## 1 Introduction
Some hypothesis conditions are required in some statistical methods of data, such as the normal distribution of data or a large number of sample data, and the statistical results are subject to outlier interference [29]. Theil-Sen median trend analysis and the MK test, which are simple in calculation, do not need to be submitted to specific statistical distribution, and are not affected by outliers, are widely used in time series trend analysis of runoff, temperature, precipitation and water quality. The combination of the two methods can not only reflect the changing trend but also quantify the amplitude of change. The Hurst exponent [30] has been used to judge whether the time series data belong to a random walk or a biased random walk, which has been used to analyze the sustainability characteristics of vegetation growth trends [31]. Jilin Province is the largest commodity grain production base in China and plays a vital role in ensuring Chinese food security. Since the implementation of Chinese commercial grain base construction policy from 1983 to 2004, 33 commercial grain base counties have provided 276 billion km of grain for China, accounting for 10% to 15% of the total Chinese commercial grain [32]. With the increase in population demand for grain, the level of CLP in Jilin, which is the main granary in northeastern China, has been a focus. However, there are increasing rates of change in climate and deteriorating environmental conditions in Jilin. Over the past 50 years, the average temperature has risen by 0.35 \({}^{\circ}\)C/decade and the average precipitation has dropped by 16.34 mm/decade in this region [33]. In the last decade years, the organic matter content (OMC) of black soil decreased from 6% to 2% in most of Jilin, which has caused some black soil farmland to lose production capacity [34]. Fertilizer is being applied 10 times more than 30 years ago and the utilization of pesticides has increased from 2.2 tons to 25,000 tons, which is the main reason for soil compaction and soil pollution [35]. It is necessary to determine the changing trend and variation amplitude of CLP in Jilin under the background of climate change and soil degradation. Further, the prediction of changes in the short term is the key to optimize the allocation of cultivated land resources, to maintain the stability of productivity and enhance the low- and medium-yield fields in Jilin. This paper is based on the hypothesis that the GPP is a proxy of land productivity, and in this paper, we analyze the CLP level, the trend and amplitude of change in Jilin from 2000 to 2018 and the future direction of CLP. The GPP time series is estimated by the VPM model derived from MODIS data. The level of CLP was estimated using the GPP mean from 2000 to 2018. The trend and amplitude of GPP were quantified by both the Theil-Sen median trend analysis and the MK test. The sustainability characteristic of future change was assessed by the Hurst exponent. The MK trend and Hurst exponent were integrated to express the future direction of change. The objectives were to determine: (1) the temporal and spatial characteristics of the CLP level; (2) the trend and amplitude of CLP during 2000-2018; and (3) the sustainability and variation direction of GPP in the short-term future. Based on this study, the level of regional CLP improvement and cultivated construction achievements are promoted by understanding the temporal variation and the spatial distribution of CLP in the Jilin.