The patterns of variation in vegetative indices received by means of data of remote land sensing are described as being dependant on geomorphological predictors and the sizes of agricultural fields in an experimental polygon within Poltava region. The possibilities of application of vegetative indices have been explored through ecogeographical determinants of the ecological niche of the common milkweed (Asclepias syriaca L.) and other weeds. On the basis of images of the land surface taken on 23 March and 27 August 2015 by the sensor control Operational Land Imager (OLI), installed on the satellite Landsat 8, vegetative indices have been calculated (AC-Index – aerosol/coastal index, Hydrothermal Composite, NDTI – Normalized Difference Tillage Index, NDVI – Normalized Difference Vegetation Index, VI – Vegetation Index, MNDW – Modified Normalized Difference Water Index, LSWI – Land Surface Water Index, NBR – Normalized Burn Ratio, M15). The data obtained have been subjected to principal component analysis and the revealed principal components have been interpreted with the help of regression analysis, in which geomorphological variables have been applied as predictors. It was possible to explain the trends of variability of the vegetative cover, formalized in the form of the principal component, by means of indices which quantitatively characterise features of relief. The various aspects of variation of vegetative cover have been shown to be characterised by the specificity of the influence of relief factors. A prominent aspect of the variation of the vegetative cover of agroecosystems is variability within a field. The degree of a variation of conditions is proportional to the size of a field. Large fields occupy level plain positions. In turn, within small fields sources of variation are changes in ecological conditions which arise owing to unevenness of relief, which increases in proximity to gullies and ravines. We have identified the aspects of the variation of vegetative cover which by their nature can be considered as contributers to the growth of weeds in agroceonoses. Satellite imaging by Landsat does not allow direct identification of concentrations of weeds, but it can reveal complex changes in the landscape cover, which act as markers of the processes connected with development of weed vegetation. The procedure of further decoding of satellite images for the purpose of identification of weeds requires greater attention in this field of research.