Study on the Evolution of Spatiotemporal Dynamics and Regional Differences in the Development of Digital Agriculture in China

In the current study, an index system for digital agriculture growth was constructed. The index encompasses six key dimensions, namely production, operation, service, management, sustainability, and digital information infrastructure. Data from 30 Chinese provinces between 2011 and 2020 were collected and analyzed using the entropy method, Moran index, Dagum’s Gini coefficient, and the kernel density estimate. An in-depth analysis of the development level and spatial patterns, dynamic evolution and intra- and inter-regional differences in China (i.e., eastern, western, and central regions) was conducted. From the result, an overall growing trend of digital agriculture in China was observed, with a relatively more advanced status in the eastern region. A positive spatial dependence, showing a “high-high” and “low-low” (HH, LL) trend, was obtained. However, the regional spatial dependence has generally weakened since 2019. The intra-regional differences were large in western and eastern areas, while the greatest inter-regional differences were unveiled between western and eastern regions. The country’s overall differences mainly stemmed from inter-regional differences. The overall kernel density curves moved to the right over time, showing a trend of a gradual rise in digital agricultural growth, accompanied by a polarization pattern in the western region.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2024-08-13
DOI
https://doi.org/10.3390/su16166947
Citations
3
Primary Topic
Regional Development and Environment
Type
article
Field-Weighted Citation Impact
3.40

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Study on the Evolution of Spatiotemporal Dynamics and Regional Differences in the Development of Digital Agriculture in China

Bangbang Zhang, Tong Chen, Xinxin Zhou
3 citations
Sustainability
Regional Development and Environment
3.40
article

Study on the Evolution of Spatiotemporal Dynamics and Regional Differences in the Development of Digital Agriculture in China

Bangbang Zhang, Tong Chen, Xinxin Zhou
article en
3 citations

Abstract

In the current study, an index system for digital agriculture growth was constructed. The index encompasses six key dimensions, namely production, operation, service, management, sustainability, and digital information infrastructure. Data from 30 Chinese provinces between 2011 and 2020 were collected and analyzed using the entropy method, Moran index, Dagum’s Gini coefficient, and the kernel density estimate. An in-depth analysis of the development level and spatial patterns, dynamic evolution and intra- and inter-regional differences in China (i.e., eastern, western, and central regions) was conducted. From the result, an overall growing trend of digital agriculture in China was observed, with a relatively more advanced status in the eastern region. A positive spatial dependence, showing a “high-high” and “low-low” (HH, LL) trend, was obtained. However, the regional spatial dependence has generally weakened since 2019. The intra-regional differences were large in western and eastern areas, while the greatest inter-regional differences were unveiled between western and eastern regions. The country’s overall differences mainly stemmed from inter-regional differences. The overall kernel density curves moved to the right over time, showing a trend of a gradual rise in digital agricultural growth, accompanied by a polarization pattern in the western region.

SustainabilityVol. 16(16)
Xinjiang Agricultural University (CN), Xinjiang Academy of Agricultural Sciences (CN), Huainan Normal University (CN), Northwest A&F University (CN)
National Natural Science Foundation of China
Zero hunger
Openalex Percentile: Top 7%
Regional Development and Environment
3.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.