[Review of change detection methods using multi-temporal remotely sensed images].

With the development of platforms and sensors, continuous repetition of remote sensing observation of the earth surface has been realized, and a mass of multi-source, multi-scale, multi-resolution remote sensing data has been accumulated. Those images have detailedly recorded the changing process of ground objects on the earth, which makes the long term global change research, such as change detection, based on remote sensing become possible, and greatly push forward the research on image processing and application. Although plenty of successful research has been reported, there are still enormous challenges in multi-temporal imagery change detection. A relatively complete mature theoretical system has not formed, and there is still a lack of systematic summary of research progress. Firstly, the current progress in change detection methods using multi-temporal remotely sensed imagery has been reviewed in this paper. Then, the methods are classified into three categories and summarized according to the type and amount of the input data, single-phase post-classification comparison, two-phase comparison, and time series analysis. After that, the possible existing problems in the current development of multi-temporal change detection are analyzed, and the development trend is discussed finally.

[Research on spatial characteristic of non-point source pollution in Liaohe River basin].

The spatial characteristic of non-point source pollution in the Liaohe River was studied. Coupling the remote sensing data and non-point source (NPS) models, a method of assessing NPS pollution by pixel unit was developed, aiming to analyse the NPS pollution characteristic of Liaohe River basin in 2010, in turn to identify the main polluted areas and prevention measures. The work will provide technical supports for pollution prevention in Liaohe River basin. The results showed that in 2010, the total discharge of total nitrogen (TN) was 1.03 x 10(5) t, the total phosphorus (TP) was 6.8 x 10(3) t, the chemical oxygen demand (COD) was 1.31 x 10(5) t and the ammonia nitrogen (NH+4 -N) was 1. 8 x 10(4) t. The main pollution source of NPS was from agriculture. The contributions of NPS pollution to water quality were 67.4% , 76.4% , 39.4% and 21.9% for TN, TP, COD and NH+4 -N, respectively. The south of Liaohe River basin was the most serious polluted area, followed by the northeast areas. In this research, a method was build to estimate the NPS loads based on remote sensing pixel and the spatial characteristic of non-point source pollution in Liaohe River in 2010 was analysed, which will provide support for pollution prevention in Liaohe River.