Ifra Aftab, Mohammad Dowajy, K. Kapitany, Tamas Lovas
Artificial Intelligence (AI), specifically machine learning (ML) and deep learning (DL), is causing a paradigm shift in coding practices and software solutions across diverse fields. This study focuses on harnessing the potential of ML/DL strategies in the geospatial domain, where geodata possesses characteristics that align with the concept of a “lingual manuscript” in aesthetic theory. By employing ML/DL techniques, such as feature evaluation and extraction from 3D point clouds, we can derive concepts that are specific to software, geographical areas, and tasks. ML/DL-based interpretation of 3D point clouds extends geospatial modelling beyond implicit representations, enabling the resolution of complex heuristic-based reconstructions and abstract concepts. These advancements in artificial intelligence have the potential to optimize and expedite geodata computation and geographic information systems. However, ML/DL encounters notable challenges in this domain, including the need for abundant training data, advanced statistical methods, and the development of effective feature representations. Overcoming these challenges is essential to enhance the performance and efficacy of ML/DL systems. Additionally, ML/DL-based solutions can simplify software engineering processes by replacing certain aspects of current adoption and implementation practices, resulting in reduced complexities in development and management. Through the adoption of ML/DL, many of the existing explicitly coded GIS implementations may gradually be replaced in the long term. Overall, this research illustrates the transformative capabilities of ML/DL in geospatial applications and underscores the significance of addressing associated challenges to drive further advancements in the field.
{"title":"Artificial Intelligence (AI) – based strategies for point cloud data and digital twins","authors":"Ifra Aftab, Mohammad Dowajy, K. Kapitany, Tamas Lovas","doi":"10.55779/ng33138","DOIUrl":"https://doi.org/10.55779/ng33138","url":null,"abstract":"Artificial Intelligence (AI), specifically machine learning (ML) and deep learning (DL), is causing a paradigm shift in coding practices and software solutions across diverse fields. This study focuses on harnessing the potential of ML/DL strategies in the geospatial domain, where geodata possesses characteristics that align with the concept of a “lingual manuscript” in aesthetic theory. By employing ML/DL techniques, such as feature evaluation and extraction from 3D point clouds, we can derive concepts that are specific to software, geographical areas, and tasks. ML/DL-based interpretation of 3D point clouds extends geospatial modelling beyond implicit representations, enabling the resolution of complex heuristic-based reconstructions and abstract concepts. These advancements in artificial intelligence have the potential to optimize and expedite geodata computation and geographic information systems. However, ML/DL encounters notable challenges in this domain, including the need for abundant training data, advanced statistical methods, and the development of effective feature representations. Overcoming these challenges is essential to enhance the performance and efficacy of ML/DL systems. Additionally, ML/DL-based solutions can simplify software engineering processes by replacing certain aspects of current adoption and implementation practices, resulting in reduced complexities in development and management. Through the adoption of ML/DL, many of the existing explicitly coded GIS implementations may gradually be replaced in the long term. Overall, this research illustrates the transformative capabilities of ML/DL in geospatial applications and underscores the significance of addressing associated challenges to drive further advancements in the field.","PeriodicalId":109211,"journal":{"name":"Nova Geodesia","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133037586","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}
The same niche cannot support two species. To avoid negative interactions, species adapt their presence and utilize different types of resources according to different time periods. Many factors, including temperature, influence insect communities. Butterfly species utilize similar habitat types or even microhabitats with other co-species and share the same daytime if the resources are plentiful. However, they follow a certain ecological pattern of temporal distribution by using different intervals of the same time frame. With the use of the Modified Pollard Walk Method, the present study explores butterfly presence, species exclusivity, and commonality in an area situated in Jolkol, Serampore, West Bengal. The presence of reliable sources of nectar, a plentiful supply of food plants conducive to egg-laying, ample sunlight in open spaces, minimal pesticide usage, and limited human interference within the examined region have all contributed to a diverse array of butterfly species in the area. Butterfly species are susceptible to changes in landscape and vegetation, and the loss of habitats caused by urbanization and environmental degradation threatens butterfly diversity. Many butterfly species function as ecological indicators and provide numerous ecosystem services. As a result, conservation and preservation of butterfly diversity are important, particularly in urban habitats.
{"title":"Temporal distribution pattern of butterflies in an unfenced location at Serampore, Hooghly, West Bengal, India","authors":"Md. Abu Imran Mallick, Narayan Ghorai","doi":"10.55779/ng33126","DOIUrl":"https://doi.org/10.55779/ng33126","url":null,"abstract":"The same niche cannot support two species. To avoid negative interactions, species adapt their presence and utilize different types of resources according to different time periods. Many factors, including temperature, influence insect communities. Butterfly species utilize similar habitat types or even microhabitats with other co-species and share the same daytime if the resources are plentiful. However, they follow a certain ecological pattern of temporal distribution by using different intervals of the same time frame. With the use of the Modified Pollard Walk Method, the present study explores butterfly presence, species exclusivity, and commonality in an area situated in Jolkol, Serampore, West Bengal. The presence of reliable sources of nectar, a plentiful supply of food plants conducive to egg-laying, ample sunlight in open spaces, minimal pesticide usage, and limited human interference within the examined region have all contributed to a diverse array of butterfly species in the area. Butterfly species are susceptible to changes in landscape and vegetation, and the loss of habitats caused by urbanization and environmental degradation threatens butterfly diversity. Many butterfly species function as ecological indicators and provide numerous ecosystem services. As a result, conservation and preservation of butterfly diversity are important, particularly in urban habitats.","PeriodicalId":109211,"journal":{"name":"Nova Geodesia","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125879615","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}
Ensuring food security through the increase in food production can be realised by converting agricultural fallow lands into cultivable ones and assuring irrigations in three crop seasons in all agricultural lands. That can be done through a village (i.e., mouza) level water management planning through rainwater harvesting. This needs step by step procedures based on hydrologic balance for providing the best way of management of water resources to secure precious agricultural lands from man-made degradation. This study was conducted at a mouza Gohalura in the Red and Laterite Zone of West Bengal, India. In that village major crops grown were ‘Aman’ rice (A practices of Rice cultivation by transplanting in rainy season and harvested in early winter season) during the rainy (i.e., monsoon) season; Groundnut during Rabi under both rainfed and irrigated farming situations and ‘Boro’ rice (a practice of rice cultivation by transplanting in late winter and harvesting in early summer) in summer. The major problems in crop production in that village were some rainfed agricultural lands with erratic and uncertain rainfall of which about 26 percent (i.e., 464 mm) received during non-monsoon period (15 October to 7 June), and a high infiltration rate of soil. Shortfall in annual water balance of 248.13 mm could be managed through existing river lift irrigation from the adjoining river Dulung, a tributary of the Subarnarekha River. Application of GIS and remote sensing were useful in land use land cover classification, creation of a digital elevation model of the village and calculation of areas under individual classes of land. Creating and renovating water harvesting ponds in the mouza would facilitate multipurpose benefits for the farming community including agriculture in three crop seasons in all cultivable lands through such rational water management planning in that village. Following such village-wise water balance approach another 16.37 ha (i.e., agricultural fallow out of the total agricultural land area of 40.23 ha) i.e., about 69 per cent increase in irrigated area could be made possible. Such methodologies could be projected for other areas, and that could be followed in other areas also.
{"title":"GIS-remote sensing-based village-level hydrological balance approach for agricultural water planning","authors":"Sambhunath Saren, Pinakesh Das, S. Panda","doi":"10.55779/ng32123","DOIUrl":"https://doi.org/10.55779/ng32123","url":null,"abstract":"Ensuring food security through the increase in food production can be realised by converting agricultural fallow lands into cultivable ones and assuring irrigations in three crop seasons in all agricultural lands. That can be done through a village (i.e., mouza) level water management planning through rainwater harvesting. This needs step by step procedures based on hydrologic balance for providing the best way of management of water resources to secure precious agricultural lands from man-made degradation. This study was conducted at a mouza Gohalura in the Red and Laterite Zone of West Bengal, India. In that village major crops grown were ‘Aman’ rice (A practices of Rice cultivation by transplanting in rainy season and harvested in early winter season) during the rainy (i.e., monsoon) season; Groundnut during Rabi under both rainfed and irrigated farming situations and ‘Boro’ rice (a practice of rice cultivation by transplanting in late winter and harvesting in early summer) in summer. The major problems in crop production in that village were some rainfed agricultural lands with erratic and uncertain rainfall of which about 26 percent (i.e., 464 mm) received during non-monsoon period (15 October to 7 June), and a high infiltration rate of soil. Shortfall in annual water balance of 248.13 mm could be managed through existing river lift irrigation from the adjoining river Dulung, a tributary of the Subarnarekha River. Application of GIS and remote sensing were useful in land use land cover classification, creation of a digital elevation model of the village and calculation of areas under individual classes of land. Creating and renovating water harvesting ponds in the mouza would facilitate multipurpose benefits for the farming community including agriculture in three crop seasons in all cultivable lands through such rational water management planning in that village. Following such village-wise water balance approach another 16.37 ha (i.e., agricultural fallow out of the total agricultural land area of 40.23 ha) i.e., about 69 per cent increase in irrigated area could be made possible. Such methodologies could be projected for other areas, and that could be followed in other areas also.","PeriodicalId":109211,"journal":{"name":"Nova Geodesia","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122740873","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}
For a range of metals originating from both natural and anthropogenic sources, bryophytes are helpful biological markers of environmental contamination. This research focuses on recent changes in air quality and uses a passive biomonitoring technique to estimate atmospheric metal deposition and its seasonal trend in Sphagnum sp., as well as its substrate, from Nainital, Bhimtal, and Mangoli of Uttarakhand, India. Bryophyte samples from the summer, winter and monsoon seasons were collected from equally spaced locations. Due to the large volume of travel, a high metal concentration was discovered in Nainital. The metal deposition loads were reported in the following order: Zn > Cu > Pb > Cd. Quantitative analysis of these elements in vegetative/plants and substrate/soil showed an increase in metallic content during summer. The results indicate this moss may serve as an important tool in estimation of both aerial pollution and mineral enrichment in soil. Such research is vital since development is frequently accompanied by unfavourable changes in air quality and negative impacts of air pollution on human health, agricultural production, and natural ecosystems that need to be monitored and mitigated.
对于天然和人为来源的一系列金属，苔藓植物是环境污染的有益生物标志物。本研究关注印度北部阿坎德邦Nainital、Bhimtal和Mangoli地区空气质量的最新变化，并使用被动生物监测技术来估计大气中Sphagnum sp.及其基质中的金属沉积及其季节性趋势。夏季、冬季和季风季节的苔藓植物样本在相同间隔的地点收集。由于大量的旅行，在奈尼塔尔发现了很高的金属浓度。金属沉降量的变化顺序为:Zn > Cu > Pb > Cd。对营养植物和基质土壤中重金属含量的定量分析表明，夏季重金属含量有所增加。结果表明，这种苔藓可以作为估算空气污染和土壤中矿物质富集的重要工具。这种研究是至关重要的，因为发展常常伴随着空气质量的不利变化和空气污染对人类健康、农业生产和自然生态系统的负面影响，需要加以监测和减轻。
{"title":"Bryomonitoring of atmospheric elements in Sphagnum sp. commonly growing bryophyte in the Indian Himalayan region of Uttarakhand","authors":"Supriya Joshi, A. Alam","doi":"10.55779/ng32127","DOIUrl":"https://doi.org/10.55779/ng32127","url":null,"abstract":"For a range of metals originating from both natural and anthropogenic sources, bryophytes are helpful biological markers of environmental contamination. This research focuses on recent changes in air quality and uses a passive biomonitoring technique to estimate atmospheric metal deposition and its seasonal trend in Sphagnum sp., as well as its substrate, from Nainital, Bhimtal, and Mangoli of Uttarakhand, India. Bryophyte samples from the summer, winter and monsoon seasons were collected from equally spaced locations. Due to the large volume of travel, a high metal concentration was discovered in Nainital. The metal deposition loads were reported in the following order: Zn > Cu > Pb > Cd. Quantitative analysis of these elements in vegetative/plants and substrate/soil showed an increase in metallic content during summer. The results indicate this moss may serve as an important tool in estimation of both aerial pollution and mineral enrichment in soil. Such research is vital since development is frequently accompanied by unfavourable changes in air quality and negative impacts of air pollution on human health, agricultural production, and natural ecosystems that need to be monitored and mitigated.","PeriodicalId":109211,"journal":{"name":"Nova Geodesia","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128216977","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}
This study was aimed at exploring the ethno-veterinary practices in the District of Kupwara in Jammu and Kashmir Union Territory of India, by examining the traditional knowledge and its application in animal healthcare. The study included qualitative methods, such as interviews with local farmers (n=100) and traditional healers, as well as observation of their practices from February to April 2023. The results revealed a rich knowledge base among the local community regarding the use of medicinal plants for treating a range of animal ailments. 32 plants of pharmaceutical value representing 23 families have been assessed, with the Asteraceae family receiving the greatest attention. Eighty-eight percent of these ethnoveterinary medicinal plant species were herbs. Leaves of these plants were used most often (27%), followed by the entire plant (21%), seeds (21%), roots and fruits (9%), bulbs (6%), and stems and rhizomes (3%). Glycine max (0.91) and Allium sativum (UVi = 0.89) had the highest UVi values, whereas Oryza sativa (0.51), Allium sativum (0.49), and Zea mays (0.43) were the most cited and most often mentioned therapeutic plant species. Traditional veterinary practices were found to be deeply embedded in the local culture and were passed down through generations of farmers and traditional healers. These practices are still widely used today, in combination with modern veterinary medicine, to provide comprehensive care to livestock in the region. This study highlights the importance of preserving and promoting ethno-veterinary knowledge and practices as a valuable resource for animal healthcare in rural communities.
{"title":"Assessing ethno-veterinary practices in Kashmir Himalayas: Traditional knowledge and its role in animal healthcare","authors":"A. Y. Mir, Muzafar Riyaz, S. Ignacimuthu","doi":"10.55779/ng32131","DOIUrl":"https://doi.org/10.55779/ng32131","url":null,"abstract":"This study was aimed at exploring the ethno-veterinary practices in the District of Kupwara in Jammu and Kashmir Union Territory of India, by examining the traditional knowledge and its application in animal healthcare. The study included qualitative methods, such as interviews with local farmers (n=100) and traditional healers, as well as observation of their practices from February to April 2023. The results revealed a rich knowledge base among the local community regarding the use of medicinal plants for treating a range of animal ailments. 32 plants of pharmaceutical value representing 23 families have been assessed, with the Asteraceae family receiving the greatest attention. Eighty-eight percent of these ethnoveterinary medicinal plant species were herbs. Leaves of these plants were used most often (27%), followed by the entire plant (21%), seeds (21%), roots and fruits (9%), bulbs (6%), and stems and rhizomes (3%). Glycine max (0.91) and Allium sativum (UVi = 0.89) had the highest UVi values, whereas Oryza sativa (0.51), Allium sativum (0.49), and Zea mays (0.43) were the most cited and most often mentioned therapeutic plant species. Traditional veterinary practices were found to be deeply embedded in the local culture and were passed down through generations of farmers and traditional healers. These practices are still widely used today, in combination with modern veterinary medicine, to provide comprehensive care to livestock in the region. This study highlights the importance of preserving and promoting ethno-veterinary knowledge and practices as a valuable resource for animal healthcare in rural communities.","PeriodicalId":109211,"journal":{"name":"Nova Geodesia","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126153903","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}
Nova Geodesia (https://novageodesia.ro), Issue 1, Volume 3, 2023: The papers published in this issue represent interesting novelties in different topics of geodetic science or related fields. Nova Geodesia publishes significant papers in geodesy and close topics, related to cartography, urban administration and environment, engineering projects and construction, landscape and ecology, environmental administration, geography, planetology, hydrography, etc. Among the exciting articles, we invite readers to find news about: Landslide susceptibility modelling in a part of Himachal Pradesh, India: An integrated method based on machine learning and geospatial techniques; Fertility and mortality differentials among the Paundra Kshatriya community living in a peri-urban setting, West Bengal, India; Comparative analysis of Road Scanning Techniques.
Nova Geodesia (https://novageodesia.ro)，第1期，第3卷，2023年:这期发表的论文代表了大地测量科学或相关领域不同主题的有趣的新事物。Nova Geodesia发表测绘学方面的重要论文，涉及地图学、城市管理与环境、工程项目与建设、景观与生态、环境管理、地理学、行星学、水文学等。在令人兴奋的文章中，我们邀请读者找到以下新闻:印度喜马偕尔邦部分地区的滑坡易感性建模:基于机器学习和地理空间技术的综合方法;印度西孟加拉邦城市周边地区Paundra Kshatriya社区的生育率和死亡率差异;道路扫描技术的对比分析。
{"title":"Introduction pages, Nova Geodesia 3(1), 2023","authors":"P. Sestras","doi":"10.55779/ng31117","DOIUrl":"https://doi.org/10.55779/ng31117","url":null,"abstract":"Nova Geodesia (https://novageodesia.ro), Issue 1, Volume 3, 2023: The papers published in this issue represent interesting novelties in different topics of geodetic science or related fields. Nova Geodesia publishes significant papers in geodesy and close topics, related to cartography, urban administration and environment, engineering projects and construction, landscape and ecology, environmental administration, geography, planetology, hydrography, etc. Among the exciting articles, we invite readers to find news about: Landslide susceptibility modelling in a part of Himachal Pradesh, India: An integrated method based on machine learning and geospatial techniques; Fertility and mortality differentials among the Paundra Kshatriya community living in a peri-urban setting, West Bengal, India; Comparative analysis of Road Scanning Techniques. \u0000 ","PeriodicalId":109211,"journal":{"name":"Nova Geodesia","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129192190","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}
D. K. Adak, Nitamoni Bharali, Niloy Bagchi, Tapas K Biswas
Relationship between fertility and mortality is well known, which exists among different populations of the world. This is known as a genetic phenomenon that has been operating in all human populations. This study examines fertility and mortality differentials among the Paundra Kshatriya community living in a peri-urban setting of West Bengal, India. Altogether, 249 Paundra Kshatriya women were interviewed. A subsample was drawn from this sample, numbering 98, who have completed their reproductive span. Differential fertility is 0.3134 and differential mortality is 0.1393, whereas, index of total selection intensity is 0.4964 according to Crow’s (1958) formula and 0.5980 according to Johnston and Kensinger’s (1971) formula in the study population. The higher value according to Johnston and Kensinger’s (1971) formula is probably because of inclusion of embryonic deaths in the latter. Findings of the present study reveals that differential fertility (If: 0.3134) contribute more than the differential mortality (Im: 0.1393) towards the total opportunity for selection (I=0.4964) in the study population. Paundra Kshatriya is placed with other populations of West Bengal like Jale, Tili, Muslim, Kayastha, Paschtya Vaidya Brahmin, Duley Bagdi, Namasudra and Lepcha in this respect.
{"title":"Fertility and mortality differentials among the Paundra Kshatriya community living in a peri-urban setting, West Bengal, India","authors":"D. K. Adak, Nitamoni Bharali, Niloy Bagchi, Tapas K Biswas","doi":"10.55779/ng31104","DOIUrl":"https://doi.org/10.55779/ng31104","url":null,"abstract":"Relationship between fertility and mortality is well known, which exists among different populations of the world. This is known as a genetic phenomenon that has been operating in all human populations. This study examines fertility and mortality differentials among the Paundra Kshatriya community living in a peri-urban setting of West Bengal, India. Altogether, 249 Paundra Kshatriya women were interviewed. A subsample was drawn from this sample, numbering 98, who have completed their reproductive span. Differential fertility is 0.3134 and differential mortality is 0.1393, whereas, index of total selection intensity is 0.4964 according to Crow’s (1958) formula and 0.5980 according to Johnston and Kensinger’s (1971) formula in the study population. The higher value according to Johnston and Kensinger’s (1971) formula is probably because of inclusion of embryonic deaths in the latter. Findings of the present study reveals that differential fertility (If: 0.3134) contribute more than the differential mortality (Im: 0.1393) towards the total opportunity for selection (I=0.4964) in the study population. Paundra Kshatriya is placed with other populations of West Bengal like Jale, Tili, Muslim, Kayastha, Paschtya Vaidya Brahmin, Duley Bagdi, Namasudra and Lepcha in this respect. \u0000 \u0000 ","PeriodicalId":109211,"journal":{"name":"Nova Geodesia","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129083068","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}
Mohammad Dowajy, Dániel Baranyai, Á. Somogyi, Robert Vrbovszki, T. Lovas
A three-dimensional road point cloud is not only useful for civil engineers (road rehabilitation, road condition assessment) but can also be useful for vehicle engineers (autonomous vehicle driving scenario, vehicle dynamics simulation). Currently, there are several scanning techniques can be used to obtain these point clouds, such as terrestrial laser scanning (TLS), mobile laser scanning (MLS), airborne laser scanning (ALS), unmanned aerial vehicle (UAV) photogrammetry or UAV laser scanning. This paper discusses the investigation of four road surface scanning techniques by comparing their point clouds and the derived products. The comparison was performed for a section of a road with 1136 m length and 4 m width, the TLS survey provided the reference data. Aspects of point cloud evaluation included geometric accuracy, density, and the parameters of plane-fitting. CRG models were created from all studied point clouds to compare the difference between the final products to be used by the automotive industry. The results show that the MLS and the UAV photogrammetry generated the most accurate point cloud, while UAV laser scanning accuracy was the lowest. Similarly, the CRG models comparison showed that there was no significant difference between MLS and TLS models, and the UAV photogrammetry gave a smoother variation relative to the reference surface. Whereas the largest differences were noted for the CRG model derived from the UAV laser scanning models.
{"title":"Comparative analysis of Road Scanning Techniques","authors":"Mohammad Dowajy, Dániel Baranyai, Á. Somogyi, Robert Vrbovszki, T. Lovas","doi":"10.55779/ng31111","DOIUrl":"https://doi.org/10.55779/ng31111","url":null,"abstract":"A three-dimensional road point cloud is not only useful for civil engineers (road rehabilitation, road condition assessment) but can also be useful for vehicle engineers (autonomous vehicle driving scenario, vehicle dynamics simulation). Currently, there are several scanning techniques can be used to obtain these point clouds, such as terrestrial laser scanning (TLS), mobile laser scanning (MLS), airborne laser scanning (ALS), unmanned aerial vehicle (UAV) photogrammetry or UAV laser scanning. This paper discusses the investigation of four road surface scanning techniques by comparing their point clouds and the derived products. The comparison was performed for a section of a road with 1136 m length and 4 m width, the TLS survey provided the reference data. Aspects of point cloud evaluation included geometric accuracy, density, and the parameters of plane-fitting. CRG models were created from all studied point clouds to compare the difference between the final products to be used by the automotive industry. The results show that the MLS and the UAV photogrammetry generated the most accurate point cloud, while UAV laser scanning accuracy was the lowest. Similarly, the CRG models comparison showed that there was no significant difference between MLS and TLS models, and the UAV photogrammetry gave a smoother variation relative to the reference surface. Whereas the largest differences were noted for the CRG model derived from the UAV laser scanning models. \u0000 \u0000 ","PeriodicalId":109211,"journal":{"name":"Nova Geodesia","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133092004","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}
Landslides are one of the most destructive natural hazards in the mountainous regions across the globe including the western Himalayas of India. Hence, it is essential to implement mitigation plans, evacuation measures, and an infrastructure plan based on precise, efficient landslide susceptibility models. Current methods of landslide susceptibility mapping are improving constantly, using geospatial techniques to incorporate visual representation of the environment. However, these current methods are often opinion driven, due to lack of consensus on which factors take precedence over others. This study aims to provide a different approach namely a machine learning based approach towards Landslide Susceptibility Mapping, integrating GIS to give an accurate visual representation of the surrounding areas ranked by order of susceptibility in/and around Kullu Valley of western Himalaya, India. The landslide conditioning factors used in the study involve both static and dynamic data such as slope, land use, land cover, and rainfall variables. The research found that although the Extremely Randomised Trees provide a considerably more accurate assessment of the study area’s vulnerability, the Random Forest Regressor has greater overall accuracy. There is a significant relationship between the model’s outputs and past landslides. According to the study, there would be significantly more regions with high susceptibility to the effects of climate change on landslides by 2030. The application can identify the geographical distribution of landscape risk and is significantly less time-consuming than current methods of susceptibility analysis. Machine learning models could be crucial in evacuation efforts and in preventing damage to life and property.
{"title":"Landslide susceptibility modelling in a part of Himachal Pradesh, India: An integrated method based on machine learning and geospatial techniques","authors":"Rudraksh Mohapatra","doi":"10.55779/ng3163","DOIUrl":"https://doi.org/10.55779/ng3163","url":null,"abstract":"Landslides are one of the most destructive natural hazards in the mountainous regions across the globe including the western Himalayas of India. Hence, it is essential to implement mitigation plans, evacuation measures, and an infrastructure plan based on precise, efficient landslide susceptibility models. Current methods of landslide susceptibility mapping are improving constantly, using geospatial techniques to incorporate visual representation of the environment. However, these current methods are often opinion driven, due to lack of consensus on which factors take precedence over others. This study aims to provide a different approach namely a machine learning based approach towards Landslide Susceptibility Mapping, integrating GIS to give an accurate visual representation of the surrounding areas ranked by order of susceptibility in/and around Kullu Valley of western Himalaya, India. The landslide conditioning factors used in the study involve both static and dynamic data such as slope, land use, land cover, and rainfall variables. The research found that although the Extremely Randomised Trees provide a considerably more accurate assessment of the study area’s vulnerability, the Random Forest Regressor has greater overall accuracy. There is a significant relationship between the model’s outputs and past landslides. According to the study, there would be significantly more regions with high susceptibility to the effects of climate change on landslides by 2030. The application can identify the geographical distribution of landscape risk and is significantly less time-consuming than current methods of susceptibility analysis. Machine learning models could be crucial in evacuation efforts and in preventing damage to life and property. \u0000 \u0000 ","PeriodicalId":109211,"journal":{"name":"Nova Geodesia","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129147954","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}
Yves Yatindo BOKO-HAYA, C. Ouinsavi, Yanick Y. Akin, C. Agbangla
Knowledge of oilseeds plants’ traits and features is fundamental to understanding the natural selection process and improving conservation programs through species selection. As a forest oilseed, Ricinodendron heudelotii is the object of growing interest among value chain actors, who are increasingly interested in its intrinsic characteristics. To date, there is a lack of information on plant morphological traits for the selection of the best genotype, especially as far as seed and kernel traits are concerned. The aim of this study was to make a typology and establish the relationship between seed and kernel traits of Ricinodendron heudelotii, depending on provenances represented by wild populations of trees in southern Benin. We sampled the provenances constituted equally and per tree, ten random samples each of fruits, seeds, kernels, and shells were collected for measurement. Hierarchical classification, common component analysis, Pearson’s, and Chi-square association tests were performed for statistical analysis. Substantial variation between seed and kernel traits was observed between and within provenances. High coefficients of variation for the quantitative descriptors (length, width, and mass) of seeds and kernels appear to be the essential traits that discriminate the plant into two morphotypes. Furthermore, seed and kernel characteristics show a significant positive correlation with these discrimination criteria. The upper morphotype contains accessions from three provenances with huge seeds and kernels but few seeds per fruit, while the lower morphotype includes the other provenances with tiny seeds and kernels. The results of the study provided essential information that could be an avenue for improvement with further biochemical and molecular characterization studies.
{"title":"Influence of geographic provenance on phenotypic variation in seed and kernel traits of the African oil tree from southern Benin and implications for species breeding","authors":"Yves Yatindo BOKO-HAYA, C. Ouinsavi, Yanick Y. Akin, C. Agbangla","doi":"10.55779/ng2476","DOIUrl":"https://doi.org/10.55779/ng2476","url":null,"abstract":"Knowledge of oilseeds plants’ traits and features is fundamental to understanding the natural selection process and improving conservation programs through species selection. As a forest oilseed, Ricinodendron heudelotii is the object of growing interest among value chain actors, who are increasingly interested in its intrinsic characteristics. To date, there is a lack of information on plant morphological traits for the selection of the best genotype, especially as far as seed and kernel traits are concerned. The aim of this study was to make a typology and establish the relationship between seed and kernel traits of Ricinodendron heudelotii, depending on provenances represented by wild populations of trees in southern Benin. We sampled the provenances constituted equally and per tree, ten random samples each of fruits, seeds, kernels, and shells were collected for measurement. Hierarchical classification, common component analysis, Pearson’s, and Chi-square association tests were performed for statistical analysis. Substantial variation between seed and kernel traits was observed between and within provenances. High coefficients of variation for the quantitative descriptors (length, width, and mass) of seeds and kernels appear to be the essential traits that discriminate the plant into two morphotypes. Furthermore, seed and kernel characteristics show a significant positive correlation with these discrimination criteria. The upper morphotype contains accessions from three provenances with huge seeds and kernels but few seeds per fruit, while the lower morphotype includes the other provenances with tiny seeds and kernels. The results of the study provided essential information that could be an avenue for improvement with further biochemical and molecular characterization studies.","PeriodicalId":109211,"journal":{"name":"Nova Geodesia","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130381840","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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