Sampling method of meso-scale crop growth information monitoring based on multi-temporal remote sensing images

At present the application effect of Precision Agriculture which is developing rapidly is highly affected by the distribution and quantity of monitoring sensor equipment. The typicalness of the monitoring location was determined by the distribution of monitoring sensor equipment, and the level of?capital?investment was determined by the quantity of the monitoring sensor equipment. How to design an efficient and economical monitoring method is the key issue to get typical monitoring results. Firstly several existing agricultural monitoring methods were evaluated, then a monitoring method which based on the Vegetation Index and Proportional Probability Sampling (PPS) was proposed. At last, a case study was carried out in Yanqing county, Beijing. The results showed that: 1) By the remote sensing theoretical support, the effect of the method could be verified well by reference data; 2) The method was easy, convenient and repeatable to implement; 3) The method can be used not only for monitoring points program design, but also for monitoring points program validation. After validation, the overall accuracy of the new method in this paper achieved 85%. The method can meet the requirements of representativeness, typicalness and stability for agricultural monitoring applications.