Soil rockiness DSM data of the Southern Gulf catchments (NT and Qld) generated by the Southern Gulf Water Resource Assessment

Soil rockiness is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Southern Gulf Water Resource Assessment (SOGWRA) through the digital soil mapping process (DSM). Soil rockiness represents areas that are excluded from agricultural production due to the abundance and size of rock outcrop, surface coarse fragments, profile coarse fragments and hard segregations. This raster data represents a modelled dataset of a set of rules applied to the above features for the top 0.10m of soil and is derived from field measured site data and environmental covariates. Data values are: 0 Not rocky, 1 Rocky. Descriptions of the rules defining rockiness are supplied with this data. Rockiness is a parameter used in land suitability assessments as restrictions relate to the intensity of rock picking required in land preparation, root crop harvesting, reduces crop growth and use of agricultural machinery particularly in the plough zone. This raster data provides improved soil information used to underpin and 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 SOGWRA. 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. The DSM process is described in the CSIRO SOGWRA published report ‘Soils and land suitability for the Southern Gulf catchments’. A technical report from the CSIRO Southern Gulf Water Resource Assessment to the Government of Australia. The Southern Gulf Water Resource Assessment provides a comprehensive overview and integrated evaluation of the feasibility of aquaculture and agriculture development in the Southern Gulf catchments NT and Qld as well as the ecological, social and cultural (indigenous water values, rights and aspirations) impacts of development. \nLineage: This soil rockiness dataset has been generated from a range of inputs and processing steps. Following is an overview. For more information refer to the CSIRO SOGWRA published reports and in particular ' Soils and land suitability for the Southern Gulf catchments’. A technical report from the CSIRO Southern Gulf Water Resource Assessment to the Government of Australia. 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 rockiness 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 confusion matrix 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: A workshop was conducted in March 2023 to review DSM soil attribute and land suitability products and facilitated an alternative to the field external validation carried out in other northern Australia water resource assessments. Stakeholders from the NT and Qld jurisdictions reviewed, evaluated and discussed the soundness of the data and processes. The workshop desk top assessment approach provided recommendations for acceptance, improvement and re-modelling of attributes based on expert knowledge and understanding of the soil distribution and landscape in the study area and available data.\n

土壤石质性（"Soil Rockiness"）是为通过数字土壤制图（"Digital Soil Mapping", DSM）流程支撑南湾水资源评估（"Southern Gulf Water Resource Assessment", SOGWRA）的土地适宜性评价而选取的18项土壤属性之一。土壤石质性指因岩石露头、地表粗碎屑、剖面粗碎屑及硬结核的丰度与规模而被排除于农业生产之外的区域。本栅格数据为针对表层0.10米土壤上述特征应用一系列规则生成的建模数据集，其数据源为野外实测样点数据与环境协变量。数据取值为：0 无石质性，1 有石质性。本数据集附带定义石质性的规则说明文档。

石质性是土地适宜性评价中使用的一项参数，其限制条件与整地所需的拣石强度、块根作物采收难度、作物生长受抑程度，以及农业机械（尤其是犁耕区域的农机）的使用可行性密切相关。本栅格数据提供了优化后的土壤信息，用于支撑各类可持续区域发展方案的机遇识别与深化调研，由澳大利亚联邦科学与工业研究组织（"Commonwealth Scientific and Industrial Research Organisation", CSIRO）下属SOGWRA项目的“土地适宜性”工作生成。本数据集附带反映数据可靠性的配套数据集与统计结果，相关说明可在本元数据记录的谱系（"Lineage"）章节中查阅。

处理代码以ranger R脚本形式提供，属性建模采用随机森林（"Random Forest"）方法。数字土壤制图流程的详细说明可参见CSIRO SOGWRA发布的技术报告《南湾流域土壤与土地适宜性》，该报告为CSIRO向澳大利亚政府提交的南湾水资源评估技术报告。南湾水资源评估项目对北领地（NT）与昆士兰州（QLD）南湾流域的水产养殖与农业开发可行性开展了全面综述与综合评估，并分析了开发活动带来的生态、社会及文化（原住民水价值观、权利与诉求）影响。

数据谱系：本土壤石质性数据集由一系列输入数据与处理步骤生成，以下为流程概览。如需了解更多细节，请参阅CSIRO SOGWRA发布的相关报告，尤其是《南湾流域土壤与土地适宜性》技术报告（该报告为CSIRO向澳大利亚政府提交的南湾水资源评估技术报告）。
1. 整合现有数据：涵盖土壤、气候、地形、自然资源、遥感数据等，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抽样方法选取额外的土壤与土地属性样点位置。
3. 开展野外调查，采集新的属性数据与土壤分析样本，并建立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特定筛选标准提取数据。
5. 采用R统计编程环境开展属性计算，通过ranger R包实现的随机森林预测学习方法，基于筛选后的输入数据与协变量数据构建模型。
6. 生成土壤石质性数字土壤制图（DSM）属性栅格数据集。数字土壤制图数据为地理参考数据集，通过定量关系将野外观测数据、实验室分析数据与环境协变量数据相结合生成，其应用了土壤计量学（"Pedometrics"）方法，即通过数学与统计模型，将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所包含的信息进行融合。
7. 基于构建的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. 采用三种方法对本DSM属性数据开展质量评估（"Quality Assurance", QA）：
方法1：模型与输入数据的统计（定量）评估。通过模型训练时预留的测试数据集检验DSM模型质量，结果以袋外（"Out-of-Bag", OOB）数据与混淆矩阵形式呈现，用于估算模型预测的可靠性，相关评估结果已随数据集提供。
方法2：对以“可靠性”栅格形式输出的空间属性数据开展统计（定量）评估。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法，相关数据已随数据集提供。
方法3：于2023年3月开展研讨会，对DSM土壤属性与土地适宜性成果开展评审，作为澳大利亚北部其他水资源评估项目中野外外部验证的替代方案。来自北领地与昆士兰州管辖范围内的利益相关方对数据与处理流程的合理性开展了审查、评估与讨论。本次研讨会桌面评估方法基于专家对研究区土壤分布、景观特征及可用数据的认知，为属性数据的验收、改进与重新建模提供了建议。