Cropland productivity assessment for Ukraine based on time series of optical satellite images

Ukraine is a large agricultural country situated in Eastern Europe (603,500 km2). Nowadays in Ukraine, there is no any land market due to the moratorium on land sales. Nevertheless, in all areas preparation for land market is undergoing. Cropland productivity assessment based on satellite data is a challenging task for Ukraine because of a large territory and big diversity of agricultural crops. Cropland productivity is one of the major factors for forming the land price. In this paper, we aim to provide land productivity maps based on analysis of MODIS and Landsat-8 data due to availability long term time-series of Normalized Difference Vegetation index (NDVI) from sensors aboard those remote sensing satellites. Taking into account the huge amount of satellite products to be analyzed, in the study we propose to exploit the Google Earth Engine (GEE) cloud platform. It was found that land productivity maps provided from MODIS data for different time periods are strongly correlated. The experiment shows that land productivity maps should have high resolution. That is why, Landsat-8 data is more appropriate for land market purpose, despite of some bias in values comparing to results based on MODIS data. Comparing crop mask from ESA Sen2Agri project and obtained results it was found the dependence of land productivity value and crop/non-crop cover. It was found that irrigated fields from the south part of the study area are the most productive lands in Ukraine.