Índice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/soja - Damian, Júnior Melo (2017)
The no-tillage system (SPD) was one of the main innovations in Brazilian agriculture, but there are still discussions about how to achieve and maintain its quality and sustainability. The management of SPD areas through management zones presents great potential for this purpose, since it integrates different variables in order to facilitate and increase the technical and computerized management of agricultural practices and consequently the reduction of polluting potencies in environments. Among the main variables used to delimit management zones are the chemical attributes, yield maps and recently the NDVI index. In this sense, with Article I, the objective was to delimit management zones through yield maps and NDVIs derived from satellite images in historical series. To do this, in an area of 118 ha, three yield maps of different cultures between the years of 2010 to 2015 were selected and for each yield map we searched for the images from the Landsat 5 and 8 satellite that included a date in of the cycle of the crop in question from which the NDVI was calculated and also with the intention of verifying the stability of the NDVI generated in different crop cycles, four other satellite images were selected for four crops according to the historical of the study area, between the years 2007 and 2013. In article II, the objective was to verify the variability caused by the winter cover crop in the summer crop and if the NDVI index performed by land and with a RPAS is able to evidence this variability in the summer crop. In an area 73.96 there was applied a sampling grid of 70.71 x 70.71 m (0.5 ha), where soil sampling for chemical analysis and dry matter nutrients accumulated in the winter cover crop of black oats where soybean was sown in the summer, in which in the R5 and R5.5 stages evaluations were carried out with a portable sensor "by land" and with a RPAS for obtaining of the NDVI index and finally the grain yield of the soybean was determined, as well as the final population of plants. With the results, NDVI from satellite images can replace and/or compose the yield maps (article I) and that the dry mass and accumulated nutrients in the winter crop interfere with the yield of the summer crop and the NDVI index performed by land or with a RPAS was effective in expressing this variability (article II).