Week 1 is mainly about meeting with Dr.Zeng and discussing the latest technique and application in remote sensing. Therefore, I get to know plenty of new trends such as how Google Earth Engine(GEE) works and contributed to current research, and how Google Earth Studio(GES) is going to affect the planning presentation despite it is too mature to write a paper on it, though it is quite practical.

Then Dr.Zeng mainly give me an assignment about what I am going to do in the next few weeks, which is about validation part in the paper “Reducing the sub-pixel heterogeneity effects on directional reflectance predictions by stochastic radiative transfer theory”. The paper focus on the transfer theory that may analyze a complex landscape like the forest patch mixed with the cropland patch, which is much better than the tradition model in the aspect of size of the detecting field. Dr.Zeng pointed it out that the model is almost done except the validation part. Therefore, I focus on the data which requires highly mixed landscape covered with cropland and forest in a low DEM used in the validation. Three series of data caught my eye, which are the Zurich data source from Dr.Weyermann’s paper, BRDF–BPDF database from Dr.Breon’s paper, CAR dataset from NASA.

I sent an e-mail to Dr.Weyermann in order to ask for the complete data in the paper but no replies are received, which also occurs in the Breon’s situation. At last I turn to the data released by NASA, which is in a file type of “NetCDF”. Then I use Matlab(R2018a) to extract it and tempt to visualize the image in different bands. Finally I succeed in the visualization.


This week is mainly about the data and method we are going to use in the validation. Finally, we all agree to use the data in the same paper while constructing the RTEC model, which is a mixed landscape in the Yigen, Heilongjiang, China. Compared with data mentioned before, Yigen data are more efficient and direct in doing validation. Yigen data can be imported from GEE and with a high resolution of 30m. So, the method we are using in the paper is a basic compare between the three which are the authentic coarse-resolution reflectance, coarse-resolution reflectance by SRTE(1km) the traditional way, coarse-resolution reflectance by RTEC(1km) the new way applying in this paper.

The confirmed versioned of the flow chart is as following.

This is the last week on of this project. I was into the paper writing and summary part.

In three weeks’ study, I mainly learn about to use all kinds of tools to deal with the data in the research, such as ENVI5.3, MatlabR2018a, QGIS, Panoply, NASA, GEE and so on. This may help me in a way of analyzing the data.
Despite I am actually major in Human Geography and Urban Planning, it is also quite important to strengthen the ability in remote sensing since it is going to help with the city planning in several ways and even more than that. Furthermore, I think it is not absolute that you once choose your major meaning other subject is not to concerned, on the contrary, all the science subjects can be connected in some ways, not to mention GIS, RS and City Planning are all in the field of geography.