary vegetation cover. Also, those municipalities with higher area under protection have more development projects (r=0.46) and some environmental conditions were relevant for percent of vegetation cover. Time, economic zones and marginalization index were all important. Time was particularly, in 2005, when both marginalization and deforestation decreased. Road densities and financial support for conservation-development projects were irrelevant as factors in the general correlation. Marginalization is still being affected by the conservation strategies applied in BR, even though that this management category considers both conservation and development of local communities as its objectives. Our results suggest that roads densities and support for conservation-development projects have not been a factor of poverty alleviation. As better conservation is being attained in the most impoverished areas, we face the dilemma of how to improve wellbeing in rural communities under conservation, since current strategies have not been able to leave behind the conservation-development contraposition.

Keywords: deforestation, local development, marginalization, protected areas

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Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

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Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

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Authors: L. M. Hayyan ul Haq, Lalu Sabardi

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This research is aimed at exploring an appropriate regulatory model in coherencing a diametrical interest between the state, Adat legal community, and private interests in utilising and optimizing land in Indonesia. This work is also highly relevant to coherencing the obligation of the state to respect, to fulfill and to protect the fundamental rights of people, especially to protect the communal or adat community rights to the land. In visualizing those ideas, this research will use the normative legal research to elaborate the normative problem in land use, as well as redesigning and creating an appropriate regulatory model in bridging and protecting all interest parties, especially, the state, Adat legal community, and private parties. In addition, it will also employ an empirical legal research for identifying some operational problems in protecting and optimising the land. In detail, this research will not only identify the problems at the normative level, such as conflicted norms, the absence of the norms, and the unclear norm in land law, but also the problems at operational level, such as institutional relationship in managing the land use. At the end, this work offers an appropriate regulatory model at the systems level, which covers value and norms in land use, as well as the appropriate mechanism in managing the utilization of the land for the state, Adat legal community, and private sector. By manifesting this objective, the government will not only fulfill its obligation to regulate the land for people and private, but also to protect the fundamental rights of people, as mandated by the Indonesian 1945 Constitution.

Keywords: adat community rights, fundamental rights, investment, land law, private sector

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Authors: Lopita Pal, Suresh V. Madha

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Wetlands are areas of marsh, fen, peat land or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six metres. The rapidly expanding human population, large scale changes in land use/land cover, burgeoning development projects and improper use of watersheds all has caused a substantial decline of wetland resources in the world. Major degradations have been impacted from agricultural, industrial and urban developments leading to various types of pollutions and hydrological perturbations. Regular fishing activities and unsustainable grazing of animals are degrading the wetlands in a slow pace. The paper focuses on the spatio-temporal change detection of the area of the water body and the main cause of this depletion. The total area under study (22°19’87’’ N, 88°20’23’’ E) is a wetland region in West Bengal of 213 sq.km. The procedure used is the Normalized Difference Water Index (NDWI) from multi-spectral imagery and Landsat to detect the presence of surface water, and the datasets have been compared of the years 2016, 2006 and 1996. The result shows a sharp decline in the area of water body due to a rapid increase in the agricultural practices and the growing urbanization.

Keywords: spatio-temporal change, NDWI, urbanization, wetland

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Authors: Ahmad Javid Habib, Tetsuo Kidokoro

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There is an increasing demand for developing urban land to provide better living conditions for all citizens in Afghanistan. Most of the development will involve the acquisition of land. And the current land acquisition method practiced by central government is expropriation, which is a cash-based transaction method that imposes heavy fiscal burden on local municipalities and central government, and it does not protect ownership rights and social equity of landowners besides it relocates the urban poor to remote areas with limited access to jobs and public services. The questionnaire analysis, backed by observations of different case studies in countries where land readjustment is used as a collaborative land development tool indicates that the method plays a key role in valuing landowners’ rights, giving other community members and stakeholders the opportunity to collaboratively implement urban development projects. The practice of the method is reducing the heavy fiscal burden on the local and central governments and is a better option to deal with the current development challenges in Afghanistan.

Keywords: collaboration, land readjustment, master plan, expropriation

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

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

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

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Authors: Tayfun Cay, Sabahattin Akkus

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Due to inheritance, urban areas can not be arranged in a planned and programmed manner. As a result of this, the social fabric is disrupted and the hostility is increasing among the people. This contradicts the understanding of the social state. The Turkish Civil Code and the Urban Development Law are effective in sharing heritage in urban areas in Turkey. Within the framework of this legislation; How to make heritage sharing and services in the title deed. In this study, these laws, regulations, and statutes are examined. In the frame of this legislation, land registry problems on inheritance are examined and the province of Konya - Selçuk district, is selected as an application place to solve the problems. In this study, the problems of heritage sharing in the land registry were investigated. The evaluation of the work is done and the results are determined and possible solutions are proposed.

Keywords: land, land registry, heritage sharing, sharing problems of heritage

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Authors: Kita R. Ashman, Anthony R. Rendall, Matthew R. E. Symonds, Desley A. Whisson

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Forest cover is decreasing globally, chiefly due to the conversion of forest to agricultural landscapes. In contrast, the area under plantation forestry is increasing significantly. For wildlife occupying landscapes where native forest is the dominant land cover, plantations generally represent a lower value habitat; however, plantations established on land formerly used for pasture may benefit wildlife by providing temporary forest habitat and increasing connectivity. This study investigates the influence of landscape, site, and climatic factors on koala population density in far south-west Victoria where there has been extensive plantation establishment. We conducted koala surveys and habitat characteristic assessments at 72 sites across three habitat types: plantation, native vegetation blocks, and native vegetation strips. We employed a hierarchical modeling framework for estimating abundance and constructed candidate multinomial N-mixture models to identify factors influencing the abundance of koalas. We detected higher mean koala density in plantation sites (0.85 per ha) than in either native block (0.68 per ha) or native strip sites (0.66 per ha). We found five covariates of koala density and using these variables, we spatially modeled koala abundance and discuss factors that are key in determining large-scale distribution and density of koala populations. We provide a distribution map that can be used to identify high priority areas for population management as well as the habitat of high conservation significance for koalas. This information facilitates the linkage of ecological theory with the on-ground implementation of management actions and may guide conservation planning and resource management actions to consider overall landscape configuration as well as the spatial arrangement of plantations adjacent to the remnant forest.

Keywords: abundance modelling, arboreal mammals plantations, wildlife conservation

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Authors: Gehad S. Kaseb, Mona F. Ahmed

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Arabic Sentiment Analysis (SA) is one of the most common research fields with many open areas. Few studies apply SA to Arabic dialects. This paper proposes different pre-processing steps and a modified methodology to improve the accuracy using normal Support Vector Machine (SVM) classification. The paper works on two datasets, Arabic Sentiment Tweets Dataset (ASTD) and Extended Arabic Tweets Sentiment Dataset (Extended-AATSD), which are publicly available for academic use. The results show that the classification accuracy approaches 86%.

Keywords: Arabic, classification, sentiment analysis, tweets

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Authors: Thinh Ngo, Paul Rad, Brian Kelley

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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

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Authors: Balázs Kulcsár

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Today, there is no part of the world that does not bear the mark of man in some way. This process seems unstoppable. So perhaps the best thing we can do is to touch that handprint gently and with the utmost care. There are multiple uses for the same piece of land, the coordination of which requires careful and sustainable spatial planning. The case study of the Rétközlake in north-eastern Hungary illustrates a habitat rehabilitation project in which a number of human uses were coordinated with the conservation and restoration of the natural environment. Today, the good condition of the habitat can only be maintained artificially, but the project has paid particular attention to finding a sustainable solution. The rehabilitation of Lake Rétköz is considered good practice in resolving land-use conflicts.

Keywords: sustainability, ecosystem service, land use conflict, landscape utilization

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Authors: Barbara Vojvodikova, Katerina Jupova, Iva Ticha

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Cities in their historical evolution have always adapted their internal structure to the needs of society (for example protective city walls during classicism era lost their defense function, became unnecessary, were demolished and gave space for new features such as roads, museums or parks). Today it is necessary to modify the internal structure of the city in order to minimize the impact of climate changes on the environment of the population. This article discusses the results of the Urban Climate model owned by VITO, which was carried out as part of a project from the European Union's Horizon grant agreement No 730004 Pan-European Urban Climate Services Climate-Fit city. The use of the model was aimed at changes in land use and land cover in cities related to urban heat islands (UHI). The task of the application was to evaluate possible land use change scenarios in connection with city requirements and ideas. Two pilot areas in the Czech Republic were selected. One is Ostrava and the other Hodonín. The paper provides a demonstration of the application of the model for various possible future development scenarios. It contains an assessment of the suitability or inappropriateness of scenarios of future development depending on the temperature increase. Cities that are preparing to reconstruct the public space are interested in eliminating proposals that would lead to an increase in temperature stress as early as in the assignment phase. If they have evaluation on the unsuitability of some type of design, they can limit it into the proposal phases. Therefore, especially in the application of models on Local level - in 1 m spatial resolution, it was necessary to show which type of proposals would create a significant temperature island in its implementation. Such a type of proposal is considered unsuitable. The model shows that the building itself can create a shady place and thus contribute to the reduction of the UHI. If it sensitively approaches the protection of existing greenery, this new construction may not pose a significant problem. More massive interventions leading to the reduction of existing greenery create a new heat island space.

Keywords: climate model, heat islands, Hodonin, land use changes, Ostrava

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Authors: Jaiden X. Schraut

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Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

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Authors: Ahmad Sharif Ahmadi, Yoshitaka Kajita

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Kabul, the capital and largest city in Afghanistan has been experiencing a massive population expansion and fast economic development in last decade, in which urban land has increasingly expanded and formed a high informal development territory in the city. This paper investigates the urban land development direction based on the integrated urbanization trends in Kabul city since the last and the fastest ever urban land growth period (1999-2008), which is parallel with the establishment of the new government in Afghanistan. Considering the existing challenges in terms of informal settlements, squatter settlements, the population expansion of the city, and fast economic development, as well as the huge influx of returning refugees from neighboring countries, and the sprawl direction of urbanization of the Kabul city urban fringes, this research focuses on the possible urban land development direction and trends for the city. The paper studies the feasible future land development direction of Kabul city in the northern part called Shamali basin, in which district 17 is the gateway for future development. The area has much developable area including eight districts of Kabul province, and the vast area of Parwan and Kapisa provinces. The northern area of the Kabul city generally has favorable conditions for further urbanization from the city. It is a large and relatively flat area of area in the northern part of Kabul city, with ample water resources available from the Panjshir basin as a base principle of land development direction in the area.

Keywords: Kabul city, land development trends, urban land development, urbanization

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Authors: Jitka Molnarova

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Based on De Soto’s idea that a formal land title can provide a secure home and access to credit to poor urban families, a large number of developing countries accepted the formalization of informal settlements as the ultimate solution for their housing crises and struggles with poverty. After two decades of implementation, very little is known about the effects this policy has on the quality of the neighborhoods it produces and on the development of cities in general. Using the capital of Peru -where the solution originated- as a case study, this paper illustrates the negative outcomes this policy has on urban development arguing that land titling encourages 1) expansion of the city often to areas of high physical risk, 2) production of precarious housing on unserviced land, and 3) practices of illegal land trafficking. The evidence is based on interviews with community leaders and officials working at the Cooperation for Formalization of Informal Property (COFOPRI), comparison of satellite images documenting the expansion of Lima in the past twenty years, and a technical evaluation of dozens of houses that have been or are in the process of being granted a land title.

Keywords: COFOPRI, De Soto, housing policies, land titling, land trafficking, Lima, Peru, precarious housing, urban expansion

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Authors: Bruno Trstenjak, Dzenana Donko

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Data mining and classification of objects is the process of data analysis, using various machine learning techniques, which is used today in various fields of research. This paper presents a concept of hybrid classification model improved with the expert knowledge. The hybrid model in its algorithm has integrated several machine learning techniques (Information Gain, K-means, and Case-Based Reasoning) and the expert’s knowledge into one. The knowledge of experts is used to determine the importance of features. The paper presents the model algorithm and the results of the case study in which the emphasis was put on achieving the maximum classification accuracy without reducing the number of features.

Keywords: case based reasoning, classification, expert's knowledge, hybrid model

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Authors: M. Karthigayan, M. Rizon, Sazali Yaacob, R. Nagarajan, M. Muthukumaran, Thinaharan Ramachandran, Sargunam Thirugnanam

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In this paper, using a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA) are applied to the lip and eye features to classify the human emotions. Two South East Asian (SEA) faces are considered in this work for the emotion classification. There are six emotions and one neutral are considered as the output. Each subject shows unique characteristic of the lip and eye features for various emotions. GA is adopted to optimize irregular ellipse characteristics of the lip and eye features in each emotion. That is, the top portion of lip configuration is a part of one ellipse and the bottom of different ellipse. Two ellipse based fitness equations are proposed for the lip configuration and relevant parameters that define the emotions are listed. The GA method has achieved reasonably successful classification of emotion. In some emotions classification, optimized data values of one emotion are messed or overlapped to other emotion ranges. In order to overcome the overlapping problem between the emotion optimized values and at the same time to improve the classification, a fuzzy clustering method (FCM) of approach has been implemented to offer better classification. The GA-FCM approach offers a reasonably good classification within the ranges of clusters and it had been proven by applying to two SEA subjects and have improved the classification rate.

Keywords: ellipse fitness function, genetic algorithm, emotion recognition, fuzzy clustering

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