通过用户友好的土壤识别密钥和拓扑序列模型提取土壤调查数据,为改善土地管理提供土壤信息

GeoResJ Pub Date : 2015-06-01 DOI:10.1016/j.grj.2015.02.006
G.J. Grealish , R.W. Fitzpatrick , J.L. Hutson
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引用次数: 11

摘要

在许多国家,有大量的土壤调查资料可以用来指导土地管理决策。这种土壤资料通常被低估和未得到充分利用,因为它通常不是一种用户友好的格式,一般作出土地管理决定的非土壤专家不能随时应用,土壤专家也不能立即进行所需的解释。这项工作的目的是开发一种方法,通过特殊用途的土壤分类和概念拓扑序列模型来传达土壤调查信息,以改善土地管理决策。该方法:(i)从大量详细出版的土壤调查技术报告及其大量定量和定性数据附录中回收和重新解释有价值的土壤调查遗留数据,(ii)使用他们能够理解并在需要时可用的词汇和图表向非土壤专家提供复杂或错综复杂的土壤调查信息。为了说明这种方法的广泛适用性,我们在世界上三个不同的地区——科威特、文莱和澳大利亚——进行了案例研究,每个地区都表现出截然不同的景观、气候、土壤类型和土地利用问题。土壤学家对公布的土壤调查信息进行了提炼,并确定了与景观位置相关的一组有限的土壤属性,这使得非土壤专家能够通过遵循用户友好的方法和格式来确定土壤类型。这为更广泛的受众提供了有关土壤的信息,而不是总是依靠有限数量的土壤专家来开展工作。案例研究中提供的细节适用于它们所针对的当地地区。但是,开发和使用的结构化方法适用于世界各地以外的其他地点:(i)文莱,特别是热带地区;(ii)科威特,特别是干旱和半干旱地区;(iii)澳大利亚冬季降雨地区,特别是地中海地区,以便建立类似的地方分类和概念模型。
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Soil survey data rescued by means of user friendly soil identification keys and toposequence models to deliver soil information for improved land management

In many countries there is a large source of soil survey information that could be used to guide land management decision. This soil information is commonly undervalued and underused, because it is usually not in a user-friendly format that non-soil specialists who generally make land management decisions can readily apply, nor are soil specialists always immediately available to conduct the interpretation required.

The aim of this work was to develop an approach to convey soil survey information by means of special-purpose soil classifications and conceptual toposequence models in order to improve land management decisions. The approach: (i) salvages and reinterprets valuable soil survey legacy data from the plethora of detailed published soil survey technical reports and their numerous appendices of quantitative and qualitative data, and (ii) delivers complex or intricate soil survey information to non-soil specialists using a vocabulary and diagrams that they can understand and have available to apply when they need it.

To illustrate the wide applicability of this approach, case studies were conducted in three different parts of the world – Kuwait, Brunei, and Australia, each of which exhibit vastly different landscapes, climates, soil types and land use problems. Pedologists distilled published soil survey information and identified a limited set of soil properties related to landscape position which enabled non-soil specialists to determine soil types by following user-friendly approach and format. This provides a wider audience with information about soils, rather than always relying on a limited number of soil specialists to conduct the work.

The details provided in the case studies are applicable for the local area that they were prepared for. However, the structured approach developed and used is applicable to other locations throughout the world outside of: (i) Brunei, especially in tropical landscapes, (ii) Kuwait, especially in arid and semi-arid landscapes and (iii) Australian winter rainfall landscapes, especially in Mediterranean landscapes – in order to establish similar local classifications and conceptual models.

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Editorial Board Soil legacy data rescue via GlobalSoilMap and other international and national initiatives Design and development of a generic spatial decision support system, based on artificial intelligence and multicriteria decision analysis A re-evaluation of the basal age in the DSDP hole at Site 534, Central Atlantic The application of machine learning for evaluating anthropogenic versus natural climate change
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