Decline in Planting Areas of Double-Season Rice by Half in Southern China over the Last Two Decades

Wenchao Zhu; Xinqin Peng; Mingjun Ding; Lanhui Li; Yaqun Liu; Wei Liu; Mengdie Yang; Xinxin Chen; Jiale Cai; Hanbing Huang; Yinghan Dong; Jiaye Lu

doi:10.3390/rs16030440

Remote Sensing (Jan 2024)

Decline in Planting Areas of Double-Season Rice by Half in Southern China over the Last Two Decades

Wenchao Zhu,
Xinqin Peng,
Mingjun Ding,
Lanhui Li,
Yaqun Liu,
Wei Liu,
Mengdie Yang,
Xinxin Chen,
Jiale Cai,
Hanbing Huang,
Yinghan Dong,
Jiaye Lu

Affiliations

Wenchao Zhu: School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
Xinqin Peng: School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
Mingjun Ding: School of Geography and Environment, Jiangxi Normal University, Nanchang 330028, China
Lanhui Li: School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
Yaqun Liu: Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Wei Liu: School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
Mengdie Yang: School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
Xinxin Chen: School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
Jiale Cai: School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
Hanbing Huang: School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
Yinghan Dong: School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
Jiaye Lu: School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China

DOI: https://doi.org/10.3390/rs16030440
Journal volume & issue: Vol. 16, no. 3
p. 440

Abstract

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Accurately tracking the changes in rice cropping intensity is a critical requirement for policymakers to formulate reasonable land-use policies. Southern China is a traditional region for rice multi-cropping, yet less is known about its spatial–temporal changes under the background of rapid urbanization in recent decades. Based on images from Landsat and MODIS and multiple land cover products, the gap-filling and Savitzky–Golay filter method (GF-SG), the enhanced pixel-based phenological features composite approach (Eppf-CM), random forest (RF), and the difference in NDVI approach (DNDVI) were combined to map the rice cropping pattern with a spatial resolution of 30 × 30 m over Southern China in 2000 and 2020 through Google Earth Engine (GEE). Subsequently, the spatial–temporal changes in rice cropping intensity and their driving factors were examined by Getis-Ord Gi* and geographical detector. The results showed that the produced rice cropping pattern maps exhibited high accuracy, with kappa coefficients and overall accuracies exceeding 0.81 and 90%, respectively. Over the past two decades, the planting areas of double-season rice in Southern China decreased by 54.49%, and a reduction was observed across eight provinces, while only half of the provinces exhibited an increase in the planting areas of single-season rice. Compared to the year 2000, the planting area of the conversion from double- to single-season rice cropping systems in 2020 was 2.71 times larger than that of the conversion from single- to double-season rice cropping systems. The hotspots of the change in rice cropping intensity were mainly located in the central part of Southern China (excluding the Poyang Lake Plain). The decline in the rural labor force, coupled with ≥10 °C accumulated temperature and topographical factors, plays a crucial role in the decreased intensity of rice cropping. Our findings can be beneficial for realizing regional agricultural sustainability and food security.

Published in Remote Sensing

ISSN: 2072-4292 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science
Website: http://www.mdpi.com/journal/remotesensing/

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