Soil permeability DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

Soil permeability is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Northern Australia Water Resource Assessment (NAWRA) through the digital soil mapping process (DSM). Soil permeability describes the ability of a soil to transmit water internally by its least permeable layer (rate of water movement into and through the soil profile). This soil permeability raster data represents a modelled dataset of permeability as described by the National Committee on Soil and Terrain 2009 (NCST) and is derived from field measured site data and environmental covariates. Data values are: 1 Very slowly permeable, 2 Slowly permeable, 3 Moderately permeable, 4 Highly permeable. Soil permeability is a parameter used in land suitability assessments of irrigation efficiency and soil wetness (in combination with soil drainage indicating site and soil conditions that result in poor soil aeration for plant growth). This raster data provides improved soil information used to identify opportunities and promote detailed investigation for a range of sustainable regional development options and was created within the ‘Land Suitability’ activity of the CSIRO NAWRA. A companion dataset and statistics reflecting reliability of this data are also provided and can be found described in the lineage section of this metadata record. Processing information is supplied in ranger R scripts and attributes were modelled using a Random Forest approach.\nThe DSM process is described in the CSIRO NAWRA published report ‘Digital soil mapping of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'. The land suitability assessment this dataset underpins is described in the CSIRO NAWRA published report ‘Land suitability of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'.\nLineage: This soil permeability dataset has been generated from a range of inputs and processing steps. Following is an overview. For more information refer to the CSIRO NAWRA published reports and in particular 'Digital soil mapping of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment, part of the National Water Infrastructure Development Fund: Water Resource Assessments. CSIRO, Australia 2018'. 1. Collated existing data (relating to: soils, climate, topography, natural resources, remotely sensed, of various formats: reports, spatial vector, spatial raster etc). 2. Selection of additional soil and land attribute site data locations by a conditioned Latin hypercube statistical sampling method applied across the covariate data space. 3. Fieldwork was carried out to collect new attribute data, soil samples for analysis and build an understanding of geomorphology and landscape processes. 4. Database analysis was performed to extract the data to specific selection criteria required for the attribute to be modelled. 5. The R statistical programming environment was used for the attribute computing. Models were built from selected input data and covariate data using predictive learning from a Random Forest approach implemented in the ranger R package. 6. Create soil permeability Digital Soil Mapping (DSM) attribute raster dataset. DSM data is a geo-referenced dataset, generated from field observations and laboratory data, coupled with environmental covariate data through quantitative relationships. It applies pedometrics - the use of mathematical and statistical models that combine information from soil observations with information contained in correlated environmental variables, remote sensing images and some geophysical measurements. 7. Companion predicted reliability data was produced from the 500 individual Random Forest attribute models created. 8. QA Quality assessment of this DSM attribute data was conducted by three methods. Method 1: Statistical (quantitative) method of the model and input data. Testing the quality of the DSM models was carried out using data withheld from model computations and expressed as OOB and R squared results, giving an estimate of the reliability of the model predictions. These results are supplied. Method 2: Statistical (quantitative) assessment of the spatial attribute output data presented as a raster of the attributes “reliability”. This used the 500 individual trees of the attributes RF models to generate 500 datasets of the attribute to estimate model reliability for each attribute. For categorical attributes the method for estimating reliability is the Confusion Index. This data is supplied. Method 3: Collecting independent external validation site data combined with on-ground expert (qualitative) examination of outputs during validation field trips. Across each of the study areas a two week validation field trip was conducted using a new validation site set which was produced by a random sampling design based on conditioned Latin Hypercube sampling using the reliability data of the attribute. The modelled DSM attribute value was assessed against the actual on-ground value. These results are published in the report cited in this metadata record.

土壤渗透率（Soil permeability）是澳大利亚北部水资源评估（Northern Australia Water Resource Assessment, NAWRA）土地适宜性评估的18项土壤属性之一，该评估依托数字土壤制图流程（Digital Soil Mapping, DSM）开展。
土壤渗透率指的是土壤通过其渗透性最弱的土层实现内部水分传输的能力，即水分进入并穿过土壤剖面的速率。
本土壤渗透率栅格数据为依据《国家土壤与地形委员会2009年报告》（National Committee on Soil and Terrain 2009, NCST）所定义的渗透率建模数据集，其数据来源为野外实测点位数据与环境协变量。数据取值如下：1 极慢渗透性，2 慢渗透性，3 中等渗透性，4 高渗透性。
土壤渗透率是灌溉效率与土壤湿度相关土地适宜性评估的核心参数之一，该参数结合土壤排水状况，可表征影响植物生长的土壤通气不良的点位与土壤条件。
本栅格数据提供了优化后的土壤信息，可用于识别可持续区域发展机遇并推动相关精细化调研，其由澳大利亚联邦科学与工业研究组织（Commonwealth Scientific and Industrial Research Organisation, CSIRO）主导的NAWRA“土地适宜性”项目所生成。
本数据集还配套提供了反映数据可靠性的辅助数据集与统计结果，相关说明可参见本元数据记录的谱系（Lineage）章节。
数据处理信息已封装于ranger R脚本中，土壤属性建模采用随机森林（Random Forest）方法实现。

数字土壤制图流程的详细说明可参见CSIRO NAWRA发布的技术报告《菲茨罗伊、达尔文与米切尔集水区数字土壤制图——澳大利亚联邦科学与工业研究组织北部澳大利亚水资源评估致澳大利亚政府的技术报告》。
本数据集所支撑的土地适宜性评估内容，可参见CSIRO NAWRA发布的技术报告《菲茨罗伊、达尔文与米切尔集水区土地适宜性——澳大利亚联邦科学与工业研究组织北部澳大利亚水资源评估致澳大利亚政府的技术报告》。

谱系（Lineage）：本土壤渗透率数据集由多类输入数据与一系列处理步骤生成，以下为流程概述。如需获取详细信息，请参考CSIRO NAWRA发布的相关报告，尤其参见《菲茨罗伊、达尔文与米切尔集水区数字土壤制图——澳大利亚联邦科学与工业研究组织北部澳大利亚水资源评估，隶属于国家水利基础设施发展基金水资源评估项目，澳大利亚CSIRO，2018年》。
1. 整合现有数据：涵盖土壤、气候、地形、自然资源、遥感等多类数据，格式包括报告、空间矢量、空间栅格等。
2. 基于协变量数据空间，通过条件拉丁超立方统计采样方法选取补充土壤与土地属性点位数据的采集位置。
3. 开展野外工作，采集新的属性数据与分析用土壤样本，并构建对地貌与景观过程的认知。
4. 开展数据库分析，按照属性建模所需的筛选标准提取对应数据。
5. 采用R统计编程环境开展属性计算：基于筛选后的输入数据与协变量数据，通过ranger R包实现的随机森林预测学习方法构建模型。
6. 生成土壤渗透率数字土壤制图（DSM）属性栅格数据集。DSM数据为地理参考数据集，由野外观测数据、实验室分析数据与环境协变量数据通过定量关联关系融合生成，其依托土壤计量学（pedometrics）方法——即结合土壤观测信息与相关环境变量、遥感影像及部分地球物理测量信息的数学与统计模型。
7. 基于所构建的500个独立随机森林属性模型，生成配套的预测可靠性数据。
8. 质量保证（Quality Assurance, QA）：本DSM属性数据采用三种方法开展质量评估。方法1：模型与输入数据的统计（定量）评估。通过袋外数据（OOB）测试DSM模型质量，以袋外误差与决定系数（R²）结果表征模型预测可靠性，相关评估结果已提供。方法2：空间属性输出数据的统计（定量）评估，以“可靠性”栅格形式呈现。该方法利用随机森林模型的500棵独立决策树生成500个属性数据集，以此估算每个属性的模型可靠性；对于分类属性，可靠性估算采用混淆指数（Confusion Index）方法。相关数据已提供。方法3：采集独立外部验证点位数据，并结合验证野外考察期间的专家实地（定性）输出检查。在每个研究区，均开展为期两周的验证野外考察，采用基于属性可靠性数据的条件拉丁超立方采样随机设计生成的全新验证点位集。将建模得到的DSM属性值与实地实测值进行比对，相关评估结果已发表于本元数据记录引用的报告中。