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Digital-Intelligence Assessment of Production–Living–Ecological Spaces for Agricultural Modernization: A Case Study of Ulanqab City
Research Article  ·  Published: 08 December 2025
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Digital Intelligence in Agriculture
Volume 1, Issue 2, 2025: 61-78
Research Article Open Access

Digital-Intelligence Assessment of Production–Living–Ecological Spaces for Agricultural Modernization: A Case Study of Ulanqab City

by
Yuxiu Cui Yuxiu Cui 1 ORCID
Yueming Chang Yueming Chang 1 * ORCID
Ying Hong Ying Hong 1 ORCID
Yuling Yan Yuling Yan 2 ORCID
1 School of Geographical Sciences, Inner Mongolia Normal University, Hohhot 010022, China
2 Propaganda Department of the Party Committee, Hetao College, Bayannur 015000, China
* Corresponding Author: Yueming Chang, [email protected]
Volume 1, Issue 2
Volume 1, Issue 2 2025
Received: 17 September 2025 Accepted: 11 November 2025 Published: 08 December 2025 CrossMark
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DOI: 10.62762/DIA.2025.135622
ARK: ark:/57805/dia.2025.135622

Article Information

Published in Digital Intelligence in Agriculture
Volume/Issue Volume 1, Issue 2, 2025
Pages 61-78

Abstract

Against the backdrop of the synergistic advancement of rural revitalization and agricultural modernization, optimizing the Production-Living-Ecological (PLE) spatial pattern and introducing digital-intelligent technologies have become key pathways for enhancing sustainable rural development capabilities. This study takes Ulanqab City in Inner Mongolia, a typical agro-pastoral ecotone, as a case study. Based on multi-source remote sensing image data from 2000 to 2020, it comprehensively utilizes a coupling coordination model and spatial information technology to evaluate the evolution characteristics of its PLE spaces and the coordination mechanisms of agricultural functions, supplemented by NDVI and soil moisture data to link ecological and agricultural functions. The results indicate that the city's PLE spaces exhibit a pattern of "North-South differentiation, overall coordination," temporally evolving through three stages: "maladjustment-breaking-in-differentiation." The southern region promotes PLE synergy and urban-rural integration leveraging clean energy and smart logistics; the central region maintains functional balance through the Grain for Green program and characteristic eco-agriculture; the northern region is constrained by traditional animal husbandry and ecological degradation. Addressing regional disparities, differentiated pathways are proposed: developing "smart agriculture + digital supply chains" in the south, constructing an "ecological–intensive" intelligent animal husbandry model in the north, and establishing a remote sensing and Internet of Things (IoT) based value realization mechanism for eco-agriculture in the central region. Recommendations include enhancing agricultural digitalization levels and PLE functional coordination through spatial regulation, green technology empowerment, and ecological compensation policies, providing theoretical and data support for achieving sustainable agricultural development and modernized rural revitalization.

Graphical Abstract

Digital-Intelligence Assessment of Production–Living–Ecological Spaces for Agricultural Modernization: A Case Study of Ulanqab City

Keywords

production-living-ecological (PLE) spaces digital intelligence agricultural modernization coupling coordination model Ulanqab City

Data Availability Statement

The data used in this study are publicly available from the following sources: (1) Administrative division data from the National Geomatics Center of China (https://cloudcenter.tianditu.gov.cn/administrativeDivision); (2) Supporting datasets available on Figshare (https://doi.org/10.6084/m9.figshare.26028769); (3) Socioeconomic and auxiliary data from Harvard Dataverse (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/GIYGJU); (4) MODIS vegetation index data (MOD13A2, Collection~6) accessed via Google Earth Engine (https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13A2).

Funding

This work was supported by the Key Project of Humanities and Social Sciences of the Education Department of Inner Mongolia Autonomous Region under Grant NJSZ23011 and the Major Science and Technology Project of Inner Mongolia Autonomous Region under Grant 2019ZD001.

Conflicts of Interest

The authors declare no conflicts of interest.

Ethical Approval and Consent to Participate

Not applicable.

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APA Style
Cui, Y., Chang, Y., Hong, Y., & Yan, Y. (2025). Digital-Intelligence Assessment of Production–Living–Ecological Spaces for Agricultural Modernization: A Case Study of Ulanqab City. Digital Intelligence in Agriculture, 1(2), 61–78. https://doi.org/10.62762/DIA.2025.135622
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TY  - JOUR
AU  - Cui, Yuxiu
AU  - Chang, Yueming
AU  - Hong, Ying
AU  - Yan, Yuling
PY  - 2025
DA  - 2025/12/08
TI  - Digital-Intelligence Assessment of Production–Living–Ecological Spaces for Agricultural Modernization: A Case Study of Ulanqab City
JO  - Digital Intelligence in Agriculture
T2  - Digital Intelligence in Agriculture
JF  - Digital Intelligence in Agriculture
VL  - 1
IS  - 2
SP  - 61
EP  - 78
DO  - 10.62762/DIA.2025.135622
UR  - https://www.icck.org/article/abs/DIA.2025.135622
KW  - production-living-ecological (PLE) spaces
KW  - digital intelligence
KW  - agricultural modernization
KW  - coupling coordination model
KW  - Ulanqab City
AB  - Against the backdrop of the synergistic advancement of rural revitalization and agricultural modernization, optimizing the Production-Living-Ecological (PLE) spatial pattern and introducing digital-intelligent technologies have become key pathways for enhancing sustainable rural development capabilities. This study takes Ulanqab City in Inner Mongolia, a typical agro-pastoral ecotone, as a case study. Based on multi-source remote sensing image data from 2000 to 2020, it comprehensively utilizes a coupling coordination model and spatial information technology to evaluate the evolution characteristics of its PLE spaces and the coordination mechanisms of agricultural functions, supplemented by NDVI and soil moisture data to link ecological and agricultural functions. The results indicate that the city's PLE spaces exhibit a pattern of "North-South differentiation, overall coordination," temporally evolving through three stages: "maladjustment-breaking-in-differentiation." The southern region promotes PLE synergy and urban-rural integration leveraging clean energy and smart logistics; the central region maintains functional balance through the Grain for Green program and characteristic eco-agriculture; the northern region is constrained by traditional animal husbandry and ecological degradation. Addressing regional disparities, differentiated pathways are proposed: developing "smart agriculture + digital supply chains" in the south, constructing an "ecological–intensive" intelligent animal husbandry model in the north, and establishing a remote sensing and Internet of Things (IoT) based value realization mechanism for eco-agriculture in the central region. Recommendations include enhancing agricultural digitalization levels and PLE functional coordination through spatial regulation, green technology empowerment, and ecological compensation policies, providing theoretical and data support for achieving sustainable agricultural development and modernized rural revitalization.
SN  - 3069-3187
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  -
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@article{Cui2025DigitalInt,
  author = {Yuxiu Cui and Yueming Chang and Ying Hong and Yuling Yan},
  title = {Digital-Intelligence Assessment of Production–Living–Ecological Spaces for Agricultural Modernization: A Case Study of Ulanqab City},
  journal = {Digital Intelligence in Agriculture},
  year = {2025},
  volume = {1},
  number = {2},
  pages = {61-78},
  doi = {10.62762/DIA.2025.135622},
  url = {https://www.icck.org/article/abs/DIA.2025.135622},
  abstract = {Against the backdrop of the synergistic advancement of rural revitalization and agricultural modernization, optimizing the Production-Living-Ecological (PLE) spatial pattern and introducing digital-intelligent technologies have become key pathways for enhancing sustainable rural development capabilities. This study takes Ulanqab City in Inner Mongolia, a typical agro-pastoral ecotone, as a case study. Based on multi-source remote sensing image data from 2000 to 2020, it comprehensively utilizes a coupling coordination model and spatial information technology to evaluate the evolution characteristics of its PLE spaces and the coordination mechanisms of agricultural functions, supplemented by NDVI and soil moisture data to link ecological and agricultural functions. The results indicate that the city's PLE spaces exhibit a pattern of "North-South differentiation, overall coordination," temporally evolving through three stages: "maladjustment-breaking-in-differentiation." The southern region promotes PLE synergy and urban-rural integration leveraging clean energy and smart logistics; the central region maintains functional balance through the Grain for Green program and characteristic eco-agriculture; the northern region is constrained by traditional animal husbandry and ecological degradation. Addressing regional disparities, differentiated pathways are proposed: developing "smart agriculture + digital supply chains" in the south, constructing an "ecological–intensive" intelligent animal husbandry model in the north, and establishing a remote sensing and Internet of Things (IoT) based value realization mechanism for eco-agriculture in the central region. Recommendations include enhancing agricultural digitalization levels and PLE functional coordination through spatial regulation, green technology empowerment, and ecological compensation policies, providing theoretical and data support for achieving sustainable agricultural development and modernized rural revitalization.},
  keywords = {production-living-ecological (PLE) spaces, digital intelligence, agricultural modernization, coupling coordination model, Ulanqab City},
  issn = {3069-3187},
  publisher = {Institute of Central Computation and Knowledge}
}

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