Study of satelite images

Part of our study is the observation of satellite photos to draw conclusions. For their selection we used the EO Browser platform which is a repository of satellite images. From the available satellites, we chose to use mainly Sentinel-2 as:

• its main use is the study of land vegetation in the visible and infrared spectrum,

• the resolution of the photos is completely satisfactory and

• the frequency of photos is too high (at least 1 photo per 5 days). 

These photos are from this year but also from previous years.

The forests that formed the field of our research were the beech forest of Olympus (near Petrostruga) and the forest of Foloi located in the region of Western Greece, where our school is also located. Regarding Olympus, we used this year's and last year's photos, while regarding Foloi, we studied photos from the years 2016, 2020, 2022 and 2023.

The purpose of our research was to establish:

(a) whether and by how much tree foliage retention was prolonged and to calculate the % of deciduous trees that retained their foliage for each autumn month compared to previous years and

(b) how "back" the winter went, i.e. the picture that the yellowing of leaves on a certain date of this year corresponds to which date of last year.

But how did we study the photos to draw conclusions? Initially the instrument of study was our eye. By carefully juxtaposing photos, and with the help of the EO Browser tools (eg the Measure tool). This way was valuable, but not enough. We wanted even more valid measurements. That's why we took screenshots from the EO Browser and put them as input to a Python program we wrote that gave us the absolutely accurate percentage of presence of a certain color (eg green or brown). 

Our first concern was to write the code (the entire code is presented in our google drive)