Natural resources constitute the material basis for human survival and economic development; therefore, the survey, monitoring, and assessment of their distribution, status, and dynamics within the Earth system are essential for informed decision-making. Nowadays, the striking development of “space-air-ground-tower” integrated monitoring infrastructure is driving natural resources survey, monitoring, and assessment into the big data era. A sheer amount of multi-source, multi-modal, multi-scale, and heterogeneous data dispersed across the web is being continuously generated via Earth Observation systems, UAVs, IoTs, tower-based facilities, and human-sensing. At the same time, making effective use of such data remains challenging, particularly in data management, multimodal fusion, efficient processing, and knowledge extraction.
Addressing these issues requires more intensive collaboration between the Earth science community and the information science community. Against this background, NRSMA 2026 aims to provide an interdisciplinary forum for researchers and practitioners to exchange recent advances in theories, methods, techniques, systems, and applications for natural resources survey, monitoring, and assessment in the big data era.
The workshop will focus on how Web and Big Data technologies can facilitate the use and interpretation of natural resources data, deepen our understanding of natural resources, and support their effective utilization and sustainable management.
The topics of interest include, but are not limited to the following:
- Big data technologies for natural resources survey, monitoring, and assessment
- Web-based data management, sharing, and utilization for natural resources
- Data analytics for multi-source and multimodal natural resources data
- Information retrieval and knowledge discovery in natural resources scenarios
- Foundation models for natural resources data understanding
- Cyber-physical systems for natural resources monitoring
- Edge intelligence for natural resources survey and monitoring
- Intelligent assessment and governance for natural resources
- Sustainable utilization and management of natural resources in the big data era
- Systems for natural resources data management/processing/analysis/visualization
All paper submissions for NRSMA 2026 will be via Microsoft CMT (under the 1st International Workshop on Natural Resources Survey, Monitoring, and Assessment in the Big Data Era (NRSMA 2026)).
All submissions must be written in English and conform to the Springer LNCS proceedings format with the following page limits: 12 pages including references. Authors must provide the complete and final list of authors at the submission stage. No addition, removal, or change in the order of authors is allowed after submission.
Please use one of the following templates for the LNCS (Lecture Notes in Computer Science) format: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines
Xiaohui Huang
China University of Geosciences (Wuhan), China
Email: [email protected]
Yuewei Wang
Associate Professor, China University of Geosciences (Wuhan), China
Email: [email protected]
Xiaodao Chen
Associate Professor, China University of Geosciences (Wuhan), China
Email: [email protected]
Wei Han
Associate Professor, China University of Geosciences (Wuhan), China
Email: [email protected]
Fan Lei
The Second Surveying and Mapping Institute of Hunan Province, China
Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region, Ministry of Natural Resources, China
Email: [email protected]
Yunliang Chen
Professor, China University of Geosciences (Wuhan), China
Email: [email protected]
Jianxin Li
Professor, Edith Cowan University, Australia
Email: [email protected]
Lizhe Wang
Professor, Tsinghua University, China
Email: [email protected]