Meteorological variables, phenology, plant health and crop management, soil physical and chemical properties, water and energy balances as well as variables related to economics, logistics and monitoring processes, among others, create complexity in the management of irrigation, which make it difficult to be administered conceptual or empirical models. Also, physico-mathematical modelsdescribing isolated phenomena cannot cover the overall complexity of the problem. This can be seen, in practice, by the gradual growth of factors which threaten the sustainability of irrigation enterprise. Currently, the advent of geotechnology application in agriculture and its integration with weather information in Geographic Information System (GIS) environments has make possible a more detailed support for irrigation management and planning. The objective of this study therefore was to organize and develop a geo-relational database with information from 30 pivots located in Cruz Alta, RS, Brazil, to further establish the usefulness of GIS in irrigation management. Data base preparation took place in two stages: (i) acquisition, georeferencing, image vectorization, snipping and calculation of vegetation indices relating to 107 images from Landsat5/TM satellite; and (2) creation of geo-related tables for each pivot containing information obtained from fieldsand weather stations in the region. Besides statistical analysis of NDVI values of pixels (picture elements) from each pivot, informationon crop type, planting date, phenological stages, soil type, evapotranspiration and weather data were also included in the database. Image processing, calculations and statistical analyzes, as well as mapping were done using SPRING software. Thus, a geographical database capable of integrating field information with those obtained by remote sensing was created and mapping of the distribution of key crop variables enabled better visualization of the dynamics of processes in progress, thus enabling comprehensive technical background for decision making with respect to planning and management of production systems in irrigated agriculture.

Among the factors that contribute the most for increasing maize cultivated area and grain yield in Southern Brazil are the crop genetic selection, soil, crop and water management and recent advances in crop remote monitoring techniques. The Normalized Difference Vegetation Index (NDVI) obtained with remote sensing techniques may be used to provide historical and real-time evaluation characteristics of a particular crop, such as density and vigor without neither field visits, nor interfering directly or indirectly in crop growth and development. This procedure may substantially reduce monitoring or control costs. In this paper, a temporal profile series of NDVI was generated during the maize crop growth period with the objective of evaluating the crop phenology of seven irrigated areas under center pivots. Eight images from LANDSAT5/TM satellite, of the 222/80 and 223/80 path/row were used. The quantitative intervals of NDVI mean values were evaluated from the temporal profile series based on the crop sowing and harvest dates. The NDVI values varied from: 0.18-0.53for initial crop stage; 0.54-0.80for rapid crop growth; 0.20-0.74 for mid-season; and 0.28-0.41for late season. The use of NDVI allows a good differentiation among the maize crop stages of irrigated areas. There has been a drop in NDVI values in the R1 stage, at 54 days after sowing (DAS), due to detasseling. Maximum NDVI value (0.80) was observed at 63DAS, with maize phenology between R2-R5 stages. NDVI values decreased from R6 growth stage till harvest (134 DAS) due to crop maturity and senescence. During this period the average NDVI value was 0.40.