Yanfei Wang

Dr. Yanfei Wang


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 August 2024 in Habitat International
Verified
Journal Article
Closed access
YWYanfei Wang
Yanfei Wang
TLTingting Li
Tingting Li

16 August 2021 in Land
Verified
Journal Article
Open access
PDF file
LTLi Tingting
Li Tingting
YWYanfei Wang
Yanfei Wang
CLChangquan Liu
Changquan Liu
STShuangshuang Tu
Shuangshuang Tu
The multiple cropping index of farmland is a significant characterization of land use intensity. Based on the NDVI data, this paper calculated the multiple cropping index of farmland in China using the S-G filtering method, and proposed an optimized regionalization scheme for the farmland use. The findings reveal that from 2000 to 2018, the multiple cropping index of farmland in China underwent the fluctuation of rising first, then falling and rising continuously, which was closely associated with the agricultural support policies enforced in China. Counties whose multiple cropping indexes decreased from 2009 to 2018 were mainly located in areas primarily producing grain, which exerted a greater influence on food security. The gap between the multiple cropping index and potential multiple cropping index of farmland is increasingly widening from north to south in China. Accordingly, four types of grain producing zones were delineated: key development zone, potential growth zone, appropriate development zone, and restricted development zone. Some suggestions, such as rotation, fallow, determination of yield by water and offsetting the quantity balance of farmland by increasing the multiple cropping index, are put forward based on different zones.

6 November 2025 in Land
Verified
Journal Article
Open access
PDF file
LTLi Tingting
Li Tingting
CLChangquan Liu
Changquan Liu
YWYanfei Wang
Yanfei Wang
Farmland abandonment poses a significant threat to China’s food security by contributing to inefficient land use. Utilizing remote sensing data and the multiple cropping index extraction method, this study extracts abandonment cropland information and analyzes its spatiotemporal patterns across China, with its findings validated against the “China Rural Revitalization Survey” (CRRS) data. The results indicate that since the 21st century, China’s cropland abandonment rate has fluctuated around 5.86%, affecting an average of 7.6 million hectares annually. Spatially, cropland abandonment is more severe in southern China, with hotspots clustered around 25° N and 30° N latitudes. This southward shift exacerbates the spatial mismatch between water resources and cropland. Furthermore, abandonment is particularly pronounced in grain production—marketing balance areas and main marketing areas, intensifying pressure on national food self-sufficiency. Slope and fragmentation also drive abandonment, with steeper (>15°) and more fragmented plots showing higher susceptibility. These complex patterns are uncovered through the study’s systematic innovations—a dual-indicator quantification method, a multi-source validation framework, a dynamic spatiotemporal atlas, and a novel interpretation of abandonment multifunctionality, which also positions farmland reuse as a buffer against unemployment risks. We thus recommend addressing land fragmentation as a core strategy, through high-standard farmland construction, innovative contract rights certification, and expanded agricultural socialized services to promote moderate-scale farming. Finally, we urge the adoption of region-specific and category-based recultivation approaches, supported by clear governance priorities.

28 October 2025 in Smart Agricultural Technology
Verified
Journal Article
Open access
ZLZiye Liu
Ziye Liu
HWHaichao Wu
Haichao Wu
YWYanxuan Wu
Yanxuan Wu
YWYanfei Wang
Yanfei Wang
QLQian Li
Qian Li
HZHongbo Zhang
Hongbo Zhang

1 January 2023 in 资源科学
Verified
Journal Article
Closed access
PDF file
YWYanfei Wang
Yanfei Wang
DZDingxiang Zhang
Dingxiang Zhang
TLTingting Li
Tingting Li