Monitoring the impacts of cultivated land quality on crop production capacity in arid regions

[Display omitted] •Monitored the cultivated land quality and crop production capacity.•Quantitatively assessed the impacts of CLQ on crop production capacity.•Captured the location of cultivated land which needs to be improved. Cultivated land plays a vital role in human survival and the development of human civilization. The cultivated land quality (CLQ) is of considerable significance for ensuring food security and social stability. Although studies have been conducted to assess CLQ, efforts regarding the quantitative impacts of CLQ on crop production capacity are still scarce, especially in arid regions. Understanding such a question greatly benefits land resources management and sustainable development of oasis agriculture. The objective of this study is to explore the spatiotemporal variations of CLQ and to quantify the impacts of CLQ on crop production capacity via an ordinary linear regression (OLS) model and correction analysis in arid regions. The Delphi-AHP (analytic hierarchy process) method is applied to assess CLQ in this study with the highest accuracy (96.35%). The average score of cultivated land quality (S-CLQ) is 58.75 in the study area. The results further suggest that the quality of decreasing cultivated land (61.53) is much higher than that of increasing cultivated land (57.99). We use net primary productivity (NPP) calculated by the vegetation photosynthesis model (VPM) to simulate the crop production capacity and find that CLQ has a significant positive impact on crop production capacity (R2 = 0.706). The distribution of average annual NPP is similar to that of CLQ. 62.41% of cultivated land shows an increasing trend in annual NPP, whereas 37.57% of cultivated land shows a decreasing trend. Pearson coefficient by intervals is calculated to identify areas where crop production capacity does not match the quality of cultivated land. The results reveal considerable differences in the Pearson coefficient in various intervals (negative correlation in 5 intervals and positive correlation in 10 intervals). This research quantifies the impacts of CLQ on crop production capacity and provides a way to accurately capture the location of cultivated land that needs to be improved in arid regions.