Evaluating and Classifying Field-Scale Soil Nutrient Status in Beijing using 3S Technology

More attention has been paid to estimating soil nutrient status, along with a sharp decrease in total farmland acreage, especially in Beijing Municipality. However, traditional site-specific investigation makes it impossible to apply it to large scale monitoring. The objective of this study was to evaluate and classify soil nutrient status using advanced 3S (global positioning system, GPS; remote sensing, RS; and geographic information system, GIS) technology. Firstly, multi-temporal Landsat TM 5 images with 30 m spatial resolution were utilized to identify the field-scale farmlands. The overall classification accuracy reached 86.96%, with a kappa coefficient of 0.743. Additionally, the correlation coefficient (r) reached 0.942 by comparing the remote sensing-based farmland area with the statistical data. Subsequently, organic matter, total nitrogen, available phosphorus and available potassium from 7,435 field sample points positioned by GPS receiver, were used to generate a comprehensive soil nutrient index in GIS software, according to the classification criteria of Beijing Soil and Fertilizer Workshop. Finally, a classification map of field-scale soil nutrient levels (very high, high, moderate, low & very low) was created using the farmlands as mask layers. The analysis results showed that the soils at moderate and low levels dominated the Beijing’s farmlands, which accounted for 46.1% and 39.1%, respectively; high and very low level soils were the second place whose ratios were 10.4% and 4.3%, respectively; and very high level soils could be rarely found. Yanqing County, Tongzhou District and Changping District have better soil nutrient status as a whole. © 2012 Friends Science Publishers