Land use efficiency in the era of digital transformations: experience of China’s land resource management

The article presents a comprehensive institutional, spatial, and econometric analysis of land resource management transformation driven by digitalization, focusing on the experience of the People’s Republic of China, and outlines conceptual directions for adapting these practices to Ukraine’s post-war recovery. The study substantiates Green Land Use Efficiency (GLUE) as an advanced paradigm that integrates economic productivity with environmental risk minimization, resource saving, and carbon footprint reduction in the context of sustainable spatial development. The research thoroughly investigates China’s pivotal 2018 institutional reform, which eliminated interagency fragmentation by establishing the Ministry of Natural Resources and implementing the “multi-plan integration” (Duogui Heyi) framework. The engineering and technological foundations of the National Territorial Spatial Planning “One Map” platform are revealed alongside the “Tiandi Wang” dynamic monitoring system (RS + AI + Beidou) and the “three zones and three lines” spatial control framework. The paper systematizes the mathematical apparatus for measuring GLUE based on non-radial Super-SBM models (accounting for undesirable outputs) and Spatial Durbin Models (SDM), and empirically verifies initial spatial siphoning and subsequent green spillover effects across neighboring regions. Furthermore, the paper highlights sectoral and spatial specificities of land digitalization: the deployment of 3D/4D cadastral modeling, BIM, and Digital Twin Cities in densely populated urban agglomerations, versus electronic farmland circulation platforms (Sanquan Fengli) and satellite-driven precision agriculture in rural regions. The analysis also identifies key structural risks, including regional digital divides, local fiscal dependencies on land finance, and data security vulnerabilities. Finally, the study proposes practical directions for modernizing Ukraine’s spatial management. These include creating a unified National GIS Superplatform compliant with EU INSPIRE standards, deploying AI-driven satellite monitoring for war-damage auditing and mine-clearance prioritization, and legally establishing a digital spatial framework for recovery and ecological-protection lines. Keywords: Green Land Use Efficiency (GLUE), digital transformation, GIS platforms, One Map system, “three zones and three lines”, Super-SBM model, Spatial Durbin Model, post-war recovery of Ukraine, Beidou, State Land Cadastre.

Authors

Institutions

Publication Details

Journal
Actual problems of innovative economy and law
Published
2026-11-03
DOI
https://doi.org/10.36887/2524-0455-2026-5-8
Primary Topic
Land Use and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Land use efficiency in the era of digital transformations: experience of China’s land resource management

Тетяна Власенко
Actual problems of innovative economy and law
Land Use and Management
article

Land use efficiency in the era of digital transformations: experience of China’s land resource management

Тетяна Власенко
article en

Abstract

The article presents a comprehensive institutional, spatial, and econometric analysis of land resource management transformation driven by digitalization, focusing on the experience of the People’s Republic of China, and outlines conceptual directions for adapting these practices to Ukraine’s post-war recovery. The study substantiates Green Land Use Efficiency (GLUE) as an advanced paradigm that integrates economic productivity with environmental risk minimization, resource saving, and carbon footprint reduction in the context of sustainable spatial development. The research thoroughly investigates China’s pivotal 2018 institutional reform, which eliminated interagency fragmentation by establishing the Ministry of Natural Resources and implementing the “multi-plan integration” (Duogui Heyi) framework. The engineering and technological foundations of the National Territorial Spatial Planning “One Map” platform are revealed alongside the “Tiandi Wang” dynamic monitoring system (RS + AI + Beidou) and the “three zones and three lines” spatial control framework. The paper systematizes the mathematical apparatus for measuring GLUE based on non-radial Super-SBM models (accounting for undesirable outputs) and Spatial Durbin Models (SDM), and empirically verifies initial spatial siphoning and subsequent green spillover effects across neighboring regions. Furthermore, the paper highlights sectoral and spatial specificities of land digitalization: the deployment of 3D/4D cadastral modeling, BIM, and Digital Twin Cities in densely populated urban agglomerations, versus electronic farmland circulation platforms (Sanquan Fengli) and satellite-driven precision agriculture in rural regions. The analysis also identifies key structural risks, including regional digital divides, local fiscal dependencies on land finance, and data security vulnerabilities. Finally, the study proposes practical directions for modernizing Ukraine’s spatial management. These include creating a unified National GIS Superplatform compliant with EU INSPIRE standards, deploying AI-driven satellite monitoring for war-damage auditing and mine-clearance prioritization, and legally establishing a digital spatial framework for recovery and ecological-protection lines. Keywords: Green Land Use Efficiency (GLUE), digital transformation, GIS platforms, One Map system, “three zones and three lines”, Super-SBM model, Spatial Durbin Model, post-war recovery of Ukraine, Beidou, State Land Cadastre.

Actual problems of innovative economy and lawVol. 2026(5)
Simon Kuznets Kharkiv National University of Economics (UA)
Openalex Percentile: Top 6%
Land Use and Management
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.

Laika access coming soon