bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantitative Morphometric Analysis Using Remote Sensing and GIS Techniques for Mandakini River Basin
Authors: Qadir Abdul , Yasir Mohammad , Abir Ismail Ahmad , Akhtar Naseem , San Lim Hwee 
Published: August 2020

Abstract
The current research in the State of Uttarakhand in Rudraprayag argued that the analysis of the morphometric drainage parameter is more appropriate than traditional approaches with a remotely sensed information and GIS-based approach. Various linear, aerial and relief aspects were considered to analyse study area morphometry and the digital elevation model (DEM) and catchment area slope map were created from 30 m resolution ASTER data. The drainage patterns were mainly dendritic to sub dendritic. The study area’s slope was divided into five ranging from 0° to 77°. The study area’s stream order ranged from 1st order to 7th order. The variation in the stream length ratio could be due to the disparity in slope and topographical conditions. Geometric characteristics in the region suggest that the area appeared to have an extended shape with an elongation ratio of 0.76 and less circulatory shape with a circulatory ratio of 0.47 suggests the varied homogenous geological and texture ratios preferred for its high texture ratio of 28.77 disfigured complex lithology. In topography and geographic growth, the range of the bifurcation ratio in the catchment area was between 3.84 and 5.30. The drainage level was medium at 2.34 km2. The drainage texture was 38.10 demonstrating the nature of lithology.
SmartKADASTER Interactive Portal (SKiP), is it fit for purpose?
Authors: Halim N Z A , Chan K L 
Published: August 2020

Abstract
The Department of Survey and Mapping Malaysia (JUPEM) developed SmartKADASTER Interactive Portal or SKiP in order to provide a multipurpose cadastral survey information-based platform for accurate spatial analysis. Whether SKiP is viable for its purpose is still undetermined. Therefore, this paper highlights the methodology of assessing the usability of SKiP. A usability test was conducted by using the System Usability Scale or SUS. Fifty-nine participants from various public and private agencies, participated in the assessment and were categorised as Existing, New and Potential users, as well as Familiar and Not Familiar with the spatial analysis concept. The overall SUS score for SKiP is 69.8, which concludes that the usability of SKiP is fit for its purpose and can be perceived as marginal high for acceptance under the Acceptability Range. The SUS score was subsequently extracted to determine additional information on the Learnability and Usability components that resulted as 57.8 and 72.8, respectively. The SUS score implies that SKiP is an excellent platform for Usability and perceived good for Learnability, within the Adjective Ratings. Further analysis of the SUS scores suggests that regardless of which category the users were grouped, those who are familiar with the spatial analysis concept are likely to score higher. The correlation efficient supports the SUS score result as the Learnability components of SKiP requires further improvement. It was also found that the usability test participants are distinct as Passively Satisfied users. In line with the overall SUS and Nett Promoter Score (NPS) scores, additional mitigation and interventions are needed to convert SKiP Passively Satisfied users to Promoters and reduced Detractors. Recommendations from the study are highlighted in this paper to value-add SKiP in the next phase while the prominence on ease of doing the spatial analysis is emphasised.
Geospatial Technology Methods for Carbon Stock Assessment: A Comprehensive Review
Authors: Dahy Basam , Issa Salem , Ksiksi Taoufik , Saleous Nazmi 
Published: August 2020

Abstract
Carbon stock estimation is becoming an important component for fighting against global warming. Assessment of biomass can give an idea of the amount of CO2 that can be removed from the atmosphere by forests and other plantations. Geo-Spatial technologies, including Remote Sensing (RS) and Geographic Information Systems (GIS), offer the mean to enable rapid assessment of terrestrial biomass over large areas in a timely and cost-effective manner, allowing for the estimation of above and below ground biomass. Hence, the deployment of an integrating RS-GIS approach for precision carbon management is of high significance. This article provides a review of various RS and GIS techniques used in forest aboveground biomass mapping and monitoring as well as highpoints the associated challenges and opportunities. The review concluded that the use of RS and GIS in large-scale forest aboveground biomass assessment provides a sound alternative when compared to the use of conventional approaches. It was noted that the freely available moderate resolution optical sensors could be used reliably for estimating forest carbon stock. Furthermore, the integration of multi-sensor data in a GIS environment increased the accuracy of the estimation results. This study helps contributing to the topic in a way that it illustrates the growing developments using geospatial technologies by identifying most sensitive RS variables to measurable biophysical parameters. Furthermore, it demonstrates the usefulness of geospatial technologies for estimating terrestrial carbon sequestered. Finally, gaps, limitations and the need for further studies are underlined.
Measuring the Magnetic Impact of Economic Agglomeration for Industrial and Business Environment through Spatial Mapping.
Authors: Che’Man Noordini Binti , Bin Jamaluddin Amirul Afiq 
Published: August 2020

Abstract
Smart City concept is known for years and it always relate with the use of smart technologies as it could manage energy efficiently. However, what if there is a way in managing energy efficiently without fully relying on smart technologies which are quite expensive. If we look in a bigger context, a proper management of land use and spatial information could also change the amount of energy used and ensure the maximum allocation of resources efficiently. This research will examine the agglomeration of industrial and business environment within Pengerang District through GIS spatial analysis. Hot Spot analysis were used in giving a visual representation of agglomeration for a better understanding on what is happening in Pengerang District. Findings shows that industrial and businesses are clustering at Bandar Penawar and Pengerang. The industrial sector includes classes mainly of mining and quarrying, manufacturing, and warehouse industry. While analysis on business sector indicate higher number of wholesale and retail, services, and accommodation. The clustering pattern of all of the mentioned class were also identified.
A deep learning approach to ship detection using satellite imagery
Authors: Stofa Marzuraikah Mohd , Zulkifley Mohd Asyraf , Muhammad Zaki Siti Zulaikha 
Published: August 2020

Abstract
Automatic ship detection on remote sensing images is one of the important modules in the maritime surveillance system. Its main task is to detect possible pirate threats as early as possible. Thus, the detection system must be accurate enough as it plays a vital role in national security. Therefore, this paper proposes a deep learning approach to detect the presence of a ship in the harbour areas. DenseNet architecture has been selected as the core convolutional neural network-based classifier, where various finetuning has been done to find the optimal setup. The three hyperparameters that have been fine-tuned are optimizer selection, batch size, and learning rate. The experimental results show a success rate of over 99.75% when Adam optimizer is selected with a learning rate of 0.0001. The test was done on the Kaggle Ships dataset with 4,200 images. This algorithm can be further fine-tuned by considering other types of convolutional neural network architecture to increase detection accuracy.
Application of thermal imaging for plant disease detection
Authors: Hashim I C , Shariff A R M , Bejo S K , Muharam FM , Ahmad K , Hashim H 
Published: August 2020

Abstract
The effects of plant diseases on agricultural production worldwide contribute to significant economic and post-harvest losses. To maintain the sustainability of the farming sector, the early detection of plant and pathogens is essential. Non - destructive methods for tracking the health conditions of plants in real-time applications are among the most realistic and feasible in this regard. Owing to non - destructive methods and non - contact measuring devices, thermal imaging advancement has become an essential technique in all fields. Thermal imaging operates by emitting infrared irradiation in all materials. The method, therefore, uses radiation to create an image of the thermal distribution of the body surface. This approach is useful for all areas where the difference in temperature helps in the area/object analyses. Therefore, this paper briefly explores the potential for thermal imaging to be used to detect plant disease in the control area and the field.
Modelling Catchment Land Use Changes against Water Yield with Satellite Multi-Temporal Data
Authors: Baiya Babangida , Hashim Mazlan 
Published: August 2020

Abstract
Land-use changes are the main issue which affects the availability of water resources. Water supply is the leading ecosystem service, directly influence the sustainable development of the social economy and ecological systems. This study model the effects of land-use changes in respect of water yield, using Soil water assessment tools (SWAT) model in Sg. Layang catchment, Johor, Malaysia. Changes in Land-use for the period of 2000-2005, 2005-2010 and 2000-2010 obtained through post-classification comparison of Landsat 7 ETM+ data acquired in 2000, 2005 and 2010 using maximum likelihood classifier. The results indicate a rise in water yield, as a result of forest decline as well as an increase in agricultural activities and urbanization. The changes in the forest are found directly proportional to water yield (R2 > 0.85, p < 0.001). It is therefore concluded that the satellite multi-temporal land use changes within the catchment are paramount for monitoring the corresponding water yield in the area. These land use changes to water yield are crucial to assist authorities to create a balance between environmental protection and urban development for sustainable management of water resources.
Seismic vulnerability assessment for buildings typology using DEMATEL approach
Authors: Jena Ratiranjan , Pradhan Biswajeet 
Published: August 2020

Abstract
During the last two decades, the severity of high magnitude earthquakes rose to a vast extent. A large amount of damage due to such devastating events reflects poor construction planning. Before the 2004 event in Indonesia, we assume poor construction planning with indigent seismic resistance in the Northern Sumatra. However, this event affected the modern buildings in Aceh province. Therefore, authors have categories all the building types into a catalogue. The typologies considered are hierarchical, construction material, structural irregularities, structural system, building height, and maintenance quality. We applied the Decision Making Trial and Evaluation Laboratory (DEMATEL) method to prepare the vulnerability map using the typology of the building. In addition, the results show that the prepared approach is effective and useful for seismic vulnerability assessment.
Determining variations in rail public transport access using GIS in Klang Valley City, Selangor, Malaysia
Authors: Syukri Mohd Sahrul , Mohd Safian Edie Ezwan , Burhan Burhaida 
Published: August 2020

Abstract
About 75% of urban areas in Malaysia have an excellent public transportation system. Malaysian Intelligent Transport System (MITS) Blueprint 2017 – 2022 is developed and mentioned public transport as the infrastructure for traffic management and the Fourth Industrial Revolution (4IR) will change the global landscape of public transportation. The primary purpose of this paper is to use Geographic Information Systems (GIS) for identifying spatial accessibility to transport in Klang Valley, Selangor supported the movement of the walk-distance analysis techniques. A geospatial database was created that has the coordinate of urban public transport (railway mode), home residence distribution, and road networks. Accessibility index tool and geoprocessing by overlay analyses were selected because of the analysis tools for this paper. The paper results indicate that urban public transport in the Klang Valley districts of Selangor has fewer registered railway line stations. Several areas of Klang Valley region have low accessibility based on z-score either dispersion or clustering pattern to public transport because they fall outside the space-distance service area for every terminal. Local transport planners in Klang Valley may use the created application to allocate public transport in low access areas.
Land Cover and NDBI analysis to map built up area in Iskandar Malaysia
Authors: Yasin Muhammad Yazrin , Abdullah Jamalunlaili , Noor Norzailawati Mohd , Yusoff Mariney Mohd 
Published: August 2020

Abstract
The growth of Iskandar Malaysia as a regional development corridor is inescapable large and rapid. The study area has been transformed from predominantly agricultural and forest land prior to 1990s into the second largest and third most urbanized area in peninsular Malaysia. The aim of this paper is to map Iskandar land cover change from 1991 to 2019 using sequential Landsat multi-spectral images with Normalized Difference Building Index (NDBI) analysis to assess spatio-temporal urban built up and its pattern. Accuracy assessment of kappa coefficient is used to measure the accuracy of classification. Research has proved a significant rapid land cover change and a vast transformation of agricultural and forest land into low density urbanized area scattered in Iskandar. A rapid land cover change of regional development corridor has significant influence on urban expansion especially to their periphery.
Development of an Android Application for Smart Farming in Crop Management
Authors: Athirah R N , Norasma C Y N , Ismail M R 
Published: August 2020

Abstract
Agriculture technologies have shown potential to improve agriculture management. This awareness has attracted researchers to develop technologies for farmers to ease their daily routine and also to reduce cost of labor and increase the yield production. Smartphone is one of the gadgets that can be useful in agriculture because of its useful functions, portability and affordable. It helps users to find locations, access information and capture images and sound. Smartphone functions can be combined to build versatile mobile agriculture applications. These helps to deliver information about crops and management needs. This paper develops an Android application for smart farming in crop management known as Padi2U. Padi2U is a mobile application developed to help farmers in their paddy field management. The application is developed using Master App Builder, a software that is used to create mobile applications. This application contains information about PadiU Putra paddy variety, agriculture agency, sites information, planting schedule, drone images, paddy disease, pest, weed, weather forecast, yield information and farmer report. All information is described in the native language of the farmers that is the Malay language. Final results of this project is the mobile application which will is useful to manage crops and improve the management. The same method can be applied to different crops in the future.
Earthquake Risk Assessment Using Integrated Influence Diagram–AHP Approach
Authors: Jena Ratiranjan , Pradhan Biswajeet 
Published: August 2020

Abstract
Indonesia is located at the joint situation of four major world tectonic plates in the Pacific Ring of Fire. Mostly, the coastal regions of Indonesia are highly prone to several natural hazards, such as tsunamis, earthquakes, and volcanic activity. The major earthquake incident in the country was the 2004 earthquake in Aceh, whereas a major volcanic eruption was the Mount Merapi volcanic eruption in 2010. With the present advancement of knowledge regarding the existing hazards, we acknowledge the importance of vulnerability and risk in monitoring and mitigating earthquake hazards. However, to date, a specific effort is unavailable for assessing the risk of earthquake hazards that will cover the city-level in Indonesia. Moreover, a comprehensive profile for risk assessment has yet to be created for small-scale urban areas. Few studies have been organized in Indonesia on city-scale risk assessment. Therefore, we attempt to fill this gap by calculating the risk percentage of Banda Aceh City by determining its conditioning factors and analyzing its variations spatially. We used an influence diagram approach and considered all the factors that affect the risk in Banda Aceh. Results show that only the central parts and some parts in the surrounding areas are under high risk compared with other locations. We validated the results using inventory earthquake events and the results of previously published articles.
The Impact of Microrelief Forms on Mobility of Terrain Vehicles
Authors: Rybansky M , Dohnal F , Rada J 
Published: August 2020

Abstract
When deploying off-road vehicles in military and rescue operations, it is necessary to analyse the characteristics of the terrain, its segmentation and obstacles, that can significantly eliminate the movement of this technique. The mobility of off-road vehicles depends on many factors such as terrain relief, soil, vegetation, water, road network, settlement unit structure, meteorological conditions, etc. The goal of this paper is to identify the critical micro-relief forms in the selected test area, which can be important for the transportation analyses and cartographic visualization, especially for the military and rescue operations management during the crisis situations and natural disasters such as floods, fires, storms, military operations, etc. Both of the relief parameters and technical vehicles parameters were considered for the cross-country movement analysis to predict the GO, SLOW GO and NO GO areas as a part of crisis management support.
Landslide Possibilities using Remote Sensing and Geographical Information System (GIS)
Authors: Yaa’cob Norsuzila , Abd Rashid Zarith Nur Atikah , Tajudin Noraisyah , Kassim Murizah 
Published: August 2020

Abstract
There are a lot of landslides occur in Malaysia and one of the landslide prone areas in Malaysia is Ulu Kelang. Integration of satellite remote sensing data which is called ArcGIS software is one of the applicable software to detect the landslide mapping and identification of high landslide risk in a certain area. Since 1993, several landslides have been reported in Ulu Kelang, Malaysia. These landslides would cause the property damaged and economic losses. The landslides cause which are geological covering the aspect such as rainfall, hilly areas, highland areas, morphological, physical and human causes. These are the major role in inducing the landslides in the study area. The objective of this research is to analyse and validate the data of the soil moisture index (SMI), temperature index (LST) and water index (NDWI) from the remote sensing Landsat Images with the electronic tool devices. There are two methods for this research paper which are by using a remote sensing and a ground-based measurement. The remote sensing software is ArcGIS. The U.S Geological Survey, USGS in coordination with NASA operates and distributes data from Landsat satellites and provides access to the space-based land remote sensing data. The ground-based measurement method, the electronic tool devices are called as LCD Soil Tester Meter and Digital Temperature Humidity Time Display. These devices are to detect the moisture of the soil, calculate the surrounding’s temperature & humidity. Also, the rainfall data has been taken for supporting the water index information. The results of the three specified parameters; soil moisture, temperature and water index; SMI, LST and NDWI shown the more moisture of the soil, the more the tendency of the landslides to occur. This research founds out that the lower the temperature, the higher possibilities on occurrences of the landslides. While, the NDWI results are depends on the data rainfall. The higher the distribution of the rainfall leads the higher possibilities on the landslide’s occurrences.
The Development of Raspi-Met System with Raspberry Pi3 for Meteorological Monitoring in Remote Areas
Authors: Suparta Wayan 
Published: August 2020

Abstract
The development of autonomous weather station systems using Raspberry Pi3 as a new alternative, named as ‘Raspi-Met’ to enhance conventional meteorological systems is reported in this paper. Today, a weather station with a compact size is required due to limited space and cost involved. Thus, this paper aims to design an application system using Raspberry Pi3 which is connected to Vaisala PTU300 sensors as Automatic Weather Station (AWS). The Python language under LINUX has been employed to design a graphical user interface (GUI) for a real-time monitoring system, acquisition process, and displaying three meteorological parameters at desired intervals. Data storage management and daily file in a text (*.txt) format have been created to archive historical data. The RTC module has also been developed and connected to Raspberry Pi3 to synchronize and maintain the time and date of the measurement system after the power is on. The system was installed at Carlini Base, Antarctica and has the ability to measure the surface pressure (P), temperature (T), and relative humidity (H). The results have been tested and validated that the system is capable as an AWS in the Antarctic Peninsula. The development of Raspi-Met system exhibits remarkable measurements of meteorological parameters for remote areas and the database organization becomes more efficient and practical.
Performance of Different Classifiers for Marine Habitat Mapping using Side Scan Sonar and Object-Based Image Analysis
Authors: Rusmadi Raihanah , Hasan Rozaimi Che 
Published: August 2020

Abstract
Acoustic sonar techniques have been one of the successful underwater mapping alternatives for identifying the seafloor features. The integration between the technique and classification analysis can produce detail map of the seafloor. Among these sonar technologies, side-scan sonar (SSS) is one of the tools for underwater mapping that can provide high spatial resolution seafloor mosaic which is presented in greyscale level. However, before it can be used for the coral reef marine habitat mapping, it is essential to properly assess its performance and quantify the amount of information that can be extracted. The objective of this study is to determine the accuracy of habitat maps derived using side scan sonar data, Object-based Image Analysis (OBIA) and five different classifier algorithms; Support Vector Machine (SVM), Random Forest (RF), k-Nearest Neighbour (k-NN), Decision Tree, and Bayes. This study utilized side-scan sonar model Klein system 3000 which operated at 100kHz combined with video data that was conducted in shallow water (depth > 10m). First, eight (8) texture layers were derived from side scan sonar mosaic using GLCM technique. Then, the GLCM layers of texture features were reduced using Principal Component Analysis (PCA) and analysed to seek for the most contributed texture layers. A total of 80 samples were derived which consist of four (4) classes; coral, sand, silt and mud. The result shows that the Support Vector Machine (SVM) method produced the highest accuracy which is 81.25% followed by k-Nearest Neighbours (k-NN), Random Forest (RF), Decision Tree and Bayes (68.75%, 66.25%, 57.5% and 45% respectively). The used of OBIA with SSS data offers a promising method to map marine habitats for a better understanding of spatial distribution and monitoring habitat changes in the future.