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The purpose of this paper is to upgrade the collaborative emergency ability of government in the tier of towns, realizing emergency resource share, emergency cost reduction and emergency efficiency improving. This paper mainly aims to solve the problem of forecasting the natural disaster happening year of every township collaborative region in Fangshan District.

First, classify the townships into five collaborative regions through grey clustering. Second, set up a grey disaster forecast model for the whole Fangshan District according the annals of disaster from 1985 to 2012, and forecast the disaster grade. Third, build a grey disaster forecast model for the collaborative regions after constructing the buffer operators of catastrophic sequence according the annals of disaster from 1949 to 2012.

The authors forecasted the happening year and flood grade of future disaster for the whole Fangshan District. The accurate degrees of both flood and drought year model are greater than 90 per cent. The accurate degree of insects calamity year is a little low, but the relative errors are all lower than 3 per cent in recent continuous three times, so in the whole, it can be used. For the collaborative regions, the authors forecasted the future disaster years of them. The accuracy rate of every model is greater than 90 per cent. The result shows that the forecast errors are acceptable.

In the models, for the purpose of good accuracy, the authors used different initial data. For example, in the forecast model for whole Fangshan District disaster year, the authors used the data from 1985 to 2012, while in the forecast model for the disaster grade of it, the authors used the data from 1949 to 2012. In the disaster year forecast model for collaborative region, the authors also used the data from 1949 to 2012. If the authors can find a model that has high accuracy rate by using all the date information, it will be better.

Township is the most basic level of government organization in China, researching on collaborative emergency in township will do help to take targeted precautions measures against calamity according to the characteristic there. At the same time realizing emergency cost reduction and emergency efficiency improving based on the advantages of emergency resource share, short rescue distance, little effects of communication destruction.

Because of the stochastic occurring of disasters, it is very important to forecast the happening time of disasters accurately. This paper forecasted the natural disaster happening time of Fangshan District through grey catastrophic model, aimed at giving decision support to related department and strengthen the disaster prevention power targetedly.

It is well known that the greater the system, the steadier it is, and the easier to forecast it. Fangshan District, Beijing, is a medium-sized and small system in regional research, while townships are small systems. It is rarely a big challenge for the authors to forecast the disaster years in Fangshan and its collaborative townships. In this paper, the authors used grey system model and Markov transfer matrix in forecasting the disaster years and the disaster grade of flood in Fangshan District. All of them are new trying to using grey system theory in disaster forecast for Fangshan District, Beijing.

The purpose of this report is to demonstrate open and distance education (ODE) can support poverty alleviation. Taking the practices of the Open University of China (the OUC) as an example, this paper aims to reveal how open universities make contributions to local residents in rural and remote areas.

Focusing on 25 poverty-stricken counties, the OUC had invested 58 million RMB to its learning centers in these counties from 2017 to 2020. The first one is to improve ICT and educational facilities in these learning centers. The second approach is to cultivate local residents with degree programs through ODE so as to promote local economic development. The third one is to design and develop training programs according to local context to meet the specific needs of local villagers.

After 3 years working, cloud-based classrooms and computer rooms have been set up. Bookstores have been founded and printed books have been donated. Hundreds of thousands of digital micro lectures have been supplied to these learning centers which have been improved and fully played their functions. Nearly 50,000 local residents have been directly benefited. Village leaders have helped lift local residents out of poverty. Poverty-stricken villagers have been financed to study on either undergraduate or diploma programs. Local residents have improved their skills by learning with the training programs offered by the OUC.

ODE is proved to be an effective way to eradicate poverty. Open universities are proved to be able to make contributions to social justice. By fulfilling its commitments to eliminate poverty within the national strategy framework, the OUC has built its brand nationwide.