TY  - JOUR
AU  - Wang, Yiyi
AU  - Wang, Xiaoqing
PY  - 2026
DA  - 2026/05/08
TI  - Farming Upward: The TsingSky Guangzhou Future Agriculture Cluster as a County-Level Model for Context-Specific Smart Agriculture
JO  - Digital Intelligence in Agriculture
T2  - Digital Intelligence in Agriculture
JF  - Digital Intelligence in Agriculture
VL  - 2
IS  - 2
SP  - 68
EP  - 78
DO  - 10.62762/DIA.2026.309098
UR  - https://www.icck.org/article/abs/DIA.2026.309098
KW  - smart agriculture
KW  - controlled-environment agriculture
KW  - sky farm
KW  - county-level development
KW  - agricultural cluster
KW  - context-specific development
KW  - low-carbon agriculture
KW  - integrated rural industries
AB  - Against the backdrop of global food-security concerns, climate change, farmland constraints, and accelerating urbanization, modern agriculture is shifting from a land-dependent model toward a new paradigm shaped by spatial reconfiguration, energy integration, advanced equipment, and digital intelligence. Food systems account for a large share of anthropogenic greenhouse-gas emissions, making low-carbon transformation a central issue. Projected global food demand and hunger risk highlight the need for both productivity and resilience. Emissions from long-distance transport also suggest that localized production near consumption centers deserves greater attention. Taking the TsingSky Guangzhou Future Agriculture Cluster as its central case, this article explores how county-level demonstration projects can serve as anchors for context-specific smart agriculture. Smart agriculture should be understood not merely as the application of sensors or data platforms, but as the creation of sustainable, replicable, and industrialized systems adapted to local conditions. Controlled-environment agriculture offers a promising pathway for high-yield, resource-efficient, climate-resilient production, but its viability depends on energy efficiency, cost structure, and system integration. The TsingSky Guangzhou Sky Farm redefines agricultural space by utilizing approximately 50 mu of factory rooftop area and integrating residual industrial heat, shallow-water source heat pumps, agricultural R&D, and intelligent equipment manufacturing into a unified county-level platform. This model preserves farmland, supports production near consumer markets, reduces pest and logistics pressures, improves spatial efficiency, and enhances economic performance. More importantly, it shows how a single demonstration project can evolve into a future agriculture cluster through integration of production, research, manufacturing, training, branding, and low-carbon energy systems.
SN  - 3069-3187
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Wang2026Farming,
  author = {Yiyi Wang and Xiaoqing Wang},
  title = {Farming Upward: The TsingSky Guangzhou Future Agriculture Cluster as a County-Level Model for Context-Specific Smart Agriculture},
  journal = {Digital Intelligence in Agriculture},
  year = {2026},
  volume = {2},
  number = {2},
  pages = {68-78},
  doi = {10.62762/DIA.2026.309098},
  url = {https://www.icck.org/article/abs/DIA.2026.309098},
  abstract = {Against the backdrop of global food-security concerns, climate change, farmland constraints, and accelerating urbanization, modern agriculture is shifting from a land-dependent model toward a new paradigm shaped by spatial reconfiguration, energy integration, advanced equipment, and digital intelligence. Food systems account for a large share of anthropogenic greenhouse-gas emissions, making low-carbon transformation a central issue. Projected global food demand and hunger risk highlight the need for both productivity and resilience. Emissions from long-distance transport also suggest that localized production near consumption centers deserves greater attention. Taking the TsingSky Guangzhou Future Agriculture Cluster as its central case, this article explores how county-level demonstration projects can serve as anchors for context-specific smart agriculture. Smart agriculture should be understood not merely as the application of sensors or data platforms, but as the creation of sustainable, replicable, and industrialized systems adapted to local conditions. Controlled-environment agriculture offers a promising pathway for high-yield, resource-efficient, climate-resilient production, but its viability depends on energy efficiency, cost structure, and system integration. The TsingSky Guangzhou Sky Farm redefines agricultural space by utilizing approximately 50 mu of factory rooftop area and integrating residual industrial heat, shallow-water source heat pumps, agricultural R\&D, and intelligent equipment manufacturing into a unified county-level platform. This model preserves farmland, supports production near consumer markets, reduces pest and logistics pressures, improves spatial efficiency, and enhances economic performance. More importantly, it shows how a single demonstration project can evolve into a future agriculture cluster through integration of production, research, manufacturing, training, branding, and low-carbon energy systems.},
  keywords = {smart agriculture, controlled-environment agriculture, sky farm, county-level development, agricultural cluster, context-specific development, low-carbon agriculture, integrated rural industries},
  issn = {3069-3187},
  publisher = {Institute of Central Computation and Knowledge}
}