In terms of accuracy and speed, Ground Penetrating Radar (GPR) is the best approach for detecting and identifying underground utilities. This technology can precisely find a wide range of underground utilities, including both metallic and non-metallic materials. It analyses the ground by emitting a signal from an antenna at various frequencies of electromagnetic (EM) pulses. However, undesirable echoes caused by heterogeneous materials, such as the wide range of soil properties and utilities, are always present in these reflected signals. The site's soil composition has a direct influence on the accuracy of the GPR signal image. Thus, this study is carried out to evaluate the accuracy of GPR data for buried objects with different types of pipes between PVC and iron pipe in different soil characteristics: fine sand, topsoil and silt soil. The objective is to interpret the resolution of radargram images on different soil types due to different soil based characteristics and to evaluate the accuracy of depth values between GPR and conventional survey data sets for different pipes and soils using the RMSE formula. GPR Electronic TriVue with high frequency (1GHz) was employed, and the resolution of the resulting radargram image was post-processed in ReflexW software to yield promising depth results. Based on this research, the radargram obtained shows different textures that provides different presentations of each soil on the radargram image. Accuracy assessment from RMSE depth difference for Iron pipe depth for the three different soil types are: topsoil is 0.025 m, silt soil is 0.032 m, and fine sand is 0.087 m. While for PVC pipe topsoil is 0.035 m, silt soil is 0.038 m, and fine sand is 0.093 m. These differences show that iron pipe is more accurate compared with PVC in terms of tendency and fine sand is suitable soil in detection compared with topsoil and silt soil. In conclusion, the type of pipe play role in the choice of utility and soil properties (texture, moisture, and electrical conductivity) that impact the most on the accuracy assessment of GPR Data.
{"title":"Accuracy Assessment of GPR Data for Buried Objects with Different Pipes and Soil-Based Conditions","authors":"","doi":"10.52939/ijg.v19i5.2651","DOIUrl":"https://doi.org/10.52939/ijg.v19i5.2651","url":null,"abstract":"In terms of accuracy and speed, Ground Penetrating Radar (GPR) is the best approach for detecting and identifying underground utilities. This technology can precisely find a wide range of underground utilities, including both metallic and non-metallic materials. It analyses the ground by emitting a signal from an antenna at various frequencies of electromagnetic (EM) pulses. However, undesirable echoes caused by heterogeneous materials, such as the wide range of soil properties and utilities, are always present in these reflected signals. The site's soil composition has a direct influence on the accuracy of the GPR signal image. Thus, this study is carried out to evaluate the accuracy of GPR data for buried objects with different types of pipes between PVC and iron pipe in different soil characteristics: fine sand, topsoil and silt soil. The objective is to interpret the resolution of radargram images on different soil types due to different soil based characteristics and to evaluate the accuracy of depth values between GPR and conventional survey data sets for different pipes and soils using the RMSE formula. GPR Electronic TriVue with high frequency (1GHz) was employed, and the resolution of the resulting radargram image was post-processed in ReflexW software to yield promising depth results. Based on this research, the radargram obtained shows different textures that provides different presentations of each soil on the radargram image. Accuracy assessment from RMSE depth difference for Iron pipe depth for the three different soil types are: topsoil is 0.025 m, silt soil is 0.032 m, and fine sand is 0.087 m. While for PVC pipe topsoil is 0.035 m, silt soil is 0.038 m, and fine sand is 0.093 m. These differences show that iron pipe is more accurate compared with PVC in terms of tendency and fine sand is suitable soil in detection compared with topsoil and silt soil. In conclusion, the type of pipe play role in the choice of utility and soil properties (texture, moisture, and electrical conductivity) that impact the most on the accuracy assessment of GPR Data.","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42090015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stochastic Modelling (SM) was a crucial component of least squares adjustment (LSA), particularly when processing data from geodetic networks. The projected variances which generate using SM execute an important part in defining both the accurateness of the computed parameter vectors and the impact of the adjustment outcomes. As positional precision becomes the primary objective, there is still potential for improvement because there are multiple sources of datasets with varying levels of data quality. Concerning the assertion that the National Digital Cadastral Database (NDCDB) is accurate, its development involved the use of historical datasets that were obtained from a number of different measurement classes, specifically the first, second, and third classes. In this study, researchers evaluated whether or not it is possible to employ stochastic modelling to maintain the position correctness of historical data that encompasses a wide range of data quality classes. In order to accomplish this, an approach known as an Least Squares Variance Component Estimator (LS-VCE) was utilised to generate reliable estimates of variances. Two (2) certified plans (CPs) that is CP93887 and CP33758 was selected as measurements for the first and second classes CP, respectively. The experiment showed that the variance that has been estimated by LS-VCE could produce realistic adjustment results, as shown by an analysis of the corrected results obtained by allocating the variance into different data classes. In light of these findings, the investigations showed and demonstrated conclusively that separate variance is necessary for each data classes with the aim of preserving positional accuracy. In conclusion, it is crucial to incorporate a realistic variance component inside a coordinated cadastral database in order to fulfil the objective of ensuring the accurateness of survey data for future time periods.
{"title":"Implementation of Stochastic Modelling in Enhanced Cadastral Databased for Multi-Classes Datasets","authors":"","doi":"10.52939/ijg.v19i5.2657","DOIUrl":"https://doi.org/10.52939/ijg.v19i5.2657","url":null,"abstract":"Stochastic Modelling (SM) was a crucial component of least squares adjustment (LSA), particularly when processing data from geodetic networks. The projected variances which generate using SM execute an important part in defining both the accurateness of the computed parameter vectors and the impact of the adjustment outcomes. As positional precision becomes the primary objective, there is still potential for improvement because there are multiple sources of datasets with varying levels of data quality. Concerning the assertion that the National Digital Cadastral Database (NDCDB) is accurate, its development involved the use of historical datasets that were obtained from a number of different measurement classes, specifically the first, second, and third classes. In this study, researchers evaluated whether or not it is possible to employ stochastic modelling to maintain the position correctness of historical data that encompasses a wide range of data quality classes. In order to accomplish this, an approach known as an Least Squares Variance Component Estimator (LS-VCE) was utilised to generate reliable estimates of variances. Two (2) certified plans (CPs) that is CP93887 and CP33758 was selected as measurements for the first and second classes CP, respectively. The experiment showed that the variance that has been estimated by LS-VCE could produce realistic adjustment results, as shown by an analysis of the corrected results obtained by allocating the variance into different data classes. In light of these findings, the investigations showed and demonstrated conclusively that separate variance is necessary for each data classes with the aim of preserving positional accuracy. In conclusion, it is crucial to incorporate a realistic variance component inside a coordinated cadastral database in order to fulfil the objective of ensuring the accurateness of survey data for future time periods.","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42715565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
On July 4, 2022, Sungai Kupang, Baling, Kedah experienced a devastating flood that caused 3 fatalities, destroyed or damaged 17 houses, affected 3,546 residents, and resulted in losses estimated at RM25.91 million. The flood was triggered by heavy rainfall in the highland area, which caused multiple landslides to occur simultaneously. The landslides led to a debris flow phenomenon in four main river branches, ultimately resulting in a tragic debris and mud flood in the lowlands and downstream villages. The aim of this study is to analyze the location of flash flood occurrences in Baling and to estimate the likelihood of flash floods based on the identified land physical factors. This study also identifies the critical area of Baling basin that have high potential for a flash flood and evaluates the effectiveness and applicability of the FFPI model compared with historical flood events and remote sensing imagery which have occurred in the few watersheds area. The FFPI model, which was created for the first time in 2003, is used in this study to analyze the flash flood that occurred in Baling by considering slope, land cover, soil data, and vegetation. The FFPI technique is applied in five scenarios to determine the flash flood potential, and the value used is also based on the references. A value of 1 on the index denotes a minimal probability of flash floods, while a value of 10 indicates the highest probability. Based on the findings, the study area had a high possibility of having a flash flood at an index value of 7. The danger level of a severe flash flood is present throughout the research region in all scenarios when the value is more than 50%. The outcome is then utilized to do comparisons using historical information on flash floods and their hotspots area, as well as utilizing satellite imagery to determine the true scale of the flood. This is also important to reduce the impact of floods occurrence in the same place as well managing risk and to plan for disaster-mitigation operations.
{"title":"Employing the Flash Flood Potential Index (FFPI) with Physical Environmental Factors in Baling, Kedah through GIS Analysis","authors":"","doi":"10.52939/ijg.v19i5.2653","DOIUrl":"https://doi.org/10.52939/ijg.v19i5.2653","url":null,"abstract":"On July 4, 2022, Sungai Kupang, Baling, Kedah experienced a devastating flood that caused 3 fatalities, destroyed or damaged 17 houses, affected 3,546 residents, and resulted in losses estimated at RM25.91 million. The flood was triggered by heavy rainfall in the highland area, which caused multiple landslides to occur simultaneously. The landslides led to a debris flow phenomenon in four main river branches, ultimately resulting in a tragic debris and mud flood in the lowlands and downstream villages. The aim of this study is to analyze the location of flash flood occurrences in Baling and to estimate the likelihood of flash floods based on the identified land physical factors. This study also identifies the critical area of Baling basin that have high potential for a flash flood and evaluates the effectiveness and applicability of the FFPI model compared with historical flood events and remote sensing imagery which have occurred in the few watersheds area. The FFPI model, which was created for the first time in 2003, is used in this study to analyze the flash flood that occurred in Baling by considering slope, land cover, soil data, and vegetation. The FFPI technique is applied in five scenarios to determine the flash flood potential, and the value used is also based on the references. A value of 1 on the index denotes a minimal probability of flash floods, while a value of 10 indicates the highest probability. Based on the findings, the study area had a high possibility of having a flash flood at an index value of 7. The danger level of a severe flash flood is present throughout the research region in all scenarios when the value is more than 50%. The outcome is then utilized to do comparisons using historical information on flash floods and their hotspots area, as well as utilizing satellite imagery to determine the true scale of the flood. This is also important to reduce the impact of floods occurrence in the same place as well managing risk and to plan for disaster-mitigation operations.","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41765234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Conventional methods in measuring tree height and crown diameter are time consuming compared to the advanced technology of unmanned aerial vehicle (UAV) multispectral imagery. UAV multispectral imagery is widely used in vegetation analysis such as crop analysis, vegetation monitoring, precise farming and vegetation health assessment. Thus, the purpose of this research is to extract the individual tree height and crown diameter from UAV- based multispectral imagery using the integration of geospatial techniques. Altogether, the total of 395 individual trees were extracted from the study area of Section U11, Shah Alam using the Support Vector Machine (SVM) classifier. Tree height values were extracted from normalized digital surface model (nDSM) using the zonal statistics tool with the tree height range between 1.568m to 27.850m. The range for derived crown diameters is between 0.919m to 24.506m. The final map shows the distribution of tree height and tree crown extraction from the UAV-based multispectral imagery. The spatial distribution data of tree height and crown diameter are beneficial especially in landscaping and identifying the potential of tree hazard in the urban area.
与无人机多光谱成像的先进技术相比，测量树木高度和树冠直径的传统方法非常耗时。无人机多光谱图像广泛应用于植被分析，如作物分析、植被监测、精确农业和植被健康评估。因此，本研究的目的是利用地理空间技术的集成，从基于无人机的多光谱图像中提取单个树木的高度和树冠直径。使用支持向量机（SVM）分类器，从Shah Alam U11部分的研究区域总共提取了395棵单株。树木高度值是使用区域统计工具从归一化数字表面模型（nRSM）中提取的，树木高度范围在1.568m至27.850m之间。得出的树冠直径范围在0.919m至24.506m之间。最终地图显示了从基于无人机的多光谱图像中提取的树木高度和树冠的分布。树木高度和树冠直径的空间分布数据有利于城市景观美化和识别树木危害的潜力。
{"title":"Tree Height and Crown Extraction From UAV-Based Multispectral Imagery","authors":"L. S. Suhaizad, N. Khalid, Abu Sari","doi":"10.52939/ijg.v19i5.2661","DOIUrl":"https://doi.org/10.52939/ijg.v19i5.2661","url":null,"abstract":"Conventional methods in measuring tree height and crown diameter are time consuming compared to the advanced technology of unmanned aerial vehicle (UAV) multispectral imagery. UAV multispectral imagery is widely used in vegetation analysis such as crop analysis, vegetation monitoring, precise farming and vegetation health assessment. Thus, the purpose of this research is to extract the individual tree height and crown diameter from UAV- based multispectral imagery using the integration of geospatial techniques. Altogether, the total of 395 individual trees were extracted from the study area of Section U11, Shah Alam using the Support Vector Machine (SVM) classifier. Tree height values were extracted from normalized digital surface model (nDSM) using the zonal statistics tool with the tree height range between 1.568m to 27.850m. The range for derived crown diameters is between 0.919m to 24.506m. The final map shows the distribution of tree height and tree crown extraction from the UAV-based multispectral imagery. The spatial distribution data of tree height and crown diameter are beneficial especially in landscaping and identifying the potential of tree hazard in the urban area.","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41383484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GNSS is utilized in numerous industries and applications to determine a location's (position and time). GNSS technology was quickly used for surveying because it can offer correct latitude, longitude, and height without establishing angles and distances. It's utilized worldwide in mapping and surveying. An ideal GNSS receiver for geodetic and other surveying applications must receive and monitor both code pseudo ranges and carrier phase signals, including the Y-codeless signal. Using geodetic equipment can offer the most accurate location data, but it depends on the instrument's quality. Choosing the proper equipment ensures trustworthy location data. Surveyors may pick cheap equipment caused by financial constraints. Does the data from different GNSS receiver brands have the same quality? By performing static observation on various GNSS receiver from CHC (i90, i83, i80, i73 and i70) key parameters are extracted from the data for data integrity assessment in terms of multipath, cycle slip, signal noise ratio, sky plot and others. CHC Geomatics Office 2 was used to extract the mentioned parameters for quality assessment. The two-day observation lasted from April 23 to April 25, 2022. (GPST). Data availability and data completeness are closely related criteria. For full potential analysis, receivers must be fully operating. No receiver has 100% data completeness or 24-hour data availability. Each receiver's data demonstrates that error varies by parameter. CHC i70 has the least multipath effect and CHC i80 the greatest. Overall, MP1 and MP2 multipath effects were below 0.5. CHC i70 had the lowest cycle slip ratio as it recorded the strongest signal strength while the greatest cycle slip ratio occurred to CHC i80. Each receiver's sky map exhibits the same pattern for both observation days, indicating they tracked the same satellite. Lastly, the average coordinates acquired either on various days or among the receivers indicates a maximum of 0.28m in vector displacement where it is appropriate to claim that each receiver received different coordinates since they were not locating on one place but adjacent within 1 meter radius. From the data analyzed, it is concluded that CHC i83 has best data quality among CHC models while CHC i80 obtained the worst data quality, but this does not indicate that model cannot provide good quality data.
{"title":"Quality Assessment of Various CHC NAV GNSS Receiver Models","authors":"","doi":"10.52939/ijg.v19i5.2655","DOIUrl":"https://doi.org/10.52939/ijg.v19i5.2655","url":null,"abstract":"GNSS is utilized in numerous industries and applications to determine a location's (position and time). GNSS technology was quickly used for surveying because it can offer correct latitude, longitude, and height without establishing angles and distances. It's utilized worldwide in mapping and surveying. An ideal GNSS receiver for geodetic and other surveying applications must receive and monitor both code pseudo ranges and carrier phase signals, including the Y-codeless signal. Using geodetic equipment can offer the most accurate location data, but it depends on the instrument's quality. Choosing the proper equipment ensures trustworthy location data. Surveyors may pick cheap equipment caused by financial constraints. Does the data from different GNSS receiver brands have the same quality? By performing static observation on various GNSS receiver from CHC (i90, i83, i80, i73 and i70) key parameters are extracted from the data for data integrity assessment in terms of multipath, cycle slip, signal noise ratio, sky plot and others. CHC Geomatics Office 2 was used to extract the mentioned parameters for quality assessment. The two-day observation lasted from April 23 to April 25, 2022. (GPST). Data availability and data completeness are closely related criteria. For full potential analysis, receivers must be fully operating. No receiver has 100% data completeness or 24-hour data availability. Each receiver's data demonstrates that error varies by parameter. CHC i70 has the least multipath effect and CHC i80 the greatest. Overall, MP1 and MP2 multipath effects were below 0.5. CHC i70 had the lowest cycle slip ratio as it recorded the strongest signal strength while the greatest cycle slip ratio occurred to CHC i80. Each receiver's sky map exhibits the same pattern for both observation days, indicating they tracked the same satellite. Lastly, the average coordinates acquired either on various days or among the receivers indicates a maximum of 0.28m in vector displacement where it is appropriate to claim that each receiver received different coordinates since they were not locating on one place but adjacent within 1 meter radius. From the data analyzed, it is concluded that CHC i83 has best data quality among CHC models while CHC i80 obtained the worst data quality, but this does not indicate that model cannot provide good quality data.","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42234764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, multispectral images can be captured not only from satellite sensors but also from cameras. Hence, using the photogrammetric approach, multispectral images can be manipulated to generate a three-dimensional model. The main issues regarding multispectral images were the low visibilities of the image features. Moreover, the tie point extractions on multispectral images were still in doubt. Hence, this paper examines the capabilities of the SIFT algorithm to extract feature points from multispectral images and generate the point cloud from the extracted feature points. This study chose a pothole as the subject of this research. The red, red edge, green, and near-infrared bands from the Parrot Sequoia camera were used to generate the pothole model. All captured images were processed using structure-from-motion (SfM) with Multi-View Stereo (MVS) technique. This study records the feature points extraction result and analysis of the pothole model and discuss it in this paper.
{"title":"Multispectral’s Three-Dimensional Model Based on SIFT Feature Extraction","authors":"","doi":"10.52939/ijg.v19i5.2649","DOIUrl":"https://doi.org/10.52939/ijg.v19i5.2649","url":null,"abstract":"Recently, multispectral images can be captured not only from satellite sensors but also from cameras. Hence, using the photogrammetric approach, multispectral images can be manipulated to generate a three-dimensional model. The main issues regarding multispectral images were the low visibilities of the image features. Moreover, the tie point extractions on multispectral images were still in doubt. Hence, this paper examines the capabilities of the SIFT algorithm to extract feature points from multispectral images and generate the point cloud from the extracted feature points. This study chose a pothole as the subject of this research. The red, red edge, green, and near-infrared bands from the Parrot Sequoia camera were used to generate the pothole model. All captured images were processed using structure-from-motion (SfM) with Multi-View Stereo (MVS) technique. This study records the feature points extraction result and analysis of the pothole model and discuss it in this paper.","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48509140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dolomite mining in Barangay Pugalo – Pasol, Alcoy, Cebu, and the Manila Bay beach project along Roxas Boulevard, Metro Manila, Philippines has long been controversial due to the ecological, environmental, and economic implications. From the threat of rising sea levels to questionable management solutions, this sand project cannot be fully measured because of the absence of an environmental impact study. The primary objective of this research is to develop a geospatial study of the Cebu mining site using Sentinel–2 satellite data utilizing remote sensing techniques and Quantum GIS where 2018, 2020, 2030, and 2050 classification and simulation analysis shows an increase in Soil and a decrease in Vegetation and Built-up classes. Dolomite sand sustainability and longevity in Manila Bay's Dolomite Beach, are also assessed using related literature. With the help of this analysis, it’s possible to identify specific changes and predict which land will be impacted by upcoming years when current practices in the area do not change. It can also be utilized as resource management, environmental policy, and regulation support tools in identifying ecological problems while serving as a source of historical information for future land management and support for the long-term use of natural resources and expanding populations.
{"title":"Land use/land cover (LULC), change detection, and simulation analysis of Manila Bay’s Dolomite mining site in Cebu, Philippines using Sentinel–2 satellite","authors":"","doi":"10.52939/ijg.v19i5.2667","DOIUrl":"https://doi.org/10.52939/ijg.v19i5.2667","url":null,"abstract":"Dolomite mining in Barangay Pugalo – Pasol, Alcoy, Cebu, and the Manila Bay beach project along Roxas Boulevard, Metro Manila, Philippines has long been controversial due to the ecological, environmental, and economic implications. From the threat of rising sea levels to questionable management solutions, this sand project cannot be fully measured because of the absence of an environmental impact study. The primary objective of this research is to develop a geospatial study of the Cebu mining site using Sentinel–2 satellite data utilizing remote sensing techniques and Quantum GIS where 2018, 2020, 2030, and 2050 classification and simulation analysis shows an increase in Soil and a decrease in Vegetation and Built-up classes. Dolomite sand sustainability and longevity in Manila Bay's Dolomite Beach, are also assessed using related literature. With the help of this analysis, it’s possible to identify specific changes and predict which land will be impacted by upcoming years when current practices in the area do not change. It can also be utilized as resource management, environmental policy, and regulation support tools in identifying ecological problems while serving as a source of historical information for future land management and support for the long-term use of natural resources and expanding populations.","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47442389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Total stations, global navigation satellite systems (GNSS) instruments, and laser scanners are common tools used in detailed surveys because of the precision they bring to measurements and data collection. While conventional land surveying methods using total stations and GNSS instruments are widely used for their accuracy, they require a team of at least three people and can be costly. In 2021, Apple introduced the iPhone 13 Pro with a built-in LiDAR sensor that can potentially be used for land surveying. However, it is unclear whether the LiDAR data obtained from the iPhone is accurate and reliable enough to replace the conventional surveying methods. Therefore, a comparison study between the conventional method and the iPhone LiDAR sensor needs to be conducted to evaluate the feasibility and potential benefits of using the iPhone LiDAR sensor in land surveying. The purpose of this study is to evaluate the differences between tacheometry method using total station and laser scanning method using iPhone 13 Pro Max in generating detail survey plan. This study was conducted UiTM Shah Alam Stadium, Shah Alam, Selangor. For scanning method, two device poses (distance of sensor to target) are used which are 5 and 10 cm. Based on results and analysis, the difference between the actual elevation value and the scanning data from the device at 5 cm and 10 cm is relatively small. The lowest values for the device's position at 5 cm and 10 cm are -0.025 m and -0.057 m, respectively, and the highest values are 0.023 m and 0.017 m, respectively. The average deviation at the device's position of 5 cm is 0.023 m, while the average deviation at the device's position of 10 cm is 0.017 m. In conclusion, the LiDAR sensor in the iPhone 13 Pro Max has the potential to be a valuable tool for assessing accuracy in detailed survey plans. Its possible applications in different fields are worth further exploration
全站仪、全球导航卫星系统（GNSS）仪器和激光扫描仪是详细调查中常用的工具，因为它们为测量和数据收集带来了精度。虽然使用全站仪和全球导航卫星系统仪器的传统土地测量方法因其准确性而被广泛使用，但它们需要至少三人的团队，而且成本高昂。2021年，苹果推出了内置激光雷达传感器的iPhone 13 Pro，该传感器可能用于土地测量。然而，目前尚不清楚从iPhone获得的激光雷达数据是否准确可靠，足以取代传统的测量方法。因此，需要对传统方法和iPhone激光雷达传感器进行比较研究，以评估在土地测量中使用iPhone激光雷达的可行性和潜在效益。本研究的目的是评估全站仪测速法和iPhone 13 Pro Max激光扫描法在生成详细调查计划方面的差异。这项研究是在雪兰莪州沙阿阿拉姆的UiTM沙阿阿拉米体育场进行的。对于扫描方法，使用了两个设备姿态（传感器到目标的距离），分别为5厘米和10厘米。根据结果和分析，实际高程值与设备在5厘米和10cm处的扫描数据之间的差异相对较小。装置在5厘米和10厘米处的位置最低值分别为-0.025米和-0.057米，最高值分别为0.023米和0.017米。设备5cm位置的平均偏差为0.023m，而设备10cm位置的平均误差为0.017m。总之，iPhone 13 Pro Max中的激光雷达传感器有可能成为评估详细调查计划准确性的宝贵工具。它在不同领域的可能应用值得进一步探索
{"title":"Accuracy Assessment on Detail Survey Plan Using iPhone 13 Pro Max LiDAR Sensor","authors":"","doi":"10.52939/ijg.v19i5.2665","DOIUrl":"https://doi.org/10.52939/ijg.v19i5.2665","url":null,"abstract":"Total stations, global navigation satellite systems (GNSS) instruments, and laser scanners are common tools used in detailed surveys because of the precision they bring to measurements and data collection. While conventional land surveying methods using total stations and GNSS instruments are widely used for their accuracy, they require a team of at least three people and can be costly. In 2021, Apple introduced the iPhone 13 Pro with a built-in LiDAR sensor that can potentially be used for land surveying. However, it is unclear whether the LiDAR data obtained from the iPhone is accurate and reliable enough to replace the conventional surveying methods. Therefore, a comparison study between the conventional method and the iPhone LiDAR sensor needs to be conducted to evaluate the feasibility and potential benefits of using the iPhone LiDAR sensor in land surveying. The purpose of this study is to evaluate the differences between tacheometry method using total station and laser scanning method using iPhone 13 Pro Max in generating detail survey plan. This study was conducted UiTM Shah Alam Stadium, Shah Alam, Selangor. For scanning method, two device poses (distance of sensor to target) are used which are 5 and 10 cm. Based on results and analysis, the difference between the actual elevation value and the scanning data from the device at 5 cm and 10 cm is relatively small. The lowest values for the device's position at 5 cm and 10 cm are -0.025 m and -0.057 m, respectively, and the highest values are 0.023 m and 0.017 m, respectively. The average deviation at the device's position of 5 cm is 0.023 m, while the average deviation at the device's position of 10 cm is 0.017 m. In conclusion, the LiDAR sensor in the iPhone 13 Pro Max has the potential to be a valuable tool for assessing accuracy in detailed survey plans. Its possible applications in different fields are worth further exploration","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48098651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Oil palm is an important crop that generates high income to Malaysia. However, the oil palm is susceptible to Ganoderma infection that reduces the productivity of the oil palm. Conventional ground-based disease detection is laborious and costly. Therefore, airborne remote sensing technology coupled with ground detection provides a more effective control of the disease. Airborne hyperspectral remote sensing utilizes narrow and contiguous bands to assist in detection of diseases in crops. Spectral responses recorded by the camera tend to suffer from interference and these noises could reduce the quality of the data. Therefore, this study presents the application of Savitzky-Golay and wavelet spectral denoising technique to improve the hyperspectral signatures for Ganoderma disease detection in oil palm
{"title":"Denoising of Hyperspectral Signal from Drone for Ganoderma Disease Detection in Oil Palm","authors":"","doi":"10.52939/ijg.v19i5.2659","DOIUrl":"https://doi.org/10.52939/ijg.v19i5.2659","url":null,"abstract":"Oil palm is an important crop that generates high income to Malaysia. However, the oil palm is susceptible to Ganoderma infection that reduces the productivity of the oil palm. Conventional ground-based disease detection is laborious and costly. Therefore, airborne remote sensing technology coupled with ground detection provides a more effective control of the disease. Airborne hyperspectral remote sensing utilizes narrow and contiguous bands to assist in detection of diseases in crops. Spectral responses recorded by the camera tend to suffer from interference and these noises could reduce the quality of the data. Therefore, this study presents the application of Savitzky-Golay and wavelet spectral denoising technique to improve the hyperspectral signatures for Ganoderma disease detection in oil palm","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41778828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using Precise point positioning (PPP) technique can help to reach decimeters accuracy for positioning by using one receiver only. Since it set to track Global Navigation Satellite System (GNSS). Recently BeiDou and Galileo systems have been devolved periodically and increasing the number of working satellites. Addition to those all-global Navigation systems is able to receive triple frequency signals. The effect of using Multi constellation of GNSS and combination of different systems with each other’s need to be investigated. In this paper, four Multi GNSS EXPERIMENT (MGEX) stations with 24 hours observation files and 30 second interval time during a 1 week of averaged data of January 2020 (2134 GPS week) are used to investigate the accuracy of using combined solution of GNSS with 12 cases of study. Data were processed by PPPH program. To investigate the effect of using the different GNSS combinations while using the PPP method, contrast experiments have been tested by mixing dual frequency ionospheric-free PPP models in static mode with G only, GLO only, G + GLO, G+ B, GLO+B, G+GAL, GLO+GAL, GLO+B+GAL, GNSS, G +GAL+B, G+GLO+B and G+GLO+GAL combination cases, where G refers to GPS, GLO refers to GLONASS, GAL refers to Galileo and B refers to BeiDou. The results show that the combined GPS and Galileo observation in PPP solution improves the convergence time and gives the shortest convergence time of the 12 study cases with average value 53 minute and with minimum value 35 minute. By comparing the root mean square error (RMS) values, the combination of G+GL+B had the minimum RMS error in North and East direction with minimum value 1.2 cm, maximum value 1.8 cm and average value1.45 cm. And the combination of GLO+GAL+B had the minimum RMS errors in up directions with average value 2.775 cm and minimum 2.775 cm and maximum 4.5 cm. In conclusion, the results indicate that the combination of different GNSS can give more accurate solution of the PPP. The combined PPP has shown an improvement in the convergence time in the case of using combined of G and GAL observation, while the positioning accuracy after convergence has no shown significant improvement. The result of G+GAL+B give the minimum RMS error in North and East direction and the combination of GLO+GAL+B give the minimum RMS errors in up directions.
{"title":"Role of Multi-Constellation GNSS in the Mitigation of the Observation Errors and the Enhancement of the Positioning Accuracy","authors":"","doi":"10.52939/ijg.v19i4.2631","DOIUrl":"https://doi.org/10.52939/ijg.v19i4.2631","url":null,"abstract":"Using Precise point positioning (PPP) technique can help to reach decimeters accuracy for positioning by using one receiver only. Since it set to track Global Navigation Satellite System (GNSS). Recently BeiDou and Galileo systems have been devolved periodically and increasing the number of working satellites. Addition to those all-global Navigation systems is able to receive triple frequency signals. The effect of using Multi constellation of GNSS and combination of different systems with each other’s need to be investigated. In this paper, four Multi GNSS EXPERIMENT (MGEX) stations with 24 hours observation files and 30 second interval time during a 1 week of averaged data of January 2020 (2134 GPS week) are used to investigate the accuracy of using combined solution of GNSS with 12 cases of study. Data were processed by PPPH program. To investigate the effect of using the different GNSS combinations while using the PPP method, contrast experiments have been tested by mixing dual frequency ionospheric-free PPP models in static mode with G only, GLO only, G + GLO, G+ B, GLO+B, G+GAL, GLO+GAL, GLO+B+GAL, GNSS, G +GAL+B, G+GLO+B and G+GLO+GAL combination cases, where G refers to GPS, GLO refers to GLONASS, GAL refers to Galileo and B refers to BeiDou. The results show that the combined GPS and Galileo observation in PPP solution improves the convergence time and gives the shortest convergence time of the 12 study cases with average value 53 minute and with minimum value 35 minute. By comparing the root mean square error (RMS) values, the combination of G+GL+B had the minimum RMS error in North and East direction with minimum value 1.2 cm, maximum value 1.8 cm and average value1.45 cm. And the combination of GLO+GAL+B had the minimum RMS errors in up directions with average value 2.775 cm and minimum 2.775 cm and maximum 4.5 cm. In conclusion, the results indicate that the combination of different GNSS can give more accurate solution of the PPP. The combined PPP has shown an improvement in the convergence time in the case of using combined of G and GAL observation, while the positioning accuracy after convergence has no shown significant improvement. The result of G+GAL+B give the minimum RMS error in North and East direction and the combination of GLO+GAL+B give the minimum RMS errors in up directions.","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44972421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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