Remotely-Sensed Arable Land Production Potential Mornitoring Based On Crop Growth Dynamics

In order to monitor agricultural condition better, and promote the potential production of arable land in Shaanxi Province, this thesis aims to study the crop planting patterns and types and the productivity potential of arable lands, taking the main crops as objects. First, crop planting types are indentified integrating 10-year (2003-2012) remote sensing datasets, meteorological datasets, soil properties data and basic geographic data. This is done according to the dynamic characteristics of typical surface features extracted from long-term remote sensing images and the determined inter-annual dynamic thresholds.Second, this thesis constructs a potential productivity estimation model for arable lands agreed with the actual conditions of the study area, using the crop type recognition results, the improved "mechanism method" model and the four factors (light, temperature, water, soil) which affecting crop growth and achieves the evaluation of the arable land potential productivity quality in Shaanxi Province using the potential productivity anomaly index.The results of crop planting types’identification are validated through spatial and quantitative aspects. The total classification accuracy and Kappa coefficient were 88.18% and 59.64% respectively according to spatial comparative analysis and the overall consistency of classification was 81.24% according to quantitative analysis. The results of arable land potential productivity estimation are validated using the statistical datasets, the analysis result conformed to the linear relationship, R2 was 0.6955. The evaluation results of arable land production potential was the positive anomaly more than negative anomaly of arable land production potential in 2005,2008,2009,2010 and 2012.The results indicate that combining phonological information with time series datasets and using the classification method presented in this thesis could identify the crop planting types effectively in large scale. The improved arable land potential productivity estimation model combining with the information of crop types could achieve the estimation of the arable land potential productivity in Shaanxi Province, and the production potential anomaly index is able to make a comprehensive evaluation for arable land production potential of 10 years in Shaanxi Province effectively.