Search results for: land use regression

Authors: Kiurski S. Jelena, Aksentijević M. Snežana, Oros B. Ivana, Kecić S. Vesna, Djogo Z. Maja

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The paper investigates the effect of light intensity on the formation of two ketones, acetone and methyl ethyl ketone, in working premises of five pad printing departments in Novi Sad, Serbia. Multiple linear regression analysis examined the form of interdependency concentrations of methyl ethyl ketone, acetone and light intensity in five printing presses at seven sampling points, using Statistica software package version 10th. The results show an average stacking variation investigated variable and can be presented by the general regression model: y = b0 + b1xi1 + b2xi2.

Keywords: acetone, methyl ethyl ketone, multiple linear regression analysis, pad printing

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Authors: Ha T. Pham, Shuichi Miyagawa

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Ongoing landscape transformation is one of the major causes behind disappearance of traditional landscapes, and lead to species and resource loss. Tree in paddy fields in the northeast of Thailand is one of those traditional landscapes. Using three different historical time layers, we acknowledged the severe deforestation and rapid urbanization happened in the region. Despite the general thinking of decline in tree density as consequences, the heterogeneous trend of changes in total tree density in three studied landscapes denied the hypothesis that number of trees in paddy field depend on the length of land use practice. On the other hand, due to selection of planting new trees on levees, existence of trees in paddy field are now rely on their values for human use. Besides, changes in land use and landscape structure had a significant impact on decision of which tree density level is considered as suitable for the landscape.

Keywords: aerial photographs, land use change, traditional landscape, tree in paddy fields

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Authors: Yashved Serhun, Kim A. Timm

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Barclays Bank has identified the need for a head office building in Lusaka, Zambia, and construction of a 7200 m2 three-storey reinforced concrete office building with a structural steel roof is currently underway. A unique characteristic of the development is that the building footprint is positioned on dolomitic land. Dolomite rock has the tendency to react with and breakdown in the presence of slightly acidic water, including rainwater. This leads to a potential for subsidence and sinkhole formation. Subsidence and the formation of sinkholes beneath a building can be detrimental during both the construction and operational phases. This paper outlines engineering principles which were considered during the structural design of the raft foundation for the Barclays head office building. In addition, this paper includes multidisciplinary considerations and the impact of these on the structural engineering design of the raft foundation. By ensuring that the design of raft foundations on dolomitic land incorporates the requirements of all disciplines and relevant design codes during the design process, the risk associated with subsidence and sinkhole formation can be effectively mitigated during the operational phase of the building.

Keywords: dolomite, dolomitic land, raft foundation, structural engineering design

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Authors: Praveena Sridhar, Nihar Devathi, Parikshit Chakraborty

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As the software product changes versions across releases, there are changes to the API’s and features and the upgrades become necessary. Hence, it becomes imperative to get the impact of upgrading the dependent components. This tool finds out API changes across two versions and their impact on other API’s followed by execution of the automated regression suites relevant to updates and their impacted areas. This tool has 4 layer architecture, each layer with its own unique pre-assigned capability which it does and sends the required information to next layer. This are the 4 layers. 1) Comparator: Compares the two versions of API. 2) Analyzer: Analyses the API doc and gives the modified class and its dependencies along with implemented interface details. 3) Impact Filter: Find the impact of the modified class on the other API methods. 4) Auto Executer: Based on the output given by Impact Filter, Executor will run the API regression Suite. Tool reads the java doc and extracts the required information of classes, interfaces and enumerations. The extracted information is saved into a data structure which shows the class details and its dependencies along with interfaces and enumerations that are listed in the java doc.

Keywords: automation impact regression, java doc, executor, analyzer, layers

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Authors: Edith Kamakune

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As much as Indigenous rights are presumed to be part of the broad human rights regime, members of the indigenous communities have continually suffered violations, exclusions, and threat. There are a number of steps taken from the international community in trying to bridge the gap, and this has been through the inclusion of provisions as well as the passing of conventions and declarations with specific reference to the rights of indigenous peoples. Some examples of indigenous people include theSiberian Yupik of St Lawrence Island; the Ute of Utah; the Cree of Alberta, and the Xosa andKhoiKhoi of Southern Africa. Uganda’s wide cultural heritage has played a key role in the failure to pay special attention to the needs of the rights of indigenous peoples. The 1995 Constitution and the Land Act of 1998 provide for abstract land rights without necessarily paying attention to indigenous communities’ special needs. Basongora are a pastoralist community in Western Uganda whose ancestral land is the present Queen Elizabeth National Park of Western Uganda, Virunga National Park of Eastern Democratic Republic of Congo, and the small percentage of the low lands under the Rwenzori Mountains. Their values and livelihood are embedded in their strong attachment to the land, and this has been at stake for the last about 90 Years. This research was aimed atinvestigating the relationship between land rights and the right to cultural identity among indigenous communities, looking at the policy available on land and culture, and whether the policies are sensitive of the specific issues of vulnerable ethnic groups; and largely the effect of land on the right to cultural identity. The research was guided by three objectives: to examine and contextualize the concept of land rights among the Basongora community; to assess the policy frame work available for the protection of the Basongora community; to investigate the forms of vulnerability of the Basongora community. Quantitative and qualitative methods were used. a case of Kaseseand Kampala Districts were purposefully selected .138 people were recruited through random and nonrandom techniques to participate in the study, and these were 70 questionnaire respondents; 20 face to face interviews respondents; 5 key informants, and 43 participants in focus group discussions; The study established that Land is communally held and used and thatit continues to be a central source of livelihood for the Basongora; land rights are important in multiplication of herds; preservation, development, and promotion of culture and language. Research found gaps in the policy framework since the policies are concerned with tenure issues and the general provisions areambiguous. Oftenly, the Basongora are not called upon to participate in decision making processes, even on issues that affect them. The research findings call forauthorities to allow Basongora to access Queen Elizabeth National Park land for pasture during particular seasons of the year, especially during the dry seasons; land use policy; need for a clear alignment of the description of indigenous communitiesunder the constitution (Uganda, 1995) to the international definition.

Keywords: cultural identity, land rights, protection, uganda

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Authors: Mahesh K. Jat, Ankan Jana, Mahender Choudhary

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Rapid population and economic growth resulted in changes in large-scale land use land cover (LULC) changes. Changes in the biophysical properties of the Earth's surface and its impact on climate are of primary concern nowadays. Different approaches, ranging from location-based relationships or modelling earth surface - atmospheric interaction through modelling techniques like surface energy balance (SEB) are used in the recent past to examine the relationship between changes in Earth surface land cover and climatic characteristics like temperature and precipitation. A remote sensing-based model i.e., Surface Energy Balance Algorithm for Land (SEBAL), has been used to estimate the surface heat fluxes over Mahi Bajaj Sagar catchment (India) from 2001 to 2020. Landsat ETM and OLI satellite data are used to model the SEB of the area. Changes in observed precipitation and temperature, obtained from India Meteorological Department (IMD) have been correlated with changes in surface heat fluxes to understand the relative contributions of LULC change in changing these climatic variables. Results indicate a noticeable impact of LULC changes on climatic variables, which are aligned with respective changes in SEB components. Results suggest that precipitation increases at a rate of 20 mm/year. The maximum and minimum temperature decreases and increases at 0.007 ℃ /year and 0.02 ℃ /year, respectively. The average temperature increases at 0.009 ℃ /year. Changes in latent heat flux and sensible heat flux positively correlate with precipitation and temperature, respectively. Variation in surface heat fluxes influences the climate parameters and is an adequate reason for climate change. So, SEB modelling is helpful to understand the LULC change and its impact on climate.

Keywords: LULC, sensible heat flux, latent heat flux, SEBAL, landsat, precipitation, temperature

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Authors: J. Satya Eswari, Ch. Venkateswarlu

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The formulation of a commercial pharmaceutical product involves several composition factors and response characteristics. When the formulation requires to satisfy multiple response characteristics which are conflicting, an optimal solution requires the need for an efficient multiobjective optimization technique. In this work, a regression is combined with a non-dominated sorting differential evolution (NSDE) involving Naïve & Slow and ε constraint techniques to derive different multiobjective optimization strategies, which are then evaluated by means of a trapidil pharmaceutical formulation. The analysis of the results show the effectiveness of the strategy that combines the regression model and NSDE with the integration of both Naïve & Slow and ε constraint techniques for Pareto optimization of trapidil formulation. With this strategy, the optimal formulation at pH=6.8 is obtained with the decision variables of micro crystalline cellulose, hydroxypropyl methylcellulose and compression pressure. The corresponding response characteristics of rate constant and release order are also noted down. The comparison of these results with the experimental data and with those of other multiple regression model based multiobjective evolutionary optimization strategies signify the better performance for optimal trapidil formulation.

Keywords: pharmaceutical formulation, multiple regression model, response surface method, radial basis function network, differential evolution, multiobjective optimization

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Authors: Shiza Zafar

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The tannery effluents contaminated about 400 acres land area in Kasur, Pakistan, has been reclaimed by removing polluted water after the long term effluent logging from the nearby tanneries. In an effort to describe the status of reclaimed soil for agricultural practices, the results of physicochemical analysis of the soil are reported in this article. The concentrations of the parameters such as pH, Electrical Conductivity (EC), Organic Matter (OM), Organic Carbon (OC), Available Phosphorus (P), Potassium (K), and Sodium (Na) were determined by standard methods of analysis and results were computed and compared with various international standards for agriculture recommended by international organizations, groups of experts and or individual researchers. The results revealed that pH, EC, OM, OC, K, and Na are in accordance with the prescribed limits but P in soil exceeds the satisfactory range of P in agricultural soil. Thus, the reclaimed soil in Kasur can be inferred fit for the purpose of agricultural activities.

Keywords: soil toxicity, agriculture, reclaimed land, physico-chemical analysis

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Authors: Kuei-Yu Chien, Nai-Wen Kan, Wan-Chun Wu, Guo-Dong Ma, Shu-Chen Chen

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Purpose: The purpose of this study was to investigate the responses of systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), rating of perceived exertion (RPE) and lactate following continued high-intensity interval exercise in water and on land. The results of studies can be an exercise program design reference for health care and fitness professionals. Method: A total of 20 volunteer postmenopausal women was included in this study. The inclusion criteria were: duration of menopause > 1 year; and sedentary lifestyle, defined as engaging in moderate-intensity exercise less than three times per week, or less than 20 minutes per day. Participants need to visit experimental place three times. The first time visiting, body composition was performed and participant filled out the questionnaire. Participants were assigned randomly to the exercise environment (water or land) in second and third time visiting. Water exercise testing was under water of trochanter level. In continuing jump testing, each movement consisted 10-second maximum volunteer jump for two sets. 50% heart rate reserve dynamic resting (walking or running) for one minute was within each set. SBP, DBP, HR, RPE of whole body/thigh (RPEW/RPET) and lactate were performed at pre and post testing. HR, RPEW, and RPET were monitored after 1, 2, and 10 min of exercise testing. SBP and DBP were performed after 10 and 30 min of exercise testing. Results: The responses of SBP and DBP after exercise testing in water were higher than those on land. Lactate levels after exercise testing in water were lower than those on land. The responses of RPET were lower than those on land post exercise 1 and 2 minutes. The heart rate recovery in water was faster than those on land at post exercise 5 minutes. Conclusion: This study showed water interval jump exercise induces higher cardiovascular responses with lower RPE responses and lactate levels than on-land jumps exercise in postmenopausal women. Fatigue is one of the major reasons to obstruct exercise behavior. Jump exercise could enhance cardiorespiratory fitness, the lower-extremity power, strength, and bone mass. There are several health benefits to the middle to older adults. This study showed that water interval jumping could be more relaxed and not tried to reach the same land-based cardiorespiratory exercise intensity.

Keywords: interval exercise, power, recovery, fatigue

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Authors: S. Deswal, M. Pal

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The paper aims to compare the performance of vertical and inclined multiple plunging jets and to model and predict their mass transfer capacity by multi-linear regression based approach. The multiple vertical plunging jets have jet impact angle of θ = 90O; whereas, multiple inclined plunging jets have jet impact angle of θ = 600. The results of the study suggests that mass transfer is higher for multiple jets, and inclined multiple plunging jets have up to 1.6 times higher mass transfer than vertical multiple plunging jets under similar conditions. The derived relationship, based on multi-linear regression approach, has successfully predicted the volumetric mass transfer coefficient (KLa) from operational parameters of multiple plunging jets with a correlation coefficient of 0.973, root mean square error of 0.002 and coefficient of determination of 0.946. The results suggests that predicted overall mass transfer coefficient is in good agreement with actual experimental values; thereby suggesting the utility of derived relationship based on multi-linear regression based approach and can be successfully employed in modelling mass transfer by multiple plunging jets.

Keywords: mass transfer, multiple plunging jets, multi-linear regression, earth sciences

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: Dan Han, Yukun Zhang, Jie Zheng, Rui Zhang

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Making full use of space along transportation infrastructure to develop renewable energy sources, especially solar energy resources, has become a research focus in relevant fields. In recent years, relevant international researches can be classified into three stages of theoretical and technical exploration, exploratory practice as well as planning implementation. Compared with traditional solar energy development mode, the development of solar energy resources in places along the transportation infrastructure has special advantages, which can also bring forth new opportunities for the development of green transportation. 'Road Integrated Photovoltaic', a development model of combining transport and new energy, has been actively studied and applied in developed countries, but it was still in its infancy in China. 'New Silk Road Economic Belt' has great advantage to carry out the 'Road Integrated Photovoltaic' because of the rich solar energy resources in its path, the shortages of renewable energy, the constraints of agricultural land and other reasons. Especially the massive amount of construction of transportation infrastructure brought by Silk Road Economic Belt, large area of developable land along the transportation line will be generated. Abundant solar energy recourses along the Silk Road will provide extremely superb practical opportunities to the land development along transportation infrastructure. We take PVsyst, GIS and Google map software for simulation of its potential by taking Lan-Xin Railway as an example, so potential electrical energy generation can be quantified and further analyzed. Research of 'New Silk Road Economic Belt' combined with 'Road Integrated Photovoltaic' is a creative development for the along transport and energy infrastructure. It not only can make full use of solar radiation and land in its path, but also bring more long-term advantages and benefits.

Keywords: land use, silk road economic belt, solar energy, transportation infrastructure

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Authors: Avijit Mahala

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Present study is primarily concerned with the physical processes and status of land degradation in a tropical plateau fringe. Chotanagpur plateau is one of the most water erosion related degraded areas of India. The granite gneiss geological formation, low to medium developed soil cover, undulating lateritic uplands, high drainage density, low to medium rainfall (100-140cm), dry tropical deciduous forest cover makes the Silabati River basin a truly representative of the tropical environment. The different physical factors have been taken for land degradation study includes- physiographic formations, hydrologic characteristics, and vegetation cover. Water erosion, vegetal degradation, soil quality decline are the major processes of land degradation in study area. Granite-gneiss geological formation is responsible for developing undulating landforms. Less developed soil profile, low organic matter, poor structure of soil causes high soil erosion. High relief and sloppy areas cause unstable environment. The dissected highland causes topographic hindrance in productivity. High drainage density and frequency in rugged upland and intense erosion in sloppy areas causes high soil erosion of the basin. Decreasing rainfall and increasing aridity (low P/PET) threats water stress condition. Green biomass cover area is also continuously declining. Through overlaying the different physical factors (geological formation, soil characteristics, geomorphological characteristics, etc.) of considerable importance in GIS environment the varying intensities of land degradation areas has been identified. Middle reaches of Silabati basin with highly eroded laterite soil cover areas are more prone to land degradation.

Keywords: land degradation, tropical environment, lateritic upland, undulating landform, aridity, GIS environment

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Authors: Chokri Slim

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The objective of this research is attempting to respond to this question: Is there a significant difference between the regression model and statistical learning models in predicting credit risk management? A Multiple Linear Regression (MLR) model was compared with neural networks including Multi-Layer Perceptron (MLP), and a Support vector regression (SVR). The population of this study includes 50 listed Banks in Tunis Stock Exchange (TSE) market from 2000 to 2016. Firstly, we show the factors that have significant effect on the quality of loan portfolios of banks in Tunisia. Secondly, it attempts to establish that the systematic use of objective techniques and methods designed to apprehend and assess risk when considering applications for granting credit, has a positive effect on the quality of loan portfolios of banks and their future collectability. Finally, we will try to show that the bank governance has an impact on the choice of methods and techniques for analyzing and measuring the risks inherent in the banking business, including the risk of non-repayment. The results of empirical tests confirm our claims.

Keywords: credit risk management, multiple linear regression, principal components analysis, artificial neural networks, support vector machines

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Authors: Sami Mestiri, Abdeljelil Farhat

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The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

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Authors: Priya Kedia, Kiranmoy Das

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There is a rich literature on variable selection in regression setting. However, most of these methods assume normality for the response variable under consideration for implementing the methodology and establishing the statistical properties of the estimates. In many real applications, the distribution for the response variable may be non-Gaussian, and one might be interested in finding the best subset of covariates at some predetermined quantile level. We develop dynamic Bayesian approach for variable selection in quantile regression framework. We use a zero-inflated mixture prior for the regression coefficients, and consider the asymmetric Laplace distribution for the response variable for modeling different quantiles of its distribution. An efficient Gibbs sampler is developed for our computation. Our proposed approach is assessed through extensive simulation studies, and real application of the proposed approach is also illustrated. We consider the data from health and retirement study conducted by the University of Michigan, and select the important predictors when the outcome of interest is out-of-pocket medical cost, which is considered as an important measure for financial risk. Our analysis finds important predictors at different quantiles of the outcome, and thus enhance our understanding on the effects of different predictors on the out-of-pocket medical cost.

Keywords: variable selection, quantile regression, Gibbs sampler, asymmetric Laplace distribution

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Authors: Adesuyi Ayodeji Steve, Zahn Munch

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This study investigates the use of MODIS NDVI to identify agricultural land cover change areas on an annual time step (2007 - 2012) and characterize the trend in the study area. An ISODATA classification was performed on the MODIS imagery to select only the agricultural class producing 3 class groups namely: agriculture, agriculture/semi-natural, and semi-natural. NDVI signatures were created for the time series to identify areas dominated by cereals and vineyards with the aid of ancillary, pictometry and field sample data. The NDVI signature curve and training samples aided in creating a decision tree model in WEKA 3.6.9. From the training samples two classification models were built in WEKA using decision tree classifier (J48) algorithm; Model 1 included ISODATA classification and Model 2 without, both having accuracies of 90.7% and 88.3% respectively. The two models were used to classify the whole study area, thus producing two land cover maps with Model 1 and 2 having classification accuracies of 77% and 80% respectively. Model 2 was used to create change detection maps for all the other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices over the years as predicted by the land cover classification. 41% of the catchment comprises of cereals with 35% possibly following a crop rotation system. Vineyard largely remained constant over the years, with some conversion to vineyard (1%) from other land cover classes. Some of the changes might be as a result of misclassification and crop rotation system.

Keywords: change detection, land cover, modis, NDVI

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Authors: Rubab Zafar Kahlon, Ibtisam Butt

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Forest resources are deteriorating and experiencing decline around the globe due to unsustainable use and over exploitation. The present study was an attempt to determine the relationship between human activities, forest resource utilization, extraction methods and practices of forest resource exploitation in the district Jhelum of Pakistan. For this purpose, primary sources of data were used which were collected from 8 villages through structured questionnaire and tabulated in Microsoft Excel 365 and SPSS 22 was used for multiple linear regression analysis. The results revealed that farming, wood cutting, animal husbandry and agro-forestry were the major occupations in the study area. Most commonly used resources included timber 26%, fuelwood 25% and fodder 19%. Methods used for resource extraction included gathering 49%, plucking 34% trapping 11% and cutting 6%. Population growth, increased demand of fuelwood and land conversion were the main reasons behind forest degradation. Results for multiple linear regression revealed that Forest based activities, sources of energy production, methods used for wood harvesting and resource extraction and use of fuelwood for energy production contributed significantly towards extensive forest resource exploitation with p value <0.5 within the study area. The study suggests that effective measures should be taken by forest department to control the unsustainable use of forest resources by stringent management interventions and awareness campaigns in Jhelum district.

Keywords: forest resource, biodiversity, expliotation, human activities

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Authors: Taleb Odeh, Nizar Abu-Jaber, Nour Khries

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The southern part of Wadi Al Yarmouk catchment area covers north of Jordan. It locates within latitudes 32° 20’ to 32° 45’N and longitudes 35° 42’ to 36° 23’ E and has an area of about 1426 km2. However, it has high relief topography where the elevation varies between 50 to 1100 meter above sea level. The variations in the topography causes different units of landforms, climatic zones, land covers and plant species. As a results of these different landscapes units exists in that region. Spatial planning is a major challenge in such a vital area for Jordan which could not be achieved without determining landscape units. However, an integrated approach of remote sensing and geographic information Systems (GIS) is an optimized tool to investigate and map landscape units of such a complicated area. Remote sensing has the capability to collect different land surface data, of large landscape areas, accurately and in different time periods. GIS has the ability of storage these land surface data, analyzing them spatially and present them in form of professional maps. We generated a geo-land surface data that include land cover, rock units, soil units, plant species and digital elevation model using ASTER image and Google Earth while analyzing geo-data spatially were done by ArcGIS 10.2 software. We found that there are twenty two different landscape units in the study area which they have to be considered for any spatial planning in order to avoid and environmental problems.

Keywords: landscape, spatial planning, GIS, spatial analysis, remote sensing

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Authors: Tsitsi Nyukurayi Muparari, Walter Timo De Vries, Jaap Zevenbergen

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The nature of Land administration accommodates diversity in terms of both spatial data handling activities and the expertise involved, which supposedly aims to satisfy the unpredictable demands of land data and the diverse demands of the customers arising from the land. However, it is known that strategic decisions of restructuring are in most cases repelled in favour of complex structures that strive to accommodate professional diversity and diverse roles in the field of Land administration. Yet despite of this widely accepted knowledge, there is scanty theoretical knowledge concerning the psychological methodologies that can extract the deeper perceptions from the diverse spatial expertise in order to explain the invisible control arm of the polarised reception of the ideas of change. This paper evaluates Q methodology in the context of a cadastre and land registry merger (under one agency) using the Swedish cadastral system as a case study. Precisely, the aim of this paper is to evaluate the effectiveness of Q methodology towards modelling the diverse psychological perceptions of spatial professionals who are in a widely contested decision of merging the cadastre and land registry components of Land administration using the Swedish cadastral system as a case study. An empirical approach that is prescribed by Q methodology starts with the concourse development, followed by the design of statements and q sort instrument, selection of the participants, the q-sorting exercise, factor extraction by PQMethod and finally narrative development by logic of abduction. The paper uses 36 statements developed from a dominant competing value theory that stands out on its reliability and validity, purposively selects 19 participants to do the Qsorting exercise, proceeds with factor extraction from the diversity using varimax rotation and judgemental rotation provided by PQMethod and effect the narrative construction using the logic abduction. The findings from the diverse perceptions from cadastral professionals in the merger decision of land registry and cadastre components in Sweden’s mapping agency (Lantmäteriet) shows that focus is rather inclined on the perfection of the relationship between the legal expertise and technical spatial expertise. There is much emphasis on tradition, loyalty and communication attributes which concern the organisation’s internal environment rather than innovation and market attributes that reveals customer behavior and needs arising from the changing humankind-land needs. It can be concluded that Q methodology offers effective tools that pursues a psychological approach for the evaluation and gradations of the decisions of strategic change through extracting the local perceptions of spatial expertise.

Keywords: cadastre, factor extraction, land administration merger, land registry, q-methodology, rotation

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Authors: Tingke Wu, Yaping Huang

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Many cities in China have been experiencing serious urban sprawl since the 1980s, which pose great challenges to a country with scare cultivated land and huge population. Because of different social and economic context and development stage, driving forces of urban sprawl in China are quite different from developed countries. Therefore, it is of great importance to probe into urban sprawl driving mechanism in Chinese context. By a comparison study of the background and features of urban sprawl between China and developed countries, this research establishes an analytical framework for sprawl dynamic mechanism in China. By literature review and analyzing data from national statistical yearbook, it then probes into the driving mechanism and the primary cause of urban sprawl. The results suggest that population increase, economic growth, traffic and information technology development lead to rapid expansion of urban space; defects of land institution and lack of effective guidance give rise to low efficiency of urban land use. Moreover, urban sprawl is ultimately attributed to imperfections of policy and institution. On this basis, this research puts forward several sprawl control strategies in Chinese context.

Keywords: China, driving forces, driving mechanism, land institution, urban expansion, urban sprawl

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Authors: Joonas Pääkkönen

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In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling

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Authors: Tahani Salman Alangari

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Student success can be impacted by internal factors such as their emotional well-being and external factors such as organizational support and instructional support in the classroom. This study is to identify at least one factor that forecasts student engagement. It is a cross-sectional, conducted on 6206 teachers and encompassed three years of data collection and observations of math instruction in approximately 50 schools and 300 classrooms. A multiple linear regression revealed that a model predicting student engagement from emotional support, classroom organization, and instructional support was significant. Four linear regression models were tested using hierarchical regression to examine the effects of independent variables: emotional support was the highest predictor of student engagement while instructional support was the lowest.

Keywords: student engagement, emotional support, organizational support, instructional support, well-being

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Authors: Mahesh Kumar Jat, Manisha Choudhary

Abstract:

Rapid population and economic growth resulted in changes in large-scale land use land cover (LULC) changes. Changes in the biophysical properties of the Earth's surface and its impact on climate are of primary concern nowadays. Different approaches, ranging from location-based relationships or modelling earth surface - atmospheric interaction through modelling techniques like surface energy balance (SEB) have been used in the recent past to examine the relationship between changes in Earth surface land cover and climatic characteristics like temperature and precipitation. A remote sensing-based model i.e., Surface Energy Balance Algorithm for Land (SEBAL), has been used to estimate the surface heat fluxes over Mahi Bajaj Sagar catchment (India) from 2001 to 2020. Landsat ETM and OLI satellite data are used to model the SEB of the area. Changes in observed precipitation and temperature, obtained from India Meteorological Department (IMD) have been correlated with changes in surface heat fluxes to understand the relative contributions of LULC change in changing these climatic variables. Results indicate a noticeable impact of LULC changes on climatic variables, which are aligned with respective changes in SEB components. Results suggest that precipitation increases at a rate of 20 mm/year. The maximum and minimum temperature decreases and increases at 0.007 ℃ /year and 0.02 ℃ /year, respectively. The average temperature increases at 0.009 ℃ /year. Changes in latent heat flux and sensible heat flux positively correlate with precipitation and temperature, respectively. Variation in surface heat fluxes influences the climate parameters and is an adequate reason for climate change. So, SEB modelling is helpful to understand the LULC change and its impact on climate.

Keywords: remote sensing, GIS, object based, classification

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Authors: Aldrin R. Logdat

Abstract:

The insights and wisdom of the Alangan Mangyans offer valuable guidance for developing alternative ecological and development frameworks. Their reverence for the sacredness of the land, rooted in their traditional cosmology, guides their harmonious relationship with nature. Through their practice of swidden farming, ecosystem preservation takes precedence as they carefully manage agricultural activities and allow for forest regeneration. This approach aligns with natural processes, reflecting their profound understanding of the natural world. Similar to early advocates like Aldo Leopold, the emphasis is on shifting our perception of land from a commodity to a community. The indigenous wisdom of the Alangan Mangyans provides practical and sustainable approaches to preserving the interdependence of the biotic community and ecosystems. By integrating their cultural heritage, we can transcend the prevailing anthropocentric mindset and foster a meaningful and sustainable connection with nature. The revitalization of cultural energy and the embrace of alternative frameworks require learning from indigenous peoples like the Alangan Mangyans, where reverence for the land and the recognition of the interconnectedness between humanity and nature are prioritized. This paves the way for a future where harmony with nature and the well-being of the Earth community prevail.

Keywords: Alangan Mangyans, ecological frameworks, sacredness of the land, cultural energy

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Authors: Seydou Sinde

Abstract:

The aims of this paper are to formulate mathematical expressions that can be used to estimate the standpipe pressure (SPP). The developed formulas take into account the main factors that, directly or indirectly, affect the behavior of SPP values. Fluid rheology and well hydraulics are some of these essential factors. Mud Plastic viscosity, yield point, flow power, consistency index, flow rate, drillstring, and annular geometries are represented by the frictional pressure (Pf), which is one of the input independent parameters and is calculated, in this paper, using Herschel-Bulkley rheological model. Other input independent parameters include the rate of penetration (ROP), applied load or weight on the bit (WOB), bit revolutions per minute (RPM), bit torque (TRQ), and hole inclination and direction coupled in the hole curvature or dogleg (DL). The technique of repeating parameters and Buckingham PI theorem are used to reduce the number of the input independent parameters into the dimensionless revolutions per minute (RPMd), the dimensionless torque (TRQd), and the dogleg, which is already in the dimensionless form of radians. Multivariable linear and polynomial regression technique using PTC Mathcad Prime 4.0 is used to analyze and determine the exact relationships between the dependent parameter, which is SPP, and the remaining three dimensionless groups. Three models proved sufficiently satisfactory to estimate the standpipe pressure: multivariable linear regression model 1 containing three regression coefficients for vertical wells; multivariable linear regression model 2 containing four regression coefficients for deviated wells; and multivariable polynomial quadratic regression model containing six regression coefficients for both vertical and deviated wells. Although that the linear regression model 2 (with four coefficients) is relatively more complex and contains an additional term over the linear regression model 1 (with three coefficients), the former did not really add significant improvements to the later except for some minor values. Thus, the effect of the hole curvature or dogleg is insignificant and can be omitted from the input independent parameters without significant losses of accuracy. The polynomial quadratic regression model is considered the most accurate model due to its relatively higher accuracy for most of the cases. Data of nine wells from the Middle East were used to run the developed models with satisfactory results provided by all of them, even if the multivariable polynomial quadratic regression model gave the best and most accurate results. Development of these models is useful not only to monitor and predict, with accuracy, the values of SPP but also to early control and check for the integrity of the well hydraulics as well as to take the corrective actions should any unexpected problems appear, such as pipe washouts, jet plugging, excessive mud losses, fluid gains, kicks, etc.

Keywords: standpipe, pressure, hydraulics, nondimensionalization, parameters, regression

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Authors: Tingting Song

Abstract:

Wetlands are significant ecosystems that provide a variety of ecosystem services for humans, such as, providing water and food resources, purifying water quality, regulating climate, protecting biodiversity, and providing cultural, recreational, and educational resources. Wetlands also provide benefits, such as reduction of flood, storm damage, and soil erosion. The flood protection ecosystem services of wetlands are often ignored. Due to climate change, the flood caused by extreme weather in recent years occur frequently. Flood has a great impact on people's production and life with more and more economic losses. This study area is in the Tone river basin in the Kanto area, Japan. It is the second-longest river with the largest basin area in Japan, and it is still suffering heavy economic losses from floods. Tone river basin is one of the rivers that provide water for Tokyo and has an important impact on economic activities in Japan. The purpose of this study was to investigate land-use changes of wetlands in the Tone River Basin, and whether there are spatial differences in the value of wetland functions in mitigating economic losses caused by floods. This study analyzed the land-use change of wetland in Tone River, based on the Landsat data from 1980 to 2020. Combined with flood economic loss, wetland area, GDP, population density, and other social-economic data, a geospatial weighted regression model was constructed to analyze the spatial difference of wetland ecosystem service value. Now, flood protection mainly relies on such a hard project of dam and reservoir, but excessive dependence on hard engineering will cause the government huge financial pressure and have a big impact on the ecological environment. However, natural wetlands can also play a role in flood management, at the same time they can also provide diverse ecosystem services. Moreover, the construction and maintenance cost of natural wetlands is lower than that of hard engineering. Although it is not easy to say which is more effective in terms of flood management. When the marginal value of a wetland is greater than the economic loss caused by flood per unit area, it may be considered to rely on the flood storage capacity of the wetland to reduce the impact of the flood. It can promote the sustainable development of wetlands ecosystem. On the other hand, spatial analysis of wetland values can provide a more effective strategy for flood management in the Tone river basin.

Keywords: wetland, geospatial weighted regression, ecosystem services, environment valuation

Procedia PDF Downloads 84

Authors: Hyon I. Paek, Sang Rim Kim, Hyon A. Ryu

Abstract:

In functional linear regression, one typical problem is to reduce dimension. Compared with multivariate linear regression, functional linear regression is regarded as an infinite-dimensional case, and the main task is to reduce dimensions of functional response and functional predictors. One common approach is to adapt functional principal component analysis (FPCA) on functional predictors and then use a few leading functional principal components (FPC) to predict the functional model. The leading FPCs estimated by the typical FPCA explain a major variation of the functional predictor, but these leading FPCs may not be mostly correlated with the functional response, so they may not be significant in the prediction for response. In this paper, we propose a supervised functional principal component analysis method for a functional response model with FPCs obtained by considering the correlation of the functional response. Our method would have a better prediction accuracy than the typical FPCA method.

Keywords: supervised, functional principal component analysis, functional response, functional linear regression

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Authors: Tsai Yu-hsin, Chung Yi-Hsin

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The employment of an HSR system, resulting in elevation in the inter-city/-region accessibility, is likely to promote spatial interaction between places in the HSR and extended territory. The inter-city/-region travel via HSR could be, among others, affected by the land use, transportation, and location of the HSR station at both trip origin and destination ends. However, relatively few insights have been shed on these impacts and spatial patterns of the HSR travel. The research purposes, as phase one of a series of HSR related research, of this study are threefold: to analyze the general spatial patterns of HSR trips, such as the spatial distribution of trip origins and destinations; to analyze if specific land use, transportation characteristics, and trip characteristics affect HSR trips in terms of the use of HSR, the distribution of trip origins and destinations, and; to analyze the socio-economic characteristics of HSR travelers. With the Taiwan HSR starting operation in 2007, this study emphasizes on the intermediate-term impact of HSR, which is made possible with the population and housing census and industry and commercial census data and a station area intercept survey conducted in the summer 2014. The analysis will be conducted at the city, inter-city, and inter-region spatial levels, as necessary and required. The analysis tools include descriptive statistics and multivariate analysis with the assistance of SPSS, HLM and ArcGIS. The findings, on the one hand, can provide policy implications for associated land use, transportation plan and the site selection of HSR station. On the other hand, on the travel the findings are expected to provide insights that can help explain how land use and real estate values could be affected by HSR in following phases of this series of research.

Keywords: high speed rail, land use, travel, spatial pattern

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Authors: Irfan Ahmad Afip

Abstract:

This main research objective is to accurately identify the possibility for a Leptospirosis outbreak severity of a certain area based on its input features into a multivariate regression model. The research question is the possibility of an outbreak in a specific area being influenced by this feature, such as social demographics and hydrometeorological extremes. If the occurrence of an outbreak is being subjected to these features, then the epidemic severity for an area will be different depending on its environmental setting because the features will influence the possibility and severity of an outbreak. Specifically, this research objective was three-fold, namely: (a) to identify the relevant multivariate features and visualize the patterns data, (b) to develop a multivariate regression model based from the selected features and determine the possibility for Leptospirosis outbreak in an area, and (c) to compare the predictive ability of multivariate regression model and machine learning algorithms. Several secondary data features were collected locations in the state of Negeri Sembilan, Malaysia, based on the possibility it would be relevant to determine the outbreak severity in the area. The relevant features then will become an input in a multivariate regression model; a linear regression model is a simple and quick solution for creating prognostic capabilities. A multivariate regression model has proven more precise prognostic capabilities than univariate models. The expected outcome from this research is to establish a correlation between the features of social demographic and hydrometeorological with Leptospirosis bacteria; it will also become a contributor for understanding the underlying relationship between the pathogen and the ecosystem. The relationship established can be beneficial for the health department or urban planner to inspect and prepare for future outcomes in event detection and system health monitoring.

Keywords: geographical information system, hydrometeorological, leptospirosis, multivariate regression

Procedia PDF Downloads 97