Link to Session Platform

Chairs(s):

Haowen Xu, Oak Ridge National Laboratory

; Xiaojuan Yang, Oak Ridge National Laboratory

Description:

In the recent decade, Geographical Information System (GIS)-based methods, combined with advanced information and computing technologies, have been increasingly applied to improve the characteristics, understanding, and management of ecosystems both temporally and spatially. At the technical level, the increasing availability and quality of soil data generated through GIS and remote sensing-powered Digital Soil Mapping (DSM) and Internet of Things (IoT) connected sensors have led to the accelerated adoption of data-driven approaches. These approaches include machine learners and statistics and their integration with process-based models, aiming to promote the analysis of large volumes of data for generating new insights and inferences regarding the interactions and feedback within and between the earth system at multiple scales. At the scientific research level, these emerging applications have created many opportunities for improving our understanding and modeling capability of ecosystems in the context of environmental and climate changes. These applications also provide guidance for the smart and efficient management of natural ecosystems, agriculture, watershed and rivers, and other natural resources.

Organizers:
Dr. Haowen Xu, Oak Ridge National Laboratory
Dr. Xiaojuan Yang, Oak Ridge National Laboratory
Dr. Umakant Mishra, Sandia National Laboratories
Jun Zhang, Institute of Mountain Hazards and Environment (CAS)
Dr. Chang Zhao, NORC at the University of Chicago

Non-Presenting Participants Agenda