bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring and change detection of concentration values for zinc and lead minerals in soil of agricultural lands based on remote sensing analysis and GIS
Authors: Hasab Hashim Ali 
Published: August 2020

Abstract
The agricultural lands are an important source for the recovery of the economy system southern of Iraq. The neglect, lack of interest, and the wars in recent years are affecting on the soil quality of these lands. There are a few techniques are developed to detect and monitor the toxic minerals in soil of the agricultural lands south of Iraq. The integration of remote sensing data and Geographic Information System (GIS) techniques with the developed of mathematical equations were as a powerful tool to monitor spatial distribution and change detections the concentrations values for zinc (Zn) and lead (Pb) in soil of the agricultural lands during winter and summer seasons in year 2018. The concentrations values for (Zn) and (Pb) in soil have been lowest in winter and highest in summer season. The change detection of spatial distribution area for (Zn) between two seasons was by range (45.06) km2 with the change ratio (37%), while the change detection of spatial distribution area for (Pb) between two seasons was by range (29.82) km2, with the change ratio (25%). In conclusion, the developed systematic and generic approach may constitute a basis for determining the soil minerals in the agricultural lands worldwide.
The Integration of Remote Sensing Data for Lineament Mapping in the Semanggol Formation, Northwest Peninsular Malaysia
Authors: Azman Ali Imran , Talib Jasmi Ab , Sokiman Mohamad Shaufi 
Published: August 2020

Abstract
The objective of this study is to prepare a final lineament map of three parts of the Semanggol Formation and its adjacent areas, located in northern Peninsular Malaysia. Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, digital elevation model (DEM) and drainage pattern were used to trace lineament. These data were digitally processed to enhance the visibility of data and derive to twenty-four images. Only negative lineaments with length more than 2 km were traced by using manual lineament extraction method. Based on the results, there are differences in the number of lineaments and total length in each data, caused the lineaments to have to compare each other. The lineaments identified from all data were integrated and evaluated to produce a final lineament map. A total of 645 lineaments were identified with a total length of 2264.42 km and a maximum length of 26.84 km. The trend of the lineaments was correlated with faults in the published geological map, especially in the Bok Bak Fault. This method proved that lineaments could be traced more accurately with the utilisation of various remote sensing data.
The Prediction of Urban Growth Trends and Patterns using Spatio-temporal CA-MC Model in Seremban Basin
Authors: Ajeeb Rabia , Aburas Maher M , Baba Faisal , Ali Abdelsalam , Alazaiza Motasem Y.D. 
Published: August 2020

Abstract
Urban growth, a dynamic and demographic phenomenon, refers to the increased spatial value of urban areas, such as cities and towns, due to social and economic forces. Nowadays, urban lands are rapidly increasing, replacing non-urban lands such as agricultural, forest, water, rural, and open lands. In this study, a CA-Markov model was utilized to predict the growth of urban lands and their spatial trends in Seremban, Malaysia. The performance of the CA-Markov model was also assessed. The Markov chain model was applied to produce the quantitative values of transition probabilities for urban and non-urban lands. Subsequently, the CA model was used to predict the dynamic spatial trends of land changes. The change in urban and non-urban land use from 1984 to 2010 was modeled using the CA-Markov model for calibration purposes and to compute optimal CA transition rules as well as to predict future urban growth. In the accuracy assessment process, the CA-Markov model was validated using a Kappa coefficient. The overall accuracy of the Kappa index statistics was 83%, which indicates the excellent performance of the model proposed in this study. Finally, based on the CA transition rules and the transition area matrix produced from the calibration process using the Markov Chain model, future urban growth in Seremban for 2020 and 2030 was simulated.
Identification of Dry Areas on Agricultural Land using Normalized Difference Drought Index in Magetan Regency
Authors: Rismayatika F , Saraswati R , Shidiq I P A , Taqyyudin  
Published: August 2020

Abstract
Indonesia is a country with vast agricultural lands. However, agricultural land production in Indonesia is threatened by climate change and land use change. One of phenomenon from climate change that threatened agricultural land is El Nino. El Nino can cause long-lasting drought. In 2018, Indonesia Ministry of Agriculture predicted that in the middle of 2019, El Nino would occur in Indonesia. Magetan Regency is one of the regencies in East Java Province that has a high level of vulnerability to drought. Magetan Regency ranked 36 in Indonesia as a Drought-Prone Regency. Drought in the agricultural sector is a drought which is one of the direct impacts of the climate change phenomenon. This research aims to identify dry areas in agricultural land using Normalized Difference Drought Index and Landsat 8 Imagery with acquisition month August 2017 (Normal Year) and 2019 (El Nino Year). The results of data processing revealed that the dry areas in 2019 are wider than dry areas in 2017 with extent area of 3350.26 ha in 2017 and 9237.28 ha in 2019.
Assessing Coastal Land Dynamics Along UAE Shoreline Using GIS and Remote Sensing Techniques
Authors: Aldogom D , Albesher S , Mansoori S Al , Nazzal T 
Published: August 2020

Abstract
the coastal areas geomorphological characteristic is greatly active, where land accretion and erosion is a continuous phenomenon with different degrees. The temporal change in coastline location is an important sign of coastal development and it can provide quantitative and descriptive information on beach dynamics. To investigate coastal variability trends, when field-based surveys are inaccessible or absent, historical remote sensing data and GIS analysis can be effective techniques. This study focuses on the United Arab Emirates (UAE) coastline that stretches for more than 1,000 km to cover the entire coastal area of the country. Multitemporal Landsat satellite images cover more than 45 years had been used to assess the coastal land dynamics by first delineate land areas from existing water bodies accurately using GIS and remote sensing approaches. Then, quantify coastline variability by measuring erosion and accretion rates, using the statistical operations within Digital Shoreline Analysis Software (DSAS) that include, Net Shoreline Movement(NSM), Linear Regression Rate (LRR), and End Point Rate (EPR). Finally, compare and analyse these rates with the associate causes for a better understanding of the coast area dynamic nature. The study results can be a feasible management tool to help coastal planners and policymakers to consider the identified coastal dynamic trends before starting any urban development.
Feasibility Study on Walkable City Through Implementation of Car-Free Zones in Georgetown, Penang Using GIS Network Analysis
Authors: Salleh A.H. , Ahamad M.S.S. , William G.W.W. 
Published: August 2020

Abstract
Motorized vehicles have brought tremendous convenience to humans today. Although it provides comforts, but the excessive dependence on cars has caused vehicles to dominate on roads, leading to various issues for cities, including congestion, road safety, and environmental issues. The implementation of the walkable city would shift people’s transportation mode, which sequentially helps reduce the number of cars on the roads. This research studies the feasibility of car-free zones in Georgetown, Penang, Malaysia. The walkability principle is presented as criteria in car-free spatial modeling and are consequently used in the spatial overlay process to produce a map showing preferred areas to be designed car-free. The result identified three (3) preferred areas as car-free zones. The spatial comparison was made between the proposed car-free zones and the superblock model, i.e., a case study from Barcelona’s Superblock project. The percentage of pedestrianized streets in Georgetown is determined together with the assessment of the effect of car-free zones on travel route, distance and time. From the results, it is found that each localized traffic has a longer traveling distance. Yet, due to the roads that the traffic was diverted to allow a higher travel speed, the travel time is sometimes reduced. Overall, the increase in travel distance ranges from 12.88% to 174.92% while travel time ranges from 0.29% to 119.40%.
Comparative Analysis of Malaria Cases Using Geospatial-statistical Approach in Hadejia Metropolis, Jigawa State, Nigeria
Authors: Gambo Jibrin , Mohd Shafri Helmi Zulhaidi Bin , Abubakar Ahmed , Yusuf Yusuf Ahmed , Adam Maryam Babangida 
Published: August 2020

Abstract
Malaria is a significant public health issue in Nigeria where it accounts for more infections and deaths than any other nation in the world. Malaria is a concern for 97 percent of Nigeria’s population. The remaining 3 percent of the people reside in the malaria free highlands. There are an estimated 100 million malaria cases with over 300,000 deaths per year in Nigeria. It contrasts with 215,000 deaths a year in Nigeria from HIV / AIDS. Malaria contributes to an estimated 11 percent of maternal mortality. The study employed interpolated approach for the assessment and mapping of malaria cases from 2014 to 2018 in Hadejia metropolis and compares five year data of malaria prevalence within the political wards in the study area, using geo-spatial tools. The results showed that certain wards in the city have malaria cases danger which have a direct impact on human safety, social welfare which economy. The prevalence of the malaria parasites primarily exists in north and east of the sample country. Consequently the district is divided into eleven strata (political wards) which demonstrate that the higher incidence of Malaria for both years around Kasuwar Kofa, Kasuwar Kuda, Dubantu, Yayari and some portion of Matsaro and Gagulmari.
Dengue Hotspot Detection in Bangi, Selangor, Malaysia
Authors: Majid Nuriah Abd , Rasdi Rozimah Muhamad 
Published: August 2020

Abstract
Dengue fever has increased dramatically in Malaysia in recent decades and has triggered tremendous public health concerns. This paper addresses the spatial and temporal aspects of Dengue epidemics in Selangor, Bangi. This study aimed to examine spatial diffusion trends and to recognize hotspots in recorded dengue cases. The study used the Malaysia Ministry of Health epidemiological data for dengue cases reported in 2016-2019. These data have been processed and converted into GIS format. The geospatial spread pattern of the 2016, 2017, 2018, and 2019 dengue outbreak was investigated and mapped. The hotspot analysis is shown as points on a map and refers to dengue cases locations in the study area and measures the Getis-Ord Gi statistics for dengue cases in 2016-2019. The related z-scores and p-values are shown spatially in the Bangi region with either a cluster of high or low values. The map produced from data range between -3 (cold spot -99% confidence level) to 3 (hotspot – 99% confidence level) is classified into very low, low, very high, and high dengue fever clustered in the urban area.
Burglary Crime Susceptibility Assessment using Bivariate Statistics Approach of Information Value Model
Authors: Azmy S N , Asmadi M A , Rahman M Z A , Amerudin S , Zainon O 
Published: August 2020

Abstract
Geospatial technology advancement has boost the ability of crime assessment in terms of the accuracy of crime location and prediction. Aforetime, the crime assessment tend to focus on the development of sanction and law, as well as behaviour studies of why certain people are prone to be a victim of crime and why certain people are prone in committing crime, but none of them incorporating the idea of place of crime until 1971 (Jeffery, 1971). With technology advancement, the crime assessment of place has evolved from pin map to large scale digital mapping, effective inventory method, and adept crime analysis as well as crime prediction. The residential area of Damansara-Penchala, Kuala Lumpur and its vicinity are chosen as study area for its urban location and vastness of socioeconomic status. According to the data in Safe City Monitoring System (Sistem Pemantauan Bandar Selamat, SPBS), the monetary loss due to burglary crime activities in the study area for 2016 are sum up to RM 5,640,087 (RM 5.6 million) within 172 burglary incidence, with the mean loss of RM 32,791.00 with every offend of burglary. Apart from monetary loss, burglary also affecting the social values of the society and in terms of the perception of safe living. Instead of providing an analysis of area with high density of burglary, this paper embarks on finding the correlated social and environmental factor that leaning towards being the target of burglary crime. Utilizing the method of information value modelling, a bi-variate statistical method in the layout of raster data analysis, the vulnerability of each premise are calculated based on its association with the identified burglary indicators. The results finds that 17 significant indicators out of 18 indicators are identified as index contributing to burglary susceptibility. The burglary susceptibility mapping are acquired to contribute in predicting the premise’s potential risk for the sake of future crime prevention.
Analysis of Canopy Height Model (CHM) Extraction using Quick Terrain Modeller (QTM) for Tropical Forest Area
Authors: Mohd Zaki Nurul Ain , Rajuli Muhammad Farhan , Latif Zulkiflee Abd , Suratman Mohd Nazip , Omar Hamdan , Norashikin Sharifah , Zainal Mohd Zainee , Talib Noorfatekah 
Published: August 2020

AbstractForest biomass or above-ground carbon stock is the mass of carbon that stored in trees which requires a continuous monitoring in order to predict the amount of potential carbon accumulation of the forest. Therefore, the forest has an important role at absorbing carbon Dioxide (CO2) from the atmosphere. This research aims to measure the capability of Quick Terrain Modeller software at estimating above-ground carbon stock by single tree segmentation combining ground inventory, Light Detection and Ranging (LiDAR), and by using allometric equations. In particular, to achieve the aim, there are three (3) objectives were outlined. Canopy Height Models (CHM) was generated via Quick Terrain Modeller (QTM) and ArcGIS. Non-linear Regression analyses were performed for both surface models to ensure the models were fit to estimate carbon stock. Secondly, tree contours were delineated using watershed transformation. Local maxima were determined at the raster as a pour point for watershed and also represent the highest peak of the tree crown. In addition, flow direction, drop output, and flow accumulation of the raster were also determined to generate contour from the watershed transformation. Manual tree crown projection was performed by watershed tree contour to generate Crown Projection Area (CPA). Then, from the digitized CPA, carbon stock and above-ground biomass was calculated using equations from [1] and [2]. Thirdly, tree species on the selected area were extracted and finally a map of tree carbon stock by species was produced. From the generated map, total carbon stock according to species and total carbon stock in single tree according to species information were extracted. As a result, Hopea sulcata; the endangered tree species appeared to be the highest appearance in the map followed byDipterocarpus verrucosus, Shorea macroptera, Endospermum diadenum, and the other less appeal species. Also from the map, Hopea Sulcata has the highest carbon stock which is 23% compared to the other species. However, for a single tree, Dipterocarpus verrucosusheld the highest carbon stock which is 1565.401 kg/tree.
Review of Conceptual Model to Spatially Assessing Safe City Level of Affordable Housing in Malaysia
Authors: Mohamad Ali Salwa Najlaa , Tarmidi Zakri , Mat Nor Noorsidi Aizuddin 
Published: August 2020

Abstract
Safety of residential area has become major concern in urban area, especially in affordable housing area, with several safety measure was implemented. Several Governments also developed safe city program, focusing on preventing crime index. Several initiatives were conducted to assess safety, including Safe City Index 2019, Safe City Program, Defensible Space Concept, crime prevention through environmental design (CPTED), Smart Sustainable Cities, etc. Some of these initiatives focus only on crime, other focus on step to improve safety and other model that are broader focus but not specific to safety. Besides that, these models are less emphasis on the aspects of spatial assessment especially the safety level assessment based on affordable housing location in Malaysia. This study focuses on integrating spatial information and analysis to improve current initiatives, and come out with conceptual model to spatially assessing safety level of affordable housing in Malaysia. This conceptual model consists of 6 main indicators; crime, safety and security, infrastructure security, accessibility, natural disaster, and health security. With proper assessment model, further planning to improve current safety can be taken by government and affordable housing community.
Remote Estimation of Gross Primary Production (GPP) using MODIS data in Kelantan: A Preliminary Assessment
Authors: Adeli Aisyah Syazana , Naim Jemali Noor Janatun , Daliman Shaparas , Abd Rani Mohd Faris , Abd Majid Nur Khyairatul Syafinie 
Published: August 2020

Abstract
Kelantan state is located in the north-eastern of Peninsular Malaysia, with 5.8 million hectares is covered by forested areas. Gross primary production (GPP) is the amount of carbon captured by plants and it is an important biophysical parameter in the spatio-temporal dynamics of CO2. GPP estimates derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are converted to the forest area and compared. GPP is estimated through a light use efficiency model (LUE) and enhanced vegetation index (EVI) as a proxy of greenness to address spatial and temporal variation in terrestrial photosynthetic activities. This study is important because the output will be used as a reference to estimate the approximate total carbon in Kelantan. Estimation GPP of Kelantan state is also useful for natural resource and land management, regional carbon cycle analysis, ecosystem status assessment, and environmental change monitoring. The objective of this study is to estimate Gross Primary Production (GPP) value of forested area in Kelantan using MODIS data. MODIS data was preprocessed, classified and analysed to get the estimated GPP of study site. The results show that average GPP value of Kelantan was estimated within the range of 0 to 646 gC/m2/month. In average, GPP in Kelantan was at 428.63 gC/m2/month. Gua Musang recorded the highest GPP value, while the lowest GPP value detected were in Kota Bharu, Tumpat and Bachok where lot of development are found at the area. The estimation of GPP in Kelantan using MODIS data is a timely significant method. However, the requirement of more study that uses MODIS data in different terrestrial types and vegetation is needed for future study.
Spatial Pattern of Affordability and Overhang in Selangor
Authors: Mohamed Aris Nur Arzwin , Fathi Mohamad Syazli , Harun Aizul Nahar , Mohamed Zainai 
Published: August 2020

Abstract
The provision of affordable housing is being developed rapidly whilst the mismatch between demand and supply in the residential market was reported as a crisis causing an increased in the overhang of residential accommodation. To date, no detailed analysis in the form of a spatial pattern for affordable housing has been studied to illustrate the crisis. Thus, this paper aims to analyse patterns for affordable house prices by using a spatial model in Selangor state with further analysis of overhang units in the Selangor district. Secondary data were obtained from various sources and the spatial model was formed and generated to examine the spatial patterns within the study area, which is in Selangor. Although previous research has found that the median household income group intended to purchase a type of landed house, for example terraced houses, the offered prices in the property market were not affordable to this particular group. Further analysis of residential overhang found that Gombak district has a high density of land use zoned for housing supply whilst facing the increased overhang. The findings of this research may guide the stakeholders on proper planning for near future of the affordable housing development with suitable type of residential to meet the residential market segmentation and demand.
Geostatistics of Oil Palm Trees Affected by Ganoderma Disease in Low and High Planting Density
Authors: Mohd Shukri I , Izzuddin M.A , Mohd Hefni R , Idris A.S 
Published: August 2020

Abstract
This study was conducted to assess the influence of two oil palm planting density (PD) on the incidence and severity of the Ganoderma basal stem rot (BSR) disease in oil palm planted in a plantation at Bagan Datuk, Perak, Malaysia. Ground surveys were conducted in oil palm planted in two planting densities involved which are: 120 palms/ha (lowest PD) and 200 palms/ha (highest PD) to assess the incidence and severity of BSR disease in oil palm plantations, over the 25 years after planting, YAP. The presence of the BSR disease symptoms as visually assigned followed the Standard Operating Procedures (SOP) Guidelines for Managing Ganoderma Disease in Oil Palm. Semivariogram analysis was performed on the data to show the spatiotemporal structure of BSR disease at 10, 15, 20 and 25 years after planting. The disease incidence was observed in all both plots with 0.57% to 1.67% at 8 years after planting, followed by increased to 15.12% to 38.3% at 16 years after planting. At 25 years, high BSR disease incidence was recorded on 200 palms/ha (72.5%), whilst low BSR disease incidence was recorded on 120 palm/ha. Effects of nugget to sill were found relatively moderate to weak of spatial pattern distribution. The observed disease patterns suggest that the progress of BSR disease incidence is firstly randomly scattered (8 to 10 years after planting) and secondly by root-to-root contact of the disease spreading to neighbouring palms may be occurred. Further study is needed to investigate factors associated with the outbreak of BSR disease in these plantations.