Spectral and NDVI values have been used to calculate the change magnitudes of land cover, but may result in many pseudo-changes because of inter-class variance. Recently, the shape information of spectral or NDVI curves such as direction, angle, gradient, or other mathematical indicators have been used to improve the accuracy of land cover change detection. However, these measurements, in terms of the single shape features, can hardly capture the complete trends of curves affected by the unsynchronized phenology. Therefore, the calculated change magnitudes are indistinct such that changes and no-changes have a low contrast. This problem has prevented traditional change detection methods from achieving a higher accuracy using bi-temporal images or NDVI time series. In this paper, a multiple shape parameters-based change detection method is proposed by combining the spectral correlation operator and the shape features of NDVI temporal curves (phase angle cumulant, baseline cumulant, relative cumulation rate, and zero-crossing rate). The change magnitude is derived by integrating all the inter-annual differences of these shape parameters. The change regions are discriminated by an automated threshold selection method known as histogram concavity analysis. The results showed that the mean differences in the change magnitudes of the proposed method between 2100 changed and 2523 unchanged pixels was 32%, the overall accuracy was approximately 88%, and the kappa coefficient was 0.76. A comparative analysis was conducted with bi-temporal image-based methods and NDVI time series-based methods, and we demonstrate that the proposed method is more effective and robust than traditional methods in achieving high-contrast change magnitudes and accuracy.

Rapid urbanization and economic growth in China have accelerated changes in rural settlements and associated land-use types that are expected to alter ecological services and the environment. Relevant studies of the dynamics of rural settlements and corresponding rural land-use changes are in short supply, however, especially in undeveloped areas in China. This study, therefore, investigated the spatio-temporal dynamics of rural settlements and their impacts on other land-use types by using 30 m rural settlement status and dynamic maps from the end of the 1980s to 2010. These maps were generated by visual interpretation with strict product quality control and accuracy. Henan province was selected as a case study of undeveloped regions in China. We examined in particular how the expansion of rural settlements affected cultivated lands and the processes of rural settlement urbanization. This study looked at three periods: the end of the 1980s–2000, 2000–2010, and the end of the 1980s–2010, with two spatial scales of province and prefecture city. Major findings about the rural settlements in Henan from the end of the 1980s to 2010 include (1) the area of rural settlements grew continuously, although the increasing trend slowed; (2) the expansion of rural settlements showed a negative trend contrary to the trend of the urbanization of rural settlements; (3) rural settlement expansion occupied considerable expanse of cultivated lands, which accounted for up to 96% of the total expansion lands; (4) urbanization of rural settlements was the main mode by which rural residential lands vanished, accounting for more than 98% of the lost lands. This study can provide suggestions for the conservation and sustainability of the rural environment and inform reasonable policies on rural development.