The information on the distribution, growth and development of crops in actual agricultural practices in major food-production regions is very important in optimizing farming systems, agricultural informatization and mechanization. It is also the scientific foundation for adapting to climate change. Based on on-site investigation, Landsat 8 images and growing season MODIS (Moderate-resolution Imaging Spectroradiometer) data derived time series vegetation index (NDVI, Normalized Difference Vegetation Index), S-G (savitzky-Golay) filtering and quartic polynomial fitting were used to reconstruct NDVI time series curve of spring maize and identify its spatial distribution in Chifeng City in 2018—2019. Dynamic amplitude threshold, inflection point and maximum value were used to determine the phenology of spring maize, namely emergence, initial jointing, tasseling and mature stages, and the growth period and maturity of spring maize were calculated and analyzed. A systematical and comprehensive study on the spatial differences of maize phenology and cultivar maturity in actual agricultural practices in Chifeng City was conducted through temporal and spatial analysis. The results showed that maize retrieval accuracy was above 85%. The emergence of spring maize occurred in May 8—May 27, jointing stage started in May 29—June 11, tasseling stage in July 21—August 10 and mature stage was in September 11—October 1 in 2018—2019. The growth period was delayed with the increase of latitude. The main spring maize cultivars are middle maturity or middle late maturity, with the former mainly distributing over the north of Chifeng, and the later in the middle and the south. The technique for remote sensing phenology and maturity of spring maize laid scientific foundation for agricultural informatization and mechanization, and provided a method for the further study on highly efficient use of climate resources.