The Experts below are selected from a list of 300 Experts worldwide ranked by ideXlab platform
Jingyi Huang - One of the best experts on this subject based on the ideXlab platform.
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Allocating Soil profile descriptions to a novel comprehensive Soil Classification system
Geoderma, 2018Co-Authors: Farzin Shahbazi, Alex B Mcbratney, Jingyi Huang, Philip HughesAbstract:Abstract Previous work has been put into the creation of a comprehensive Soil Classification system (CSCS) using a harmonised dataset of 23 Soil properties at 18 depth intervals. The Classification consists of selected Soil taxa from the US Soil Taxonomy, World Reference Base for Soil Resources, the Australian Soil Classification, and the New Zealand Soil Classification. In this paper, the CSCS was tested for allocation using data for from 44 Soil profiles collected in Iran. A distance-based algorithm was used to allocate and name the Soil profiles according to the CSCS. It was found that 36 Iranian Soil profiles are close to the existing taxa of the CSCS in the taxonomic space. Three Iranian profiles with distances between 25 and 30 taxonomic units to the closest CSCS taxa were added to the CSCS and assigned with new systematic names. Allocating the remaining 5 Iranian taxa would require regenerating the nomenclature system. The CSCS has shown advantages for allocating Soil profiles from other regions of the world other than the USA, Australia and New Zealand. It also enables cross-referencing with existing Soil Classification systems. In the future, the CSCS can be further improved by adding taxa from other global or regional Soil Classification systems.
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Creating a novel comprehensive Soil Classification system by sequentially adding taxa from existing systems
Geoderma Regional, 2017Co-Authors: Philip Hughes, Alex B Mcbratney, Jingyi Huang, Budiman Minasny, Jonathan Hempel, David J. Palmer, Erika MicheliAbstract:Abstract Many different Soil Classification systems exist around the world and Soil profile descriptions have always been difficult to successfully translate between taxonomic systems. In order to do this, there is the requirement for a comprehensive Soil Classification. This database needs to be comprehensive, non-duplicated, have the capacity for other suitable taxa to be added to, and at the same time to be small and simple. In this paper, we proposed a nearest-neighbour distance calculated based on the principal component space of the Soil variables to remove redundancy of the existing Soil Classification and evaluate the equivalence between the different Soil Classification system. After removing the redundancy, Great Groups of the New Zealand Classification and Australian Soil Classification and Soil Groups of the World Reference Base for Soil Resources were sequentially added to the Great Groups of the US Soil Taxonomy. This resulted in a comprehensive Soil Classification. The comprehensive Soil Classification allowed for the further addition of taxa from other Soil Classification and was capable of robustly allocating unknown Soil profiles via either hard or fuzzy Classification methods. The possibility merging and simplifying of such different systems demonstrates the possibility of similar mergers with taxonomies of other nations, creating a fully populated taxonomic space – a truly global or universal Soil Classification system.
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comparisons between usda Soil taxonomy and the australian Soil Classification system i data harmonization calculation of taxonomic distance and inter taxa variation
Geoderma, 2017Co-Authors: Philip Hughes, Erika Micheli, Alex B Mcbratney, Jingyi Huang, Budiman Minasny, Jonathan HempelAbstract:Abstract Soil Classification as a world exercise consists of predominantly individual organizations, creating locally meaningful categories for regional Soils. This process has inevitably created a recognized disconnect between Classification systems, and a push for a universal Classification has been proposed. In this paper, as a way of standardization between systems, Soil taxa at the great group level from two separate regions and Soil Classification systems, Australia and the United States of America were represented by separate databases of Soil profile descriptions (SPDs) comprising the same 23 properties at 18 depth intervals. Taxa centroids from Soil Taxonomy (ST) and the Australian Soil Classification System (ASC) were calculated via principal component analysis. Convex hulls of each Soil order of both systems were created and the associations each taxon had with other individuals in the same taxon discussed, as well as the variance. We determined that ASC orders have smaller overall dispersion compared with the ST. The influence of each property to the overall taxonomic distances was also explored. It was concluded that this analysis opened the way for the possibility of comparing differing taxonomies and could pave the way for a more comprehensive Classification method.
Dongsheng Yu - One of the best experts on this subject based on the ideXlab platform.
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a webgis system for relating genetic Soil Classification of china to Soil taxonomy
Computers & Geosciences, 2010Co-Authors: Guoxiang Yang, Dongsheng Yu, Shengxiang Xu, Eric D Warner, Gary W Petersen, Yongcun Zhao, William E Easterling, Hongjie WangAbstract:Soil Classification is the basis for the exchange of Soil science research results and the foundation for the application of modern Soil resource management methods. A WebGIS-based system designed to relate genetic Soil Classification of China (GSCC) to Soil taxonomy (ST) was developed to enhance global cooperation and to support communication between China and the other countries on important agricultural and environmental issues. The system has a Browse Server (B/S) structure and exploits the 1:1,000,000 Soil databases of China using WebGIS functionality. This paper describes the application of the WebGIS system for easily accessing cross-reference information between GSCC to ST. First, we describe the three-level B/S structure of the system. The cross-reference methodologies, referenceability and maximum referenceability, are then explained and applied at three geographic scales (i.e. nation, region and pedon). Finally, three sub-modules based on the supported scales are described and illustrated with application scenarios to familiarize users with the inquiry system and its usage. The main advantage of the system is that it considers statistical similarity in the spatial distributions between the two different Classification systems. Users with limited knowledge are able to obtain Soil cross-reference information using an intuitive interface, which supports query, visualization and analysis via a web browser at the most detailed level. The inquiry system benefits the development of Soil Classification science and international academic exchange.
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cross reference for relating genetic Soil Classification of china with wrb at different scales
Geoderma, 2010Co-Authors: Dongsheng Yu, Shengxiang Xu, Eric D Warner, Huifeng Wang, Yuguo Zhao, Zitong GongAbstract:Soil Classification systems are not consistent between countries or organizations thereby hindering the communication and organizational functions they are intended to promote. World Reference Base for Soil resources (WRB) was endorsed and adopted by the International Union of Soil Sciences (IUSS) as the standard for Soil correlation and international communication. As a widely used Classification system in China, Genetic Soil Classification of China (GSCC) differs from WRB in its underlying understanding about the genetic process. The differences limit communication between Chinese and international Soil scientists because there is no standard cross-reference between GSCC and WRB. This paper describes a cross-reference of GSCC to WRB at different scales. The basic Soil data set used in the study includes 7292 Soil profile data (representative of Soil series) collected throughout China. First, a brief history of Soil Classification in China is provided to familiarize readers with GSCC and its origins. Second, cross-reference at the pedon scale is addressed based on data compiled from 51 monoliths acquired in China by the International Soil Reference and Information Centre (ISRIC) in the 1980s and 1990s. Each of GSCC's 7292 Soil series is classified into their equivalent reference Soil groups according to the WRB Soil reference key. Pedon scale cross referencing is discussed using the database from the Second National Soil Survey of China. Third, the concept and calculation of referencibility is introduced and the process for cross-referencing Soil Classification systems at national scale is addressed. GIS based analysis generates 60 reference results between GSCC Soil great groups and WRB reference group. Results demonstrate that there is great variability in the maximum referencibility between Soil great groups of GSCC and WRB Soil groups, which ranged from 29.4% to 100%. In terms of the maximum referencibility, it can be divided into three categories: high (80%–100%), intermediate (50%–80%), and low (< 50%). Among the 60 Soil great groups of GSCC, 12 could be labeled as high maximum referencibility, 27 categorized as medium maximum referencibility and the remaining 21 are associated with low maximum referencibility. Finally, the main cause of low maximum referencibility is explored and the potential solution to improve cross reference accuracy was proposed.
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cross reference system for translating between genetic Soil Classification of china and Soil taxonomy
Soil Science Society of America Journal, 2006Co-Authors: Dongsheng Yu, Eric D Warner, Gary W Petersen, Z T GongAbstract:Soil Classification systems are not consistent among countries or organizations thereby hindering the communication and organizational functions they are intended to promote. The development of translations between systems will be critical for overcoming the gap in understanding that has resulted from the lack of a single internationally accepted Classification system. This paper describes the application of a process that resulted in the translation of the Genetic Soil Classification of China (GSCC) to Soil Taxonomy (ST). A brief history of Soil Classification in China is also provided to familiarize readers with GSCC and its origins. Genetic Soil Classification of China is the attribute base for the recently assembled digital form of the 1:1000 000 Soil map of The People's Republic of China. The translation between GSCC and ST was based on profile, chemical, and physical descriptions of 2540 Soil series. First, the 2540 Soil series were classified to their equivalent Soil order, suborder, great group, and subgroup according to ST and GSCC subgroup descriptors. Order names for both Classification systems were then linked to corresponding map units in the 1:1 000 000 digital Soil map of China using a geographic information system (GIS). Differences in Classification criteria and in the number of orders of the two systems (there are more GSCC orders than ST orders) meant that each GSCC order could possibly be assigned to more than one ST order. To resolve the differences, the percent correspondence in area between orders was determined and used as the criterion for assigning GSCC orders to ST orders. Some percentages of correspondence were low so additional processing was used to improve the assignment process. The GSCC suborders were then matched with ST orders. When the area for each order was summarized, the percentage of correspondence increased except for two subgroups in the Ferrasols order.
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reference benchmarks relating to great groups of genetic Soil Classification of china with Soil taxonomy
Chinese Science Bulletin, 2004Co-Authors: Dongsheng Yu, Hongjie Wang, Qiguo Zhao, Zitong GongAbstract:Soil Classification forms the basis for the exchange and extension of research findings in Soil science and for the modernization of management of Soil resources. This paper systematically reviews the compatibility of the genetic Soil Classification of China (GSCC) and Soil taxonomy (ST). This includes a study of the evolution and consummation of the GSCC and assessment of the databases and methods of the study. Using the “Soil Species of China (six volumes)” and some provincial Soil species as the basic material, the authors gathered information from 2540 Soil species. Based on the key described in ST, the 2540 Soil species were taxonomically classified into corresponding Soil orders, suborders, great groups and subgroups and then matched with corresponding map units in the 1: 1000000 digital Soil map of China. Using the high-level Classification units of the two Soil Classification systems, and the attributes of each Soil species, the sizes of distribution areas were mapped. The Soil distribution results were analyzed and compared statistically. The reference compatibility between the great groups used in GSCC system and the Soil orders of the ST is discussed. It is believed that 20 great groups display maximum referencibility>95% and 15 great groups depict maximum referencibility in the range of 70%–95%, which can be cited as reference benchmarks. The remaining 25 great groups are less compatible (with maximum referencibility <70%) and need further study, or require referencing at lower Classification levels or at a regional level to help to improve the accuracy of the reference.
Alex B Mcbratney - One of the best experts on this subject based on the ideXlab platform.
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Numerical Soil Classification: a missed, but not a lost, opportunity.
2020Co-Authors: Alex B Mcbratney, Budiman Minasny, R. V. Rossel, R. J. Gilkes, N. PrakongkepAbstract:The history of numerical Soil Classification from its advent in the 1960s is reviewed. The current and future possibilities for a numerical approach are explored in the light of available large Soil databases and prior Soil classificatory knowledge.
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Allocating Soil profile descriptions to a novel comprehensive Soil Classification system
Geoderma, 2018Co-Authors: Farzin Shahbazi, Alex B Mcbratney, Jingyi Huang, Philip HughesAbstract:Abstract Previous work has been put into the creation of a comprehensive Soil Classification system (CSCS) using a harmonised dataset of 23 Soil properties at 18 depth intervals. The Classification consists of selected Soil taxa from the US Soil Taxonomy, World Reference Base for Soil Resources, the Australian Soil Classification, and the New Zealand Soil Classification. In this paper, the CSCS was tested for allocation using data for from 44 Soil profiles collected in Iran. A distance-based algorithm was used to allocate and name the Soil profiles according to the CSCS. It was found that 36 Iranian Soil profiles are close to the existing taxa of the CSCS in the taxonomic space. Three Iranian profiles with distances between 25 and 30 taxonomic units to the closest CSCS taxa were added to the CSCS and assigned with new systematic names. Allocating the remaining 5 Iranian taxa would require regenerating the nomenclature system. The CSCS has shown advantages for allocating Soil profiles from other regions of the world other than the USA, Australia and New Zealand. It also enables cross-referencing with existing Soil Classification systems. In the future, the CSCS can be further improved by adding taxa from other global or regional Soil Classification systems.
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Creating a novel comprehensive Soil Classification system by sequentially adding taxa from existing systems
Geoderma Regional, 2017Co-Authors: Philip Hughes, Alex B Mcbratney, Jingyi Huang, Budiman Minasny, Jonathan Hempel, David J. Palmer, Erika MicheliAbstract:Abstract Many different Soil Classification systems exist around the world and Soil profile descriptions have always been difficult to successfully translate between taxonomic systems. In order to do this, there is the requirement for a comprehensive Soil Classification. This database needs to be comprehensive, non-duplicated, have the capacity for other suitable taxa to be added to, and at the same time to be small and simple. In this paper, we proposed a nearest-neighbour distance calculated based on the principal component space of the Soil variables to remove redundancy of the existing Soil Classification and evaluate the equivalence between the different Soil Classification system. After removing the redundancy, Great Groups of the New Zealand Classification and Australian Soil Classification and Soil Groups of the World Reference Base for Soil Resources were sequentially added to the Great Groups of the US Soil Taxonomy. This resulted in a comprehensive Soil Classification. The comprehensive Soil Classification allowed for the further addition of taxa from other Soil Classification and was capable of robustly allocating unknown Soil profiles via either hard or fuzzy Classification methods. The possibility merging and simplifying of such different systems demonstrates the possibility of similar mergers with taxonomies of other nations, creating a fully populated taxonomic space – a truly global or universal Soil Classification system.
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comparisons between usda Soil taxonomy and the australian Soil Classification system i data harmonization calculation of taxonomic distance and inter taxa variation
Geoderma, 2017Co-Authors: Philip Hughes, Erika Micheli, Alex B Mcbratney, Jingyi Huang, Budiman Minasny, Jonathan HempelAbstract:Abstract Soil Classification as a world exercise consists of predominantly individual organizations, creating locally meaningful categories for regional Soils. This process has inevitably created a recognized disconnect between Classification systems, and a push for a universal Classification has been proposed. In this paper, as a way of standardization between systems, Soil taxa at the great group level from two separate regions and Soil Classification systems, Australia and the United States of America were represented by separate databases of Soil profile descriptions (SPDs) comprising the same 23 properties at 18 depth intervals. Taxa centroids from Soil Taxonomy (ST) and the Australian Soil Classification System (ASC) were calculated via principal component analysis. Convex hulls of each Soil order of both systems were created and the associations each taxon had with other individuals in the same taxon discussed, as well as the variance. We determined that ASC orders have smaller overall dispersion compared with the ST. The influence of each property to the overall taxonomic distances was also explored. It was concluded that this analysis opened the way for the possibility of comparing differing taxonomies and could pave the way for a more comprehensive Classification method.
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time for a universal Soil Classification system
Proceedings of the 19th World Congress of Soil Science: Soil solutions for a changing world Brisbane Australia 1-6 August 2010. Symposium 1.4.1 Classi, 2010Co-Authors: Micheal Golden, Zhang Ganlin, Erika Micheli, Craig Ditzler, H Eswaran, Phillip R Owens, Alex B Mcbratney, Jon Hempel, L Montanarellai, Peter SchadAbstract:Soil science, unlike many other scientific disciplines, does not have a universally accepted Classification system. Many countries have developed systems to classify their Soils, but the results often do not translate well between taxonomic systems. Attempts have been made through efforts such as the FAO Legend for the Soil Map of the World , the World Reference Base for Soil Resources , and Soil Taxonomy to address the need for a globally accepted Soil Classification system. But so far, this goal has not been achieved. We believe the time is right to form a working group under the auspices of the International Union of Soil Sciences to explore the development of a universal Soil Classification system. Background Most natural sciences struggle for a common Classification system such as botany, anthropology and astronomy. Natural Classification systems should be accepted and used globally. Soil science and Soil Classification are viewed as National Systems yet none have received full international acceptance. Common reasons given for universal systems are pleas from a discipline to work together towards a common understanding and to provide a common language for communication.
Philip Hughes - One of the best experts on this subject based on the ideXlab platform.
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Allocating Soil profile descriptions to a novel comprehensive Soil Classification system
Geoderma, 2018Co-Authors: Farzin Shahbazi, Alex B Mcbratney, Jingyi Huang, Philip HughesAbstract:Abstract Previous work has been put into the creation of a comprehensive Soil Classification system (CSCS) using a harmonised dataset of 23 Soil properties at 18 depth intervals. The Classification consists of selected Soil taxa from the US Soil Taxonomy, World Reference Base for Soil Resources, the Australian Soil Classification, and the New Zealand Soil Classification. In this paper, the CSCS was tested for allocation using data for from 44 Soil profiles collected in Iran. A distance-based algorithm was used to allocate and name the Soil profiles according to the CSCS. It was found that 36 Iranian Soil profiles are close to the existing taxa of the CSCS in the taxonomic space. Three Iranian profiles with distances between 25 and 30 taxonomic units to the closest CSCS taxa were added to the CSCS and assigned with new systematic names. Allocating the remaining 5 Iranian taxa would require regenerating the nomenclature system. The CSCS has shown advantages for allocating Soil profiles from other regions of the world other than the USA, Australia and New Zealand. It also enables cross-referencing with existing Soil Classification systems. In the future, the CSCS can be further improved by adding taxa from other global or regional Soil Classification systems.
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Creating a novel comprehensive Soil Classification system by sequentially adding taxa from existing systems
Geoderma Regional, 2017Co-Authors: Philip Hughes, Alex B Mcbratney, Jingyi Huang, Budiman Minasny, Jonathan Hempel, David J. Palmer, Erika MicheliAbstract:Abstract Many different Soil Classification systems exist around the world and Soil profile descriptions have always been difficult to successfully translate between taxonomic systems. In order to do this, there is the requirement for a comprehensive Soil Classification. This database needs to be comprehensive, non-duplicated, have the capacity for other suitable taxa to be added to, and at the same time to be small and simple. In this paper, we proposed a nearest-neighbour distance calculated based on the principal component space of the Soil variables to remove redundancy of the existing Soil Classification and evaluate the equivalence between the different Soil Classification system. After removing the redundancy, Great Groups of the New Zealand Classification and Australian Soil Classification and Soil Groups of the World Reference Base for Soil Resources were sequentially added to the Great Groups of the US Soil Taxonomy. This resulted in a comprehensive Soil Classification. The comprehensive Soil Classification allowed for the further addition of taxa from other Soil Classification and was capable of robustly allocating unknown Soil profiles via either hard or fuzzy Classification methods. The possibility merging and simplifying of such different systems demonstrates the possibility of similar mergers with taxonomies of other nations, creating a fully populated taxonomic space – a truly global or universal Soil Classification system.
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comparisons between usda Soil taxonomy and the australian Soil Classification system i data harmonization calculation of taxonomic distance and inter taxa variation
Geoderma, 2017Co-Authors: Philip Hughes, Erika Micheli, Alex B Mcbratney, Jingyi Huang, Budiman Minasny, Jonathan HempelAbstract:Abstract Soil Classification as a world exercise consists of predominantly individual organizations, creating locally meaningful categories for regional Soils. This process has inevitably created a recognized disconnect between Classification systems, and a push for a universal Classification has been proposed. In this paper, as a way of standardization between systems, Soil taxa at the great group level from two separate regions and Soil Classification systems, Australia and the United States of America were represented by separate databases of Soil profile descriptions (SPDs) comprising the same 23 properties at 18 depth intervals. Taxa centroids from Soil Taxonomy (ST) and the Australian Soil Classification System (ASC) were calculated via principal component analysis. Convex hulls of each Soil order of both systems were created and the associations each taxon had with other individuals in the same taxon discussed, as well as the variance. We determined that ASC orders have smaller overall dispersion compared with the ST. The influence of each property to the overall taxonomic distances was also explored. It was concluded that this analysis opened the way for the possibility of comparing differing taxonomies and could pave the way for a more comprehensive Classification method.
Jonathan Hempel - One of the best experts on this subject based on the ideXlab platform.
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Creating a novel comprehensive Soil Classification system by sequentially adding taxa from existing systems
Geoderma Regional, 2017Co-Authors: Philip Hughes, Alex B Mcbratney, Jingyi Huang, Budiman Minasny, Jonathan Hempel, David J. Palmer, Erika MicheliAbstract:Abstract Many different Soil Classification systems exist around the world and Soil profile descriptions have always been difficult to successfully translate between taxonomic systems. In order to do this, there is the requirement for a comprehensive Soil Classification. This database needs to be comprehensive, non-duplicated, have the capacity for other suitable taxa to be added to, and at the same time to be small and simple. In this paper, we proposed a nearest-neighbour distance calculated based on the principal component space of the Soil variables to remove redundancy of the existing Soil Classification and evaluate the equivalence between the different Soil Classification system. After removing the redundancy, Great Groups of the New Zealand Classification and Australian Soil Classification and Soil Groups of the World Reference Base for Soil Resources were sequentially added to the Great Groups of the US Soil Taxonomy. This resulted in a comprehensive Soil Classification. The comprehensive Soil Classification allowed for the further addition of taxa from other Soil Classification and was capable of robustly allocating unknown Soil profiles via either hard or fuzzy Classification methods. The possibility merging and simplifying of such different systems demonstrates the possibility of similar mergers with taxonomies of other nations, creating a fully populated taxonomic space – a truly global or universal Soil Classification system.
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comparisons between usda Soil taxonomy and the australian Soil Classification system i data harmonization calculation of taxonomic distance and inter taxa variation
Geoderma, 2017Co-Authors: Philip Hughes, Erika Micheli, Alex B Mcbratney, Jingyi Huang, Budiman Minasny, Jonathan HempelAbstract:Abstract Soil Classification as a world exercise consists of predominantly individual organizations, creating locally meaningful categories for regional Soils. This process has inevitably created a recognized disconnect between Classification systems, and a push for a universal Classification has been proposed. In this paper, as a way of standardization between systems, Soil taxa at the great group level from two separate regions and Soil Classification systems, Australia and the United States of America were represented by separate databases of Soil profile descriptions (SPDs) comprising the same 23 properties at 18 depth intervals. Taxa centroids from Soil Taxonomy (ST) and the Australian Soil Classification System (ASC) were calculated via principal component analysis. Convex hulls of each Soil order of both systems were created and the associations each taxon had with other individuals in the same taxon discussed, as well as the variance. We determined that ASC orders have smaller overall dispersion compared with the ST. The influence of each property to the overall taxonomic distances was also explored. It was concluded that this analysis opened the way for the possibility of comparing differing taxonomies and could pave the way for a more comprehensive Classification method.
