Analysis of the Spatiotemporal Evolution Patterns and Driving Factors of Various Planting Structures in Henan Province Based on Mixed-Pixel Decomposition Methods DOI Open Access
Kun Han, Jingyu Yang, Chao Liu

и другие.

Sustainability, Год журнала: 2025, Номер 17(3), С. 1227 - 1227

Опубликована: Фев. 3, 2025

Understanding the spatiotemporal evolution patterns and drivers of cropping structures is crucial for adjusting structure policies, ensuring sustainability land resources, safeguarding food security. However, existing research lacks sub-pixel scale data on planting structure, where planted area are mainly derived from manual counting results. In this study, remote sensing technology was combined with geostatistical methods to realize crop at scale. Firstly, spatial distribution multiple in Henan Province extracted based a mixed-pixel decomposition model, analyzed using combination Sen’s slope estimator Mann–Kendall trend analysis, as well centroid migration. Then, Pearson correlation coefficients were calculated explore contribution driving factors. The results indicate following: (1) 2001 2022, shows slightly obvious increase. (2) different migrates main production areas whole. (3) Among factors, there positive labor force negative urbanization rate. This study provides new insights into large-scale offers significant theoretical practical value sustainable agricultural development optimization structures.

Язык: Английский

Hybrid Integer Programming Model for Optimizing Crop Planting Strategies Considering Dynamic Market and Seasonal Factors DOI
Weihua Ruan,

Zihan Wu,

Ziyan Yang

и другие.

Highlights in Business Economics and Management, Год журнала: 2025, Номер 53, С. 111 - 119

Опубликована: Март 17, 2025

This study explores the challenge of determining optimal crop allocation across various land types in context environmental degradation and resource scarcity. Focusing on northern regions China, this paper proposes a mixed-integer programming model designed to account for seasonal variations market fluctuations, with goal maximizing cumulative planting income over multiple years. The integrates comprehensive analysis both economic factors, including yield, costs, prices, associated risks. In addition, research employs entropy weighting TOPSIS methods effective risk assessment address uncertainty. Validation is conducted using datasets from several villages highlighting its capability predict fluctuations while providing practical insights agricultural planning. findings indicate that not only stabilizes but also improves efficiency offers valuable references regulation. By addressing complexities allocation, contributes sustainable practices management strategies face ongoing challenges.

Язык: Английский

Процитировано

0

The Role of the Digital Economy in Promoting Sustainable Agricultural Development: Implications for Sustainable Food Security DOI Open Access

Xia Kuang,

Hailan Qiu,

Zhipeng Wang

и другие.

Sustainability, Год журнала: 2025, Номер 17(9), С. 3777 - 3777

Опубликована: Апрель 22, 2025

The digital economy is increasingly recognized as a key force behind sustainable agricultural development, transforming farm management and enhancing food security through innovation, resource optimization, data-driven decision-making. This study examines how participation in the affects scale of high-quality farmers Jiangxi Province, China. Based on survey data from 868 collected 2022, we apply Ordinary Least Squares regression models, instrumental variable approaches, mediation analysis to identify mechanisms at work. findings indicate that significantly expands by promoting land transfer-in elevating farmers’ subjective social status. Further heterogeneity shows positive impact more pronounced among older those not intending pursue further education. These insights highlight essential role tools fostering scalable farming practices offer practical implications for rural transformation strategies.

Язык: Английский

Процитировано

0

Prediction of Changes to the Suitable Distribution Area of Fritillaria przewalskii Maxim. in the Qinghai-Tibet Plateau under Shared Socioeconomic Pathways (SSPs) DOI Open Access

Daoguang Song,

Zhilian Li,

Ting Wang

и другие.

Sustainability, Год журнала: 2023, Номер 15(3), С. 2833 - 2833

Опубликована: Фев. 3, 2023

The Qinghai–Tibet Plateau has given birth to many indigenous highland plants due its special geographical location and sensitivity climate change. Relevantly, the impact of change on species distribution been a hot issue for research in biogeography. Using maximum entropy (MaxEnt) model, spatial habitat suitability Fritillaria przewalskii Maxim. (FPM) Tibetan was predicted ranked by combining ecological data information actual current distribution. potential trends FPM from 2021 2040, 2041 2060, 2061 2080 2081 2100 under four future scenarios (SSP126, SSP245, SSP370 SSP585) were also predicted. predictions found be highly accurate with AUC values 0.9645 0.9345 training test sets, respectively. A number conclusions could drawn results. Firstly, main factors limiting growth Vegetation types, NPP (net primary production), Soil Bio7 (temperature annual range), Pop (population), Slope, GDP, Aspect, Bio1 (annual mean temperature) Elevation, cumulative contribution 97.6%. Secondly, recent past period 1970–2000, total suitable area accounted 5.55% plateau’s area, which about 14.11 × 104 km2, concentrated eastern central regions. Thirdly, compared previous period, aforementioned will, spanning 2021–2040, increase 14.48%, 16.23%, 16.99%, 21.53% SSP126, SSP370, SSP585 scenarios, This comes an overall expansion trend, areas affected are central-western parts Plateau. other three periods 2041–2060, 2061–2080, 2081–2100 show increases these varying degrees. It is noteworthy that 2061–2080 2081–2100, high decreases or even disappears. Lastly, will shift towards western part

Язык: Английский

Процитировано

10

Improving Northeast China’s soybean and maize planting structure through subsidy optimization considering climate change and comparative economic benefit DOI

Yihang Huang,

Zhengjia Liu

Land Use Policy, Год журнала: 2024, Номер 146, С. 107319 - 107319

Опубликована: Авг. 24, 2024

Язык: Английский

Процитировано

3

Analysis of the Spatiotemporal Evolution Patterns and Driving Factors of Various Planting Structures in Henan Province Based on Mixed-Pixel Decomposition Methods DOI Open Access
Kun Han, Jingyu Yang, Chao Liu

и другие.

Sustainability, Год журнала: 2025, Номер 17(3), С. 1227 - 1227

Опубликована: Фев. 3, 2025

Understanding the spatiotemporal evolution patterns and drivers of cropping structures is crucial for adjusting structure policies, ensuring sustainability land resources, safeguarding food security. However, existing research lacks sub-pixel scale data on planting structure, where planted area are mainly derived from manual counting results. In this study, remote sensing technology was combined with geostatistical methods to realize crop at scale. Firstly, spatial distribution multiple in Henan Province extracted based a mixed-pixel decomposition model, analyzed using combination Sen’s slope estimator Mann–Kendall trend analysis, as well centroid migration. Then, Pearson correlation coefficients were calculated explore contribution driving factors. The results indicate following: (1) 2001 2022, shows slightly obvious increase. (2) different migrates main production areas whole. (3) Among factors, there positive labor force negative urbanization rate. This study provides new insights into large-scale offers significant theoretical practical value sustainable agricultural development optimization structures.

Язык: Английский

Процитировано

0