Committee on Remote Sensing and Spatiotemporal Intelligence (RSSI)
The Committee on Remote Sensing and Spatiotemporal Intelligence focuses on the application of remote sensing, geographic information science, spatial analysis, spatiotemporal modeling, artificial intelligence, and big data technologies in natural resource research and management. Its scope covers satellite observation, UAV monitoring, geospatial databases, land use mapping, resource inventory, ecological monitoring, disaster assessment, spatial decision support, digital twins, and intelligent resource governance. The Committee recognizes that modern resource science increasingly depends on accurate, timely, and multi-scale spatiotemporal information.
The mission of RSSI is to promote technological innovation and interdisciplinary application of remote sensing and spatiotemporal intelligence in natural resource studies. It seeks to improve the capacity for observing, analyzing, predicting, and managing complex resource and environmental systems. The Committee connects remote sensing science, geography, computer science, artificial intelligence, ecology, hydrology, urban studies, resource management, and policy analysis.
The vision of RSSI is to build an advanced international platform for intelligent observation and decision support in natural resource governance. It supports the development of high-resolution, multi-source, real-time, and intelligent monitoring systems that can serve resource assessment, environmental protection, land planning, climate adaptation, disaster response, and sustainable development. The Committee emphasizes that spatiotemporal intelligence should not only improve data acquisition, but also strengthen interpretation, forecasting, scenario simulation, and policy-relevant decision-making.
The responsibilities of RSSI include organizing academic exchanges, technical training, data-sharing initiatives, algorithm development, and collaborative research projects. It supports studies on remote sensing inversion, spatial data fusion, machine learning, change detection, resource monitoring, ecological assessment, and spatiotemporal simulation. The Committee may also contribute to technical standards, open data platforms, methodological guidelines, and demonstration applications. It encourages cooperation among scientists, engineers, policymakers, and industry partners to transform geospatial technologies into practical tools for resource governance. Through its work, RSSI aims to enhance the digital and intelligent capacity of the Society, providing technical support for evidence-based, precise, and adaptive management of natural resources.
Under construction