Intelligent models and methods for determining land degradation indicators based on satellite data

Project within the NRFU competition “Science for the safety of human and society”

Project duration: 2020-2021

Supervisor: prof. Andrii Shelestov

Project abstract

The problem of land degradation is relevant today. Many signs of land degradation, such as declining crop yields, deforestation identification or uncultivated land cultivation, can be tracked using satellite data, in particular vegetation indices. There is implementation of UNCCD technology for land degradation assessing based on satellite data, but this product has some drawbacks: it is built based on a global land cover map with a rough 300 m resolution and calculates productivity regardless of the land cover type. Thus, within the project land degradation assessment methodology will be modified by producing a higher resolution land cover maps (10 m), noise reduction on the map, calculating productivity with according to different types of land cover, detecting and taking into account deforestation. For the first time for Ukraine territory, the developed methodology will be implemented in a cloud environment, which will allow us to monitore the land degradation on a regular basis.