bluuebunny/crossref_metadata_2025 huggingface dataset:
Mapping of Archaeological Sites using UAV Aerial Survey and PPK GNSS Ground Survey Techniques in Central Asia
Authors: Suab Stanley Anak , Hayakawa Yuichi , Kume Shogo , Yamaguchi Yuji , Amanbaeva Bakyt , Kadyrov Abdynaby , Avtar Ram , Ogura Takuro
Published: August 2020

Geospatial technologies such as Unmanned Aerial Vehicle (UAV) and Global Navigation Satellite Systems (GNSS) are becoming popular in various applications also for archaeological purposes. This is due to the abilities also the usefulness of UAV and GNSS technologies for digitally documenting and recording archaeological sites in great detail. Such information is crucial for the efforts of preserving and protecting historical sites. This paper demonstrates the workflows and results of mapping techniques using consumer-grade UAV for aerial survey and low-cost Post-Processing Kinematics (PPK) GNSS ground survey for documentation of two archaeological sites in Batken State, Kyrgyzstan in Central Asia. Both UAV and PPK GNSS data were acquired simultaneously during the fieldworks in early winter while processing were explicitly done using currently available commercial and open-source software. Results of the UAV and PPK GNSS was combined and qualitatively evaluated. Despite advantages and disadvantages identified in both UAV and PPK GNSS results, it was learned that the combination of both techniques found to be very beneficial for mapping of archaeological sites.
Correlation Analysis of Urban Development and Land Surface Temperature Using Google Earth Engine in Sleman Regency, Indonesia
Authors: Maishella A , Dewantoro B E B , Aji M A P
Published: August 2020

The development of urban areas in Sleman Regency occurs continuously along with an increase in population, encourages changes in any kind of land cover to be built-up area to meet the needs of citizen housing. The objectives of this study were to analyse changes in land cover and its correlation with Land Surface Temperature (LST) and to determine the direction of regional development that occurs in Sleman Regency. The methods used in this research were multispatio-temporal data analysis that contained spectral transformations and supervised classification of Maximum Likelihood on Google Earth Engine, statistical analysis of Landsat 8 OLI/TIRS imagery from 2014 to 2019, and accuracy assessments to determine the accuracy of the results. The results showed there were the increase in built-up area by 1713.374 ha from 2014 to 2019 and supported by the increase in population density of 2038 inhabitants/km2. There was an increase in LST in the converted areas from 2014 to 2019 with an estimated increase of 2.73°C. The distribution of built-up area that indicated as the direction of urban area development has a tendency to head north and northeast of Sleman regency, such as to Ngemplak sub-district, Kalasan sub-district, and Berbah sub-district. The correlation between building density and LST showed the correlation coefficient of 0.61 which was considered as a strong correlation and the determination coefficient of 0.38 also regarded as significant, based on the t-Test. The accuracy assessment was done on the land cover map, generating the overall accuracy of 88.42%.
Comparative Assessment of the Unsupervised Land Use Classification by Using Proprietary GIS and Open Source Software
Authors: Ismail Muhammad Azizol , Muhamad Ludin Ahmad Nazri , Hosni Nafisa
Published: August 2020

Mapping and investigating land use land cover (LULC) changes over a particular region is crucial for resource management, sustainability development, and holistic planning. An increasing rate of urban growth and urban sprawl could induce changes in land use as well as land transformation. However, accurate and up-to-date information about LULC is required for providing better understanding and assessing the environmental consequences of such changes. In this study, the 2017 image from the Sentinel-2A Satellite was utilized to demonstrate the land cover classification analysis in Iskandar Malaysia. Usually, land use classification analysis is conducted through proprietary GIS software. However, this decade shows the advancement in software development, thus the emerging of free/open source software in the geospatial world. Hence, to execute land cover analysis using the Unsupervised Classification technique, the proprietary GIS software (ArcGIS) and free/open source software (QGIS) were deployed. Then, the examination of accuracy assessment was carried out for the selected software. The sum of 250 random points was established for the assessment purpose. The results showed the overall accuracy for ArcGIS and QGIS were 82.80% and 80.40% respectively. The kappa coefficient for ArcGIS was 0.7395, while kappa coefficient for QGIS was 0.7094. Besides that, ArcGIS demonstrated better producer’s accuracy in the forest and agriculture land covers classification. Meanwhile, QGIS exhibited better producer’s accuracy in the built-up and water features classification. To summarize, ArcGIS and QGIS software are reliable to be used in the land cover classification.
Improved Land Cover Mapping Using Landsat 8 Thermal Imagery
Authors: Al-Doski Jwan , Mansor Shattri B. , San H’ng Paik , Khuzaimah Zailani
Published: August 2020

Detection of land cover (LC) changes allows policymakers to recognize the complexities of environmental modification and change to achieve sustainability of economic growth. As a result, recognition of LC features has appeared as an essential research dimension and, consequently, an appropriate and reliable methodology for classifying LC is occasionally required. In this research, Landsat 8 satellite data captured by Operational Land Imager (OLI) and Thermal Infrared Scanner (TIRS) were utilized for the LC classification using the Support Vector Machine (SVM) classifier algorithm. The aim of the study is to enhance classification accuracy by integrating the use of data from satellite thermal and spectral imaging. Land Surface Temperature (LST) is sensitive to the soil surface characteristics, therefore, it may be used to gather LC feature information. The classification accuracy was designed to enhance the integration of thermal information from Landsat 8’s thermal band TIRS and Landsat 8 OLI’s spectral data. In this study, Advanced Thermal Integrated Vegetation Index (ATLIVI) and Thermal Integrated Vegetation Index (TLIVI) established and revealed fairly strong correlations with the related surface temperature (Ts) by R2=0,7 and 0,65 respectively. The relationship between Ts and the other vegetation indices based on the empirical parameterization demonstrate that these two indices showed an improvement of almost 6% in the overall accuracy of the LC classification results compared to the Landsat 8 Standard False Colour Composite image as an input data using SVM algorithm.
Conceptual Framework for Walkability Assessment for Pedestrian Access to Rail Transit Services by using Spatial-MCDA
Authors: Naharudin Nabilah , Salleh Abdul Hakim , Halim Maisarah Abdul , Latif Zulkiflee Abd
Published: August 2020

Rail transit services are becoming an important aspect in enhancing mobility in a city. Its level of service is influenced by the journey from the very first to the last mile of using the transit service which refers to walking to access a transit station. Many studies had emerged in an attempt to measure walkability which most of them translated pedestrian’s preferences or perception on walking or used accessibility analysis. There could be drawbacks in these studies which are (a) only few of them had include indoor walking environment in measuring walkability, (b) there could be inconsistencies in making judgement for many criteria simultaneously, and (c) walkability is never a measure of accessibility only. Therefore, this study will attempt to (a) create a spatial model representing indoor walking environment that can be applied in measuring walkability, (b) evaluate the priorities for each of the walkability criteria by using Analytical Network Process (ANP) and (c) measure walkability of pedestrian routes and the existing rail transit stations by using GIS. The main finding of this study will be the walkability index for pedestrian routes to the existing rail transit stations in KL city centre.
Non-Destruction Method for Detecting Corroded Underground Pipe Using Ground Penetrating Radar
Authors: Shokri Nurhazimah Husna , Amin Zulkarnaini Mat , Seli Vanessa Ak
Published: August 2020

Ground-penetrating radar (GPR) is a geophysical method that can accurately map the spatial extent of near-surface objects or changes in soil. It also produce radargram of those features. The demand for underground utility mapping in Malaysia is increasing rapidly for construction and non-construction activities. However, implementation of GPR in detecting corroded underground pipe in Malaysia can considered unpopular due to less exposure and exploration. Over the time, underground utility pipe will undergo corrosion process. Thus, is it relevant to detect old corroded pipe using GPR? On this basis, the aim of this experimental study was to validate the condition of corroded pipe by comparing its radagram profiles and to evaluate the significant signal reflectivity which were tested on three different pipe condition, namely new, average and old corroded pipe. The result of GPR calibration and data on GPR were processed using Reflex 2D software. In this study, with the aid of Time-Domain Reflectometry (TDR) sensor was used to obtain the soil moisture as it is one of the biggest in fluent to corrosion activity. In the GPR method, radar antennas moved along the ground in transects (B-scan), and two-dimensional profiles of a large number of periodic reflections (A-scan) were obtained. As conclusion, these GPR datasets and soil moisture from TDR reading are evaluated and been analysed thoroughly. At the end of this paper, it is suggested that GPR is efficiently can be used to detect corroded pipe.
Assessing Hutan Simpan Ampang using GIS-based Potential Surface Analysis approach
Authors: Hussainzad Emal Ahmad , Mohd Yusof Mohd Johari , Gao Hangyu , Yu Yang Kevin Kor , Kueng Ming Norman Wong , Abdul Majid Mohammad Shafiq Bin , Xu Tengyun
Published: August 2020

This paper aims to determine potential spaces for sustainable future development at Hutan Simpan Ampang, Ulu Klang, Malaysia. The site is highly valuable due to strategic location and high availability of spaces. However, due to several landslide incidents happened in Ulu Klang over the past decades, the site is categorised as a landslide-prone area. Therefore, Potential Surface Analysis (PSA) is conducted to determine the potential areas within the site that are safe and suitable for future development. All the factors were processed in Geographic Information System (GIS) through the overlay mapping technique, combining spatial and attribute data to obtain the suitability map. The result found that the majority coverage of the site is not suitable for any future development. There are only a few coverage areas that are suitable for small scale development. However, a combination of the very high suitability area and the high suitability area expanded the opportunity for sustainable future development.
Predictive Model of Mangroves Carbon Stocks in Kedah, Malaysia using Remote Sensing
Authors: Hashim T M Z T , Suratman M N , Singh H R , Jaafar J , Bakar A N
Published: August 2020

Mangroves are recognized as an ecosystem that grow and dominate the coastal areas of tropical and sub-tropical regions across the world. They not only provide ecological and socio-economic support, but also play a pivotal role in offsetting an excess of carbon from the atmosphere. Despite the crucial roles provided by mangroves, the ecosystem has degraded at an alarming rate mainly due to anthropogenic activities. Remote sensing technology provides a new dimensional perspective in monitoring and estimating tree biomass and carbon stocks. Therefore, this study aimed at (1) estimating the carbon stocks of mangroves in Kedah, Malaysia, (2) investigating the relationships between mangrove stand parameters with spectral reflectance recorded from Landsat 8 Operational Land Imager (OLI) data, and (3) developing predictive models for estimating the carbon stocks of mangroves by combining the ground and Landsat 8 (OLI) data. For the purpose of this study, a total of 81 mangrove stand data sets measuring at 100 m × 100 m were collected throughout Kedah, Malaysia. Within the stand, seven randomly selected plots were established and all individual mangroves parameter (diameter at breast height (DBH) and height) were measured. The 81 stands were split into two independent data sets for developing and validating the models (56 and 25 stands, respectively). Multiple regression technique with least square approach was used in the model development process. From several good candidate models, a model consists of four predictive variables (bands 3 and 6, Normalized Difference Vegetation Index (NDVI) and simple ratio seems to be predicting reasonably well based on its simplicity and practicality (p≤0.001, R2 = 0.56). Validation of the model has resulted in Mallow’s prediction criterion (Cp) value of 4.28 and Root Mean Squared Error (RMSE) of 4.11 Mg/ha. The information from this study may provide useful input for future research and can be crucial tools for the government and stakeholders in future decision making for the sustainability of mangrove resources.
Lineament Assessment of Aynak Copper mine using Remote Sensing approach
Authors: Mohammadi Farid Ahmad , Amin Zulkarnaini Mat , Ahmad Anuar Bin
Published: August 2020

This research developed a new approach to extract the lineaments using Landsat, QuickBird and ALOS PALSAR satellite remotely sensed data in Aynak copper mine which is located in Kabul tectonic block and the Tethyan Copper Belt of Afghanistan. Lineaments and trench directions are not relatively studied in the study area which will bring obstacles in exploration and extraction of the mine. This research aims to extract the lineaments for studying the better trench direction in the study area. Lineaments such as faults and joints are extremely important structures that not only show the surface structure but also give us important knowledge about the subsurface of the earth. Afghanistan is a part of the Alpine-Himalayan orogenic belt which suffers from high tectonic movements in some areas, especially north-eastern and central parts which leads to the occurrence of different lineaments and unconformities. Lineaments can be surveyed and mapped using field geological survey or using satellite remotely sensed data. Satellite remote sensing data costs less and takes less time compare to field geological survey for lineament extraction. This research used Landsat 8 natural color with 2, 3, 4 band composition, QuickBird 1m resolution, and ALOS PALSAR 12.5 m satellite imagery to detect and map the lineaments in the Aynak copper mine area in Afghanistan. Geomatica software was used for lineament extraction using the Manual technique. Then the rose diagrams of the lineaments were plotted using Polar Plots extension of ArcGIS. Next, the rose diagrams derived from the two mentioned lineament extraction techniques were compared and evaluated. Global Mapper software was used for the extraction of lineaments using Visual technique and to map the rivers and ridges in the Aynak area of interest for validation of the results. Finally, the best orientation for trenches in Aynak copper mine was derived. This study found that faults and joints in the study area have a NE-SW trend and directions. This study will contribute to a better understanding of the trench direction and mineral exploration in Aynak copper mine.
Evaluation of allometries for estimating above-ground biomass using airborne LiDAR data in tropical montane forest of Northern Borneo
Authors: Loh Ho Yan , James Daniel , Fei Liew Jim Jun , Ioki Keiko , Phua Mui-How
Published: August 2020

Tropical forests play a crucial component of the terrestrial carbon pool and estimate of above-ground biomass (AGB) with high accuracy is important in quantifying tropical forest carbon stocks. There are several allometries available for estimating tropical forest tree AGB using field measurements, the choice of allometric equation is a decisive factor that can influence the AGB estimation accuracy. This study examined the use of allometric equations to accurately estimate AGB using airborne LiDAR data. The LiDAR data of Ulu Padas area was acquired using Optech Orion C200. 56 field plots were established to collect data on diameter at breast height, tree height and tree species. Field AGB was calculated from allometric equations of Yamakuraet al. (1986), Basukiet al. (2009), Chaveet al. (2005) and Chaveet al. (2014). All LiDAR-derived height metrics and variables were correlated with field AGB (R: 0.30-0.88). Based on stepwise multiple regression analysis, Chaveet al. (2014) allometry had highest model R2, explaining 81% of the variance of the field AGB. In short, allometry that includes wood density should be used in LiDAR applications on tropical forest AGB estimation.
Modelling Burglary Susceptibility – An Expert Judgement Approach
Authors: Azmy S N , Rahman M Z A , Amerudin S , Zainon O
Published: August 2020

Developing a model allow a better understanding of the nature of a complicated phenomenon. With advancement of tools and technology, model development has been applied widely to mimic the phenomena of interest, spatial or non-spatial wise, allowing a guided decision making to be made. In this paper, the phenomena of burglary vulnerability and susceptibility are modelled based on expert opinion input to create a model that imitates the expert profiling of burglary occurrences, which is dependent on individual expert wisdom and experience in handling the burglary investigation. Due to seriousness of burglary crime offences in Malaysia, especially the urban areas, a prediction model is needed to correlates the factor of crime and further estimates the spatial susceptibility to work hand in hand with other government initiatives in reducing crime. Eighteen (18) indicators and 63 sub-indicators has been identified to be significant in defining the susceptibility of burglary. Apart from input of rating and ranking of indicators and sub-indicators obtained from questionnaire distribution to expert in handling burglary, the geospatial based data were also incorporated into the model to add the element of spatial accuracy in susceptibility prediction. The geospatial data includes the distribution of burglary incidence from 2010 – 2016, the census data, the building footprint data and the demarcation area. For the collected questionnaire feedback, the procedure of Analytical Hierarchy Process (AHP) were adapted to determine the weight value considering the rating input of expert from the distributed questionnaire. The input of weight and scoring were applied to the corresponding spatial features and combined with the operation of weighted sum to yield the total burglary susceptibility of a place. The results of the model were validated with the real reported burglary frequency based on True Positive Rate correlation matrix. The model validation finds that the model have a sensitivity of 82% in classifying the burglary susceptibility of the building polygon inside the study area. However this model still requires some improvement as it is still lacking to perform the classification of incidence intensity correctly.
Implementing Sustainable Urbanization Development Using Geospatial Approach
Authors: Ismail Muhammad Azizol , Muhamad Ludin Ahmad Nazri , Hosni Nafisa
Published: August 2020

There are many factors that contribute to urbanization such as natural increase in population and migration from rural to urban areas. Failure to regulate sustainable urban growth management will arise significant issues for instances depletion of natural resources, urban sprawl, and environmental pollution. This paper is geared towards investigating and mapping land use land cover (LULC) changes in Iskandar Malaysia, specifically in Iskandar Puteri and western gate development. The satellite images from the Landsat Thematic Mapper (TM) and Sentinel 2A for the year of 2007 and 2017 were deployed in the process of quantification of changes detection by using the Supervised Classification technique. Then, the magnitude of the changes was determined. IDRISI Terrset software was used in order to predict the future expansion of the study area until 2030. Finally, this paper proposed the delineation of urban growth limit as a sustainable strategy to direct further geographical development. The modelling of urban growth limit was based on the socio-economic and bio-physical factors. The findings and analysis in this paper have proven how prominent geospatial technology can be deployed in implementing sustainable development. The generated results have important policy implication for urban planners, stakeholders, and industrial players.
Review of Spatial Model to Assess Suitability of Affordable Housing Based on Demand Criteria
Authors: Zamri Zur’ain , Tarmidi Zakri , Adi Maimun Nurul Hana
Published: August 2020

Affordable housing has become essential, especially in developing countries, to cater the people needs on house. Most of the affordable housing focus is on providing house at affordable prices, but the locations of these affordable housing often not suitable with demand of people. Several initiatives were conducted to identified the demand of people, and the suitability of their houses with their demand. These model has different purpose, and lack of spatial element. Some model defining the people preference in order to choose a suitable for their house, while other model focusing on goals that relate to the site suitability of house that involve several cities. This study focus on integrating spatial information and analysis to assessing the suitability level of affordable housing in Malaysia. The assessment model consists of four main indicators; suitable site of affordable house, demographic factor, suitability house according neighbourhood context, and commute distance. With proper assessment, a better location can be defined, or more suitable facilities can be implement in the future in surrounding area of these affordable housing.
The use of geospatial data from GIS in the quantitative analysis of landslides
Authors: Ibrahim Muhammad B , Harahap Inrda S H , Balogun Abdul-Lateef B , Usman Aliyu
Published: August 2020

This study was conducted in order to compare two advanced technique used in establishing landslides susceptibility maps. The study considers a method of landslides analysis using the analytical hierarchy process (AHP) to check the occurrence of landslides in the study area through the establishment of a landslides susceptibility map based on the causative factors of landslides in the area. To further check and validate the process, it was compared with a more recent approach that is the soft computing (machine learning) technique. After the comparison, the enhanced analytical hierarchy process performed wonderfully well but not better than the machine learning method of analysis. Using the AHP methods, it was able to identify rainfall precipitation to be the major trigger mechanisms while 12 other conditioning factors were also identified. From the results obtained, it was observed that a good portion of the study area can be said to be susceptible to landslides. The analysis suggested that though the slides were fully triggered by rainfall precipitation, other factors such the geological and hydrological conditions facilitate the rapid occurrences of the phenomenal landslides in the study area. Validation was carried out by comparison of obtained results with inventories.
A spatial analysis of the relationship between socio-demographic characteristics with burglar behaviours on burglary crime
Authors: Chiew Ling Sie , Amerudin Shahabuddin , Yusof Zainab Mohamed
Published: August 2020

In recent years, the criminal and violent behaviour has become a national crisis in Asia and many pieces of research have been implemented to determine the criminal phenomena and the pattern of a crime occurred. Among the occurrences of crime incidence, the burglary crime was the most regular type of crime that commonly occurred in the urban area after the motor vehicles theft in Malaysia. Normally, the crime incidences were affected by several coinciding variables such as the offender’s behaviour and motivation, the physical environment factor and the victim’s behaviour. Overall, there are seven fundamental socio-demographic variables were determined and applied to investigate the pattern and motivation of burglar commit a crime incidence. The results showed that the burglary crime incidences were affected by the socio-demographic variable and burglar behaviour by using the spatial analysis method.
Spatio-temporal assessment of Aerosol Optical Depth from Himawari-8 satellite data over Malaysia
Authors: Kamarul Zaman Nurul Amalin Fatihah , Kanniah Kasturi Devi
Published: August 2020

Aerosols, particulate matters and air pollution are significant atmospheric issues in the Southeast Asia (SEA) countries particularly Malaysia. Despite their importance, data to investigate their spatio-temporal variation, estimating their abundance and modelling the trend are not widely available due to financial constraints and technical expertise. Remote sensing data are alternative solution to the limited data available from ground stations. One of the latest remotely sensed Aerosol Optical depth (AOD) data available is from Himawari-8 satellite that provides high temporal resolution data (every 10 minutes) at moderate spatial resolution of 5 km. Nevertheless, the robustness of these data for the tropical region has not yet been validated yet. This study aimed at assessing the performance of Himawari-8 AOD L2 product by (i) comparing its absolute AOD values against AOD retrieved from AERONET stations and (ii) analysing the spatial and temporal patterns of the AOD data. The AERONET data were averaged for ±5 min of the Himawari-8 overpass and matched to each other using statistical measures i.e. Correlation, Root mean square error (RMSE), Relative bias (RB) and Mean Absolute Error (MAE). Preliminary results of the analysis provided a coefficient of determination (R2) value = 0.31, RMSE = 0.16, and MAE = 0.15. The Himawari-8 AOD product is found to be overestimated the AOD values by 24.19%. Nevertheless, Himawari-8 AOD L2 product is able to exhibit similar spatial and temporal patterns compared to other remotely sensed AOD data such as that of MODIS. The high temporal resolution of Himawari data will facilitate frequent monitoring of air pollution in this region.
Monitoring Groundwater Depletion Due to Drought using Satellite Gravimetry: A Review
Authors: Mohamad N , Ahmad A , Din A H M
Published: August 2020

Groundwater plays a vital role in the global water cycle as a source of water for human use in daily life. The problem of groundwater depletion attracts researchers to understand the phenomenon of terrestrial water storage (TWS) and the primary technique used to monitor changes in groundwater mass in the subsurface. Accurate quantification is subtle due to the weakness of gravity measurement methods, which cover a wide range with high precision. A global evaluation of improvements in groundwater storage used a calculation tool that may involve temporal differences in TWS. The Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow-On (GRACE-FO) satellite missions were able to monitor changes in water mass in the basin and calculate changes in water levels by measuring gravity variations and quantifying groundwater tables at 1-micron precision. This paper aims to discuss GRACE, GRACE-FO and hydrological variables in the monitoring of groundwater depletion during the drought season. This paper presents an estimation technique using satellite gravimetry and hydrological methods, as well as a study of several case studies in central Amazon (Brazil), Murray-Darling (Australia) and Mongolia Basin. Previous observations, including TWS-hydrological variables, trends in groundwater depletion and drought intensity, have been discussed as a vital outcome of the paper as a whole.
Deep Learning-Based Water Segmentation for Autonomous Surface Vessel
Authors: Mohd Adam Muhammad Ammar , Ibrahim Ahmad Imran , Abidin Zulkifli Zainal , Mohd Zaki Hasan Firdaus
Published: August 2020

Visual-based obstacle detection from an autonomous surface vessel (ASV) is a complex task due to high variance of scene properties such as different illumination and presence of reflections. One approach in implementing the task is through extracting waterlines to enable inferring of vessel orientation and obstacles presence. Classical computer vision algorithms for detection holds limitation in robustness and scalability. With recent breakthroughs in deep neural network architectures, vision-based object detection is seen to obtain high performance. In this work, the deep learning models based on Convolutional Neural Network (CNN) to implement binary semantic segmentation is studied. This architecture identifies each pixel to water and non-water classes. In purpose of benchmarking models, Fully Convolutional Network (FCN), SegNet and U-Net are trained on a publicly available dataset, IntCatch Vision Data Set (ICVDS), to evaluate the performance. From the experiments carried out, quantitative results show effectiveness of the models with accuracy all above 95.55% and lowest average speed of 11 frames per second. To improve, pre-trained networks (VGG 16, Resnet-50 and MobileNet) are used as a backbone, obtaining an improved accuracy above 98.14% with lowest inferring speed of 10 frame per second. Using the developed ASV, new dataset of 143 images called Malaysia ASV Dataset (MASVD) is collected, labelled and made publicly available. The trained models are tested with the newly collected dataset obtaining accuracy of 75%. The high accuracy performance shows potential for the models to be employed for collision avoidance algorithm in ASV navigation.
Estimated relative permittivity of contaminated laterite soil: An empirical model for GPR waves
Authors: Ghazali Mimi Diana , Zainon Othman , Mohsin Rahmat , Idris Khairulnizam M. , Mustafa Nordhalia
Published: August 2020

Estimated relative permittivity performed on soil is essential for forecasting the performance of Ground Penetrating Radar (GPR) in an in-depth manner. This study investigated and verified the empirical relationship model between relative permittivity and volumetric water content in soil to predict the relative permittivity of contaminated laterite soil. In this study, a 24-hour measurement involving 800 MHz shielded antenna GPR was carried out in a concrete simulation field tank filled with Terap Red soil (1.5 m x 2.6 m x 1.5 m) at UiTM Perlis, Malaysia. Embedded moisture content probe was simultaneously measured to monitor the response of volumetric water content in contaminated soil in order to formulate an empirical relationship between relative permittivity and moisture content. The GPR data were pre-processed and filtered with Reflexw 7.5, while regression analysis was performed to evaluate the empirical relationship model. The model outcomes were retrieved from a number of cross-validation schemes, including correlation analysis (R2), root mean square error (RMSE), and calibrated Agilent Technologies Automated Vector Analyser (VNA). A third-order polynomial for analysis of variance (ANOVA) best fitted the model with positively strong correlation (R2=0.989, N=24, P < 0.01) and RMSE 0.003< RMSEpredicted < 0.19. Verification of the proposed model using calibrated VNA displayed exceptional agreement between 0.06% comparisons.
Assessing the economic value of carbon sequestration in Taman Negara Pahang
Authors: Hussainzad Emal Ahmad , Mohd Yusof Mohd Johari
Published: August 2020

Aesthetic benefits are not enough. Authorities need to be presented with economic benefits as well to make decisions in favour of forests and help them conserved or expanded. Thus, this paper aims to evaluate the economic value of carbon sequestration in Taman Negara Pahang (TNP), Malaysia, a national park with an extensive forest area. The study area covers 247,700 hectares of the Pahang State. The study uses a Geographic Information System (GIS) method of Normalized Difference Vegetation Index (NDVI) to identify the density of the forest across the study area. Consequently, by using the NDVI results, the carbon sequestration in TNP and its economic value were calculated. As a result, the research found that the potential of carbon storage or sequestration in TNP was 142,560,513 tonnes CO2. The economic value of which was worth RM2,637,369,490.50. The results of the GIS calculation were more accurate than the conventional method. It was due to the reason that they were based on evaluating density on a smaller scale of 900m x 900m (81ha). The results were aligned with previous studies pointing out higher density areas holding higher economic values. The study results can be used to convince Malaysian authorities to make wise decisions about such forests as they worth billions of Ringgit Malaysia.
An Approach for the Retrieval of Land Surface Temperature from the Industrial Area Using Landsat-8 Thermal Infrared Sensors
Authors: Dahiru M Z , Hashim Mazlan
Published: August 2020

The thermal imagine provides data with synoptic coverage for investigating thermal information from hot sources for detecting, mapping energy loss from the industrial area. This study attempts to retrieved heat loss from the industrial area using Landsat-8 TIRS experimented at an industrial area of Pasir Gudang, Peninsular Malaysia, the main objective is to investigate the sensitivity of Landsat-8 TIR for detecting industrial thermal energy within the various range of targets of different temperatures. An estimated heat map with absolute surface temperature values is the final output. Apart of the pre-processing of Landsat-8 TIRS data, data are processed for the retrieval of land surface temperature, then subjected to a downscaling process to final 30 x 30 m pixels, hence enable to merge with all Landsat-8 bands for visualization and validation of results. The split window algorithm (SWA) is used for the temperature retrieval from band 10 and 11, with other driven parameters. The Multiple Adaptive Regression Splines (MARS) model for spatial downscaling was adopted in this study. The generated thermal energy map was then validated over selected targets in the field and compared to corresponding downscaled MODIS LST product (MODIS11A2). TIR bands applied with SWA generated 13.7°C temperature dynamic range from 22.35˜51.36° C in comparison with MODIS LST product values range from 27.17 ˜ 37.65°C). Results indicated good agreement between the generated thermal energy map with the in-situ validations (RMSE=0.43 °C). It is therefore concluded that derived Land surface temperature map derived is suitable for study industrial thermal environment at 1:50,000 ˜ 100,000 scales, adequately to be used for environmental impact assessment.
Integrated Facility and Assets Management using GIS-Web Application
Authors: Saiful Bahri Mohd Aizat , Abdul Maulud Khairul Nizam , Rahman Muhammad Amartur , Ridzuan Oon Aslinda Oon , Che Hashim Che Hafify
Published: August 2020

Facility and assets management has to become a crucial practice in the era of income generation in an education institution, the need to provide better service to the client/student or public as well as minimizing the maintenance cost has become a challenge to the institution. The aim of this paper is to develop a web GIS to store, manage, and manipulate the data in order to maximize the use of space and assets as well as making sure the assets is in good condition. Also, to determine the higher value assets to optimize its use for income generation. The methodology of this study is asset and space data acquisition to store in the GIS database and integrate with another native database (Structured Query Language-SQL) to ensure the efficiencies of data updates. The findings of this study focusing on the capabilities of the GIS to manage, store and manipulate as well as display all the online data with such query, searching and analysis widget in the application. In conclusion, asset and space management in university with the modules included in the application has become useful for personnel and assets officials to query, searching and make analysis for preliminary planning and decision making.
Spatiotemporal analysis land surface temperature in relation to earthquake occurrence around the cimandiri fault
Authors: Huda Diki Nurul , Supriatna  , Ash Shidiq Iqbal Putut , Taqyuddin
Published: August 2020

Cimandiri Fault is one of the faults that have high tectonic activity. Several earthquake events around the Cimandiri Fault have caused impacts and losses on humans. Efforts to detect earthquake events need to be done as disaster mitigation. Detection of earthquake events in this study by looking at deviations in surface temperature. This study was conducted to investigate the relationship between changes in land surface temperature (LST) in relation to the earthquake that occurred on 7 July 2018 (ML = 4.73) and 11 October 2018 (ML = 3.77). Landsat 8 satellite imagery are used in this study to get the value of the land surface temperature using the LST algorithm. To find out the deviation that occurred researchers used a statistical test x ± σ with a 66% confidence level and compared with the average LST for five years. The results of the study are an increase in land surface temperature due to the earthquake occurrence on July 7, 2011, an increase in surface temperature of land was 6.56 oC on the day before the earthquake, and October 11, 2011, there was an increase of 7.02°C the day before the earthquake.
Comprehensive Spatial Criteria and Parameters for Sustainable Landfill Site Selection
Authors: Ahamad M S S , Ahmad S Z
Published: August 2020

A landfill site is an important facility that must be occasionally evaluated when its demand gets high with the increment of generated waste. The task of selecting new landfill sites becomes difficult when there is a shortage of land and time available. It requires tedious planning decision about identifying the suitable sites. The complication will proliferate when there are various criteria that need to be apprehended. In Malaysia, the procedures for landfill site selection (LSS) is provided in the National Strategic Plan for Solid Waste Management (NSPSWM). It specifies the mitigation measures to be followed, but the restrictions on the appropriateness of suitable new landfill sites were not comprehensively deliberated. The criteria for the site suitability problem was not distinctly characterized as prescribed by the local Environmental Impact Assessment (EIA) guidelines. The significance of selecting proper landfill sites must encompass the physical characteristics, environmental impact, economic and social acceptance for the necessity of the sustainability community life. From the works of literature, this study introduced seventeen (17) universally adopted spatial criteria categorized under the environmental, physical and socio-economic (EPSE) characteristics. They were successively assigned with the relative weights and standard parameters. The EPSE criteria can assist in improving the regulated LSS policy currently available in the local NSPSWM and EIA guidelines. This will ascertain that future landfill site will be sustainable, safeguard public health, ensuring minimal impact on the environment, and provide long term isolation of the solid waste deposited.
RFID Monitoring System and Management on Deer Husbandry
Authors: Anak Rechie Rizzo Mungka , Kassim Murizah , Ya’acob Norsuzila , Mohamad Roslina
Published: August 2020

This research presents an RFID Monitoring System and Management on Deer Husbandry. The design of an RFID system monitoring on a deer farm that used the RFID Mifare tag at its 13.56 frequencies and database system is presented. The deer in a farm in Malaysia are hardly monitored with technological assistant such as the tagging system is not well supported. Thus, deer husbandry farm is hard to monitor especially on the management of deer biodata where a fast retrieved for a specific deer need to be located and inspected. Today, deer farmers faced a slow process and lack of Quality of Services. This research presents a designed system that the RFID able to scan the deer and data is captured in a short amount of time to a database. Every deer is designed with its monitoring ID based on group by ages, weight, breed, and its descendant. The design of deer farm management and monitoring system is developed based on hardware, software, and data analysis on deer on a farm that is presented on the web and mobile application. The result presents a success designed for prototype system on mobile application and data from the RFID tag deer is presented in gender, species, and year of birth. Analysis has been done based on a deer farm in Kulim Kedah and graphical outputs are presented. A total of 54 deers are successfully captured, monitored, and manage where Blynk and FavorIOT platform is designed. This research is significant to deer husbandry farmer in Malaysia where deer just become a new market in Malaysia.
A 2-way geo-crowdsourcing approach in flood relief coordination and distribution
Authors: Idris N H , Ishak M H I
Published: August 2020

Over recent years, the use of Web 2.0 social platforms and geo-crowdsourcing in disaster management and emergency responses has become common. The emergence of various communication channels has led to abundance of information, but it cannot be used directly by the first responders and flood volunteers in their responses for several reasons. This paper proposes a 2-way geo-crowdsourcing framework to centralise the flood relief distribution channels using mobile geolocation technology. The framework is anticipated to be suitable for use by flood volunteers, including NGOs, private agencies and ad-hoc volunteers, to systematically distribute the relief items to the victims. The lessons learnt from the NGOs previously involved in the volunteer efforts in the 2014 Kelantan massive flood were discussed and become the basis of this framework. The framework could be applied for other studies that seek to support a 2-way communication between netizens and the authorities using a geo-crowdsourcing platform.
Drone Technology as A Modern Tool in Monitoring the Rural-Urban Development
Authors: Yunus Asniza Md , Hamzah Abd Halim , Md. Azmi Fatin Afiqah
Published: August 2020

The current practice of monitoring the rural-urban development in Malaysia is mainly based on conventional method that has limitations. This suggests that a modern technology, both hardware and software could be investigated to examine the application of drone technology and the appropriate systems namely Rural Grid System and Characteristics of Rural Malaysia System (CHARMs). An extensive literature review has been conducted to address the weaknesses of conventional method, the potential of drone technology in monitoring rural urban development, as well as the challenges of drone technology in term of limitation usage, pilot and auto pilot, and the rules and regulations. The finding shows that drone technology has its own strengths and weaknesses but its role in monitoring the rural urban development should be given priority. It is hoped that this paper can be a guideline for government agencies like local authorities, Department of Director General of Lands and Mines, and also private sector such as developer and investor who partake and apply modern monitoring through technological innovation notably in the land development process and site development progress.
Mapping of Affordable Housing Sustainability Level from Environmental Geospatial Aspect in Gombak, Selangor
Authors: Ismail Nurul Aini , Tarmidi Zakri , Mohamed Razali Muhammad Najib , Adi Maimun Nurul Hana , Hassan Noordyana , Md Nasir Ahmad Nabil , Sidek Akhmal , Che Ya Nik Norasma
Published: August 2020

Housing is important since it provides security, privacy, neighbourhood and social relations, status, community facilities and services, access to jobs and control over the environment. To enable everybody to afford a house, affordable housing was introduced and developed throughout the world. But there’s an issues with current affordable housing development, especially the sustainability of these affordable housing, especially from environmental aspects. Several initiatives have been done to improve current sustainability, but current initiatives lack of spatial indicators to assess the sustainability level, from environmental aspects. This study focus on assessment of sustainability level from environmental aspect. The assessment method consists of 3 main components; the green space availability, proximity to water features, and proximity of flood areas. The results show that most of the affordable housing in this study area was less sustainable in term of environmental aspects. From this results, proper planning and development to sustain the affordable housing surrounding area can be done by government, or other stakeholders in the future.
Earthquake Social Vulnerability Assessment Using Entropy Method
Authors: Jena Ratiranjan , Pradhan Biswajeet
Published: August 2020

Earthquake is the most devastating event in the current time. Given the probability of highly dangerous future events, risk estimation should be given focus by using the limited and freely available data to predict future vulnerable scenarios of an area that observe the involved uncertainty in the analysis. However, vulnerability assessments should be prospective and based on expected scientifically acceptable events. Therefore, we applied a valuable weight calculation approach called entropy to produce a social vulnerability map for a particular city. We used the population data, including educated and non-educated people and household information, to develop the earthquake social vulnerability map. We used entropy to evaluate the actual weight and produce a good quality map because of some difficulty in the fuzzy synthetic evaluation method for factor weight calculation and relationship ignorance among layers. Results showed that approximately 6% of the population is under very high vulnerability and around 14% are under high vulnerability areas in Banda Aceh City. The developed model is accurate by considering the inventory earthquake vulnerability map. The applied method was favorable, and the process provided good evaluation results, which was reasonable for earthquake hazard, vulnerability, and risk assessment.
GIS Based Multi-Criteria Decision Making for Identification of Important Plant Areas: A Case Study in Johor, Malaysia
Authors: Hamidah M , Mohd Hasmadi I , Chua LSL , Lau KH , Yong WSY
Published: August 2020

Important Plant Areas (IPA) is a concept developed by Plantlife International to identify sites of exceptional botanical importance for conservation priority. The three main criteria for IPA are presence of threatened species, exceptional botanical richness and threatened habitats. Studies have shown that scoring method based on expert judgement is widely used in IPA identification as it is the easiest to understand and implement. However, reported drawbacks were uncertainty in score judgement and effect of the weighted score on each criterion was not understood. Therefore, a robust scoring system was needed to overcome this obscurity. The current study utilized Kepong Herbarium records, GIS-based multi-criteria decision making and analytical hierarchy process to identify IPA in the state of Johor, Malaysia. These techniques were considered to be effective tools in providing decision support for spatial planning aimed for plant conservation in Malaysia.