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首页> 外文期刊>Soil Science Society of America Journal >Optimal Soil Raster Unit Resolutions in Estimation of Soil Organic Carbon Pool at Different Map Scales
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Optimal Soil Raster Unit Resolutions in Estimation of Soil Organic Carbon Pool at Different Map Scales

机译:不同地图比例尺下土壤有机碳库估算中最佳土壤栅格单元分辨率

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摘要

A proper soil raster unit resolution for grid sampling design is important to estimate the soil organic carbon (SOC) pool at certain map scales, which is related to the soil sampling density and the accuracy of the estimation. A series of raster soil unit data sets at varying resolutions were derived from different vector soil unit data sets at six map scales of 1:50,000, 1:200,000, 1:500,000, 1:1,000,000, 1:4,000,000, and 1:14,000,000 in the Tai-Lake region of China. Four indices-soil type number (STN) and area (AREA), average SOC density (ASOCD), and total SOC stocks (SOCS) of surface paddy soils-were attributed from all these vector and raster units data sets. Subjected to the four index values (IV) from parent vector unit data set, the relative variability (VIV, %) from raster unit data set was used to assess its accuracy and redundancy, which reflects uncertainty and workload of SOC estimation, respectively. Optimal raster unit resolutions were generated and suggested for each map scale's SOC estimation, in which the soil raster unit data set can hold the same accuracy as its parent vector unit data set without any redundancy when VIV < 1% of all the four indices was assumed as criteria to the assessment. A relationship between map scale (1: x) of soil vector unit and its optimal grid resolution (y, km) was found to be: y = -8.03 x 10(-6)x(2) + 0.0256x-0.087 (R-2 = 0.998, p < 0.05). The results may serve for soil unit conversion from vector to raster and soil grid sampling design at a certain map scale in the investigation of regional SOC pool
机译:对于网格采样设计而言,合适的土壤栅格单位分辨率对于估计某些地图比例下的土壤有机碳(SOC)池非常重要,这与土壤采样密度和估计的准确性有关。来自不同矢量土壤单位数据集的一系列分辨率不同的栅格土壤单位数据集分别来自六个地图比例,分别为1:50,000、1:200,000、1:500,000、1:1,000,000、1:4,000,000和1:14,000,000中国的太湖地区。从所有这些向量和栅格单位数据集中,得出了四个指标:土壤类型号(STN)和面积(AREA),平均SOC密度(ASOCD)和表层土壤的总SOC储量(SOCS)。接受来自父向量单位数据集的四个索引值(IV),使用来自栅格单位数据集的相对变异性(VIV,%)评估其准确性和冗余度,这分别反映了SOC估计的不确定性和工作量。生成最佳栅格单位分辨率并建议用于每个地图比例尺的SOC估计,其中假定VIV <所有四个指标的1%,土壤栅格单位数据集可以保持与其父向量单位数据集相同的精度,而没有任何冗余。作为评估的标准。发现土壤矢量单位的地图比例尺(1:x)与最佳网格分辨率(y,km)之间的关系为:y = -8.03 x 10(-6)x(2)+ 0.0256x-0.087(R -2 = 0.998,p <0.05)。该结果可用于在一定比例尺上将土壤单位从矢量转换为栅格,并在一定比例尺的土壤网格采样设计中用于区域SOC库的研究。

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