FGARA Digital Soil Mapping Output - Soil Surface Structure

Soil surface structure is one of 19 attributes of soils chosen to underpin the land suitability assessment of the Flinders and Gilbert Agricultural Resource Assessment (FGARA) project through the digital soil mapping process (DSM). This raster data (in GeoTIFF format) represents a modelled surface of structure of surface soil using descriptions from the Australian Soil and Land Survey Field Handbook (ASLSFH). This data is derived from measured site data and environmental covariates. The data is used in assessment of soil physical factors eg water infiltration, seedling establishment and machinery workability.\nCodes are: 1 Single grain, 2 Massive or weak, 3 Moderate/strong and fine, 4 Moderate/strong and coarse.\nThe attribute data file is named "StructureClasses.tif". \nAlso included are data reflecting confidence of the main dataset. This file is named "Structure_CI.tif". "CI" represents "confusion index".\nThe DSM process is described in the technical report: Bartley R, Thomas MF, Clifford D, Phillip S, Brough D, Harms D, Willis R, Gregory L, Glover M, Moodie K, Sugars M, Eyre L, Smith DJ, Hicks W and Petheram C (2013) Land suitability: technical methods. A technical report to the Australian Government for the Flinders and Gilbert Agricultural Resource Assessment (FGARA) project, CSIRO.\nThis raster data provides improved soil information to identify opportunities and promote detailed investigation for a range of sustainable development options and was created within the “Land Suitability” component of FGARA projects.\nLineage: This data has been created from a range of inputs and processing steps. Below is an overview. Broadly, the steps were to: \n1. Collate existing data (data related to: climate, topography, soils, natural resources, remotely sensed etc of various formats; reports, spatial vector, spatial raster etc.). \n2. Select additional soil and attribute site data by Latin hypercube statistical sampling method applied across the covariate space. \n3. Carry out fieldwork to collect additional soil and attribute data and understand geomorphology and landscapes. \n4. Build models from selected input data and covariate data using predictive learning via rule ensembles in the RuleFit3 software. \n5. Create Soil Surface Structure Digital Soil Mapping (DSM) key attribute output data. DSM is the creation and population of a geo-referenced database, generated using field and laboratory observations, coupled with environmental 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.\nQuality assessment of the attribute data is mapped spatially as a function of the model output by evaluating the rigour of the DSM attribute data using non-parametric bootstrapping of the DSM modelling. For more information refer to “Land suitability: technical methods. A technical report to the Australian Government for the Flinders and Gilbert Agricultural Resource Assessment (FGARA) project”.

土壤表层结构是为支撑弗林德斯与吉尔伯特农业资源评估（Flinders and Gilbert Agricultural Resource Assessment, FGARA）项目的土地适宜性评价而遴选的19项土壤属性之一，该遴选基于数字土壤制图（Digital Soil Mapping, DSM）流程开展。本栅格数据采用GeoTIFF格式，依托《澳大利亚土壤与土地调查野外手册》（Australian Soil and Land Survey Field Handbook, ASLSFH）中的描述，构建了表层土壤结构的模拟表面。本数据源于实测点位数据与环境协变量，可用于评估土壤物理因子，例如水分入渗、幼苗建植与农机作业适宜性。

其编码规则如下：1 单粒结构，2 块状或弱结构体，3 中-强发育细粒结构体，4 中-强发育粗粒结构体。

该属性数据文件命名为"StructureClasses.tif"。此外还包含反映主数据集置信度的数据，其文件名为"Structure_CI.tif"，其中"CI"即混淆指数（confusion index）。

DSM流程的详细说明可参阅技术报告：Bartley R, Thomas MF, Clifford D, Phillip S, Brough D, Harms D, Willis R, Gregory L, Glover M, Moodie K, Sugars M, Eyre L, Smith DJ, Hicks W 与 Petheram C (2013) 《土地适宜性：技术方法》，为澳大利亚政府提交的弗林德斯与吉尔伯特农业资源评估（FGARA）项目技术报告，CSIRO。

本栅格数据提供了更精准的土壤信息，可用于识别开发机遇并推动针对各类可持续发展方案开展详细调研，其产出隶属于FGARA项目的“土地适宜性”模块。

数据溯源：本数据集由多类输入数据经多步处理流程生成，概述如下。整体流程如下：
1. 整合现有数据：涵盖气候、地形、土壤、自然资源、遥感等多类格式的数据，以及各类报告、空间矢量、空间栅格等数据载体。
2. 基于协变量空间，采用拉丁超立方统计抽样法选取补充土壤与属性点位数据。
3. 开展野外调查，采集补充土壤与属性数据，并解析地貌与景观特征。
4. 基于RuleFit3软件中的规则集成预测学习方法，利用筛选后的输入数据与协变量数据构建模型。
5. 生成土壤表层结构数字土壤制图（DSM）核心属性输出数据。数字土壤制图即通过定量关系将野外与实验室观测数据与环境数据相结合，构建并填充地理参考数据库的过程。其依托土壤计量学（pedometrics）——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应用方法。

属性数据的质量评估通过对DSM建模开展非参数Bootstrap（自助法）抽样，以此评估DSM属性数据的严谨性，并将评估结果以空间分布图形式关联模型输出。更多细节可参阅《土地适宜性：技术方法》，为澳大利亚政府提交的弗林德斯与吉尔伯特农业资源评估（FGARA）项目技术报告。

搜集汇总

背景与挑战

背景概述

该数据集是弗林德斯和吉尔伯特农业资源评估（FGARA）项目的一部分，通过数字土壤制图（DSM）方法生成的土壤表面结构栅格数据（GeoTIFF格式），用于支持土地适宜性评估。数据基于现场测量和环境协变量建模，包含四个结构类别（如单粒、大块状等），并附带置信度指数文件，以评估土壤物理特性如水分渗透和机械可操作性。