Programme

I was insterested in Programme after graduating. Then I wrote some programmes for geography, paleoclimate and raster data. I think recent computer science can improve the level of physical geography. Some data (like NetCDF format data and some time series data) are difficult to use, we need to lower the threshold to use these data and reduce repetition stages of data preprocessing.

I thought the data of paleoclimate are too difficult to search and use, so I made the PaleoCal. In 2D Data section, it is easy to get the monthly precipitation or temperature and calculate them. I also provide a CNN model to forecast the precipitation by SST. In this way, I want to show the "power" of Deep Learning, because I think Deep Learning may improve the technique of paleoclimate. In 1D Data section, you can find annual precipitation or temperature from CMA. I also preprocess them in a proper way. By using AMap, you can compare these 1D data by selecting their locations. This project is a combination of collect, process and show the data of paleoclimate. It also involves database, front-end and back-end by using different languages.

In order to process the raster data faster, I made the second project Geovector. It contains more matrix calculations and more flexible operations. The most important thing is that it is extremly fast because of the Web Assembly. In the future, the data from Paleocal will support the geovector and vice versa.

I wanted that everyone can easily use the NetCDF data, so I wrote an GUI reader of these format data, called NC Viewer. In this project, I tried new framework of PC app, and new framework of front-end. To display the raster DEM data, I used some functions that showed them in original WebGL. This software could also support the data from Geovector. In the future, I want to directly render the data to WebGL by Web Assembly. And also I want to write them in OpenGL in Rust.