No abstract

English writing, as a basic language skill for second language learners, is being paid close attention to. How to achieve better results in English teaching and how to develop students' writing competence remain an arduous task for English teachers. Based on the review of the concerning literature from other researchers as well as a summery of the author's own experimental research, the author of this essay for the first time tries to give definitions of the process approach to writing, make a comparison between product and process approach to teaching writing and accordingly make suggestions about the basic principles of teaching writing with the application of the process approach. With this understanding of the process approach to writing, the author focuses on a discussion about the two classroom teaching models by using the process approach, namely teaching models with minimal control and maximal control to different English level students. Experimental study shows that the subjects were all making significant progress in their writing skill. Keywords: English writing, Process approach, Product approach I. Definition of process approach to teaching writingProcess approach to the teaching of English Writing has been advocated in contrast with the traditional product-oriented method of teaching writing, and has been generally accepted and applied by English teachers in their classroom teaching of English writing, though controversy occurs occasionally among researchers concerning which P is better, the process approach or the product method.The controversy occurs mainly because there isn't yet a definite and universally accepted definition for the process approach to writing although some features for the approach have been discussed.. According to Graham Stanley, the process approach treats all writing as a creative act which requires time and positive feedback to be done well. In process writing, the teacher moves away from being someone who sets students a writing topic and receives the finished product for correction without any intervention in the writing process itself. Vanessa Steele defines the process approach as focusing more on the varied classroom activities which promote the development of language use; brainstorming, group discussion, re-writing. Nunan (1991) clearly states that the process approach focuses on the steps involved in creating a piece of work and the process writing allows for the fact that no text can be perfect, but that a writer will get closer to perfection by producing, reflecting on, discussing and reworking successive drafts of a text. Fowler (1989) acknowledges that process writing evolved as a reaction to the product approach, in that it met the need to match the writing processes inherent in writing in one's mother tongue, and consequently allow learners to express themselves better as individuals.According to these above definitions as well as a summery of my own experimental research, I think that process approach to teaching writing should be a process includin...

Timely and accurate information on rice cultivation makes important contributions to the profound reform of the global food and agricultural system, and promotes the development of global sustainable agriculture. With all-day and all-weather observing ability, synthetic aperture radar (SAR) can monitor the distribution of rice in tropical and subtropical areas. To solve the problem of misclassification of rice with no marked signal during the flooding period in subtropical hilly areas, this paper proposes a new feature combination and dual branch bi-directional long short-term memory (DB-BiLSTM) model to achieve high-precision rice mapping using Sentinel-1 time series data. Based on field investigation data, the backscatter time series curves of the rice area were analyzed, and a characteristic index (VV − VH)/(VV + VH) (VV: vertical emission and vertical receipt of polarization, VH: vertical emission and horizontal receipt of polarization) for small areas of hilly land was proposed to effectively distinguish rice and non-rice crops with no marked flooding period. The DB-BiLSTM model was designed, ensuring the independent learning of multiple features and effectively combining the time series information of both (VV − VH)/(VV + VH) and VH features. The city of Shanwei, Guangdong Province, China, was selected as the study area. Experimental results showed that the overall accuracy of the rice mapping results was 97.29%, and the kappa coefficient reached 0.9424. Compared to other methods, the rice mapping results obtained by the proposed method maintained good integrity and had less misclassification, which demonstrated the proposed method’s practical value in accurate and effective rice mapping tasks.

Timely and accurate rice distribution information is needed to ensure the sustainable development of food production and food security. With its unique advantages, synthetic aperture radar (SAR) can monitor the rice distribution in tropical and subtropical areas under any type of weather condition. This study proposes an accurate rice extraction and mapping framework that can solve the issues of low sample production efficiency and fragmented rice plots when prior information on rice distribution is insufficient. The experiment was carried out using multitemporal Sentinel-1A Data in Zhanjiang, China. First, the temporal characteristic map was used for the visualization of rice distribution to improve the efficiency of rice sample production. Second, rice classification was carried out based on the BiLSTM-Attention model, which focuses on learning the key information of rice and non-rice in the backscattering coefficient curve and gives different types of attention to rice and non-rice features. Finally, the rice classification results were optimized based on the high-precision global land cover classification map. The experimental results showed that the classification accuracy of the proposed framework on the test dataset was 0.9351, the kappa coefficient was 0.8703, and the extracted plots maintained good integrity. Compared with the statistical data, the consistency reached 94.6%. Therefore, the framework proposed in this study can be used to extract rice distribution information accurately and efficiently.