Qiang Liao

Mr. Qiang Liao

Sichuan Academy of Agricultural Sciences, Chengdu, Sichuan, China
orcid

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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6 March 2023 in Ecological Indicators
Verified
Journal Article
Open access
Qiang LiaoQiang Liao
Qiang Liao
TLTong Li
Tong Li
QWQiyou Wang
Qiyou Wang
DLDeer Liu
Deer Liu

21 April 2024 in Natural Resources Research
Verified
Journal Article
Closed access
PDF file
QWQiyou Wang
Qiyou Wang
TLTong Li
Tong Li
Qiang LiaoQiang Liao
Qiang Liao
DLDeer Liu
Deer Liu


12 March 2024 in Environmental Monitoring and Assessment
Verified
Journal Article
Closed access
PDF file
Qiang LiaoQiang Liao
Qiang Liao
TLTong Li
Tong Li
DLDeer Liu
Deer Liu

10 January 2022 in Science of The Total Environment
Verified
Journal Article
Closed access
TLTong Li
Tong Li
Qiang LiaoQiang Liao
Qiang Liao
Shuai WangShuai Wang
Shuai Wang
BFBojie Fu
Bojie Fu

23 January 2025 in Land
Verified
Journal Article
Open access
PDF file
LYLiu Yuanli
Liu Yuanli
Qiang LiaoQiang Liao
Qiang Liao
Zhouling ShaoZhouling Shao
Zhouling Shao
WGWenbo Gao
Wenbo Gao
CJCao Jie
Cao Jie
LZLin Zhengyu
Lin Zhengyu
Given the constraints of limited cultivated land resources, ensuring and enhancing crop productivity are crucial for food security. This study takes Chengdu as a case study. Using the cultivated land productivity (CLP) evaluation model, we calculated the cultivated land productivity index (CLPI) and analyzed its spatial distribution characteristics. The Geographical Detector model was employed to identify the main factors influencing CLP, and corresponding countermeasures and measures were proposed based on the limiting degrees of these factors. The findings reveal that Chengdu’s CLP index ranges from 1231 to 3053. Global spatial autocorrelation analysis indicates a spatial agglomeration pattern in Chengdu’s overall crop productivity distribution. The local spatial autocorrelation analysis demonstrates that township (street)-level crop productivity in Chengdu is primarily characterized by “high–high”, “low–low”, and “low–high” clusters. Key factors influencing the spatial differentiation of CLP in Chengdu include the agronomic management level, soil bulk density, irrigation guarantee rate, soil body configuration, field slope, and farmland flood control standard. Interaction detection shows that there are both double-factor and nonlinear enhancements among the factors. Specifically, the interaction between soil bulk density and the agronomic management level among other factors have the most explanatory power for the spatial differentiation of CLP. The CLP in Chengdu is highly restricted by its technical level, with the agronomic management level severely limiting CLP by more than 50%. These research results provide a theoretical reference for regional high-standard farmland construction and the protection and utilization of cultivated land resources.