Maps of Australian soil composition measured with visible-near infrared spectra

We measured the spectra of 4606 surface soil samples from across Australia using a vis-NIR spectrometer. These spectra provide an integrative measure that provides information on the fundamental characteristics and composition of the soil, including colour, iron oxide, clay and carbonate mineralogy, organic matter content and composition, the amount of water present and particle size. This soil information content of the spectra was summarised using a principal component analysis (PCA). We used model trees to derive statistical relationships between the scores of the PCA and 31 predictors that were readily available and we thought might best represent the factors of soil formation (climate, organisms, relief, parent material, time and the soil itself). The models were validated and subsequently used to produce digital maps of the information content of the spectra, as summarised by the PCA, with estimates of prediction error at 3-arc seconds (around 90 m) pixel resolution. The maps might be useful in situations requiring high-resolution, quantitative soil information e.g. in agricultural, environmental and ecologic modelling and for soil mapping and classification.

Attributes:
Units of measurement:
1. Principal component 1;
2. Principal component 3;
3. Principal component 3.

For interpretations please see Viscarra Rossel & Chen (2011).

Data Type: Float Grid.

Map Projection: Geographic.

Datum: GDA94.

Map units: Decimal degrees.

Resolution: 0.00083333333 degrees.

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本研究采用可见-近红外（vis-NIR）光谱仪，对澳大利亚全境的4606个表层土壤样本采集光谱数据。此类光谱可作为综合表征手段，反映土壤的基础特性与组成信息，涵盖颜色、氧化铁、黏土与碳酸盐矿物组成、有机质含量与组分、含水量以及粒径分布。
我们通过主成分分析（PCA）对光谱所蕴含的土壤信息进行降维汇总。随后，利用模型树构建了PCA得分与31项易获取预测因子间的统计关联模型——这些预测因子被认为可最优表征土壤形成的五大要素（气候、生物、地形、母质、时间，以及土壤自身）。
经模型验证后，我们基于该模型生成了以PCA汇总的光谱信息含量的数字地图，其像素分辨率可达3弧秒（约90米），并附带预测误差估算值。此类地图可应用于诸多需要高分辨率定量土壤信息的场景，例如农业、环境与生态建模，以及土壤制图与分类工作。

属性：
测量单位：
1. 主成分1；
2. 主成分3；
3. 主成分3。
相关解释可参见Viscarra Rossel & Chen（2011）。
数据类型：浮点网格（Float Grid）。
地图投影：地理坐标系（Geographic）。
基准面：GDA94。
地图单位：十进制度。
分辨率：0.00083333333度。
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nrows 40373；
xllcorner 112.91246795654；
yllcorner -43.642475129116；
cellsize 0.00083333333333333；
NODATA_value -9999；
byteorder LSBFIRST。