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Spatial Estimation of Soil Total Nitrogen Using Cokriging with Predicted Soil Organic Matter Content

机译:预测土壤有机质含量的协同克里格法估算土壤总氮的空间

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Accurate measurement of soil total N (TN) content in agricultural fields is important to guide reasonable application of nitrogenous fertilizer. Estimation of soil TN content with limited in situ data at an acceptable level of accuracy is important because laboratory measurement of N is a time- and labor-consuming procedure. This study was conducted to evaluate cokriging of soil TN with predicted soil organic matter (SOM) content as auxiliary data. The SOM content was predicted by cokriging with a digital number (DN) of Band 1 of Landsat Enhanced Thematic Mapper (ETM) imagery. Soil TN content was estimated by using 88 soil samples for prediction and 43 soil samples for validation in a study area of 367 km2 in Haining City, China. Field-measured soil TN content ranged from 0.47 to 2.48 g kg-1, with a mean of 1.25 g kg-1. Soil TN content of all 131 soil samples including samples for prediction and validation was highly correlated with measured (r = 0.81, p < 0.01) and predicted (r = 0.81, p < 0.01) SOM content in paddy fields. Then, the predicted SOM content was used as auxiliary variable for the prediction of soil TN content. By using the 43 samples for validation, we had a mean error (ME) of 0.03 g kg-1 and a root mean square error (RMSE) of 0.31 g kg-1 for kriging, and a mean error of 0.00 g kg-1 and a root mean square error of 0.25 g kg-1 for cokriging, respectively. Our results indicate cokriging with predicted SOM content data was superior to kriging. In addition, predicted data of the auxiliary variable have the potential to be useful for cokriging when the predicted auxiliary data have high prediction accuracy.
机译:准确测量农田土壤总氮(TN)含量对指导合理施用氮肥很重要。用有限的原位数据以可接受的准确度估算土壤总氮含量非常重要,因为实验室对氮的测定非常耗时且费力。进行了这项研究,以评估土壤TN的协同克里格法,并以预测的土壤有机质(SOM)含量作为辅助数据。 SOM内容是通过与Landsat Enhanced Thematic Mapper(ETM)图像的波段1的数字编号(DN)共克里金法预测的。在中国海宁市一个367 km2的研究区域中,通过使用88个土壤样本进行预测和43个土壤样本进行验证来估算土壤总氮含量。实地测得的土壤总氮含量为0.47至2.48 g kg-1,平均为1.25 g kg-1。包括用于预测和验证的样品在内的所有131个土壤样品的土壤总氮含量与稻田中测得的SOM含量(r = 0.81,p <0.01)和预测的(r = 0.81,p <0.01)高度相关。然后,将预测的SOM含量用作预测土壤TN含量的辅助变量。通过使用这43个样本进行验证,克里金法的平均误差(ME)为0.03 g kg-1,克里格的均方根误差(RMSE)为0.31 g kg-1,平均误差为0.00 g kg-1对于协同克里金,均方根误差分别为0.25 g kg-1。我们的结果表明,具有预测的SOM内容数据的协同克里金法优于克里金法。另外,当预测的辅助数据具有高的预测精度时,辅助变量的预测数据具有对协同克里金有用的潜力。

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