The basic concept and recent research progress of Digital Basin (DB) are introduced in the light of the strategic demand of water resource development in the new era. Key technologies inclusive of the basic framework and technical standards, the comprehensive observation system involving space, air, and ground data, the organization, processing and sharing of multi  source mass spatio  temporal data, and multi  disciplinary model integration and application are discussed in detail. The practices of applying digital basin to the operation and management of Three Gorges Project are analyzed. The applications are summarized and looked forward.

为了应对全球气候变化和人类剧烈活动导致的水资源短缺、洪灾旱灾并重和生态环境恶化等复杂水资源情势, 推动流域信息化水平向更高层次发展, 借鉴"智慧地球"的理念提出了"智慧流域"这一概念. 分析了智慧流域建设的战略需求和技术推动因素, 提出了智慧流域的涵义并阐述了其特征, 设计了智慧流域总体框架, 对其中使用的关键技术和支撑平台, 如物联网技术、射频识别标签、无线传感器网络、云计算与云存储、 流域虚拟现实系统平台、基于多源耦合的气象水文信息保障平台、二元水循环数值模拟平台、水资源数值调控平台和流域数据同化系统平台等进行了探讨. 最后研究了智慧流域在防洪减灾、抗御干旱、防治污染和水资源管理 中的具体应用. 智慧流域是水利信息化的发展趋势和最高层次, 必将产生新的学科增长点, 在水利各个领域有着良好的应用前景.

测绘生产与服务面临着数据获取实时化、信息处理自动化、服务应用知识化等诸多新难题。以算法、模型为核心的数字化测绘，往往无法用简洁的算法、模型，实现对纷繁多样、多维动态现实世界进行完整描述与表达，难以满足高维、非线性的空间问题求解要求。为破解这一难题，应模仿和利用人类的测绘自然智能，研发以知识为引导、算法为基础的智能化测绘技术。本文首先讨论了智能化测绘的基本概念与思路；继而分析指出了智能化测绘的三个基本问题，包括测绘自然智能的解析与建模、混合型智能计算范式的构建与实现、赋能生产的机制与路径；然后提出了今后一段时间的主要努力方向，包括构建智能化测绘的知识体系、研究技术方法、研发应用系统和仪器装备。为了切实地推动这方面的科技研发与工程应用，应该加强顶层设计，推动跨学科协同创新，促进产学研合作，营造良好发展环境。

Surveying and mapping production and services are facing many new problems such as real-time data acquisition, automation of information processing, and intellectualization of service applications. The main reason is that digital surveying and mapping involves complex algorithms and models as the core, and it is often impossible to use simple algorithms and models to completely describe and express the diverse, multi-dimensional and dynamic real world, which makes it difficult to address high-dimensional, nonlinear spatial problems. In order to address this challenge, it is necessary to explore the use of natural intelligence in surveying and mapping, and develop smart surveying and mapping technologies guided by knowledge and based on algorithms. This paper first discusses the basic concepts and ideas of smart surveying and mapping and then analyzes and points out the three basic problems of smart surveying and mapping, including the analysis and modeling of natural intelligence in surveying and mapping, the construction and realization of hybrid intelligent computing paradigm, and the mechanism and path of empowering production. The main directions for further development in the near future are then proposed, including the construction of knowledge system of smart surveying and mapping, research of technology methods, research and development of application systems and instrument equipment. In order to effectively promote scientific research and engineering applications in this area, efforts should be placed on top-level designing, promoting interdisciplinary collaborative innovation and industry-university-research cooperation, and creating good development environments.

高空间分辨率的地表或者大气环境动态监测需要高时间-空间分辨率的卫星遥感影像作为数据支撑，但由于卫星传感器硬件技术及卫星发射成本等客观因素的限制，使得获取高时空分辨率遥感影像的较为便捷高效、低成本的可行手段就是将分别具有高时间和高空间分辨率的多源遥感影像进行时空融合，从而生成不同研究和应用所需的高时空分辨率卫星影像。现阶段，虽然国内外的学者进行了大量的时空融合算法研究，但是这些研究都局限于特定的数据类型、算法原理、应用目的等客观限制，而且其发展呈现出多样性。本文对现有主流的时空融合算法研究进行了归纳总结，将其分为4种：①基于地物组分的时空融合；②基于地表空间信息的时空融合；③基于地物时相变化的时空融合；④组合性的时空融合。同时，本文还对时空融合算法中存在的问题和面临的挑战进行了分析，并对其未来的发展方向进行了前瞻性的展望。

High spatial resolution monitoring of land surface and atmospheric environment dynamics requires high spatiotemporal resolution satellite remote sensing imagery as data support. However, the efficient, low-cost, and feasible solution is to blend the multi-source images with high-spatial and high-temporal resolution respectively to produce the desired high spatiotemporal resolution imagery required by different research or applications, which is subject to the limitations of satellite sensor' hardware technology and the budget constraints of launching more satellites. Although plenty of spatiotemporal image fusion research has been conducted, they are limited to specific data types, algorithm principles, application purposes, etc. Furthermore, the development of spatiotemporal image fusion algorithm presents a phenomenon of disorder. This study summarizes and generalizes the existing mainstream spatiotemporal fusion methods and classified them into four categories:①spatiotemporal fusion based on land components; ②spatiotemporal fusion based on spatial information; ③spatiotemporal fusion based on temporal changes; ④combined spatiotemporal fusion. Meanwhile, the study analyzes the problems and challenges faced by spatiotemporal fusion; and informs the prospects of the future development of spatiotemporal fusion method.

从实景三维建模到数字孪生建模是国家数字经济和智慧社会建设与发展的基本需求。本文探讨了实景三维建模和数字孪生建模的关键技术内涵,介绍了数字乡村、未来社区和智能铁路等典型应用场景。广域范围实景三维建模在低成本高效数据采集和智能化自动化三维精细建模与动态更新方面面临挑战,城市级或重大工程级的数字孪生建模在全要素整体性的表征数据与机理模型集成表达方面还存在关键技术瓶颈。测绘技术亟须多学科交叉融合创新,突破天空地有机协同实时动态获取多细节层级实景三维数据、智能化处理多专业多尺度多模态时空数据、不完备数据条件下复杂场景的三维实体化精细建模、表征数据与机理模型结合的全生命周期数字孪生模型动态构建等核心关键技术,形成通用地理空间智能,实现测绘技术的高质量发展和对经济社会发展不可替代的更有力的基础支撑。

From real 3D modeling to digital twin modeling is the basic requirement for the construction and development of the country's digital economy and smart society. This paper discusses the connotations and key technologies of real 3D modeling and digital twin modeling, and introduces three typical application scenarios: digital villages, future communities and intelligent railways. Wide-area real 3D modeling is facing challenges in low-cost and efficient data collection and intelligent automated modeling and dynamic updating. There are still key technical bottlenecks in the integrated expression of all-element holistic representation data and mechanism models for digital twin modeling at the city level or major engineering level. Surveying and mapping technology is in urgent need of multi-disciplinary cross-integration innovation, breakthroughs in organic collaboration between the sky and the ground, real-time and dynamic acquisition of multi-detailed real 3D data, automated intelligent processing of multi-specialty, multi-scale and multi-modal spatio-temporal data, and detailed 3D construction of complex scenes under incomplete data conditions. Core key technologies such as dynamic construction of full-life-cycle digital twin models that combine characterization data and mechanism models to form general geospatial intelligence to achieve high-quality development of surveying and mapping technology and an irreplaceable and more powerful basic support for economic and social development.

长期以来，地球空间信息服务无法反映现场实况，不能满足综合监测实时信息服务需求。本文围绕空天地平台观测共享集成管理和时空信息高效服务问题，提出了传感网观测共享信息模型，重点阐述了基于对地观测传感网的最大时空覆盖优化布局、任务反馈控制、流式观测实时接入和动态仿真与预警决策支持的实时动态GIS关键技术，介绍了实时动态网络GIS平台GeoSensor及长江流域通航、防洪和发电时空信息感知管理应用。

The geo-spatial information service has failed to reflect the live status of spot and meet the needs of integrated monitoring and real-time information for a long time. To tackle the problems in observation sharing and integrated management of space-borne, air-borne, and ground-based platforms and efficient service of spatio-temporal information, an observation sharing model was proposed. The key technologies in real-time dynamic geographical information system (GIS) including maximum spatio-temporal coverage-based optimal layout of earth-observation sensor Web, task-driven and feedback-based control, real-time access of streaming observations, dynamic simulation, warning and decision support were detailed. An real-time dynamic Web geographical information system (WebGIS) named GeoSensor and its applications in sensing and management of spatio-temporal information of Yangtze River basin including navigation, flood prevention, and power generation were also introduced.

城市感知与决策是实现城市智慧化的首要前提。针对当前的最新研究进展，分别从基于空天地集成化传感网的城市综合感知、城市时空大数据的管理与分析、面向多层次用户的智能决策等3方面进行了分析论述，对比分析了当前城市时空信息平台及应用，在此基础上，提出了未来智慧城市感知决策面临的"三高"挑战，即高度融合的物理感知与社会感知，高度智能化的城市管理分析能力，以及高置信度的城市信物融合系统决策。

City sensing and decision-making are the primary prerequisites for the realization of urban intelligence. In view of the current research progress, this paper reviewed the urban comprehensive sensing based on the integrated satellite-airborne-ground sensor web, the management and analysis of urban spatio-temporal big data, and the intelligent decision-making and focusing service for multi-level users. Meanwhile, this paper compares and analyzes the current urban spatio-temporal information platforms and their applications in smart cities. On this basis, it puts forward three challenges faced by the sensing and management of smart cities in the future, including the highly fused physical sensing and social sensing, highly intelligent city management and analytical capability, and highly confident decision based on cyber-physical system.