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Accurately measuring soil organic matter content (SOM) in paddy fields is important because SOM is one of the key soil properties controlling nutrient budgets in agricultural production systems. Estimation of this soil property at an acceptable level of accuracy is important; especially in the case when SOM exhibits strong spatial dependence and its measurement is a time- and labor-consuming procedure. This study was conducted to evaluate and compare spatial estimation by kriging and cokriging with remotely sensed data to predict SOM using limited available data for a 367-[km.sup.2] study area in Haining City, Zhejiang Province, China. Measured SOM ranged from 5.7 to 40.4 g [kg.sup.-1], with a mean of 19.5 g [kg.sup.-1]. Correlation analysis between the SOM content of 131 soil samples and the corresponding digital number (DN) of six bands (Band 1-5 and Band 7) of Landsat Enhanced Thematic Mapper (ETM) imagery showed that correlation between SOM and DN of Band I was the highest (r = -0.587). We used the DN of Band 1 as auxiliary data for the SOM prediction, and used descriptive statistics and the kriging standard deviation (STD) to compare the reliabilities of the predictions. We also used cross-validation to validate the SOM prediction. Results indicate that cokriging with remotely sensed data was superior to kriging in the case of limited available data and the moderately strong linear relationship between remotely sensed data and SOM content. Remotely sensed data such as Landsat ETM imagery have the potential as useful auxiliary variables for improving the precision and reliability of SOM prediction. Abbreviations: CV, coefficient of variation; DN, digital number; ETM, Landsat Enhanced Thematic Mapper; NDVI, normalized difference vegetation index; SE, standard error of the estimate; SOM, soil organic matter content; STD, standard deviation; TM, Landsat Thematic Mapper.

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. [ABSTRACT FROM AUTHOR]