Extraction and Prediction of Spatiotemporal Pattern Characteristics of Farmland Non-Grain Conversion in Yunnan Province Based on Multi-Source Data
文献类型：期刊论文
| 作者 | Ma, Xianguang2,3,4; Tang, Bohui3,4,6; He, Feng5; Huang, Liang3,4; Zhang, Zhen3,4; Cui, Dongguang1,3 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2025-09-25 |
| 卷号 | 17期号:19页码:3295 |
| 关键词 | non grain conversion of cultivated land spatial and temporal patterns driving mechanism multi-source data karst agriculture Yunnan |
| DOI | 10.3390/rs17193295 |
| 产权排序 | 4 |
| 文献子类 | Article |
| 英文摘要 | Highlights What are the main findings? Yunnan Province experienced 54% intensification in farmland non-grain conver-sion from 2001-2021 (NGCI: 45.91 -> 21.05), with karst areas showing 23% faster conversion rates and 73% of high-intensity conversion clusters occurring in re-gions with >30% karst coverage despite karst terrain covering only 28% of the province. The Dynamic Spatial-Temporal Clustering Model (DSTCM) achieved 92.51% pre-diction accuracy and identified NGCI = 10 as the critical threshold for irreversible agricultural degradation, with model projections indicating 89% of karst areas will cross this threshold by 2035 compared to 41% in non-karst regions. What is the implication of the main finding? Karst terrain fundamentally alters agricultural land use decisions through geo-logical constraints (soil depth <30 cm, 40% lower water retention, 0.3ha average parcels), requiring specialized management strategies distinct from conventional agricultural regions to prevent irreversible degradation. Standard agricultural interventions demonstrate significantly reduced effective-ness in karst landscapes (3x higher implementation costs at 1340 CNY/hectare), while targeted karst-specific strategies incorporating soil conservation, water harvesting systems, and adapted crop varieties achieve 73% success probability in maintaining agricultural sustainability above critical thresholds.Highlights What are the main findings? Yunnan Province experienced 54% intensification in farmland non-grain conver-sion from 2001-2021 (NGCI: 45.91 -> 21.05), with karst areas showing 23% faster conversion rates and 73% of high-intensity conversion clusters occurring in re-gions with >30% karst coverage despite karst terrain covering only 28% of the province. The Dynamic Spatial-Temporal Clustering Model (DSTCM) achieved 92.51% pre-diction accuracy and identified NGCI = 10 as the critical threshold for irreversible agricultural degradation, with model projections indicating 89% of karst areas will cross this threshold by 2035 compared to 41% in non-karst regions. What is the implication of the main finding? Karst terrain fundamentally alters agricultural land use decisions through geo-logical constraints (soil depth <30 cm, 40% lower water retention, 0.3ha average parcels), requiring specialized management strategies distinct from conventional agricultural regions to prevent irreversible degradation. Standard agricultural interventions demonstrate significantly reduced effective-ness in karst landscapes (3x higher implementation costs at 1340 CNY/hectare), while targeted karst-specific strategies incorporating soil conservation, water harvesting systems, and adapted crop varieties achieve 73% success probability in maintaining agricultural sustainability above critical thresholds.Abstract Non-grain conversion threatens food security in karst mountainous regions where fragmented terrain and shallow soils create unique agricultural challenges. This study examines Yunnan Province (28% karst coverage) in the Yunnan-Guizhou Plateau, where cultivated land faces distinct pressures from limited soil depth (average < 30 cm in karst areas) and poor water retention capacity. Using multi-source data (2001-2021) and an integrated Dynamic Spatial-Temporal Clustering Model (DSTCM), we quantify non-grain conversion through a clearly defined Non-Grain Conversion Index (NGCI = 0.35 x CPI + 0.25 x LUI + 0.20 x RSI + 0.20 x PSI). Results reveal the NGCI declined from 45.91 to 21. 05, indicating a 54% intensification in conversion (lower values = higher conversion intensity). Spatial analysis shows significant clustering (Moran's I = 0.57, p < 0.001), with karst areas experiencing 23% higher conversion rates than non-karst regions. Key drivers include soil fertility limitations (t = 2.35, p = 0.027), crop type transitions (t = 3.12, p = 0.047), and economic pressures (t = 2.88, p = 0.012). Model predictions (accuracy: 92.51% +/- 2.3%) forecast continued intensification with NGCI reaching 9.31 by 2035 under current policies. Spatial distribution mapping reveals concentrated conversion hotspots in southeastern karst regions, with 73% of high-intensity conversion occurring in areas with >30% karst coverage. This research provides critical insights for managing cultivated land in karst landscapes facing unique geological constraints. |
| URL标识 | 查看原文 |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001595044800001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217542]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Tang, Bohui |
| 作者单位 | 1.Yunnan Inst Geol Survey, Kunming 650051, Peoples R China 2.Yunnan Land Resources Planning & Design Res Inst, Kunming 658216, Peoples R China; 3.Kunming Univ Sci & Technol, Fac Land Resource Engn, Kunming 650093, Peoples R China; 4.Key Lab Quantitat Remote Sensing Yunnan, Kunming 650093, Peoples R China; 5.Yunnan Univ Finance & Econ, Sch Logist & Management Engn, Kunming 650221, Peoples R China; 6.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Ma, Xianguang,Tang, Bohui,He, Feng,et al. Extraction and Prediction of Spatiotemporal Pattern Characteristics of Farmland Non-Grain Conversion in Yunnan Province Based on Multi-Source Data[J]. REMOTE SENSING,2025,17(19):3295. |
| APA | Ma, Xianguang,Tang, Bohui,He, Feng,Huang, Liang,Zhang, Zhen,&Cui, Dongguang.(2025).Extraction and Prediction of Spatiotemporal Pattern Characteristics of Farmland Non-Grain Conversion in Yunnan Province Based on Multi-Source Data.REMOTE SENSING,17(19),3295. |
| MLA | Ma, Xianguang,et al."Extraction and Prediction of Spatiotemporal Pattern Characteristics of Farmland Non-Grain Conversion in Yunnan Province Based on Multi-Source Data".REMOTE SENSING 17.19(2025):3295. |
入库方式： OAI收割
来源：地理科学与资源研究所
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