Water is an important limiting factor for sparse vegetation growth in northern China. The trade-off between sparse vegetation growth and water consumption highly related to the carbon and water cycle process is important for studying the water demand and optimal utilization of vegetation restoration in northern China. In this study, the sensitive band to sparse vegetation was selected to establish a new vegetation index by remote sensing and the time series similarity comparison method was used to obtain the Mean Absolute Distance (MAD) distribution to indicate the sparse vegetation growth. The Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model was driven by multiple sources data such as ground and remote sensing to simulate sparse vegetation transpiration. The results show that vegetation has increased from 2001 to 2015 in northern China. The upward trend in transpiration of sparse vegetation was aligned primarily with changes in sparse vegetation. However, there are localized areas in eastern Inner Mongolia and northwest Xinjiang where a decreasing trend was observed. The transpiration and water use are highly related to vegetation cover during the afforestation process. Optimal vegetation cover considering water use was obtained by analysing the relationship between sparse vegetation and transpiration, and the optimal vegetation cover value (MAD = 0.4) for water use was proposed. The results of the study can fill the gaps in sparse vegetation distribution and transpiration data in desertification areas in China, and provide theoretical support for the selection of optimal site conditions in the process of vegetation restoration to strengthen forest management.