###### Abstract  
The Han River Basin is a main agricultural production area and a water source for the middle route of the South-to-North Water Diversion Project in China. Over the past 20 years, human exploitation and ecological construction have disturbed the sustainability of land productivity in the Han River Basin. Theil-Sen trend analysis, Mann-Kendall statistical test, and Hurst index methods were applied to examine spatial-temporal trends and sustainability characteristics of land net primary productivity (NPP) change in the Han River Basin from 2001 to 2019 using MOD17A3 NPP product, natural, and socio-economic data obtained from Google Earth Engine (GEE). The findings demonstrated that the interannual variation of land NPP exhibited a fluctuating upward trend, with a more pronounced growth rate from 2001 to 2010 than from 2011 to 2019. The spatial heterogeneity of land NPP was evident, with high values in the west and low values in the east. Of the basin area, 57.82% presented a significant increase in land NPP, while only 0.96% showed a significant decrease. In the future, land NPP in the Han River Basin will present sustained growth. The results were also compared with Trends.Earth's calculations for the SDG 15.3.1 sub-indicator of land productivity. In addition, the spatial heterogeneity of factors influencing land NPP change was explored using a multiscale geographically weighted regression (MGWR) model. Precipitation and population count were the dominant factors in most regions. Besides, precipitation, population count, and human modification all exhibited inhibitory effects on the increase in land NPP except for elevation. The research can provide a scientific basis for tracking land degradation neutrality (LDN) progress and achieving sustainable socio-ecological development of the Han River Basin. 11 November 2021 8 December  
15.3.1 assessments. It is of great theoretical and practical significance for achieving LDN and ensuring sustainable socio-ecological development. Net primary productivity (NPP) is the total quantity of dry organic matter produced by green plants per unit area per unit time through photosynthesis after subtracting autotrophic respiration [10]. NPP is a crucial parameter in terrestrial ecological processes. It reflects the combined effects of climate change and human activities on terrestrial vegetation. As a result, it is a critical indicator for determining carbon balance, health, and sustainability of terrestrial ecosystems [3; 11]. Studies have demonstrated that NPP can effectively capture the state of land productivity. It is more vulnerable to climate change and human activities than vegetation indexes such as NDVI [12; 13]. Climatic factors (e.g., temperature, precipitation, and solar radiation) and human activities (e.g., land-use change, vegetation construction, and soil-water conservation) are now widely regarded as the main drivers of land productivity change [1; 14]. For instance, government-led ecological projects, including aforestation and conversion of farmland to forest or grassland, will improve land productivity; urban expansion will decrease land productivity by occupying ecological land, including farmland, forest, and grassland. The earliest methods of quantifying NPP were in situ measurements, which mainly included harvest measurements, biomass surveys, photosynthesis measurements, radiation measurements, chlorophyll measurements, and feedstock material consumption measurements [15]. However, these methods are often restricted by several factors that make them difficult to implement. Thus, scholars presented statistical climate models, physiological-ecological process models, light energy utilization models, and multiple interactive models [16; 17; 18; 19]. Long timeseries and wide coverage of remote sensing data make data-driven models of ecosystem processes a vital tool for understanding the spatial and temporal characteristics of land productivity and its driving mechanisms.