Currently, while the informatization of real estate registration in China has achieved initial completion, bottlenecks persist in business process coordination, human-machine intelligent interaction, and service response efficiency, making it difficult to meet the demand for high-efficiency services in the digital era. Addressing these challenges, this paper proposes a system intelligent reconstruction solution that integrates Large Language Models (LLMs), Model Context Protocols (MCP), and atomic services. This solution utilizes LLM as the interactive interface for deep semantic understanding and task decomposition of user meeds expressed in natural language. It utilizes MCP as the core bridge to manage and transmit structured context, connecting semantics with execution. Atomic services form the functional cornerstone, supporting the dynamic and flexible intelligent orchestration of business processes based on real-time contexts. This paper constructs a new end-to-end intelligent process model that extends from "intelligent consultation" for precise intent understanding to "assisted execution" for efficient transaction processing. An AI-native system architecture is designed, encompassing layers for user interaction, intelligent cognition, context orchestration, and atomic services. This architecture breaks through the critical barrier between semantic understanding and backend business execution, transforming the real estate registration process from a fixed, predefined process to a dynamic and intelligent one. This paper not only provides a systematic technical solution and theoretical support for the intelligent upgrading of the real estate registration services, but also offers a replicable paradigm for the intelligent reconstruction of other government services.

Cultivated land non-grainization conversion has always been an unavoidable major problem of food security. At present, although the relevant data of cultivated land non-grainization conversion has been obtained through the three surveys and the latest land change survey data, the information has not yet been systematically integrated, and it is impossible to combine geographical and professional knowledge reasoning to produce high-value knowledge outputs, which makes it difficult for the government to make the best decisions and judgments when facing massive data. Therefore, in order to solve this problem, this paper proposes a process and technical framework for the construction of knowledge graph of survey and monitoring results of cultivated land non-grainization conversion, so as to provide comprehensive and high-quality services for the protection of cultivated land non-grainization conversion. Specifically, this paper uses the RoBERTa-BiLSTM-CRF deep learning algorithm to extract the knowledge of multi-source heterogeneous survey and monitoring data of various types of cultivated land, and obtains the business knowledge in the field of cultivated land non-grainization conversion, and constructs a knowledge system of cultivated land non-grainization conversion. Then, the knowledge question and answer system is developed based on the RoBERTa model to realize interactive, efficient and high-precision natural language question and answer analysis, and realize the construction and application of knowledge graph of survey and monitoring results of cultivated land non-grainization conversion. Finally, the automatic construction, knowledge extraction, and high-degree automation improvement and updating of the knowledge base of cultivated land non-grainization ontology are summarized and prospected.

The low-altitude economy is undergoing explosive expansion as a strategic emerging industry, facilitated by the technological convergence of communication, navigation, remote sensing, and artificial intelligence. The resource management and infrastructure construction of low-altitude airspace are gradually becoming new research directions. This study aims to thoroughly examine the definition, characteristics, current development status, and challenges faced by the low-altitude economy, and systematically explore the specific development opportunities that exist for the natural resources departments. Utilizing the methods of literature review and comprehensive analysis, the following conclusions have been drawn: as an emerging economic form, the low-altitude economy has become an important engine for promoting high-quality economic development. However, it faces challenges such as limited airspace resources, insufficient infrastructure, inadequate control capabilities, and insufficient application scenarios. Natural resources departments can focus on the digital representation of low-altitude airspace, integrated air-ground planning of air and ground, construction of low-altitude UAV remote sensing networks, and the development of intelligent drone navigation maps. These efforts can address the key challenges in the development of the low-altitude economy. Additionally, strengthening the application of low-altitude UAVs in natural resources surveys, natural resources protection, post-approval land supervision, and law enforcement supervision can promote innovation and reform in the management of natural resources. The study ultimately points out that the development of the low- altitude economy is gradually involving core issues such as the planning and management of low-altitude airspace as a special type of natural resources. As the unified exercising department of natural resources ownership, if natural resources departments can make early strategic deployments and actively strive for the management authority of low- altitude airspace, it is expected to become one of the leading forces in the future development of the low-altitude economy, injecting new and powerful impetus into its growth.

In recent years, global carbon dioxide emissions have continued to rise, and replacing fossil fuels with clean energy has become a crucial approach to addressing global climate issues. Solar energy, as one of the most widely distributed clean energy sources, holds enormous development potential in China due to its vast territory. Based on ERA5 data from 1994 to 2023, this article analyzes the spatial distribution pattern of solar energy resources in China by using geographical suitability and resource potential analysis methods, taking into account factors such as terrain conditions, land use types, and social policies, and evaluates the resource potential. The study shows that China is rich in solar energy resources, generally presenting a distribution characteristic of "high in the northwest and low in the southeast". However, when geographical suitability is taken into account, the solar energy resources in regions such as Xizang, southern Xinjiang, Qinghai, and northwestern Sichuan significantly decrease. The solar radiation intensity generally shows the order of summer, spring, autumn and winter, but under the combined influence of geography and climate, some areas exhibit special phenomena where spring radiation intensity is higher than that in summer, and the rankings between spring-summer and autumn-winter differ significantly. Xinjiang, Inner Mongolia, Gansu, and Qinghai have higher net solar power generation while regions like Zhejiang, Guangdong, Jiangsu, Shanghai, and Beijing have lower solar power generation.

In order to promote the reform of the "land use list system" for social investment projects, implement the requirements of "decentralization, management, and service", and promote the development of project planning and generation work, this study has sorted out and formed the content of the land use list and the process of project generation. It explores a new mode of integration of "project planning generation", "regional evaluation", and "land use list system". By leveraging Geographic Information Systems (GIS) and internet-based information technologies, a full-process generation model for engineering construction project planning is designed, and a corresponding model system is established. Through solidifying processes, clarifying responsibilities, integrating regional evaluation results, and analyzing various indicators, the model achieves full-process control of project planning from project input, reserve, initiation planning, site selection, compliance review, regional evaluation analysis, coordination and consultation, feedback to the final generation of project planning reports. This approach achieves full process control of project planning, coordinates project construction conditions, promotes the operation of "land use list system", achieves decentralization and empowerment, enables early planning, accelerates approval and services, and opens up a "fast track" for project planning.

This article is aiming at the problem of low efficiency of manual comparison between as-built project drawings and digital orthophoto maps in the verification of new cultivated land renovation, and an intelligent comparison and efficient verification method based on maps under the framework of deep learning technology has been proposed. The technical methods and processes of specific elements extraction of images, deep learning feature recognition, automatic registration of images, and intelligent comparison of images are designed. Five groups of data distributed in different terrain areas in Guangdong are randomly selected for feature recognition and automatic registration experiments. The recall rates of the extraction results are all better than 81 %, and the accuracy rates are all better than 83 %. At the same time, the automatic registration intersection ratios are all better than 0.9, which meets the basic needs of automatic interpretation in practical projects. The experiments show this method can greatly reduce the manual effort of comparison of the total workload of cultivated land construction and the scope of newly added cultivated land.

Regional ecological sensitivity evaluation plays an important role in guiding regional urban planning, industrial layout and ecological environment protection, and it is also an important basic work for the construction of ecological civilization. Taking Shunde as the study area, 11 evaluation indexes have been selected from 3 dimensions of soil erosion, geological disasters and habitat, and the weight system of ecological sensitivity evaluation indexes is constructed by using AHP-DEA optimal combination weighting method, and the single factor and multi-factor comprehensive ecological sensitivity of Shunde are analyzed by using GIS geospatial analysis and visualization technology. According to the results of the analysis, the study area is divided into 5 kinds of areas: extremely sensitive, highly sensitive, moderately sensitive, slightly sensitive and insensitive. Suggestions and references are provided for urban planning and ecological protection in each area.

At present, there are problems in the integrated monitoring of natural resources, such as lack of the systematic planning and collaboration between monitoring works, unsmooth connection among system platforms, heavy workload at the grassroots level, and limited governance rights in natural resources comprehensive monitoring. This paper proposes a technical framework for building natural resources comprehensive monitoring technological capabilities, including collaborative collection of natural resources data, rapid production and intelligent interpretation of basemaps, parallel processing of in-field work and rapid evidence collection, and intelligent services based on patch entities. The explorations of the UAVs collaborative and fast acquisition of high-resolution imagery, image control library-based rapid production and service of basemaps, interpretation of UAV images based on artificial intelligence and the single patch-based land change survey operation platform development are implemented, which will strongly support the refined management of natural resources in Guangxi and further promote the modernization of governance system and governance capacity of natural resources.

Comprehensively and accurately grasping the current status of industrial land use of the city is of great significance for optimizing the allocation of resource elements, promoting the transformation and upgrading of industrial structures, and facilitating the high-quality development of the industrial chain. Taking Nanjing as an example, by combing multi-source industrial land use data such as the results of the third national land survey, industrial enterprise land use survey, and industrial enterprises from industrial and information technology departments, and based on a comprehensive analysis of the differences among various data sources, the construction path of the thematic database for the industrial land use status has been explored. By selecting typical areas to carry out practice, data standards, technical requirements and mapping specifications for the thematic database of industrial land use status have been formed, which has provided references for the construction of the thematic database for the industrial land use status of the city.

The three-dimensional exploration of mineral resource ownership registration for proven reserves is of great significance for more intuitively delineating the "four boundaries" of mineral resource, defining the subject of mineral resource property rights, promoting the assetization management of mineral resources and the clarification of property rights, and achieving mineral resource ownership registration. This article is based on the practice and application of mineral resource certification and registration for provincial-level proven reserves in Hebei. The Ningjin Duanjiazhuang Salt Mine and Shahe Zhongguan Iron Mine were selected as pilot projects, and the exploration and application of 3D modeling and 3D visualization technology methods were systematically carried out. A series of technical issues that need attention have been sorted out and summarized around key registration processes such as data collection, data analysis, and 3D modeling. The study analyzed the challenges in the current process of mineral resource rights registration, including the utilization of multi-source data, optimization of registration units, model accuracy, optimization of registration books, and optimization of natural resource databases. Targeted suggestions were put forward to promote data sharing, optimize modeling methods, and clarify three-dimensional registration standards. This study not only provides a practical and feasible three-dimensional technical path and practical reference for promoting the registration of mineral resource rights in Hebei, but also has important reference significance for the development of similar work in other regions.

Under the strategic background of regional coordinated development, it is of great value to explore the "production-living-ecological space" for coordinating territorial spatial planning and improving land conflicts. Based on 1499 papers related to "production-life-ecological space" on CNKI from 2013 to 2023, this paper uses CiteSpace software to analyze the number of papers, research hotspots and evolution trends. The results show that from the perspective of the number of publications, the research results of "production-life-ecological space" have gradually increased since the 18th National Congress of the Communist Party of China; from the perspective of research hotspots, the biggest keyword nodes are rural revitalization, land use, territorial space and temporal and spatial evolution. The literature topics mainly focus on the functional identification, influencing factors and spatial optimization of "production-living-ecological space"; and from the perspective of evolution trend, the research on "production-living-ecological space" is guided by national policy documents, among which the research heat of territorial space, resilient cities and carbon emissions is gradually increasing.

Conducting natural resources auditing is a fundamental task for achieving ecological civilization construction and high-quality economic development. Based on this, using bibliometric literature analysis methods, and CiteSpace software, this study visualizes and analyzes 1090 journal articles related to "natural resource auditing" published in China from 2009 to 2023. The research stages are divided into a slow development period (2009-2013), a rapid growth period (2014-2018), and a fluctuating decline period (2019-present). The authors and institutions of the publication are relatively scattered, and academic exchanges still need to be further strengthened. The research hotspots mainly focus on three aspects: the improvement of natural resources asset auditing mode, the development and application of natural resources auditing technologies, and the significance of natural resources auditing. In the future, it is necessary to promote exchanges between different disciplines and regions, broaden the resources scope of natural resources auditing, and accelerate the establishment of a long-term mechanism for relevant departments to coordinate and cooperate in natural resources auditing work, thereby enhancing the research level of natural resources auditing in China.