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Spatial and temporal dynamics of cropland in the Sanjiang Plain from 2014 to 2020 based on annual 30 m crop data layers

Published online by Cambridge University Press:  16 February 2023

Cui Jin Open the ORCID record for Cui Jin [Opens in a new window] ,
Zeyu Zhang ,
Hongyan Cai ,
Ge Cao ,
Xintao Li  and
Xueming Li
Cui Jin
Affiliation:
School of Geography, Liaoning Normal University, 850 Huanghe Road, Dalian 116029, China
Zeyu Zhang
Affiliation:
School of Geography, Liaoning Normal University, 850 Huanghe Road, Dalian 116029, China
Hongyan Cai*
Affiliation:
State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Beijing 100101, China
Ge Cao
Affiliation:
School of Geography, Liaoning Normal University, 850 Huanghe Road, Dalian 116029, China
Xintao Li
Affiliation:
School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China
Xueming Li
Affiliation:
School of Geography, Liaoning Normal University, 850 Huanghe Road, Dalian 116029, China
*
Author for correspondence: Hongyan Cai, E-mail: caihy@igsnrr.ac.cn
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Abstract

The land cover of the Sanjiang Plain has changed dramatically since the 1950s. Although previous studies have analysed its spatiotemporal dynamics at long time intervals, a near real-time and accurate representation of the interannual evolution of cropping patterns in this region is of far-reaching importance for rationally allocating agricultural resources and ensuring food security. Based on the 30 m and 10 m land cover datasets in 2015 and 2017–2019, the current study used Landsat-8 satellite data in 2014, 2016 and 2020 to identify paddy rice and dryland crops using a decision tree classification approach and constructed the annual cropland datasets of the Sanjiang Plain from 2014 to 2020. The results show that the overall classification accuracies of crop datasets exceeded 95%, and the Kappa coefficients were higher than 0.92. The average annual accuracies of users and producers were 93% and 94% for rice fields and 97% and 95% for dryland crops, respectively. During the 7 years, the total area of paddy fields and dryland crops decreased by 5% and 8%. However, with minor positive and negative variation between years. 24.2% of paddy rice and 42% of dryland crops has been cultivated under 4 years. The centres of gravity for both crops mainly aggregated in the central counties with the migration direction and magnitude varying interannually. The current study emphasizes the importance of establishing annual high-resolution crop datasets to track the detailed spatio-temporal trajectories of cropping patterns that are essential to support sustainable cropland management and agricultural development.

Keywords

Decision tree classificationfood securityland cover and land use changeremote sensing-based crop mappingspatio-temporal dynamic analysis
Type
Climate Change and Agriculture Research Paper
Information
The Journal of Agricultural Science , Volume 161 , Issue 2 , April 2023 , pp. 175 - 186
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Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

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