| Outlier identification and reasonable sampling number of soil nutrient at county level |
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| DOI：10.7606/j.issn.1000-7601.2012.02.10 |
| Key Words: soil nutrient spatial outlier reasonable sampling number |
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| Abstract: |
| The aim of our experiment was to provide more accurate datasets and less cost of sampling and analysis for evaluating the nutrient quality of arable land at a county level. The Quartile method and the local Moran’s I method were used to identify the global and local outlier of AP, AN and AK in Baishui County. Spatial characteristics were analyzed after removing the outlier. The classical statistics method (Cochran formula) and geo-statistics method (Kriging) were used to calculate the reasonable sampling number of soil nutrient. The results showed that 3 global outliers were detected in AN and AK, the number of global outlier in AP was 7. The local outliers in AN, AK and AP were 89, 90 and 92, respectively. Three of the soil nutrient performed significant spatial correlation. The coefficient of variation (CV) fell down after outliers were removed. Cochran method was more suitable for the research of the general trend of soil nutrient while the reasonable sampling number calculated by Kriging method could present the local spatial characteristics of the soil nutrient more accurately. |
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