Prediction of China’s Grain Consumption from the Perspective of Sustainable Development—Based on GM(1,1) Model

Zhang, Xiaoyun; Bao, Jie; Xu, Shiwei; Wang, Yu; Wang, Shengwei

doi:10.3390/su141710792

Cited by 13 publications

(12 citation statements)

References 17 publications

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“…The commonly used generation methods of the GM (1,1) model include the following: (1) cumulative sum, (2) cumulative subtraction, (3) mean generation, (4) grade ratio generation, etc. This is a kind of quantization of uncertainty by grey mathematics, which can make full use of known information to seek the inherent relationship of limited data and predict the changes in land cover in the future [71][72][73][74]; the computing formula is as follows:…”

Section: Gm (11) Prediction Modelmentioning

confidence: 99%

“…In particular, it has a unique effect on the analysis and modeling of a system with a short time series, less statistical data, and incomplete information. Compared with a common regression analysis, the GM (1,1) model will not produce a large error in the case of small samples, so it has a wide range of applications in various prediction fields, such as grain consumption, satellite clock bias, and runoff forecasts, and is an effective tool for dealing with the problem of small-sample prediction [72][73][74].…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal Conflict Analysis and Prediction of Long Time Series Land Cover Changes in the Black Soil Region of Northeast China Using Remote Sensing and GIS

Ding

Jiang

Tan

et al. 2023

IJGI

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Using remote sensing and GIS techniques to monitor long time series land cover changes is of great significance to understanding the impact of human activities on spatiotemporal conflicts and changes in cropland and forest ecosystems in the black soil region of Northeast China. Spatial analysis and dynamic degree were used to analyze the evolutionary process and spatiotemporal association of land cover from 1990 to 2020; the transfer matrix was used to analyze and reveal dynamic conversions of land cover from 1990 to 2000, 2000 to 2010, and 2010 to 2020; and the GM (1,1) model was used to forecast the changes in land cover by 2025 based on historical data. The results indicated that the dominance of forest and cropland did not change from 1990 to 2020, and the average area of forest and cropland was 512,713 km2 and 486,322 km2, respectively. The mutual conversion between cropland, forest, grassland, and bare areas was the most frequent. The area of cropland converted into forest and grassland was 14,167 km2 and 25,217 km2, respectively, and the area of forest and grassland converted into cropland was 27,682 km2 and 23,764 km2, respectively, from 1990 to 2000. A similar law of land cover change was also presented from 2000 to 2020. In addition, the predicted values of cropland, forest, grassland, shrubland, wetland, water bodies, impervious surfaces, and bare areas were 466,942 km2, 499,950 km2, 231,524 km2, 1329 km2, 11,775 km2, 18,453 km2, 30,549 km2, and 189,973 km2, respectively, by 2025. The maximum and minimum residuals between the predicted and actual values were 6241 km2 and −156 km2 from 1990 to 2020. The evaluation results of the GM (1,1) model showed that all of the evaluation indices were within an acceptable range, and that the posteriori error ratio and class ratio dispersion were both less than 0.25. Through comparison with other studies, this study is not only able to provide some experience for further analyzing the spatial and temporal changes in land cover and its future prediction but also provide a basis for comprehensive management in Northeast China.

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Section: Gm (11) Prediction Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Conflict Analysis and Prediction of Long Time Series Land Cover Changes in the Black Soil Region of Northeast China Using Remote Sensing and GIS

Ding

Jiang

Tan

et al. 2023

IJGI

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“…Gray system modeling is a technique for identifying the features of complex data and creating precise simulation models [50,51]. It can forecast nonlinear data sequence events.…”

Section: Ef 3d Prediction By Gm (1 1) Modelmentioning

confidence: 99%

Assessing the Ecological Risks Based on the Three-Dimensional Ecological Footprint Model in Gansu Province

Liu

et al. 2022

Sustainability

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It has become a hot topic in sustainable development to determine how to use data series to predict the trajectory of ecological footprints (EFs), precisely map biocapacity (BC), and effectively analyze regional sustainability. The sustainability of the ecological system in Gansu province must be investigated because the province is situated in western China and serves as a significant economic and transportation hub. We used the EF model to compute the per capita EF and BC of Gansu province from 2010 to 2020. We created a three-dimensional ecological footprint (EF3D) model by incorporating the ecological footprint size (EFsize) and ecological footprint depth (EFdepth) into the EF model and the EF3D of Gansu province from 2010 to 2020 was measured. The EF3D value was estimated using the gray GM (1, 1) prediction model in order to determine the sustainability condition of Gansu province during the next ten years. Finally, the risk of ecosystem loss in the province of Gansu was ultimately assessed using an ecological risk model (EVR). The results show that Gansu province’s per capita EF and BC displayed generally rising trends and the province is experiencing unsustainable development. The region’s projected future consumption of natural capital was estimated by the results, and the EF3D of Gansu province is expected to increase significantly in the future. These findings have a certain reference value for adjusting the industrial structure and utilizing resources in Gansu province. Furthermore, these findings will assist Gansu province in achieving sustainable development policy recommendations.

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“…Moreover, current food management measures and policies, such as the control measures of non-cereal crop production, may become obsolete. These changes are constantly challenging China's food supply security and have garnered significant attention from stakeholders (Du et al, 2020;Shimokawa, 2015;Zhang et al, 2022;Zhao et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Towards more sustainable diets: Insights from food production responses to diet transitions in China

Xiang

Zhang

2023

Sustainable Development

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Similar to most middle-income countries, residents' dietary patterns are continuously changing in China. However, their future development directions (for instance, to a more sustainable diet) and impacts on national food production systems remain uncertain. This study links a diets driver module to a dynamic computable general equilibrium (DCGE) framework to identify potential diet changes and the consequent food production responses. The results show that China would shift its dietary structure towards a high consumption of vegetables, fruits and animal-source foods in 'conventional paths', which are a continuation of previous variation trends. This is likely to induce a rapid expansion in the yields of major foods during the period from 2018 to 2030, following which this increase would slow down. However, there would be a considerable decrease in staple foods, meat and egg intakes, as well as a sharp increase in dairy demand when diets shift towards the targets put forth in the Chinese Dietary Guideline. Under this shock, most food production activities would decrease in scale and the 'cereal-pork' agricultural priority would be diminished.These findings also stress the importance of synergy between the two endpoints of the food system and potential challenges facing the shift to sustainable diets.

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Prediction of China’s Grain Consumption from the Perspective of Sustainable Development—Based on GM(1,1) Model

Cited by 13 publications

References 17 publications

Spatiotemporal Conflict Analysis and Prediction of Long Time Series Land Cover Changes in the Black Soil Region of Northeast China Using Remote Sensing and GIS

Spatiotemporal Conflict Analysis and Prediction of Long Time Series Land Cover Changes in the Black Soil Region of Northeast China Using Remote Sensing and GIS

Assessing the Ecological Risks Based on the Three-Dimensional Ecological Footprint Model in Gansu Province

Towards more sustainable diets: Insights from food production responses to diet transitions in China

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