This paper reviews the application of NOAA/NASA Pathfinder AVHRR Land (PAL) dataset (8 km) to detect land-cover change in China between 1982 and 1992. Changes in productivity, as indicated by a normalized difference vegetation index (NDVI), not changes in land-cover classifications are analysed. The research uses the change detection techniques of simple differencing, or univariate differencing, and standardised principal component analysis. Both techniques produce similar results which indicate that forest regions are decreasing in productivity while agricultural regions are increasing. The majority of pixels indicating changes are ones showing an increase in productivity and are clustered primarily in agricultural regions, especially the North China Plain, along with grasslands. The paper demonstrates the potential of using global-scale PAL data to monitor land-cover change in areas where official governmental data are either suspect or hard to acquire. China is an important area in which to analyse landcover change because little is known about recent changes and the region has a strong potential impact on global environmental change.